An Extensible Mathematical Model of Glucose Metabolism

The American Diabetes Association reports that diabetes is the fifth leading cause of death by disease in the United States. An estimated 23.6 million individuals, or seven percent of the population, have diabetes. Nearly one-third are unaware that they have the disease. The total of the direct and indirect medical costs associated with diabetes in 2007 was projected to be $174 billion, or approximately one out of every ten health care dollars. One must understand the glucose regulatory system of the healthy body to understand diabetes. Blood glucose concentration returns to a constant level after eating and is maintained during exercise. With thousands of chemical reactions involved in the process, a complete mathematical model is not yet realistic. Proposed here is the evolution of a model beginning with a three-variable model of glucose, insulin, and glucagon and ending with its extension to the four-variable model incorporating the additional interdependent mechanics of hepatic glycogen. The three-variable model mimics the return of blood glucose levels to a constant, or basal, state; however, this model is consistent only with short-term dynamics since it excludes consideration of finite energy stores. Thus, the extension includes the effects of a finite store of hepatic glycogen. The solution of the four-variable model demonstrates the short-term return of glucose concentration to near basal levels despite the constant energy usage which draws upon the glycogen stores. Long-term glucose homeostasis is explained by investigating the storage of a glucose load in the postprandial period and dispersion of stored glucose during the extended postprandial period. Increased hepatic glucose production in people with diabetes is thought to be the driving mechanism for increased basal glucose levels. Analysis of this model indicates the genesis of this phenomenon. Elevated prandial glucose and insulin levels associated with insulin resistance increase the glycogen-storage levels above normal which then increase hepatic glucose production in the postprandial period. Increased energy input exasperates this problem, but only in insulin resistant individuals. This simple model suggests that Type II diabetes results from insulin resistance more than from overeating

Partnership for Development: The Case of Savelugu Municipal Assembly and World Vision Ghana

This study explored the effectiveness of the partnership relationship between the Savelugu Municipal Assembly (SMA) and the World Vision Ghana (WVG) as a case study of how partnerships between MMDAs and NGOs contribute to development in the Northern Region of Ghana. The exploration was done within the context of Development Cooperation as espoused in the Goal 8 of the MDGs as a means of promoting aid effectiveness. A Mixed Research Strategy, the Case Study Design and the Purposive Sampling Technique were some of the research methodological techniques employed for the study. The study suggests that the partnership between the two organisations was a mutual and impacted positively on the development of the Savelugu Municipality. This included improvement in water supply, sanitation, as well as education and healthcare delivery. The study suggests that partnership relationships that thrive on cordiality or mutual respect are most likely to impact positively on development. Keywords: Partnership, MMDAs, NGOs, Development, Cooperation, Decentralisatio

An Overview of Distributed Spacecraft Autonomy at NASA Ames

Autonomous decision-making significantly increases mission effectiveness by mitigating the effects of communication constraints, like latency and bandwidth, and mission complexity on multi-spacecraft operations. To advance the state of the art in autonomous Distributed Space Systems (DSS), the Distributed Spacecraft Autonomy (DSA) team at NASA\u27s Ames Research Center is developing within five relevant technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. DSA is maturing these technologies - critical for future large autonomous DSS - from concept to launch via simulation studies and orbital deployments. A 100-node heterogenous Processor-in-the-Loop (PiL) testbed aids distributed autonomy capability development and verification of multi-spacecraft missions. The DSA software payload deployed to the D-Orbit SCV-004 spacecraft demonstrates multi-agent reconfigurability and reliability as part of an ESA-sponsored in-orbit technology demonstration. Finally, DSA\u27s primary flight mission showcases collaborative resource allocation for multipoint science data collection with four small spacecraft as a payload on NASA\u27s Starling 1.0 satellites

A Summary of Neural Radiance Fields for Shadow Removal and Relighting of Satellite Imagery

Multi-view stereo photogrammetric techniques are conventionally utilized to generate Global Digital Elevation Models (GDEM) of planetary and lunar surfaces. However, these methods, relying on conventional feature detectors, are often subject to inaccuracies caused by changes in lighting conditions, including diffuse reflection and harsh shading. This has limited the ability of these methods to accurately reconstruct shadowed regions in orbital imagery, such as highly shaded urban areas and the permanently shadowed regions (PSRs) located on the lunar surface, which are critical targets for NASA’s Artemis program. Neural Radiance Fields (NeRFs) offer a novel solution to these limitations by breaking away from traditional photogrammetric assumptions of ridged, opaque surfaces. NeRFs are capable of reconstructing 3D objects with variably transmissive properties and reflective surfaces. In this summary analysis, we articulate the robustness of NeRFs in generating high-fidelity 3D models of terrain from highly shaded orbital imagery acquired from satellites in low earth orbit (LEO) and emphasize their applicability to a lunar environment. We showcase emerging NeRF-derived methods that overcome the limitations of traditional photogrammetric methods and provide a promising solution for reconstructing complex scenes in challenging lighting conditions

Design requirements for a cloud-based automated red team in a cyber range for security operations training

Competitions for students, novices, and professionals to practice hacking and cyber defense skills (Conklin 2005; White et al. 2010). In cyber defense competitions teams design, implement, manage, and defend a network of computers and services (Schepens and James 2003). Cyber defense competitions are great learning opportunities for students and professionals. Typically, as in the case of the National Collegiate Cyber Defense Competition (https://www.nationalccdc.org/), the competitions consist of multiple blue teams of contestants and multiple red teams that attacks the services and systems that blue team is trying to counteract. An automated attack system needs to be intelligent, have low overhead, be realistic, and be modular (Miller et al. 2018). The components of automated attack systems vary. A patent for a very high-level design of an automated penetration system uses simulators (virtual machines or software that mimics the behavior of computers or networks), an exploit database, storage for scenarios, configuration files, and a penetration testing framework (Futoransky et al. 2013). Other systems can simulate network and user traffic (Rossey et al. 2002). We have so far identified four high-level design requirements: 1) ability to perform many types of attacks, 2) ability to follow a good process, 3) possession of a high-level situational understanding of the scenario, and 4) ease of sanitation and reuse of the simulation. Our continued work will identify more design requirements and areas of research that are needed to further the technological abilities and efficiency of automated red team design

The Feasibility of Structure from Motion Over Planetary Bodies Using Small Satellites

The Mapping and Ocean Color Imager (MOCI) is a 3U cube satellite mission that seeks to preform Structure from Motion (SfM) at a landscape scale while in Low Earth Orbit (LEO). MOCI will have the ability to passively map terrains by slewing over targeted regions and taking a rapid succession of images. MOCI is being developed by the University of Georgia’s (UGA) Small Satellite Research Laboratory (SSRL) through the Air Force Research Laboratory\u27s ninth iteration of the University NanoSatellite Program (UNP-9). The project is led by undergraduates from a wide range of backgrounds and supervised by a multidisciplinary team of Principal Investigators at UGA. The students are developing the software capable of on orbit calculations to derive 3-D point clouds and compression techniques allowing the transmission of 3-D data sets. The majority of works using point clouds employ 3D representations derived from terrestrial and aerial LiDAR (Light Detection and Ranging) and have benefitted from the increased availability of LiDAR data in recent years. But progresses in computer vision have made available a series of algorithms that allow for the generation of point clouds and surfaces that do not need a point-based collection characteristic of LiDAR systems. Among those algorithms, Structure from Motion (SfM) has received increased attention due to its ability of extracting 3D features and reconstruction of objects/structures based on multiple photographs or video frames. MOCI will uses these techniques on a space based platform that acquires sets of 2D images, which will then perform a series of machine vision algorithms to produce a topographical mesh. A Scale-Invariant Feature Transform (SIFT) is first performed on the set to find various gradients and determine image rotations. A sparse point cloud, consisting of points identified as similar between a series of images, can be computed from a combination of SIFT and the parallax of satellite with its target area. This sparse point cloud can then be used to compute a dense point cloud. This dense point cloud, typically consisting of 100,000 or more vertices, is used to compute a surface mesh with Poisson Surface Reconstruction. Initial tests have been performed to determine the feasibility of this type of passive mapping in LEO. Tests consisted of generating an earth sized model in blender and placing various features on the surface of the modeled earth. Using python scripts, the imaging process of the MOCI satellite can be simulated with the resulting images being similar to what would be expected from LEO. Structure from Motion is then performed on the image set and a sparse point cloud, dense point cloud, and mesh are computed. Initial test have shown SfM to be feasible at a landscape scale. Planetary SfM was also performed with data from the International Space Station. It was demonstrated that cloud lines, with height differentials of 1000 - 3000 feet, could be distinguished. Large scale surface maps of pluto were also generated using the techniques described above with available imaging data from the New Horizons pluto fly by

The Reliability of the Seated Medicine Ball Throw as Assessed with Accelerometer Instrumentation

The Seated Medicine Ball Throw (SMBT) is low-risk, easy to perform, requires minimal equipment, and is a valid measure of upper body explosiveness. The Ballistic Ball™ (BB) medicine ball contains inertial sensors which estimate peak velocity, and transmits these values to an iPad™ app via Bluetooth™. This method of gathering data may be superior to using horizontal distance as there is less chance of confounding factors and it is easier to administer. The objective of this study was to evaluate the reliability of the BB peak velocity measurement in the SMBT. Twenty healthy, rested, recreationally-active, undergraduate students volunteered to participate in this study. After a standard dynamic warm-up, subjects were taught proper throwing technique. For familiarization, subjects performed repeated SMBTs with a 10 lb BB until horizontal distance thrown for 3 consecutive trials was within 0.25m. After 20 minutes of rest, subjects repeated the warm-up protocol, then performed 6 trials with the same 10 lb BB for which peak velocity was recorded. The test-retest reliability of these 6 trials was analyzed using intraclass correlations (ICC). The ICCs between consecutive trials ranged from 0.94 to 0.98. Peak velocity for trials 1-6 were: 3.85±1.14 m/s, 3.86±1.06 m/s, 3.94±1.22 m/s, 3.85±1.13 m/s, 3.95±1.21 m/s, 3.92±1.20 m/s, respectively. The high ICC values suggest excellent reliability of the peak velocity measurement from the BB device. The BB peak velocity as assessed during a SMBT is a reliable method for assessment of upper body explosiveness