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City Beautiful leader J. Horace McFarland and Herman Miller, working with landscape designer and urban planner Warren Manning, conceived and developed Bellevue Park in the 1910s and 1920s as Pennsylvania's first fully planned suburban community at the eastern edge of Harrisburg's city limits. They committed to creating a stylistically consistent and rationally designed environment, focus on preserving and enhancing the natural landscape, belief in the power of natural and human-made beauty to uplift, and preference for neoclassical Colonial Revival forms. McFarland, Miller, and Manning—joined by the new neighborhood's first residents—applied City Beautiful approaches and values previously applied to civic and other public spaces to a new sphere: the private and domestic.

In the 1920s Harrisburg's acculturated Reform and Conservative Jews found in City Beautiful aesthetics and ideals the architecture and ideology appropriate for expressing publicly their cultural identity as thoroughly modern Americans and Jews. Temple Beth El and Temple Ohev Sholom, both built on Front Street in uptown Harrisburg, stand as the ultimate material outcome and testimony to the synergistic interweaving of early twentieth century American and Jewish progressivism. A book commemorating Temple Beth El's 1928 dedication, produced by J. Horace McFarland's Mount Pleasant Press in 1930, documents in word and image connections between the founding of the congregation, the building of its temple, and the sensibilities and goals of the City Beautiful movement.

Multiple system atrophy is a rare, fatal neurodegenerative disorder with symptoms of autonomic failure plus parkinsonism, cerebellar ataxia, or both. We report results of the first prospective natural history study of multiple system atrophy in the USA, and the effects of phenotype and autonomic failure on prognosis. We recruited participants with probable multiple system atrophy—of either the parkinsonism subtype (MSA-P) or the cerebellar ataxia subtype (MSA-C)—at 12 neurology centres in the USA specialising in movement or autonomic disorders. We followed up patients every 6 months for 5 years and assessed them with the Unified Multiple System Atrophy Rating Scale part I (UMSARS I; a functional score of symptoms and ability to undertake activities of daily living), UMSARS II (neurological motor evaluation), and the Composite Autonomic Symptoms Scale (COMPASS)-select (a measure of autonomic symptoms and autonomic functional status). We assessed potential predictors of outcome. We used Cox proportional hazards models to calculate univariate hazard ratios for shorter survival using age at disease onset as a continuous variable and sex, clinical phenotype, and early development of neurological and autonomic manifestations as categorical variables. We recruited 175 participants. Mean age at study entry was 63·4 years (SD 8·6). Median survival from symptom onset was 9·8 years (95% CI 8·8–10·7) and median survival from enrolment was 1·8 years (0·9–2·7). Participants with severe symptomatic autonomic failure (symptomatic orthostatic hypotension, urinary incontinence, or both) at diagnosis (n=62) had a worse prognosis than those without severe disease (n=113; median survival 8·0 years, 95% CI 6·5–9·5 vs 10·3 years, 9·3–11·4; p=0·021). At baseline, patients with MSA-P (n=126) and MSA-C (n=49) had much the same symptoms and functional status: mean UMSARS I 25·2 (SD 8·08) versus 24·6 (8·34; p=0·835); mean UMSARS II 26·4 (8·8) versus 25·4 (10·5; p=0·764); COMPASS-select 43·5 (18·7) versus 42·8 (19·6; p=0·835). Progression over 5 years, assessed by change in UMSARS I, UMSARS II, and COMPASS-select, was modest. Probable multiple system atrophy is a late-stage disease with short survival. The natural histories of MSA-P and MSA-C are similar and severe symptomatic autonomic failure at diagnosis is associated with worse prognosis. US National Institutes of Health, Mayo Clinic, and Kathy Shih Memorial Foundation.

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

Cosmic neutrinos provide a unique window into the otherwise hidden mechanism of particle acceleration in astrophysical objects. The IceCube Collaboration recently reported the likely association of one high-energy neutrino with a flare from the relativistic jet of an active galaxy pointed towards the Earth. However a combined analysis of many similar active galaxies revealed no excess from the broader population, leaving the vast majority of the cosmic neutrino flux unexplained. Here we present the likely association of a radio-emitting tidal disruption event, AT2019dsg, with a second high-energy neutrino. AT2019dsg was identified as part of our systematic search for optical counterparts to high-energy neutrinos with the Zwicky Transient Facility. The probability of finding any coincident radio-emitting tidal disruption event by chance is 0.5%, while the probability of finding one as bright in bolometric energy flux as AT2019dsg is 0.2%. Our electromagnetic observations can be explained through a multizone model, with radio analysis revealing a central engine, embedded in a UV photosphere, that powers an extended synchrotron-emitting outflow. This provides an ideal site for petaelectronvolt neutrino production. Assuming that the association is genuine, our observations suggest that tidal disruption events with mildly relativistic outflows contribute to the cosmic neutrino flux. The tidal disruption event AT2019dsg is probably associated with a high-energy neutrino, suggesting that such events can contribute to the cosmic neutrino flux. The electromagnetic emission is explained in terms of a central engine, a photosphere and an extended synchrotron-emitting outflow.

SRX246 is a vasopressin (AVP) 1a receptor antagonist that crosses the blood-brain barrier. It reduced impulsive aggression, fear, depression and anxiety in animal models, blocked the actions of intranasal AVP on aggression/fear circuits in an experimental medicine fMRI study and demonstrated excellent safety in Phase 1 multiple-ascending dose clinical trials. The present study was a 3-arm, multicenter, randomized, placebo-controlled, double-blind, 12-week, dose escalation study of SRX246 in early symptomatic Huntington’s disease (HD) patients with irritability. Our goal was to determine whether SRX246 was safe and well tolerated in these HD patients given its potential use for the treatment of problematic neuropsychiatric symptoms. Participants were randomized to receive placebo or to escalate to 120 mg twice daily or 160 mg twice daily doses of SRX246. Assessments included standard safety tests, the Unified Huntington’s Disease Rating Scale (UHDRS), and exploratory measures of problem behaviors. The groups had comparable demographics, features of HD and baseline irritability. Eighty-two out of 106 subjects randomized completed the trial on their assigned dose of drug. One-sided exact-method confidence interval tests were used to reject the null hypothesis of inferior tolerability or safety for each dose group vs. placebo. Apathy and suicidality were not affected by SRX246. Most adverse events in the active arms were considered unlikely to be related to SRX246. The compound was safe and well tolerated in HD patients and can be moved forward as a candidate to treat irritability and aggression.

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

Good education requires student experiences that deliver lessons about practice as well as theory and that encourage students to work for the public good—especially in the operation of democratic institutions (Dewey 1923; Dewy 1938). We report on an evaluation of the pedagogical value of a research project involving 23 colleges and universities across the country. Faculty trained and supervised students who observed polling places in the 2016 General Election. Our findings indicate that this was a valuable learning experience in both the short and long terms. Students found their experiences to be valuable and reported learning generally and specifically related to course material. Postelection, they also felt more knowledgeable about election science topics, voting behavior, and research methods. Students reported interest in participating in similar research in the future, would recommend other students to do so, and expressed interest in more learning and research about the topics central to their experience. Our results suggest that participants appreciated the importance of elections and their study. Collectively, the participating students are engaged and efficacious—essential qualities of citizens in a democracy.

The origins of the high-energy cosmic neutrino flux remain largely unknown. Recently, one high-energy neutrino was associated with a tidal disruption event (TDE). Here we present AT2019fdr, an exceptionally luminous TDE candidate, coincident with another high-energy neutrino. Our observations, including a bright dust echo and soft late-time X-ray emission, further support a TDE origin of this flare. The probability of finding two such bright events by chance is just 0.034%. We evaluate several models for neutrino production and show that AT2019fdr is capable of producing the observed high-energy neutrino, reinforcing the case for TDEs as neutrino sources.