A study of liquid propellant behavior during periods of varying accelerations Final report

Liquid propellant behavior under space flight conditions and predicting Apollo spacecraft liquid stabilit

Emission estimates of HCFCs and HFCs in California from the 2010 CalNex study

The CalNex 2010 (California Research at the Nexus of Air Quality and Climate Change) study was designed to evaluate the chemical composition of air masses over key source regions in California. During May to June 2010, air samples were collected on board a National Oceanic and Atmospheric Administration (NOAA) WP-3D aircraft over the South Coast Air Basin of California (SoCAB) and the Central Valley (CV). This paper analyzes six effective greenhouse gases - chlorodifluoromethane (HCFC-22), 1,1-dichloro-1-fluoroethane (HCFC-141b), 1-chloro-1,1-difluoroethane (HCFC-142b), 2-chloro-1,1,1,2-tetrafluoroethane (HCFC-124), 1,1,1,2- tetrafluoroethane (HFC-134a), and 1,1-difluoroethane (HFC-152a) - providing the most comprehensive characterization of chlorofluorocarbon (CFC) replacement compound emissions in California. Concentrations of measured HCFCs and HFCs are enhanced greatly throughout the SoCAB and CV, with highest levels observed in the SoCAB: 310 ± 92 pptv for HCFC-22, 30.7 ± 18.6 pptv for HCFC-141b, 22.9 ± 2.0 pptv for HCFC-142b, 4.86 ± 2.56 pptv for HCFC-124, 109 ± 46.4 pptv for HFC-134a, and 91.2 ± 63.9 pptv for HFC-152a. Annual emission rates are estimated for all six compounds in the SoCAB using the measured halocarbon to carbon monoxide (CO) mixing ratios and CO emissions inventories. Emission rates of 3.05 ± 0.70 Gg for HCFC-22, 0.27 ± 0.07 Gg for HCFC-141b, 0.06 ± 0.01 Gg for HCFC-142b, 0.11 ± 0.03 Gg for HCFC-124, 1.89 ± 0.43 Gg for HFC-134a, and 1.94 ± 0.45 Gg for HFC-152b for the year 2010 are calculated for the SoCAB. These emissions are extrapolated from the SoCAB region to the state of California using population data. Results from this study provide a baseline emission rate that will help future studies determine if HCFC and HFC mitigation strategies are successful. Key PointsHCFC and HFC emissions are calculated for the year 2010 for the SoCABEmissions are extrapolated to the state of CaliforniaEmissions are calculated using CalNex field measurements © 2013. American Geophysical Union. All Rights Reserved

Adsorption in non interconnected pores open at one or at both ends: A reconsideration of the origin of the hysteresis phenomenon

We report on an experimental study of adsorption isotherme of nitrogen onto porous silicon with non interconnected pores open at one or at both ends in order to check for the first time the old (1938) but always current idea based on Cohan's description which suggests that the adsorption of gaz should occur reversibly in the first case and irreversibly in the second one. Hysteresis loops, the shape of which is usually associated to interconnections in porous media, are observed whether the pores are open at one or at both ends in contradiction with Cohan's model.Comment: 5 pages, 4 EPS figure

AS1411 Aptamer-Anionic Linear Globular Dendrimer G2-Iohexol Selective Nano-Theranostics

Molecular theranostics is of the utmost interest for diagnosis as well as treatment of different malignancies. In the present study, anionic linear globular dendrimer G2 is employed as a suitable carrier for delivery and AS1411 aptamer is exploited as the targeting agent to carry Iohexol specifically to the human breast cancer cells (MCF-7). Dendrimer G2 was prepared and conjugation of dendrimer and aptamer was carried out thereafter. Based on the data yielded by AFM, morphology of smooth and spherical non-targeted dendrimer changed to the rough aspherical shape when it conjugated. Then, conjugation was confirmed using DLS, ELS and SLS methods. Toxicity on nucleolin positive MCF-7 cells and nucleolin negative HEK-293 cells was assessed by XTT and apoptosis/necrosis assays. In vitro uptake was determined using DAPI-FITC staining and ICP-MS methods. In vivo studies including in vivo CT imaging, pathology and blood tests were done to confirm the imaging ability, bio-safety and targeted nature of the Nano-Theranostics in vivo. In a nutshell, the prepared construction showed promising effects upon decreasing the toxicity of Iohexol on normal cells and accumulation of it in the cancer tumors as well as reducing the number of cancer cells. © 2017 The Author(s)

Bayesian modeling of recombination events in bacterial populations

Background: We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. The currently available methods for recombination detection capable of probabilistic characterization of uncertainty have a limited applicability in practice as the number of strains in a data set increases. Results: We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites. Conclusion: A multitude of challenging simulation scenarios and an analysis of real data from seven housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/ mnf//mate/jc/software/brat.html

Metabolic flexibility as a major predictor of spatial distribution in microbial communities

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology

Optimizing the post-graduate institutional program evaluation process

Abstract Background Reviewing program educational efforts is an important component of postgraduate medical education program accreditation. The post-graduate review process has evolved over time to include centralized oversight based on accreditation standards. The institutional review process and the impact on participating faculty are topics not well described in the literature. Methods We conducted multiple Plan-Do-Study-Act (PDSA) cycles to identify and implement areas for change to improve productivity in our institutional program review committee. We also conducted one focus group and six in-person interviews with 18 committee members to explore their perspectives on the committee’s evolution. One author (MLL) reviewed the transcripts and performed the initial thematic coding with a PhD level research associate and identified and categorized themes. These themes were confirmed by all participating committee members upon review of a detailed summary. Emergent themes were triangulated with the University of Michigan Medical School’s Admissions Executive Committee (AEC). Results We present an overview of adopted new practices to the educational program evaluation process at the University of Michigan Health System that includes standardization of meetings, inclusion of resident members, development of area content experts, solicitation of committed committee members, transition from paper to electronic committee materials, and focus on continuous improvement. Faculty and resident committee members identified multiple improvement areas including the ability to provide high quality reviews of training programs, personal and professional development, and improved feedback from program trainees. Conclusions A standing committee that utilizes the expertise of a group of committed faculty members and which includes formal resident membership has significant advantages over ad hoc or other organizational structures for program evaluation committees.http://deepblue.lib.umich.edu/bitstream/2027.42/117363/1/12909_2016_Article_586.pd

Surprises in the Orbital Magnetic Moment and g-Factor of the Dynamic Jahn-Teller Ion C_{60}^-

We calculate the magnetic susceptibility and g-factor of the isolated C_{60}^- ion at zero temperature, with a proper treatment of the dynamical Jahn-Teller effect, and of the associated orbital angular momentum, Ham-reduced gyromagnetic ratio, and molecular spin-orbit coupling. A number of surprises emerge. First, the predicted molecular spin-orbit splitting is two orders of magnitude smaller than in the bare carbon atom, due to the large radius of curvature of the molecule. Second, this reduced spin-orbit splitting is comparable to Zeeman energies, for instance, in X-band EPR at 3.39KGauss, and a field dependence of the g-factor is predicted. Third, the orbital gyromagnetic factor is strongly reduced by vibron coupling, and so therefore are the effective weak-field g-factors of all low-lying states. In particular, the ground-state doublet of C_{60}^- is predicted to show a negative g-factor of \sim -0.1.Comment: 19 pages RevTex, 2 postscript figures include

Mining the Context of Citations in Scientific Publications

Recent advancements in information retrieval systems significantly rely on the context-based features and semantic matching techniques to provide relevant information to users from ever-growing digital libraries. Scientific communities seek to understand the implications of research, its importance and its applicability for future research directions. To mine this information, absolute citations merely fail to measure the importance of scientific literature, as a citation may have a specific context in full text. Thus, a comprehensive contextual understanding of cited references is necessary. For this purpose, numerous techniques have been proposed that tap the power of artificial intelligence models to detect important or incidental (non-important) citations in full text scholarly publications. In this paper, we compare and build upon on four state-of-the-art models that detect important citations using 450 manually annotated citations by experts - randomly selected from 20,527 papers from the Association for Computational Linguistics corpus. Of the total 64 unique features proposed by the four selected state-of-the-art models, the top 29 were chosen using the Extra-Trees classifier. These were then fed it to our supervised machine learning based models: Random Forest (RF) and Support Vector Machine. The RF model outperforms existing selected systems by more than 10%, with 89% precision-recall curve. Finally, we qualitatively assessed important and non-important citations by employing and self-organizing maps. Overall, our research work supports information retrieval algorithms that detect and fetch scientific articles on the basis of both qualitative and quantitative indices in scholarly big data