Mission Concept for the Single Aperture Far-Infrared (SAFIR) Observatory

The Single Aperture Far-InfraRed (SAFIR) Observatory's science goals are driven by the fact that the earliest stages of almost all phenomena in the universe are shrouded in absorption by and emission from cool dust and gas that emits strongly in the far-infrared and submillimeter. Over the past several years, there has been an increasing recognition of the critical importance of this spectral region to addressing fundamental astrophysical problems, ranging from cosmological questions to understanding how our own Solar System came into being. The development of large, far-infrared telescopes in space has become more feasible with the combination of developments for the James Webb Space Telescope and of enabling breakthroughs in detector technology. We have developed a preliminary but comprehensive mission concept for SAFIR, as a 10 m-class far-infrared and submillimeter observatory that would begin development later in this decade to meet the needs outlined above. Its operating temperature (<4K) and instrument complement would be optimized to reach the natural sky confusion limit in the far-infrared with diffraction-limited peformance down to at least 40 microns. This would provide a point source sensitivity improvement of several orders of magnitude over that of Spitzer or Herschel, with finer angular resolution, enabling imaging and spectroscopic studies of individual galaxies in the early universe. We have considered many aspects of the SAFIR mission, including the telescope technology, detector needs and technologies, cooling method and required technology developments, attitude and pointing, power systems, launch vehicle, and mission operations. The most challenging requirements for this mission are operating temperature and aperture size of the telescope, and the development of detector arrays.Comment: 36 page

DAVINCI: Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging

DAVINCI is one of five Discovery-class missions selected by NASA in October 2015 for Phase A studies. Launching in November 2021 and arriving at Venus in June of 2023, DAVINCI would be the first U.S. entry probe to target Venus atmosphere in 45 years. DAVINCI is designed to study the chemical and isotopic composition of a complete cross-section of Venus atmosphere at a level of detail that has not been possible on earlier missions and to image the surface at optical wavelengths and process-relevant scales

The OptiMine feasibility study: a novel implementation strategy to electronically screen and signpost patients to health behaviour apps

Background: Behavior change apps have the potential to provide individual support on a population scale at low cost, but they face numerous barriers to implementation. Electronic health records (EHRs) in acute care hospitals provide a valuable resource for identifying patients at risk, who may benefit from behavior change apps. A novel, emerging implementation strategy is to use digital technologies not only for providing support to help-seeking individuals but also for signposting patients at risk to support services (also called proactive referral in the United States). Objective: The OptiMine study aimed to increase the reach of behavior change apps by implementing electronic signposting for smoking cessation and alcohol reduction in a large, at-risk population that was identified through an acute care hospital EHR. Methods: This 3-phase, mixed methods implementation study assessed the acceptability, feasibility, and reach of electronic signposting to behavior change apps by using a hospital’s EHR system to identify patients who are at risk. Phase 1 explored the acceptability of the implementation strategy among the patients and staff through focus groups. Phase 2 investigated the feasibility of using the hospital EHR to identify patients with target risk behaviors and contact them via SMS text message, email, or patient portal. Phase 3 assessed the impact of SMS text messages sent to patients who were identified as smokers or risky drinkers, which signposted them to behavior change apps. The primary outcome was the proportion of participants who clicked on the embedded link in the SMS text message to access information about the apps. The acceptability of the SMS text messages among the patients who had received them was also explored in a web-based survey. Results: Our electronic signposting strategy—using SMS text messages to promote health behavior change apps to patients at risk—was found to be acceptable and feasible and had good reach. The hospital sent 1526 SMS text messages, signposting patients to either the National Health Service Smokefree or Drink Free Days apps. A total of 13.56% (207/1526) of the patients clicked on the embedded link to the apps, which exceeded our 5% a priori success criterion. Patients and staff contributed to the SMS text message content and delivery approach, which were perceived as acceptable before and after the delivery of the SMS text messages. The feasibility of the SMS text message format was determined and the target population was identified by mining the EHR. Conclusions: The OptiMine study demonstrated the proof of concept for this novel implementation strategy, which used SMS text messages to signpost at-risk individuals to behavior change apps at scale. The level of reach exceeded our a priori success criterion in a non–help-seeking population of patients receiving unsolicited SMS text messages, disconnected from hospital visits. International Registered Report Identifier (IRRID): RR2-10.2196/2366

Novel implementation strategy to electronically screen and signpost patients to health behavior apps: Mixed methods implementation study (OptiMine study)

BACKGROUND: Behavior change apps have the potential to provide individual support on a population scale at low cost, but they face numerous barriers to implementation. Electronic health records (EHRs) in acute care hospitals provide a valuable resource for identifying patients at risk, who may benefit from behavior change apps. A novel, emerging implementation strategy is to use digital technologies not only for providing support to help-seeking individuals but also for signposting patients at risk to support services (also called proactive referral in the United States). OBJECTIVE: The OptiMine study aimed to increase the reach of behavior change apps by implementing electronic signposting for smoking cessation and alcohol reduction in a large, at-risk population that was identified through an acute care hospital EHR. METHODS: This 3-phase, mixed methods implementation study assessed the acceptability, feasibility, and reach of electronic signposting to behavior change apps by using a hospital\u27s EHR system to identify patients who are at risk. Phase 1 explored the acceptability of the implementation strategy among the patients and staff through focus groups. Phase 2 investigated the feasibility of using the hospital EHR to identify patients with target risk behaviors and contact them via SMS text message, email, or patient portal. Phase 3 assessed the impact of SMS text messages sent to patients who were identified as smokers or risky drinkers, which signposted them to behavior change apps. The primary outcome was the proportion of participants who clicked on the embedded link in the SMS text message to access information about the apps. The acceptability of the SMS text messages among the patients who had received them was also explored in a web-based survey. RESULTS: Our electronic signposting strategy-using SMS text messages to promote health behavior change apps to patients at risk-was found to be acceptable and feasible and had good reach. The hospital sent 1526 SMS text messages, signposting patients to either the National Health Service Smokefree or Drink Free Days apps. A total of 13.56% (207/1526) of the patients clicked on the embedded link to the apps, which exceeded our 5% a priori success criterion. Patients and staff contributed to the SMS text message content and delivery approach, which were perceived as acceptable before and after the delivery of the SMS text messages. The feasibility of the SMS text message format was determined and the target population was identified by mining the EHR. CONCLUSIONS: The OptiMine study demonstrated the proof of concept for this novel implementation strategy, which used SMS text messages to signpost at-risk individuals to behavior change apps at scale. The level of reach exceeded our a priori success criterion in a non-help-seeking population of patients receiving unsolicited SMS text messages, disconnected from hospital visits. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/23669

Hif-1α regulates differentiation of limb bud mesenchyme and joint development

Recent evidence suggests that low oxygen tension (hypoxia) may control fetal development and differentiation. A crucial mediator of the adaptive response of cells to hypoxia is the transcription factor Hif-1α. In this study, we provide evidence that mesenchymal condensations that give origin to endochondral bones are hypoxic during fetal development, and we demonstrate that Hif-1α is expressed and transcriptionally active in limb bud mesenchyme and in mesenchymal condensations. To investigate the role of Hif-1α in mesenchymal condensations and in early chondrogenesis, we conditionally inactivated Hif-1α in limb bud mesenchyme using a Prx1 promoter-driven Cre transgenic mouse. Conditional knockout of Hif-1α in limb bud mesenchyme does not impair mesenchyme condensation, but alters the formation of the cartilaginous primordia. Late hypertrophic differentiation is also affected as a result of the delay in early chondrogenesis. In addition, mutant mice show a striking impairment of joint development. Our study demonstrates a crucial, and previously unrecognized, role of Hif-1α in early chondrogenesis and joint formation

Stability analysis of the GAL regulatory network in Saccharomyces cerevisiae and Kluyveromyces lactis

<p>Abstract</p> <p>Background</p> <p>In the yeast <it>Saccharomyces cerevisiae</it>, interactions between galactose, Gal3p, Gal80p, and Gal4p determine the transcriptional status of the genes required for the galactose utilization. Increase in the cellular galactose concentration causes the galactose molecules to bind onto Gal3p which, via Gal80p, activates Gal4p, which induces the GAL3 and GAL80 gene transcription. Recently, a linear time-invariant multi-input multi-output (MIMO) model of this GAL regulatory network has been proposed; the inputs being galactose and Gal4p, and the outputs being the active Gal4p and galactose utilization. Unfortunately, this model assumes the cell culture to be homogeneous, although it is not so in practice. We overcome this drawback by including more biochemical reactions, and derive a quadratic ordinary differential equation (ODE) based model.</p> <p>Results</p> <p>We show that the model, referred to above, does not exhibit bistability. We establish sufficiency conditions for the domain of attraction of an equilibrium point of our ODE model for the special case of full-state feedback controller. We observe that the GAL regulatory system of <it>Kluyveromyces lactis </it>exhibits an aberration of monotone nonlinearity and apply the Rantzer multipliers to establish a class of stabilizing controllers for this system.</p> <p>Conclusion</p> <p>Feedback in a GAL regulatory system can be used to enhance the cellular memory. We show that the system can be modeled as a quadratic nonlinear system for which the effect of feedback on the domain of attraction of the equilibrium point can be characterized using <it>linear matrix inequality </it>(LMI) conditions that are easily implementable in software. The benefit of this result is that a mathematically sound approach to the synthesis of full-state and partial-state feedback controllers to regulate the cellular memory is now possible, irrespective of the number of state-variables or parameters of interest.</p

The Role of Industry, Geography and Firm Heterogeneity in Credit Risk Diversification

In theory the potential for credit risk diversification for banks could be substantial. Portfolio diversification is driven broadly by two characteristics: the degree to which systematic risk factors are correlated with each other and the degree of dependence individual firms have to the different types of risk factors. We propose a model for exploring these dimensions of credit risk diversification: across industry sectors and across different countries or regions. We find that full firm-level parameter heterogeneity matters a great deal for capturing differences in simulated credit loss distributions. Imposing homogeneity results in overly skewed and fat-tailed loss distributions. These differences become more pronounced in the presence of systematic risk factor shocks: increased parameter heterogeneity greatly reduces shock sensitivity. Allowing for regional parameter heterogeneity seems to better approximate the loss distributions generated by the fully heterogeneous model than allowing just for industry heterogeneity. The regional model also exhibits less shock sensitivity

Mining electronic health records to promote the reach of digital interventions for cancer prevention through proactive electronic outreach:Protocol for the mixed methods OptiMine study

BACKGROUND: Digital behavior change interventions have demonstrated effectiveness for smoking cessation and reducing alcohol intake, which ultimately reduce cancer risk. Leveraging electronic health records (EHR) to identify at-risk patients and increasing the reach of digital interventions through proactive electronic outreach provide a novel approach that may increase the number of individuals who engage with evidence-based treatment. OBJECTIVE: This study aims to increase the reach of digital behavior change interventions by implementing a proactive electronic message system for smoking cessation and alcohol reduction among a large, at-risk population identified through an acute hospital EHR. METHODS: This protocol describes a 3-phase, mixed-methods implementation study to assess the acceptability, feasibility, and reach of a proactive electronic message system to digital interventions using a hospital's EHR system to identify eligible patients. In Phase 1, we will conduct focus group discussions with patients and hospital staff to assess the overall acceptability of the electronic message system. In Phase 2, we will conduct a descriptive analysis of the patient population in the hospital EHR regarding target risk behaviors and other person-level characteristics to determine the project's feasibility and potential reach. In Phase 3, we will send proactive messages to patients identified as smokers or risky drinkers. Messages will encourage and provide access to behavior change mobile apps via an embedded link; the primary outcome will be the proportion of participants who click on the link to access information about the apps. RESULTS: At the time of initial protocol submission, data collection was complete, but analysis had not begun. This study was funded by Cancer Research UK from April 2019 to March 2020. Health Research Authority approval was granted in June 2019. CONCLUSIONS: Increasing the reach of digital behavior change interventions can improve population health by reducing the burden of preventable death and disease. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23669

Differential branching fraction and angular analysis of the decay B 0 → K ∗0 μ + μ −

The angular distribution and differential branching fraction of the decay B[superscript O]→ K*[superscript O]μ⁺μ⁻ are studied using a data sample, collected by the LHCb experiment in pp collisions at s√=7 TeV, corresponding to an integrated luminosity of 1.0 fb⁻¹. Several angular observables are measured in bins of the dimuon invariant mass squared, q². A first measurement of the zero-crossing point of the forward-backward asymmetry of the dimuon system is also presented. The zero-crossing point is measured to be q²₀=4.9±0.9GeV²/c⁴, where the uncertainty is the sum of statistical and systematic uncertainties. The results are consistent with the Standard Model predictions