Microspacecraft and Earth observation: Electrical field (ELF) measurement project

The Utah State University space system design project for 1989 to 1990 focuses on the design of a global electrical field sensing system to be deployed in a constellation of microspacecraft. The design includes the selection of the sensor and the design of the spacecraft, the sensor support subsystems, the launch vehicle interface structure, on board data storage and communications subsystems, and associated ground receiving stations. Optimization of satellite orbits and spacecraft attitude are critical to the overall mapping of the electrical field and, thus, are also included in the project. The spacecraft design incorporates a deployable sensor array (5 m booms) into a spinning oblate platform. Data is taken every 0.1 seconds by the electrical field sensors and stored on-board. An omni-directional antenna communicates with a ground station twice per day to down link the stored data. Wrap-around solar cells cover the exterior of the spacecraft to generate power. Nine Pegasus launches may be used to deploy fifty such satellites to orbits with inclinations greater than 45 deg. Piggyback deployment from other launch vehicles such as the DELTA 2 is also examined

Designed to Fail: Flexible, Anisotropic Silver Nanorod Sheets for Low-Cost Wireless Activity Monitoring

We describe the fabrication and properties of flexible, anisotropic silver nanorod sheets and investigate their potential to function as a sensor. Aligned and tilted silver nanorod (AgNR) arrays are incorporated into poly­dimethyl­siloxane (PDMS) to form flexible conductive sheets. The electrical properties of these sheets are investigated and show large anisotropies, which are related to the alignment direction of the nanorods. Notably, the films show the greatest electrical resistance in the direction perpendicular to the nanorod alignment, and when strain is applied along this direction, the resistance increases monotonically with increasing loading/unloading cycles. In comparison, the resistance along the nanorod alignment direction remains constant over many strain cycles and therefore can serve as an internal reference or as a stable strain gauge. These changes in resistivity are attributed to changes in the internanorod connectivity and can be modeled using an effective medium approximation for anisotropic percolation. Stable piezoresistivity (in one orientation) and surface-enhanced Raman scattering activity of the AgNR sheets make them attractive for flexible electronics applications such as electronic skin or as monitors for human–machine interactions. However, the ability to encode a surface’s dynamic history into material properties through resistance changes is a considerable simplification over other systems and can enable wireless activity monitoring where cost or demanding environments prevent more complicated devices from being implemented

Teaching Cheminformatics through a Collaborative Intercollegiate Online Chemistry Course (OLCC)

While cheminformatics skills necessary for dealing with an ever-increasing amount of chemical information are considered important for students pursuing STEM careers in the age of big data, many schools do not offer a cheminformatics course or alternative training opportunities. This paper presents the Cheminformatics Online Chemistry Course (OLCC), which is organized and run by the Committee on Computers in Chemical Education (CCCE) of the American Chemical Society (ACS)’s Division of Chemical Education (CHED). The Cheminformatics OLCC is a highly collaborative teaching project involving instructors at multiple schools who teamed up with external chemical information experts recruited across sectors, including government and industry. From 2015 to 2019, three Cheminformatics OLCCs were offered. In each program, the instructors at participating schools would meet face-to-face with the students of a class, while external content experts engaged through online discussions across campuses with both the instructors and students. All the material created in the course has been made available at the open education repositories of LibreTexts and CCCE Web sites for other institutions to adapt to their future needs

Effects of 6-month aerobic interval training on skeletal muscle metabolism in middle-aged metabolic syndrome patients

Aerobic interval training (AIT) improves the health of metabolic syndrome patients (MetS) more than moderate intensity continuous training. However, AIT has not been shown to reverse all metabolic syndrome risk factors, possibly due to the limited duration of the training programs. Thus, we assessed the effects of 6 months of AIT on cardio-metabolic health and muscle metabolism in middle-aged MetS. Eleven MetS (54.5±0.7 years old) underwent 6 months of 3 days a week supervised AIT program on a cycle ergometer. Cardio-metabolic health was assessed, and muscle biopsies were collected from the vastus lateralis prior and at the end of the program. Body fat mass (-3.8%), waist circumference (-1.8%), systolic (-10.1%), and diastolic (-9.3%) blood pressure were reduced, whereas maximal fat oxidation rate and VO2peak were significantly increased (38.9% and 8.0%, respectively; all P<.05). The remaining components of cardio-metabolic health measured (body weight, blood cholesterol, triglycerides, and glucose) were not changed after the intervention, and likewise, insulin sensitivity (CSi) remained unchanged. Total AMPK (23.4%), GLUT4 (20.5%), endothelial lipase (33.3%) protein expression, and citrate synthase activity (26.0%) increased with training (P<.05). Six months of AIT in MetS raises capacity for fat oxidation during exercise and increases VO2peak in combination with skeletal muscle improvements in mitochondrial enzyme activity. Muscle proteins involved in glucose, fat metabolism, and energy cell balance improved, although this was not reflected by parallel improvements in insulin sensitivity or blood lipid profile.Spanish Ministry of Economy and Competiveness. Grant Number: DEP2014-52930-R3.631 JCR (2018) Q1, 11/83 Sport Sciences1.627 SJR (2018) Q1, 21/289 Orthopedics and Sports Medicine, 11/209 Physical Therapy, Sports Therapy and Rehabilitation, 17/125 Sports ScienceNo data IDR 2018UE