OzDES reverberation mapping program: Lag recovery reliability for 6-yr C iv analysis

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 509.3 (2022): 4008-4023 is available online at: https://academic.oup.com/mnras/article-abstract/509/3/4008/6409154?redirectedFrom=fulltextArtículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, los autores pertenecientes a la UAM y el nombre del grupo de colaboración, si lo hubiereWe present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius-Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R-L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R-L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AG

Do facial first impressions reflect a shared social reality?

This work was supported by an Australian Research Council (ARC) Discovery Early Career Research Award to CS [DE 190101043], the ARC Centre of Excellence in Cognition and its Disorders [CE110001021], and an ARC Discovery Award [DP170104602]. The funding sources had no influence on the research.Peer reviewedPostprintPostprin

Sensor Data Analysis in Smart Buildings

Data analysis and Machine Learning are destined to evolve the current technology infrastructure by solving technology and economy demands present mainly in developed cities like New York. This research proposes a machine learning (ML) based solution to alleviate one of the main issues that big buildings such as CUNY campuses have, that is the waste of energy resources. The analysis of data coming from the readings of different deployed sensors such as CO2, humidity and temperature can be used to estimate occupancy in a specific room and building in general. The outcome of this research established a relationship between the CO2, temperature and humidity values of the room and occupancy by applying ML methods such as p-analysis, naive, logistic regression models, feature selection and others. The result, together with the implementation of an automatic infrastructure for light and HVAC systems, can be used to save money and resources

Decapentaplegic is required for arrest in G1 phase during Drosophila eye development

During eye development in Drosophila, cell cycle progression is coordinated with differentiation. Prior to differentiation, cells arrest in G1 phase anterior to and within the morphogenetic furrow. We show that Decapentaplegic (Dpp), a TGF-&bgr; family member, is required to establish this G1 arrest, since Dpp-unresponsive cells located in the anterior half of the morphogenetic furrow show ectopic S phases and ectopic expression of the cell cycle regulators Cyclins A, E and B. Conversely, ubiquitous over-expression of Dpp in the eye imaginal disc transiently inhibits S phase without affecting Cyclin E or Cyclin A abundance. This Dpp-mediated inhibition of S phase occurs independently of the Cyclin A inhibitor Roughex and of the expression of Dacapo, a Cyclin E-Cdk2 inhibitor. Furthermore, Dpp-signaling genes interact genetically with a hypomorphic cyclin E allele. Taken together our results suggest that Dpp acts to induce G1 arrest in the anterior part of the morphogenetic furrow by a novel inhibitory mechanism. In addition, our results provide evidence for a Dpp-independent mechanism that acts in the posterior part of the morphogenetic furrow to maintain G1 arrest

Pauci Immune crescentic glomerulonephritis in a patient with T-cell lymphoma and argyria

Background Silver is a transition metal, toxic when ingested in significant amounts, causing argyria (skin deposition) and argyrosis (eye deposition). It is excreted mainly via the gastrointestinal tract with only small amounts eliminated by the kidneys, and rarely have cases of nephrotoxicity due to silver been reported. Here we present the case of a woman who used colloidal silver as an alternative remedy for a T cell lymphoma, who subsequently developed argyria and a pauci-immune crescentic glomerulonephritis with evidence of extensive glomerular basement membrane silver deposition. Case Presentation A 47 year old woman of Indo-Asian descent with a T-cell lymphoma who refused conventional chemotherapy for 18 months but self-medicated with a remedy containing colloidal silver, was admitted with acute dialysis-dependent kidney injury. A kidney biopsy demonstrated a pauci-immune crescentic glomerulonephritis with deposition of silver particles in the mesangium and along the glomerular basement membranes. The patient was treated with intravenous methylprednisolone and intravenous cyclophosphamide and recovered independent renal function. Conclusion Chronological evolution of the the pauci-immune glomerulonephritis suggests that a cellular immune-mediated process was induced, potentially mediated by lymphomatous T cells directed at the glomerular basement membrane, following silver deposition. Immunosuppressive therapy improved the situation and allowed cessation of haemodialysis, supporting the hypothesis of an immune-mediated process

Effects of emotion recognition training on mood among individuals with high levels of depressive symptoms: study protocol for a randomised controlled trial.

BACKGROUND: We have developed a new paradigm that targets the recognition of facial expression of emotions. Here we report the protocol of a randomised controlled trial of the effects of emotion recognition training on mood in a sample of individuals with depressive symptoms over a 6-week follow-up period. METHODS/DESIGN: We will recruit 190 adults from the general population who report high levels of depressive symptoms (defined as a score ≥ 14 on the Beck Depression Inventory-II). Participants will attend a screening session and will be randomised to intervention or control procedures, repeated five times over consecutive days (Monday to Friday). A follow-up session will take place at end-of -treatment, 2-weeks and 6-weeks after training. Our primary study outcome will be depressive symptoms, Beck Depression Inventory- II (rated over the past two weeks). Our secondary outcomes are: depressive symptoms, Hamilton Rating Scale for Depression; anxiety symptoms, Beck Anxiety Inventory (rated over the past month); positive affect, Positive and Negative Affect Schedule (rated as 'how you feel right now'); negative affect, Positive and Negative Affect Schedule (rated as 'how you feel right now'); emotion sensitivity, Emotion Recognition Task (test phase); approach motivation and persistence, the Fishing Game; and depressive interpretation bias, Scrambled Sentences Test. DISCUSSION: This study is of a novel cognitive bias modification technique that targets biases in emotional processing characteristic of depression, and can be delivered automatically via computer, Internet or Smartphone. It therefore has potential to be a valuable cost-effective adjunctive treatment for depression which may be used together with more traditional psychotherapy, cognitive-behavioural therapy and pharmacotherapy. TRIAL REGISTRATION: Current Controlled Trials: ISRCTN17767674.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are