Sinc-Galerkin estimation of diffusivity in parabolic problems

A fully Sinc-Galerkin method for the numerical recovery of spatially varying diffusion coefficients in linear partial differential equations is presented. Because the parameter recovery problems are inherently ill-posed, an output error criterion in conjunction with Tikhonov regularization is used to formulate them as infinite-dimensional minimization problems. The forward problems are discretized with a sinc basis in both the spatial and temporal domains thus yielding an approximate solution which displays an exponential convergence rate and is valid on the infinite time interval. The minimization problems are then solved via a quasi-Newton/trust region algorithm. The L-curve technique for determining an approximate value of the regularization parameter is briefly discussed, and numerical examples are given which show the applicability of the method both for problems with noise-free data as well as for those whose data contains white noise

Integration issues of a plasma contactor Power Electronics Unit

A hollow cathode-based plasma contactor is baselined on International Space Station Alpha (ISSA) for spacecraft charge control. The plasma contactor system consists of a hollow cathode assembly (HCA), a power electronics unit (PEU), and an expellant management unit (EMU). The plasma contactor has recently been required to operate in a cyclic mode to conserve xenon expellant and extend system life. Originally, a DC cathode heater converter was baselined for a continuous operation mode because only a few ignitions of the hollow cathode were expected. However, for cyclic operation, a DC heater supply can potentially result in hollow cathode heater component failure due to the DC electrostatic field. This can prevent the heater from attaining the proper cathode tip temperature for reliable ignition of the hollow cathode. To mitigate this problem, an AC cathode heater supply was therefore designed, fabricated, and installed into a modified PEU. The PEU was tested using resistive loads and then integrated with an engineering model hollow cathode to demonstrate stable steady-state operation. Integration issues such as the effect of line and load impedance on the output of the AC cathode heater supply and the characterization of the temperature profile of the heater under AC excitation were investigated

Education Leadership Data Analytics (ELDA): A White Paper Report on the 2018 ELDA Summit

Education Leadership Data Analytics (ELDA) is an emerging domain that is centered at the intersection of education leadership, the use of evidence-based improvement cycles in schools to promote instructional improvement, and education data science. ELDA practitioners work collaboratively with school and district leaders and teachers to analyze, pattern, and visualize previously unknown patterns and information from the vast sets of data collected by schooling organizations, and then integrate findings in easy to understand language and digital tools into collaborative and community-building evidence-based improvement cycles with stakeholders. In June of 2018, over 100 participants gathered for the Education Leadership Data Analytics Summit at Teachers College, Columbia University in New York City, including researchers, practitioners, policymakers, and funders. This report provides a summary of the central issues, themes, and recommendations for the future of the field that emerged from the discussions at the ELDA Summit event. These issues include building capacity in the field through incentivizing researcher practitioner partnerships, and providing conference and networking opportunities, professional development, certification, and ultimately degree programs to train ELDA researchers and practitioners. Additionally, a central focus of the ELDA field is equity, data security and privacy, in concert with open and FAIR data standards to develop and share de-identified data and tools across contexts. We conclude the report with a blueprint of possible skills and competencies needed for ELDA practitioner training and professional development and provide recommendations for next steps to help grow the field

Expressions 2021

https://openspace.dmacc.edu/expressions/1037/thumbnail.jp

Detection of emotions in Parkinson's disease using higher order spectral features from brain's electrical activity

Non-motor symptoms in Parkinson's disease (PD) involving cognition and emotion have been progressively receiving more attention in recent times. Electroencephalogram (EEG) signals, being an activity of central nervous system, can reflect the underlying true emotional state of a person. This paper presents a computational framework for classifying PD patients compared to healthy controls (HC) using emotional information from the brain's electrical activity

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

Anopheles gambiae Antiviral Immune Response to Systemic O'nyong-nyong Infection

Mosquito-borne viral diseases are found across the globe and are responsible for numerous severe human infections. In order to develop novel methods for prevention and treatment of these diseases, detailed understanding of the biology of viral infection and transmission is required. Little is known about invertebrate responses to infection in mosquito hosts. In this study we used a model system of Anopheles gambiae mosquitoes and O'nyong-nyong virus to study mosquito immune responses to infection. We examined the global transcriptional responses of A. gambiae to viral infection of the mosquito blood equivalent (the hemolymph) identifying a number of genes with immune functions that are switched on or off in response to infection, including complement-like proteins that circulate in the mosquito hemolymph. The switching on of these genes combined with co-infection experiments with malaria parasites suggests that viral infection inhibits the melanisation pathway. Through silencing the function of a selection of viral responsive genes, we identified four genes that have roles in A. gambiae anti-viral immunity; two putative recognition receptors (a galectin and an MD2-like receptor); two effector lysozymes. These molecules have previously non-described roles in antiviral immunity, and suggest uncharacterised mechanisms for targeting viral infection in A. gambiae mosquitoes

A behavioral database for masked form priming

Reading involves a process of matching an orthographic input with stored representations in lexical memory. The masked priming paradigm has become a standard tool for investigating this process. Use of existing results from this paradigm can be limited by the precision of the data and the need for cross-experiment comparisons that lack normal experimental controls. Here, we present a single, large, high-precision, multicondition experiment to address these problems. Over 1,000 participants from 14 sites responded to 840 trials involving 28 different types of orthographically related primes (e.g., castfe–CASTLE) in a lexical decision task, as well as completing measures of spelling and vocabulary. The data were indeed highly sensitive to differences between conditions: After correction for multiple comparisons, prime type condition differences of 2.90 ms and above reached significance at the 5% level. This article presents the method of data collection and preliminary findings from these data, which included replications of the most widely agreed-upon differences between prime types, further evidence for systematic individual differences in susceptibility to priming, and new evidence regarding lexical properties associated with a target word’s susceptibility to priming. These analyses will form a basis for the use of these data in quantitative model fitting and evaluation and for future exploration of these data that will inform and motivate new experiments