Parametric CubeSat flight simulation architecture

This paper presents the architecture of a system of models that provides realistic simulation of the dynamic, in-orbit behaviour of a CubeSat. Time-dependent relationships between sub-systems and between the satellite and external nodes (ground stations and celestial bodies) are captured through numerical analysis of a multi-disciplinary set of state variables including position, attitude, stored energy, stored data and system temperature. Model-Based Systems Engineering and parametric modelling techniques are employed throughout to help visualise the models and ensure flexibility and expandability. Operational mode states are also incorporated within the design, allowing the systems engineer to assess flight behaviour over a range of mission scenarios. Finally, both long and short term dynamics are captured using a coupled-model philosophy; described as Lifetime and Operations models. An example mission is analysed and preliminary results are presented as an illustration of early capabilities

Through-life modelling of nano-satellite power system dynamics

This paper presents a multi-fidelity approach to finding optimal, mission-specific power system configurations for CubeSats. The methodology begins with propagation of the orbit elements over the mission lifetime, via a continuous-time model, accounting for orbital perturbations (drag, solar radiation and non-spherical geo-potential). Analytical sizing of the power system is then achieved at discrete long-term intervals, to account for the effects of variations in environmental conditions over the mission life. This sizing is based on worst case power demand and provides inputs to a numerical assessment of the in-flight energy collection for each potential solar array deployment configuration. Finally, two objective functions (minimum deviation about the orbit average power and maximum average power over the entire mission) are satisfied to identify the configurations most suitable for the specific mission requirement. Most Nano-satellites are designed with relatively simple, static-models only and tend to be over-engineered as a result, often leading to a power-limited system. The approach described here aims to reduce the uncertainty in energy collection during flight and provide a robust approach to finding the optimal solution for a given set of mission requirements

Tidal synchronous orbit : A novel approach to remote sensing of oceanic regions

To-date space-based remote sensing of oceans and coastal regions has principally been conducted from platforms in Sun-Synchronous Low Earth Orbit (LEO). Such a trajectory, while beneficial in terms of solar illumination angle, has limitations in that geometric patterns driven primarily by tidal variation (such as coastal bathymetry and suspended sediment reflectance) may not be captured effectively. As such, tidal-synchronous observations can be expected to provide enhanced remote sensing of oceanic regions where tidal variation plays a key role. This paper introduces the concept of Tidal synchronism, defining it as when the orbit period of a platform is synchronised with the rotation period of the Earth such that a repeat ground-track is achieved after an integer number of ‘tidal periods’ (twice the ‘principal lunar semi-diurnal’ constituent). Such a Tidal-Synchronous platform would facilitate analysis of specific locations, at specific times in the regular tidal sequence, resulting in improved monitoring of evolving patterns as a function of tidal variation. Whilst a Sun-Synchronous orbit has been necessary for the majority of large, multi-functional Earth Observation platforms (e.g. ENVISAT), specific mission applications realised through smaller, specialised technologies are becoming increasingly common, for which a tidal synchronous orbit is found to be beneficial. For the first time, this paper introduces the concept of a Tidal-Synchronous orbit and describes the astrodynamic properties of such a trajectory under the influence of natural perturbations (J2) via a set of Modified Equinoctial Elements. Analytical solutions for low thrust propulsive station-keeping are presented, for the general case of orbit and repeat parameter combinations, indicating the applicability of such a mission to small, resource limited spacecraft. It is shown that a repeat ground-track can be achieved every 28 tidal periods with a single platform, through exploitation of natural perturbations alone (imager field of view would govern temporal resolution over any given region). A constellation of satellites could be deployed to achieve greater temporal resolution (additional satellites in an orbit plane) and greater number of ground-track repeats at specific tidal times (additional orbit planes). It is also shown that orbit parameters attributed to a repeat ground-track after exactly 57 tidal periods are almost identical to those required for a Sun-Synchronous orbit (approximately 5deg drift in relative solar angle per year). In this case, benefits from each class of synchronism could be exploited in order to achieve high quality, reliable visible imaging data at regular times in the tidal sequence

Maximum Likelihood, Profile Likelihood, and Penalized Likelihood: A Primer

The method of maximum likelihood is widely used in epidemiology, yet many epidemiologists receive little or no education in the conceptual underpinnings of the approach. Here we provide a primer on maximum likelihood and some important extensions which have proven useful in epidemiologic research, and which reveal connections between maximum likelihood and Bayesian methods. For a given data set and probability model, maximum likelihood finds values of the model parameters that give the observed data the highest probability. As with all inferential statistical methods, maximum likelihood is based on an assumed model and cannot account for bias sources that are not controlled by the model or the study design. Maximum likelihood is nonetheless popular, because it is computationally straightforward and intuitive and because maximum likelihood estimators have desirable large-sample properties in the (largely fictitious) case in which the model has been correctly specified. Here, we work through an example to illustrate the mechanics of maximum likelihood estimation and indicate how improvements can be made easily with commercial software. We then describe recent extensions and generalizations which are better suited to observational health research and which should arguably replace standard maximum likelihood as the default method

Bayesian Posterior Distributions Without Markov Chains

Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976–1983) assessing the relation between residential exposure to magnetic fields and the development of childhood cancer. Results from rejection sampling (odds ratio (OR) = 1.69, 95% posterior interval (PI): 0.57, 5.00) were similar to MCMC results (OR = 1.69, 95% PI: 0.58, 4.95) and approximations from data-augmentation priors (OR = 1.74, 95% PI: 0.60, 5.06). In example 2, the authors apply rejection sampling to a cohort study of 315 human immunodeficiency virus seroconverters (1984–1998) to assess the relation between viral load after infection and 5-year incidence of acquired immunodeficiency syndrome, adjusting for (continuous) age at seroconversion and race. In this more complex example, rejection sampling required a notably longer run time than MCMC sampling but remained feasible and again yielded similar results. The transparency of the proposed approach comes at a price of being less broadly applicable than MCMC

Marijuana use and DNA methylation-based biological age in young adults

BACKGROUND: Marijuana is the third most commonly used drug in the USA and efforts to legalize it for medical and recreational use are growing. Despite the increase in use, marijuana\u27s effect on aging remains understudied and understanding the effects of marijuana on molecular aging may provide novel insights into the role of marijuana in the aging process. We therefore sought to investigate the association between cumulative and recent use of marijuana with epigenetic age acceleration (EAA) as estimated from blood DNA methylation. RESULTS: A random subset of participants from The Coronary Artery Risk Development in Young Adults (CARDIA) Study with available whole blood at examination years (Y) 15 and Y20 underwent epigenomic profiling. Four EAA estimates (intrinsic epigenetic age acceleration, extrinsic epigenetic age acceleration, PhenoAge acceleration, and GrimAge acceleration) were calculated from DNA methylation levels measured at Y15 and Y20. Ever use and cumulative marijuana-years were calculated from the baseline visit to Y15 and Y20, and recent marijuana use (both any and number of days of use in the last 30 days) were calculated at Y15 and Y20. Ever use of marijuana and each additional marijuana-year were associated with a 6-month (P \u3c 0.001) and a 2.5-month (P \u3c 0.001) higher average in GrimAge acceleration (GAA) using generalized estimating equations, respectively. Recent use and each additional day of recent use were associated with a 20-month (P \u3c 0.001) and a 1-month (P \u3c 0.001) higher GAA, respectively. A statistical interaction between marijuana-years and alcohol consumption on GAA was observed (P = 0.011), with nondrinkers exhibiting a higher GAA (β = 0.21 [95% CI 0.05, 0.36], P = 0.008) compared to heavy drinkers (β = 0.05 [95% CI - 0.09, 0.18], P = 0.500) per each additional marijuana-year. No associations were observed for the remaining EAA estimates. CONCLUSIONS: These findings suggest cumulative and recent marijuana use are associated with age-related epigenetic changes that are related to lifespan. These observed associations may be modified by alcohol consumption. Given the increase in use and legalization, these findings provide novel insight on the effect of marijuana use on the aging process as captured through blood DNA methylation

The association of heart rate recovery immediately after exercise with coronary artery calcium: the coronary artery risk development in young adults study

We tested whether slower heart rate recovery (HRR) following graded exercise treadmill testing (GXT) was associated with the presence of coronary artery calcium (CAC). Participants (n = 2,648) ages 18–30 years at baseline examination underwent GXT, followed by CAC screening 15 years later. Slow HRR was not associated with higher odds of testing positive (yes/no) for CAC at year 15 (OR = 0.99, p = 0.91 per standard deviation change in HRR). Slow HRR in young adulthood is not associated with the presence of CAC at middle age

Global agricultural intensification during climate change: a role for genomics

Agriculture is now facing the ‘perfect storm’ of climate change, increasing costs of fertilizer and rising food demands from a larger and wealthier human population. These factors point to a global food deficit unless the efficiency and resilience of crop production is increased. The intensification of agriculture has focused on improving production under optimized conditions, with significant agronomic inputs. Furthermore, the intensive cultivation of a limited number of crops has drastically narrowed the number of plant species humans rely on. A new agricultural paradigm is required, reducing dependence on high inputs and increasing crop diversity, yield stability and environmental resilience. Genomics offers unprecedented opportunities to increase crop yield, quality and stability of production through advanced breeding strategies, enhancing the resilience of major crops to climate variability, and increasing the productivity and range of minor crops to diversify the food supply. Here we review the state of the art of genomic-assisted breeding for the most important staples that feed the world, and how to use and adapt such genomic tools to accelerate development of both major and minor crops with desired traits that enhance adaptation to, or mitigate the effects of climate change

Comparative quantification of health risks: Conceptual framework and methodological issues

Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability. In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty