Retooling Space Solar Cell System CIC for CXBN-2

The power subsystem is vital to any spacecraft operation, making solar cells a valuable aspect. Critical to all spacecraft, they provide constant charge to the batteries and produce power for the electronics onboard. Solar cells have been engineered for large commercial and military space missions, up to thousand kilogram class satellites, and may not fit the requirements for smaller CubeSat form factors. Additionally, this restrains CubeSats from using higher voltage busses due to the mismatch in solar cell scaling. The purpose of this project is to retool the solar cell CIC (Solar Cell Interconnects Coverglass) to satisfy the small satellite system requirements while having the most effective surface area and providing the necessary wattage. We have undertaken an experimental process to dice commercial solar cells to customize them for the CXBN-2 (Cosmic X-Ray Background NanoSat 2) mission. CXBN-2 is constrained by having two scientific payloads extruding outward from the space frame in opposite directions that make fitting large format solar cells impossible. Staff and students from the Morehead State University Space Science Center and the Micro-Nano Technology Center at the University of Louisville are developing a process to dice existing commercial off the shelf solar cells to facilitate mission customization. The CXBN-2 mission provides an opportunity to develop these processes. This project will reveal the design decisions, dicing, testing, and model verification of the modified solar cells that will be mounted onto the spacecraft body and deployable solar panels, achieving higher power system performance

Time and Frequency Domain Measures of Motor Symptoms in Parkinson's Disease

International audienceParkinson’s disease (PD) is the second most common neurodegenerative disorder of aging and results from a progressive loss of dopaminergic neurons. PD motor features leading to the loss of balance and increased fall risk include slowness of movement, hastening of the gait, blocked movement, paucity of spontaneous movements, reduced arm swing, poor postural stability, and freezing of gait (FOG). Some individuals with PD can overcome FOG with external auditory or visual stimuli. An automated system capable of delivering such cues in ambient settings, where FOG often occurs, requires an accurate algorithm to detect and quantify PD dysfunction.The current study focuses on the development of an algorithm to measure the severity of PD motor symptoms including asymmetry, slowing, and FOG using signals received from wearable inertial sensors (IMUs) attached to the lumbar back, shanks and wrists. The experiment utilizes real-world stimuli to trigger PD symptoms. We will compare motor performances of five individuals with PD to those of five age-matched control participants. We hypothesize that frequency-domain features extracted from IMU measurements will be sensitive to arm swing asymmetry and freezing of gait in PD participants when compared with the control participants. Our prior results indicate the ratio of the acceleration signal power from IMUs on the left and right wrists discriminates between more and less affected sides of the PD participant. In this study we will use these features as well as wavelet features, sample entropy and dimensionless jerk to design an algorithm, using machine learning techniques, to detect occurrence of symptoms in sliding windows of recorded signals during daily activities.Five participants with PD and five age-matched control subjects will be recruited to perform a series of walking, turning and stopping tasks in a 9.1 \times 1.3m wide with various obstacles. The study uses a 2x2 design with one level of objects (0, 1, and 3) of the walkway (150% or 100% of the shoulder width) at the object area will change for the next 4 trials. Participants will repeat each trial 4 laps (20 total laps). At one end, the participants are asked to stop for 3 seconds and then make a turn in a 3\times3ft box marked on the floor and then stop for 3 seconds; at the other end, they are asked to make a narrow turn in a 2\times2ft box with no prior stop. Participants will also make unanticipated stops. Gait events will be classified as walking (approaching and passing the objects), turning (wide and narrow), stop (expected and unexpected) and gait transition (initiation and termination), and the performance of the algorithm will be compared during these gait events

Molecular ion trap-depletion spectroscopy of BaCl+^+

We demonstrate a simple technique for molecular ion spectroscopy. BaCl$^+$ molecular ions are trapped in a linear Paul trap in the presence of a room-temperature He buffer gas and photodissociated by driving an electronic transition from the ground X$^1\Sigma^+$ state to the repulsive wall of the A$^1\Pi$ state. The photodissociation spectrum is recorded by monitoring the induced trap loss of BaCl$^+$ ions as a function of excitation wavelength. Accurate molecular potentials and spectroscopic constants are determined. Comparison of the theoretical photodissociation cross-sections with the measurement shows excellent agreement. This study represents the first spectroscopic data for BaCl$^+$ and an important step towards the production of ultracold ground-state molecular ions.Comment: 5 pages, 5 figure

Supporting data – Floating Gardens, Chicago River, April 29, 2018 to November 19, 2019

Between April 29, 2018 to November 19, 2019, water samples were collected upstream and downstream of a floating garden installed along the Chicago River. At each location, samples were collected at the surface and at 0.3 m below the surface. In-situ measurements of Dissolved Oxygen, Specific Conductance, and Temperature were recorded with a YSI 85. Anion samples were analyzed using a Ion Chromatograph for fluoride (F-), chloride (Cl-), nitrate as nitrogen (NO3-N), phosphate (PO4-3), and sulfate (SO4-2). The available dataset provides the recorded field parameters and the analyzed ion concentrations