Family Unity, Family Health: How Family-Focused Immigration Reform Will Mean Better Health for Children and Families

This report builds on a body of evidence on the impact of immigration policy on communities, paying particular attention to the health and mental health of children and families.Using existing research, predictive quantitative analysis and data from a convenience survey and two focus groups, this reportshines a light on the consequences of a continued policy of detention and deportation on: physical health, mental health, educational and behavioral outcomes among children; adult health status and lifespan; and economic hardship and food access in households

Circadian rest-activity rhythms predict cognitive function in early Parkinson's disease independently of sleep

BACKGROUND: Cognitive impairment is a common and debilitating symptom of Parkinson's disease (PD), and its etiology is likely multifactorial. One candidate mechanism is circadian disruption. Although there is evidence of circadian abnormalities in PD, no studies have directly assessed their association with cognitive impairment. OBJECTIVES: Investigate whether circadian rest-activity rhythm is associated with cognitive function in PD independently of sleep. METHODS: Thirty-five participants with PD wore wrist actigraph monitors and completed sleep diaries for 7 to 10 days, then underwent neuropsychological testing. Rest-activity rhythm was characterized using nonparametric circadian rhythm analysis of actigraphy data. Objective sleep parameters were also estimated using actigraphy data. Hierarchical regression models assessed the independent contributions of sleep and rest-activity rhythm to cognitive performance. RESULTS: Less stable day-to-day rest-activity rhythm was associated with poorer executive, visuospatial, and psychomotor functioning, but not with memory. Hierarchical regressions showed that interdaily stability's contribution to cognitive performance was independent of sleep's contributions. Whereas sleep contributed to executive function, but not psychomotor or visuospatial performance, rest-activity rhythm stability significantly contributed to variance in all three of these domains, uniquely accounting for 14.4% to 17.6% of their performance variance. CONCLUSIONS: Our findings indicate that circadian rest-activity rhythm is associated with cognitive impairment independently of sleep. This suggests the possible utility of rest-activity rhythm as a biomarker for circadian function in PD. Future research should explore interventions to stabilize behavioral rhythms in order to strengthen circadian function, which, in turn, may reduce cognitive impairment in PD.R00 HL102241 - NHLBI NIH HHS; R01 AG048108 - NIA NIH HHSAccepted manuscrip

A Simple and Efficient Method for Preparing Cell Slides and Staining without Using Cytocentrifuge and Cytoclips

Cell staining is a necessary and useful technique for visualizing cell morphology and structure under a microscope. This technique has been used in many areas such as cytology, hematology, oncology, histology, virology, serology, microbiology, cell biology, and immunochemistry. One of the key pieces of equipment for preparing a slide for cell staining is cytology centrifuge (cytocentrifuge) such as cytospin. However, many small labs do not have this expensive equipment and its accessory, cytoclips (also expensive relatively), which makes them difficult to study cell cytology. Here we present an alternative method for preparing a slide and cell staining in the absence of a cytocentrifuge (and cytoclips). This method is based on the principle that a regular cell centrifuge can be used to concentrate cells harvested from cell culture and then deposit the concentrated cell suspension to a slide evenly by using a cell spreader, followed by cell staining. The method presented is simple, rapid, economic, and efficient. This method may also avoid a possible change in cell morphology induced by cytocentrifuge

Magnetars as Astrophysical Laboratories of Extreme Quantum Electrodynamics: The Case for a Compton Telescope

A next generation of Compton and pair telescopes that improve MeV-band detection sensitivity by more than a decade beyond current instrumental capabilities will open up new insights into a variety of astrophysical source classes. Among these are magnetars, the most highly magnetic of the neutron star zoo, which will serve as a prime science target for a new mission surveying the MeV window. This paper outlines the core questions pertaining to magnetars that can be addressed by such a technology. These range from global magnetar geometry and population trends, to incisive probes of hard X-ray emission locales, to providing cosmic laboratories for spectral and polarimetric testing of exotic predictions of QED, principally the prediction of the splitting of photons and magnetic pair creation. Such fundamental physics cannot yet be discerned in terrestrial experiments. State of the art modeling of the persistent hard X-ray tail emission in magnetars is presented to outline the case for powerful diagnostics using Compton polarimeters. The case highlights an inter-disciplinary opportunity to seed discovery at the interface between astronomy and physics.Comment: 11 pages, 4 figures, Astro2020 Science White Paper submitted to the National Academies of Science

Diagnosing and predicting wind turbine faults from SCADA data using support vector machines

Unscheduled or reactive maintenance on wind turbines due to component failure incurs significant downtime and, in turn, loss of revenue. To this end, it is important to be able to perform maintenance before it's needed. To date, a strong effort has been applied to developing Condition Monitoring Systems (CMSs) which rely on retrofitting expensive vibration or oil analysis sensors to the turbine. Instead, by performing complex analysis of existing data from the turbine's Supervisory Control and Data Acquisition (SCADA) system, valuable insights into turbine performance can be obtained at a much lower cost. In this paper, fault and alarm data from a turbine on the Southern coast of Ireland is analysed to identify periods of nominal and faulty operation. Classification techniques are then applied to detect and diagnose faults by taking into account other SCADA data such as temperature, pitch and rotor data. This is then extended to allow prediction and diagnosis in advance of specific faults. Results are provided which show recall scores generally above 80\% for fault detection and diagnosis, and prediction up to 24 hours in advance of specific faults, representing significant improvement over previous techniques

Unleashing Quantum Simulation Advantages: Hamiltonian Subspace Encoding for Resource Efficient Quantum Simulations

Number-conserved subspace encoding for fermionic Hamiltonians, which exponentially reduces qubit cost, is necessary for quantum advantages in variational quantum eigensolver (VQE). However, optimizing the trade-off between qubit compression and increased measurement cost poses a challenge. By employing the Gilbert-Varshamov bound on linear code, we optimize qubit scaling $\mathcal{O}(N\log_2M)$ and measurement cost $\mathcal{O}(M^4)$ for $M$ modes $N$ electrons chemistry problems. The compression is implemented with the Randomized Linear Encoding (RLE) algorithm on VQE for $\text{H}_2$ and LiH in the 6-31G* and STO-3G/6-31G* basis respectively. The resulting subspace circuit expressivity and trainability are enhanced with less circuit depth and higher noise tolerance

Impact of stressful life events on central adiposity in the Pelotas Birth Cohort

OBJECTIVE: To investigate how stressful life events and social support relate to central adiposity in Southern Brazil. METHODS: Data included information from 802 participants in the 1982 Pelotas Birth Cohort that was collect in 2004–2005 and 2006. Stratifying by sex, we studied self-reported stressful life events during the year before 2004–2005 in relation to change in waist circumference between 2004–2005 and 2006 and waist-to-hip ratio in 2006, using both bivariate and multivariate linear regression models. RESULTS: In adjusted models, the experience of stressful life events during the year before 2004–2005 predicted a change in waist circumference in 2006 in men and a change in both waist-to-hip ratio in 2006 and waist circumference between 2004–2005 and 2006 in women. Men who experienced two or more stressful events had on average a one centimeter increase in their waist circumference between 2004–2005 and 2006 (β = 0.97, 95%CI 0.02–1.92), compared to those reporting no stressful events. For women, those who had one and those who had two or more stressful life events had over a 1 cm increase in their waist circumference from 2004–2005 to 2006 (β = 1.37, 95%CI 0.17–2.54; β = 1.26, 95%CI 0.11–2.40, respectively), compared to those who did not experience any stressful event. For both sexes, social support level was not significantly related to either waist-to-hip ratio or change in waist circumference, and it did not modify the association between stress and central adiposit

Twin identification over viewpoint change: A deep convolutional neural network surpasses humans

Deep convolutional neural networks (DCNNs) have achieved human-level accuracy in face identification (Phillips et al., 2018), though it is unclear how accurately they discriminate highly-similar faces. Here, humans and a DCNN performed a challenging face-identity matching task that included identical twins. Participants (N=87) viewed pairs of face images of three types: same-identity, general imposter pairs (different identities from similar demographic groups), and twin imposter pairs (identical twin siblings). The task was to determine whether the pairs showed the same person or different people. Identity comparisons were tested in three viewpoint-disparity conditions: frontal to frontal, frontal to 45-degree profile, and frontal to 90-degree profile. Accuracy for discriminating matched-identity pairs from twin-imposters and general imposters was assessed in each viewpoint-disparity condition. Humans were more accurate for general-imposter pairs than twin-imposter pairs, and accuracy declined with increased viewpoint disparity between the images in a pair. A DCNN trained for face identification (Ranjan et al., 2018) was tested on the same image pairs presented to humans. Machine performance mirrored the pattern of human accuracy, but with performance at or above all humans in all but one condition. Human and machine similarity scores were compared across all image-pair types. This item-level analysis showed that human and machine similarity ratings correlated significantly in six of nine image-pair types [range r=0.38 to r=0.63], suggesting general accord between the perception of face similarity by humans and the DCNN. These findings also contribute to our understanding of DCNN performance for discriminating high-resemblance faces, demonstrate that the DCNN performs at a level at or above humans, and suggest a degree of parity between the features used by humans and the DCNN