II.3 Exposure based algorithm for removing systematics out of the CoRoT light curves

This book is dedicated to all the people interested in the CoRoT mission and the beautiful data that were delivered during its six year duration. Either amateurs, professional, young or senior researchers, they will find treasures not only at the time of this publication but also in the future twenty or thirty years. It presents the data in their final version, explains how they have been obtained, how to handle them, describes the tools necessary to understand them, and where to find them. It also highlights the most striking first results obtained up to now. CoRoT has opened several unexpected directions of research and certainly new ones still to be discovered

ARCHI: pipeline for light curve extraction of CHEOPS background star

High precision time series photometry from space is being used for a number of scientific cases. In this context, the recently launched CHEOPS (ESA) mission promises to bring 20 ppm precision over an exposure time of 6 hours, when targeting nearby bright stars, having in mind the detailed characterization of exoplanetary systems through transit measurements. However, the official CHEOPS (ESA) mission pipeline only provides photometry for the main target (the central star in the field). In order to explore the potential of CHEOPS photometry for all stars in the field, in this paper we present archi, an additional open-source pipeline module{\dag}to analyse the background stars present in the image. As archi uses the official Data Reduction Pipeline data as input, it is not meant to be used as independent tool to process raw CHEOPS data but, instead, to be used as an add-on to the official pipeline. We test archi using CHEOPS simulated images, and show that photometry of background stars in CHEOPS images is only slightly degraded (by a factor of 2 to 3) with respect to the main target. This opens a potential for the use of CHEOPS to produce photometric time series of several close-by targets at once, as well as to use different stars in the image to calibrate systematic errors. We also show one clear scientific application where the study of the companion light curve can be important for the understanding of the contamination on the main target.Comment: 14 pages, 13 figures, accepted for publication in MNRAS, all code available at https://github.com/Kamuish/arch

Not-So-Innocent Anions Determine the Mechanism of Cationic Alkylators

Alkylating reagents based on thioimidazolium ionic liquids were synthesized and the influence of the anion on the alkylation reaction mechanism explored in detail using both experimental and computational methods. Thioimidazolium cations transfer alkyl substituents to nucleophiles, however the reaction rate was highly dependent on anion identity, demonstrating that the anion is not innocent in the mechanism. Detailed analysis of the computationally-derived potential energy surfaces associated with possible mechanisms indicated that this dependence arises from a combination of anion induced electronic, steric and coordinating effects, with highly nucleophilic anions catalyzing a 2-step process while highly non-nucleophilic, delocalized anions favor a 1-step reaction. This work also confirms the presence of ion-pairs and aggregates in solution thus supporting anion-induced control over the reaction rate and mechanism. These findings provide new insight into an old reaction allowing for better design of cationic alkylators in synthesis, gene expression, polymer science, and protein chemistry applications

Not-So-Innocent Anions Determine the Mechanism of Cationic Alkylators

Alkylating reagents based on thioimidazolium ionic liquids were synthesized and the influence of the anion on the alkylation reaction mechanism explored in detail using both experimental and computational methods. Thioimidazolium cations transfer alkyl substituents to nucleophiles, however the reaction rate was highly dependent on anion identity, demonstrating that the anion is not innocent in the mechanism. Detailed analysis of the computationally-derived potential energy surfaces associated with possible mechanisms indicated that this dependence arises from a combination of anion induced electronic, steric and coordinating effects, with highly nucleophilic anions catalyzing a 2-step process while highly non-nucleophilic, delocalized anions favor a 1-step reaction. This work also confirms the presence of ion-pairs and aggregates in solution thus supporting anion-induced control over the reaction rate and mechanism. These findings provide new insight into an old reaction allowing for better design of cationic alkylators in synthesis, gene expression, polymer science, and protein chemistry applications

Giant Multipole Resonances in the (3-He,t) Reaction at 200 MeV

This work was supported by the National Science Foundation Grants NSF PHY 78-22774 A03, NSF PHY 81-14339, and by Indiana Universit

Implementing an inpatient social early warning system for child maltreatment

Objectives: The current article describes the process evaluation of a social early warning system (SEWS) for the prevention of child maltreatment in the federal state of Hamburg. This prevention initiative targets expectant mothers and their partners including an initial screening of risk factors for child maltreatment, a subsequent structured clearing interview further exploring risks and identifying protective factors and an optional referral to the regional health and social care system. Method: The process evaluation was conducted by examining the flow of participants through the different stages of the SEWS as well as asking social education workers, parents, and regional institutions about their satisfaction with the process of the SEWS. Results: The participation rate throughout the SEWS as well as the satisfaction rates were high. Conclusions: The SEWS is a secondary prevention initiative with a substantial difference to other early prevention initiatives, as it aims to facilitate intervention rather than providing it

Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial.

BACKGROUND: Comorbid depression is a significant challenge for safety-net primary care systems. Team-based collaborative depression care is effective, but complex system factors in safety-net organizations impede adoption and result in persistent disparities in outcomes. Diabetes-Depression Care-management Adoption Trial (DCAT) evaluated whether depression care could be significantly improved by harnessing information and communication technologies to automate routine screening and monitoring of patient symptoms and treatment adherence and allow timely communication with providers. OBJECTIVE: The aim of this study was to compare 6-month outcomes of a technology-facilitated care model with a usual care model and a supported care model that involved team-based collaborative depression care for safety-net primary care adult patients with type 2 diabetes. METHODS: DCAT is a translational study in collaboration with Los Angeles County Department of Health Services, the second largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: usual care, supported care, and technology-facilitated care. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design. RESULTS: DCAT enrolled 1406 patients (484 in usual care, 480 in supported care, and 442 in technology-facilitated care), most of whom were Hispanic or Latino and female. Compared with usual care, both the supported care and technology-facilitated care groups were associated with significant reduction in depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate, LSE: usual care=6.35, supported care=5.05, technology-facilitated care=5.16; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.02); decreased prevalence of major depression (odds ratio, OR: supported care vs usual care=0.45, technology-facilitated care vs usual care=0.33; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.007); and reduced functional disability as measured by Sheehan Disability Scale scores (LSE: usual care=3.21, supported care=2.61, technology-facilitated care=2.59; P value: supported care vs usual care=.04, technology-facilitated care vs usual care=.03). Technology-facilitated care was significantly associated with depression remission (technology-facilitated care vs usual care: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: usual care=3.20, technology-facilitated care=3.70; P=.05); reduced total cholesterol level (LSE: usual care=176.40, technology-facilitated care=160.46; P=.01); improved satisfaction with diabetes care (LSE: usual care=4.01, technology-facilitated care=4.20; P=.05); and increased odds of taking an glycated hemoglobin test (technology-facilitated care vs usual care: OR=3.40, P\u3c.001). CONCLUSIONS: Both the technology-facilitated care and supported care delivery models showed potential to improve 6-month depression and functional disability outcomes. The technology-facilitated care model has a greater likelihood to improve depression remission, patient satisfaction, and diabetes care quality