Stink Bugs (Hemiptera: Heteroptera: Pentatomidae) of Minnesota: An Annotated Checklist and New State Records

Pentatomidae have been relatively poorly documented in Minnesota. Based on literature and museum records, an annotated checklist of the Pentatomidae of Minnesota was created. State-level and county-level records for Minnesota and the distribution of each species in North America are provided. Fifty-one species of Pentatomidae (12 Asopinae, 37 Pentatominae, and 2 Podopinae) are recorded for Minnesota. Of this total, 15 species are newly recorded for the state. Knowledge of the fauna of Pentatomidae in Minnesota will be important for providing baseline data for monitoring of potential shifts in the fauna resulting from the invasions of exotic Pentatomidae. Furthermore, a list of native Pentatomidae will be necessary for monitoring non-target impacts, if classical biological control is implemented for management of exotic Pentatomidae

Long-Run Earnings Mobility among Low-Income Individuals

We construct earnings mobility matrices for low-income individuals over 6-year and 13-year periods. Our sample of low-income individuals is drawn from the population of SNAP recipients in Georgia. Using Georgia administrative records, we identify SNAP participants in 2000 and their earnings for each year through 2013 using matched employment security records. We find that a substantial percentage of these individuals have zero earnings in both the initial and ending years. We find that there is a heavier concentration of males, whites, and disabled individuals with zero earnings in the initial and ending years than in the overall SNAP sample. This contradicts some of the characterizations of SNAP recipients in the popular press which often characterizes those stuck in poverty as single black mothers. In fact, the disabled represent the vast majority of those stuck in the no earnings category. Another interesting finding is that single mothers with zero earnings in 2000 have a greater probability, in some cases a much greater probability, of escaping the zero earnings category than the general population of SNAP recipients. We also find that individuals with positive earnings in the initial year experience substantial earnings mobility

Designing Good Partial Coverage Satellite Constellations

Design of satellite constellations providing partial coverage of certain ground regions is becoming more important as small low-altitude satellites receive increased attention. The purpose of this study is to develop the procedures necessary for deriving the best constellations for partial coverage

Teager-Kaiser Operator improves the accuracy of EMG onset detection independent of signal-to-noise ratio

A temporal analysis of electromyographic (EMG) activity has widely been used for non-invasive study of muscle activation patterns. Such an analysis requires robust methods to accurately detect EMG onset. We examined whether data conditioning, supplemented with Teager–Kaiser Energy Operator (TKEO), would improve accuracy of the EMG burst onset detection. EMG signals from vastus lateralis, collected during maximal voluntary contractions, performed by seventeen subjects (8 males, 9 females, mean age of 46 yrs), were analyzed. The error of onset detection using enhanced signal conditioning was significantly lower than that of onset detection performed on signals conditioned without the TKEO (40 ±99 ms vs. 229 ±356 ms, t-test, p = 0.023). The Pearson correlations revealed that neither accuracy after enhanced conditioning nor accuracy after standard conditioning was significantly related to signal-to-noise ratio (SNR) (r = −0.05, p = 0.8 and r = −0.19, p = 0.46, respectively). It is concluded that conditioning of the EMG signals with TKEO significantly improved the accuracy of the threshold-based onset detection methods, regardless of SNR magnitude. Originally published Acta Bioeng Biomech, Vol. 10, No. 2, 200

Accelerator Design for the CHESS-U Upgrade

During the summer and fall of 2018 the Cornell High Energy Synchrotron Source (CHESS) is undergoing an upgrade to increase high-energy flux for x-ray users. The upgrade requires replacing one-sixth of the Cornell Electron Storage Ring (CESR), inverting the polarity of half of the CHESS beam lines, and switching to single-beam on-axis operation. The new sextant is comprised of six double-bend achromats (DBAs) with combined-function dipole-quadrupoles. Although the DBA design is widely utilized and well understood, the constraints for the CESR modifications make the CHESS-U lattice unique. This paper describes the design objectives, constraints, and implementation for the CESR accelerator upgrade for CHESS-U

Sleep physiology and executive function during chronic partial sleep restriction

Introduction: The detrimental effects of sleep deprivation on waking performance are well documented, but questions remain regarding the relationship between sleep physiology and specific domains of cognitive function. Research suggests sleep may also play a role in waking executive functions. However, the existing studies investigating executive functioning have generally been carried out under conditions of total sleep deprivation and only in one instance was the specific relationship between physiological sleep stages and waking executive function investigated. Methods: In this study, N = 137 (22 – 45y, 77m, 60f) participants completed a chronic sleep restriction protocol of four hours time in bed for sleep for five consecutive nights. Following sleep restriction, the Hayling and Brixton tests of executive functioning (HBT) were administered. Sleep variables, recorded the night prior to test administration, were regressed on the HBT measures. In a secondary analysis, the performance of a small group of control participants was compared to the group of sleep restricted participants using t-tests. Results: The results supported our hypothesis that slow wave sleep would be the best predictor of subsequent performance on tests of executive function, though the amount of variability accounted for was less than 10%. Additionally, the performance of sleep restricted individuals was relatively worse than individuals obtaining normal sleep on certain measures of cognitive functioning, including attention and certain aspects of executive function. Discussion: These findings indicate that having more slow wave sleep during sleep restriction predicts fewer errors, shorter response latencies, and better overall performance on tests of executive function. Implications are discussed for clinical neuropsychological practice with respect to the potential impact of sleep loss on neuropsychological testing.M.S., Clinical Psychology -- Drexel University, 6/5

Exploring the relationship between mindfulness in waking and lucidity in dreams

The continuity theory of dreaming proposes that waking and dreaming rely on a shared set of brain-mind processes. Research in the fields of lucid dreaming and mindfulness suggest continuity of certain neurocognitive processes. Specifically, the high levels of attention, reflection, self-awareness, volition, and control which are hypothesized to be related to lucidity are presumed here to be continuous with waking mindfulness. This study aimed to investigate relationships between: 1) Mindfulness in waking and lucidity/mindfulness in dreaming; 2) Neuropsychological functions related to mindfulness and lucidity/mindfulness in dreaming; and 3) Neuropsychological functions and subjective mindfulness in waking.N = 44 participants completed measures of general and recent mindfulness skills and a battery of neuropsychological tests. Each morning for seven days following this initial assessment, participants rated their levels of lucidity, cognitive functioning, sensory and emotional intensity from their preceding night’s dream. Relationships between waking mindfulness levels, neuropsychological functions, and dream variables were evaluated using a correlational design.Waking mindfulness did not account for a significant amount of variance in dream lucidity, but did account for a significant amount of variance in dream mindfulness. Correlations between dream lucidity and neuropsychological measures were not significant. However, better performances on two neuropsychological measures (sustained attention and behavioral self-monitoring) were moderately correlated with dream mindfulness. Also, general mindful awareness and recent mindful acceptance were positively associated with sustained attention and behavioral self-monitoring.Significant relationships found between waking mindfulness and dream mindfulness provide support for continuity theory. Mindfulness appears to be expressed in dreams to a degree that is consistent with recent and general levels of mindful awareness. The relationships between neuropsychological functions and dream mindfulness suggest a shared brain bases for attention and behavioral self-monitoring across dreaming and waking. The failure to find a relationship between lucidity and any of the variables assessed in waking in this study may be due to methodological limitations. Alternatively, while high levels of attention, reflection, volition, self-awareness, and control are often observed in lucid dreams, they may not be exclusive to lucid dreams.Ph.D., Clinical Psychology -- Drexel University, 201

Central limit theorems for the real eigenvalues of large Gaussian random matrices

Let G be an N×N real matrix whose entries are independent identically distributed standard normal random variables Gij∼N(0,1). The eigenvalues of such matrices are known to form a two-component system consisting of purely real and complex conjugated points. The purpose of this paper is to show that by appropriately adapting the methods of [E. Kanzieper, M. Poplavskyi, C. Timm, R. Tribe and O. Zaboronski, Annals of Applied Probability 26(5) (2016) 2733–2753], we can prove a central limit theorem of the following form: if λ1,…,λNR are the real eigenvalues of G, then for any even polynomial function P(x) and even N=2n, we have the convergence in distribution to a normal random variable 1E(NR)−−−−−√⎛⎝∑j=1NRP(λj/2n−−√)−E∑j=1NRP(λj/2n−−√)⎞⎠→N(0,σ2(P)) as n→∞, where σ2(P)=2−2√2∫1−1P(x)2dx