Advances in representing interactive methane in ModelE2-YIBs (version 1.1)

This is the final version. Available on open access from EGU via the DOI in this recordCode and data availability: The source code for the site-level YIBs model version 1.0 (Yue and Unger, 2015) is available at https://github.com/YIBS01/YIBS site (last access: 5 August 2015). The source code for the frozen CMIP5/AR5 version of the GISS ModelE2 (Schmidt et al., 2014) can be obtained from NASA GISS (https://www.giss.nasa.gov/tools/modelE/, last access: 31 July 2014). Included as supplemental information are the gridded natural methane fluxes and the numerical model output used to make the figures. Gridded files of natural methane fluxes associated with the Fung et al. (1991) dataset were obtained from NASA GISS (https://data.giss.nasa.gov/ch4_fung/, last access: 4 June 2014). Column-averaged methane concentrations from SCIAMACHY (Schneising et al., 2009) were obtained from the University of Bremen (http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/index.html, last access: 27 April 2015). Other data used as model input or for analysis of model output are listed in the references.Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry-climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry-climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry-climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 yr-1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 yr-1 and a global annual methane soil sink of 60 Tg CH4 yr-1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to-1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry-climate model is able to capture the principal processes that control atmospheric methane

Report of the Working Group on the Composition of Ultra High Energy Cosmic Rays

For the first time a proper comparison of the average depth of shower maximum ($X_{\rm max}$) published by the Pierre Auger and Telescope Array Observatories is presented. The $X_{\rm max}$ distributions measured by the Pierre Auger Observatory were fit using simulated events initiated by four primaries (proton, helium, nitrogen and iron). The primary abundances which best describe the Auger data were simulated through the Telescope Array (TA) Middle Drum (MD) fluorescence and surface detector array. The simulated events were analyzed by the TA Collaboration using the same procedure as applied to their data. The result is a simulated version of the Auger data as it would be observed by TA. This analysis allows a direct comparison of the evolution of $\langle X_{\rm max} \rangle$ with energy of both data sets. The $\langle X_{\rm max} \rangle$ measured by TA-MD is consistent with a preliminary simulation of the Auger data through the TA detector and the average difference between the two data sets was found to be $(2.9 \pm 2.7\;(\text{stat.}) \pm 18\;(\text{syst.}))~\text{g/cm}^2$.Comment: To appear in the Proceedings of the UHECR workshop, Springdale USA, 201

The instability of Alexander-McTague crystals and its implication for nucleation

We show that the argument of Alexander and McTague, that the bcc crystalline structure is favored in those crystallization processes where the first order character is not too pronounced, is not correct. We find that any solution that satisfies the Alexander-McTague condition is not stable. We investigate the implication of this result for nucleation near the pseudo- spinodal in near-meanfield systems.Comment: 20 pages, 0 figures, submitted to Physical Review

Confidential Boosting with Random Linear Classifiers for Outsourced User-generated Data

User-generated data is crucial to predictive modeling in many applications. With a web/mobile/wearable interface, a data owner can continuously record data generated by distributed users and build various predictive models from the data to improve their operations, services, and revenue. Due to the large size and evolving nature of users data, data owners may rely on public cloud service providers (Cloud) for storage and computation scalability. Exposing sensitive user-generated data and advanced analytic models to Cloud raises privacy concerns. We present a confidential learning framework, SecureBoost, for data owners that want to learn predictive models from aggregated user-generated data but offload the storage and computational burden to Cloud without having to worry about protecting the sensitive data. SecureBoost allows users to submit encrypted or randomly masked data to designated Cloud directly. Our framework utilizes random linear classifiers (RLCs) as the base classifiers in the boosting framework to dramatically simplify the design of the proposed confidential boosting protocols, yet still preserve the model quality. A Cryptographic Service Provider (CSP) is used to assist the Cloud's processing, reducing the complexity of the protocol constructions. We present two constructions of SecureBoost: HE+GC and SecSh+GC, using combinations of homomorphic encryption, garbled circuits, and random masking to achieve both security and efficiency. For a boosted model, Cloud learns only the RLCs and the CSP learns only the weights of the RLCs. Finally, the data owner collects the two parts to get the complete model. We conduct extensive experiments to understand the quality of the RLC-based boosting and the cost distribution of the constructions. Our results show that SecureBoost can efficiently learn high-quality boosting models from protected user-generated data

Drug Loaded Biodegradable Load-Bearing Nanocomposites for Damaged Bone Repair

In this paper we present a short review-scientific report on processing and properties, including in vitro degradation, of load bearing biodegradable nanocomposites as well as of macroporous 3D scaffolds for bone ingrowth. Biodegradable implantable devices should slowly degrade over time and disappear with ingrown of natural bone replacing the synthetic graft. Compared to low strength biodegradable polymers, and brittle CaP ceramics, biodegradable CaP-polymer and CaP-metal nanocomposites, mimicking structure of natural bone, as well as strong and ductile metal nanocomposites can provide to implantable devices both strengths and toughness. Nanostructuring of biodegradable [beta]- TCP (tricalcium phosphate)-polymer (PCL and PLA), [beta]-TCP-metal (FeMg and FeAg) and of Fe-Ag composites was achieved employing high energy attrition milling of powder blends. Nanocomposite powders were consolidated to densities close to theoretical by high pressure consolidation at ambient temperature-cold sintering, with retention of nanoscale structure. The strength of developed nanocomposites was significantly higher as compared with microscale composites of the same or similar composition. Heat treatment at moderate temperatures in hydrogen flow resulted in retention of nanoscale structure and higher ductility. Degradation of developed biodegradable [beta]-TCP-polymer, [beta]-TCPmetal and of Fe-Ag nanocomposites was studied in physiological solutions. Immersion tests in Ringer's and saline solution for 4 weeks resulted in 4 to 10% weight loss and less than 50% decrease in compression or bending strength, the remaining strength being significantly higher than the values reported for other biodegradable materials. Nanostructuring of Fe-Ag based materials resulted also in an increase of degradation rate because of creation on galvanic Fe-Ag nanocouples. In cell culture experiments, the developed nanocomposites supported the attachment the human osteoblast cells and exhibited no signs of cytotoxicity. Interconnected system of nanopores formed during processing of nanocomposites was used for incorporation of drugs, including antibiotics and anticancer drugs, and can be used for loading of bioactive molecules enhancing bone ingrowth

Comparing the efficacy, safety, and utility of intensive insulin algorithms for a primary care practice

Diabetes management is firmly based within the primary care community. Landmark randomized, controlled trials have demonstrated that even modest reductions in glycated hemoglobin (HbA1c) can yield improvements in economic and medical end-points. Diabetes is a chronic, progressive disease associated with loss of pancreatic β-cell function. Therefore, most patients will eventually require insulin therapies in order to achieve their individualized targeted HbA1c as their β-cell function and mass wanes. Although clinicians understand the importance of early insulin initiation, there is little agreement as to when to introduce insulin as a therapeutic option. Once initiated, questions remain as to whether to allow the patients to self-titrate their dose or whether the dosing should be tightly regulated by the clinician. Physicians have many evidence-based basal insulin protocols from which to choose, all of which have been shown to drive HbA1c levels to the American Diabetes Association target of ≤7%. This article will discuss ways by which insulin therapies can be effectively introduced to patients within busy primary care practices. Published evidence-based basal insulin protocols will be evaluated for safety and efficacy

Advances in representing interactive methane in ModelE2-YIBs (version 1.1)

Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry–climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry–climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry–climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140&thinsp;Tg&thinsp;CH4&thinsp;yr−1. The updated inventory includes total global annual methane emissions from natural sources of 181&thinsp;Tg&thinsp;CH4&thinsp;yr−1 and a global annual methane soil sink of 60&thinsp;Tg&thinsp;CH4&thinsp;yr−1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1&thinsp;% higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1&thinsp;% (i.e., +1&thinsp;% to −1&thinsp;%) of the observed value at 76&thinsp;% of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5&thinsp;%. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95&thinsp;% of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry–climate model is able to capture the principal processes that control atmospheric methane.</p

A Search for OH Megamasers at z > 0.1. III. The Complete Survey

We present the final results from the Arecibo Observatory OH megamaser survey. We discuss in detail the properties of the remaining 18 OH megamasers detected in the survey, including 3 redetections. We place upper limits on the OH emission from 85 nondetections and examine the properties of 25 ambiguous cases for which the presence or absence of OH emission could not be determined. The complete survey has discovered 50 new OH megamasers (OHMs) in (ultra)luminous infrared galaxies ([U]LIRGs) which doubles the sample of known OHMs and increases the sample at z>0.1 sevenfold. The Arecibo OH megamaser survey indicates that the OHM fraction in LIRGs is an increasing function of the far-IR luminosity (L_{FIR}) and far-IR color, reaching a fraction of roughly one third in the warmest ULIRGs. Significant relationships between OHMs and their hosts are few, primarily due to a mismatch in size scales of measured properties and an intrinsic scatter in OHM properties roughly equal to the span of the dataset. We investigate relationships between OHMs and their hosts with a variety of statistical tools including survival analysis, partial correlation coefficients, and a principal component analysis. There is no apparent OH megamaser ``fundamental plane.'' We compile data on all previously known OHMs and evaluate the possible mechanisms and relationships responsible for OHM production in merging systems. The OH-FIR relationship is reexamined using the doubled OHM sample and found to be significantly flatter than previously thought: L_{OH} ~ L_{FIR}^{1.2 +/- 0.1}. This near-linear dependence suggests a mixture of saturated and unsaturated masers, either within individual galaxies or across the sample.Comment: 28 pages, 14 figures, accepted by AJ. (AASTeX, includes emulateapj5 and onecolfloat5