Abstract. With the first direct detection of gravitational waves, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) has initiated a new field of astronomy by providing an alternate means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of time-frequency representations of glitches into preidentified morphological classes and to discover new classes that appear as the detectors arXiv:1611.04596v2 [gr-qc]
In early-stage breast cancer, the primary treatment option for most women is breast-conserving surgery (BCS). There is a clear need for more accurate techniques to assess resection margins intraoperatively, because on average 20% of patients require further surgery to achieve clear margins. Cerenkov luminescence imaging (CLI) combines optical and molecular imaging by detecting light emitted by 18 F-FDG. Its high-resolution and small size imaging equipment make CLI a promising technology for intraoperative margin assessment. A first-in-human study was conducted to evaluate the feasibility of 18 F-FDG CLI for intraoperative assessment of tumor margins in BCS. Methods: Twenty-two patients with invasive breast cancer received 18 F-FDG (5 MBq/kg) 45-60 min before surgery. Sentinel lymph node biopsy was performed using an increased 99m Tc-nanocolloid activity of 150 MBq to facilitate nodal detection against the g-probe background signal (cross-talk) from 18 F-FDG. The cross-talk and 99m Tc dose required was evaluated in 2 lead-in studies. Immediately after excision, specimens were imaged intraoperatively in an investigational CLI system. The first 10 patients were used to optimize the imaging protocol; the remaining 12 patients were included in the analysis dataset. Cerenkov luminescence images from incised BCS specimens were analyzed postoperatively by 2 surgeons blinded to the histopathology results, and mean radiance and margin distance were measured. The agreement between margin distance on CLI and histopathology was assessed. Radiation doses to staff were measured. Results: Ten of the 12 patients had an elevated tumor radiance on CLI. Mean radiance and tumor-to-background ratio were 560 6 160 photons/s/cm 2 /sr and 2.41 6 0.54, respectively. All 15 assessable margins were clear on CLI and histopathology. The agreement in margin distance and interrater agreement was good (k 5 0.81 and 0.912, respectively). Sentinel lymph nodes were successfully detected in all patients. The radiation dose to staff was low; surgeons received a mean dose of 34 6 15 mSv per procedure. Conclusion: Intraoperative 18 F-FDG CLI is a promising, low-risk technique for intraoperative assessment of tumor margins in BCS. A randomized controlled trial will evaluate the impact of this technique on reexcision rates. In early-stage breast cancer, the primary treatment option for most women is breast-conserving surgery (BCS) by wide local excision (WLE) of the tumor. WLE often fails to achieve clear surgical margins, and on average 20% of patients who undergo BCS will require repeated surgery to achieve clear margins (1) (although this may vary because there is no global agreement of the definition of clear margins). Reoperations potentially have several negative consequences including delayed commencement of adjuvant therapy, worse cosmesis, increased patient anxiety, and costs (2,3).There have been several attempts to assess surgical margins intraoperatively to reduce breast cancer reoperation rates after WLE (1). Techniques evaluated to date in...
K2-138 is a moderately bright (V=12.2, K=10.3) main-sequence K star observed in Campaign 12 of the NASA K2 mission. It hosts five small (1.6-3.3 R Å ) transiting planets in a compact architecture. The periods of the five planets are 2. 35, 3.56, 5.40, 8.26, and 12.76 days, forming an unbroken chain of near 3:2 resonances. Although we do not detect the predicted 2-5 minute transit timing variations (TTVs) with the K2 timing precision, they may be observable by higher-cadence observations with, for example, Spitzer or CHEOPS. The planets are amenable to mass measurement by precision radial velocity measurements, and therefore K2-138 could represent a new benchmark system for comparing radial velocity and TTV masses. K2-138 is the first exoplanet discovery by citizen scientists participating in the Exoplanet Explorers project on the Zooniverse platform.
A conceptual model of strong school-based interventions is presented. Strong interventions are ecological in nature, naturalistic in scope, contain elements from the research base that are predictive for success, and incorporate the constructs of social validity in a practical manner. The latter concept relates to the ideas of treatment acceptability and socially important outcomes, and is important for insuring treatment integrity. While there exists a robust research data base for effective school interventions, generalization to regular school settings without the overriding influence of researcher/consultant is difficult. Thus, all of these concepts must be practically utilized if strong interventions are to be applied to school problems. Suggestions and implications for school psychology practitioners are discussed.
The observation of gravitational waves from compact binary coalescences by LIGO and Virgo has begun a new era in astronomy. A critical challenge in making detections is determining whether loud transient features in the data are caused by gravitational waves or by instrumental or environmental sources. The citizen-science project Gravity Spy has been demonstrated as an efficient infrastructure for classifying known types of noise transients (glitches) through a combination of data analysis performed by both citizen volunteers and machine learning. We present the next iteration of this project, using similarity indices to empower citizen scientists to create large data sets of unknown transients, which can then be used to facilitate supervised machine-learning characterization. This new evolution aims to alleviate a persistent challenge that plagues both citizen-science and instrumental detector work: the ability to build large samples of relatively rare events. Using two families of transient noise that appeared unexpectedly during LIGO's second observing run (O2), we demonstrate the impact that the similarity indices could have had on finding these new glitch types in the Gravity Spy program. PACS numbers: 95.75.-z,04.30.-w,95.55.Ym
Multiple regression was used to determine the unique predictive contributions of several variables to problem-solving appraisal in 2 samples comprising 443 Ss, total. Problem-solving appraisal was the dependent variable, and the following variables were possible predictors: level of problemsolving skill; negative and positive coping strategies; internal-external locus of control; and a composite sum score of depression, trait anxiety, and self-concept. The combined multiple regression (SPSSX) results accounted for 50% and 41% of the variance for Samples 1 and 2, respectively, in problem-solving appraisal. The results revealed 2 consistent significant predictors: (a) positive coping strategies that seem to represent the process of doing something positively to solve problems through cognitive restructuring, focusing on the problem, and effecting interpersonal actions; and (b) global problem-solving self-efficacy.We gratefully acknowledge Terry Gutkin, for his assistance with earlier drafts of this article.
We evaluated the effectiveness of a dentist-implemented intervention in which brief escape from dental treatment was provided to manage disruptive child behavior during restorative dental treatment. Within a multiple baseline design across subjects, 4 children, aged 3 to 7 years, were provided temporary escape from dental treatment contingent upon brief periods of cooperative behavior. Disruptive behavior decreased when the appropriate escape contingency was used at least 80% of the time. The escape contingency required no more time than traditional management procedures (e.g., tell-show-do, reprimands and loud commands, restraint) to bring disruptive behavior under control. Independent ratings by two dentists provided social validation of the efficacy of the escape contingency.DESCRIPTORS: escape, negative reinforcement, dentistry, disruptive behavior, childrenThe adequacy ofthe behavior management skills of pediatric dentists has recently become a topic of debate, and with much justification. A recent survey found that over 60% ofpediatric dentists expressed concern about ethical, legal, or safety issues related to invasive management procedures, such as physical restraint, sedation, and a hand-over-mouth procedure. The survey found that nearly 25% of all children served present moderate to severe management problems, and the respondents requested alternatives for safe and cost-effective management of these difficult children. In response to these types of requests, the American Academy of Pediatric Dentistry recently issued a mandate to encourage and support research of new behavior management technology and to improve the education and training of dentists in behavior management techniques (American Academy of Pediatric Dentistry, 1988).At the time of this investigation the second author was a resident in pediatric dentistry and is now in private practice in Chicago. The third author was an intern in pediatric psychology and is now at the University of Rhode Island.Appreciation is extended to Trevor Stokes for valuable consultation in the initial stages ofthe project, toJohn Parrish for his editorial assistance, and to Brenda Kirby for assistance in data analysis.Correspondence and reprint requests may be addressed to
We present the results from the first two years of the Planet Hunters TESS (PHT) citizen science project, which identifies planet candidates in the TESS (Transiting Exoplanet Survey Satellite) data by engaging members of the general public. Over 22 000 citizen scientists from around the world visually inspected the first 26 sectors of TESS data in order to help identify transit-like signals. We use a clustering algorithm to combine these classifications into a ranked list of events for each sector, the top 500 of which are then visually vetted by the science team. We assess the detection efficiency of this methodology by comparing our results to the list of TESS Objects of Interest (TOIs) and show that we recover 85 per cent of the TOIs with radii greater than 4 R⊕ and 51 per cent of those with radii between 3 and 4 R⊕. Additionally, we present our 90 most promising planet candidates that had not previously been identified by other teams, 73 of which exhibit only a single-transit event in the TESS light curve, and outline our efforts to follow these candidates up using ground-based observatories. Finally, we present noteworthy stellar systems that were identified through the Planet Hunters TESS project.
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