Advanced Langmuir Probe (LP)

The dynamic response of the MK-2 version of the Langmuir probe amplifier was studied. The settling time of the step response is increased by: (1) stray node-to-ground capacitance at series connections between high value feedback resistors; and (2) input capacitance due to the input cable, FET switches, and input source follower. The stray node-to-ground capacitances can be reduced to tolerable levels by elevating the string of feedback resistors above the printing board. A new feedback network was considered, with promising results. The design uses resistances having much lower nominal values, thereby minimizing the effect of stray capacitances. Faster settling times can be achieved by using an operational amplifier having a higher gain-bandwidth product

Solar extreme ultraviolet sensor and advanced langmuir probe

For more than two decades, the staff of the Space Physics Research Laboratory (SPRL) has collaborated with the Goddard Space Flight Center (GSFC) in the design and implementation of Langmuir probes (LP). This program of probe development under the direction of Larry Brace of GSFC has evolved methodically with innovations to: improve measurement precision, increase the speed of measurement, and reduce the weight, size, power consumption and data rate of the instrument. Under contract NAG5-419 these improvements were implemented and are what characterize the Advanced Langmuir Probe (ALP). Using data from the Langmuir Probe on the Pioneer Venus Orbiter, Brace and Walter Hoegy of GSFC demonstrated a novel method of monitoring the solar extreme ultraviolet (EUV) flux. This led to the idea of developing a sensor similar to a Langmuir probe specifically designed to measure solar EUV (SEUV) that uses a similar electronics package. Under this contract, a combined instrument package of the ALP and SEUV sensor was to be designed, constructed, and laboratory tested. Finally the instrument was to be flight tested as part of sounding rocket experiment to acquire the necessary data to validate this method for possible use in future earth and planetary aeronomy missions. The primary purpose of this contract was to develop the electronics hardware and software for this instrument, since the actual sensors were suppied by GSFC. Due to budget constraints, only a flight model was constructed. These electronics were tested and calibrated in the laboratory, and then the instrument was integrated into the rocket payload at Wallops Flight Facility where it underwent environmental testing. After instrument recalibration at SPRL, the payload was reintegrated and launched from the Poker Flat Research Range near Fairbanks Alaska. The payload was successfully recovered and after refurbishment underwent further testing and developing to improve its performance for future use

Tethered Satellites as Enabling Platforms for an Operational Space Weather Monitoring System

Space weather nowcasting and forecasting models require assimilation of nearreal time (NRT) space environment data to improve the precision and accuracy of operational products. Typically, these models begin with a climatological model to provide "most probable distributions" of environmental parameters as a function of time and space. The process of NRT data assimilation gently pulls the climate model closer toward the observed state (e.g. via Kalman smoothing) for nowcasting, and forecasting is achieved through a set of iterative physicsbased forwardprediction calculations. The issue of required space weather observatories to meet the spatial and temporal requirements of these models is a complex one, and we do not address that with this poster. Instead, we present some examples of how tethered satellites can be used to address the shortfalls in our ability to measure critical environmental parameters necessary to drive these space weather models. Examples include very long baseline electric field measurements, magnetized ionospheric conductivity measurements, and the ability to separate temporal from spatial irregularities in environmental parameters. Tethered satellite functional requirements will be presented for each space weather parameter considered in this study

Unlearning through Mad Studies: Disruptive pedagogical praxis

Medical discourse currently dominates as the defining framework for madness in educational praxis. Consequently, ideas rooted in a mental health/illness binary abound in higher learning, as both curriculum content and through institutional procedures that reinforce structures of normalcy. While madness, then, is included in university spaces, this inclusion proceeds in ways that continue to pathologize madness and disenfranchise mad people. This paper offers Mad Studies as an alternative entry point for engaging with madness in higher education, arguing that centring madness in pedagogical praxis has the potential to interrupt hegemonic ways of knowing, being, and learning. We illustrate how this disruption is facilitated by examining particular aspects of pedagogical praxis mobilized in Mad Studies, including building curriculum alongside mad community, centring madness in course design and student assessment, and the practice of mad positivity. Ultimately, this approach provides a metacurriculum of unlearning, challenging students to consider how their engagement with madness in the classroom, and beyond, has the potential to disrupt sanist systems of oppression and the normalcy they reconstitute

Best practice framework for Patient and Public Involvement (PPI) in collaborative data analysis of qualitative mental health research: methodology development and refinement

Background Patient and Public Involvement (PPI) in mental health research is increasing, especially in early (pre-funding) stages. PPI is less consistent in later stages, including in analysing qualitative data. The aims of this study were to develop a methodology for involving PPI co-researchers in collaboratively analysing qualitative mental health research data with academic researchers, to pilot and refine this methodology, and to create a best practice framework for collaborative data analysis (CDA) of qualitative mental health research. Methods In the context of the RECOLLECT Study of Recovery Colleges, a critical literature review of collaborative data analysis studies was conducted, to identify approaches and recommendations for successful CDA. A CDA methodology was developed and then piloted in RECOLLECT, followed by refinement and development of a best practice framework. Results From 10 included publications, four CDA approaches were identified: (1) consultation, (2) development, (3) application and (4) development and application of coding framework. Four characteristics of successful CDA were found: CDA process is co-produced; CDA process is realistic regarding time and resources; demands of the CDA process are manageable for PPI co-researchers; and group expectations and dynamics are effectively managed. A four-meeting CDA process was piloted to o-produce a coding framework based on qualitative data collected in RECOLLECT and to create a mental health service user-defined change model relevant to Recovery Colleges. Formal and informal feedback demonstrated active involvement. The CDA process involved an extra 80 person-days of time (40 from PPI coresearchers, 40 from academic researchers).The process was refined into a best practice framework comprising Preparation, CDA and Application phases. Conclusions This study has developed a typology of approaches to collaborative analysis of qualitative data in mental health research, identified from available evidence the characteristics of successful involvement, and developed, piloted and refined the first best practice framework for collaborative analysis of qualitative data. This framework has the potential to support meaningful PPI in data analysis in the context of qualitative mental health research studies, a previously neglected yet central part of the research cycle