Discrete element models of soil-geogrid interaction

Geogrids are the geosynthetics of choice for soil reinforcement applications. To evaluate the efficiency of geogrid reinforcement, several methods are used including field tests, laboratory tests and numerical modeling. Field studies consume long period of time and conducting these investigations may become highly expensive because of the need for real-size structures. Laboratory studies present also significant difficulties: large-size testing machines are required to accommodate realistic geogrid designs. The discrete element method (DEM) may be used as a complementary tool to extend physical testing databases at lower cost. Discrete element models do not require complex constitutive formulations and may be fed with particle scale data (size, strength, shape) thus reducing the number offree calibration parameters. Discrete element models also are well suited to problems in which large displacements are present, such as geogrid pullout. This paper reviews the different approaches followed to model soil-geogrid interaction in DEM and presents preliminary results from pull-out conditions.Peer ReviewedPostprint (author's final draft

Single-Dose Oritavancin Treatment of Acute Bacterial Skin and Skin Structure Infections: SOLO Trial Efficacy by Eron Severity and Management Setting.

INTRODUCTION: Introduction of new antibiotics enabling single-dose administration, such as oritavancin may significantly impact site of care decisions for patients with acute bacterial skin and skin structure infections (ABSSSI). This analysis compared the efficacy of single-dose oritavancin with multiple-dose vancomycin in patients categorized according to disease severity via modified Eron classification and management setting. METHODS: SOLO I and II were phase 3 studies evaluating single-dose oritavancin versus 7-10 days of vancomycin for treatment of ABSSSI. Patient characteristics were collected at baseline and retrospectively analyzed. Study protocols were amended, allowing outpatient management at the discretion of investigators. In this post hoc analysis, patients were categorized according to a modified Eron severity classification and management setting (outpatient vs. inpatient) and the efficacy compared. RESULTS: Overall, 1910 patients in the SOLO trials were categorized into Class I (520, 26.5%), II (790, 40.3%), and III (600, 30.6%). Of the 767 patients (40%) in the SOLO trials who were managed entirely in the outpatient setting 40.3% were categorized as Class II and 30.6% were Class III. Clinical efficacy was similar between oritavancin and vancomycin treatment groups, regardless of severity classification and across inpatient and outpatient settings. Class III patients had lower response rates (oritavancin 73.3%, vancomycin 76.6%) at early clinical evaluation when compared to patients in Class I (82.6%) or II (86.1%); however, clinical cure rates at the post-therapy evaluation were similar for Class III patients (oritavancin 79.8%, vancomycin 79.9%) when compared to Class I and II patients (79.1-85.7%). CONCLUSION: Single-dose oritavancin therapy results in efficacy comparable to multiple-dose vancomycin in patients categorized according to modified Eron disease severity classification regardless of whether management occurred in the inpatient or outpatient setting. FUNDING: The Medicines Company, Parsippany, NJ, USA. TRIAL REGISTRATION: ClinicalTrials.gov identifiers, NCT01252719 (SOLO I) and NCT01252732 (SOLO II)

Tight coupling of leaf area index to canopy nitrogen and phosphorus across heterogeneous tallgrass prairie communities

Nitrogen (N) and phosphorus (P) are limiting nutrients for many plant communities worldwide. Foliar N and P along with leaf area are among the most important controls on photosynthesis and hence productivity. However, foliar N and P are typically assessed as species level traits, whereas productivity is often measured at the community scale. Here, we compared the community-level traits of leaf area index (LAI) to total foliar nitrogen (TFN) and total foliar phosphorus (TFP) across nearly three orders of magnitude LAI in grazed and ungrazed tallgrass prairie in north-eastern Kansas, USA. LAI was strongly correlated with both TFN and TFP across communities, and also within plant functional types (grass, forb, woody, and sedge) and grazing treatments (bison or cattle, and ungrazed). Across almost the entire range of LAI values and contrasting communities, TFN:TFP ratios indicated co-limitation by N and P in almost all communities; this may further indicate a community scale trend of an optimal N and P allocation per unit leaf area for growth. Previously, results from the arctic showed similar tight relationships between LAI:TFN, suggesting N is supplied to canopies to maximize photosynthesis per unit leaf area. This tight coupling between LAI, N, and P in tallgrass prairie suggests a process of optimal allocation of N and P, wherein LAI remains similarly constrained by N and P despite differences in species composition, grazing, and canopy density

The intellectual structure and substance of the knowledge utilization field: A longitudinal author co-citation analysis, 1945 to 2004

<p>Abstract</p> <p>Background</p> <p>It has been argued that science and society are in the midst of a far-reaching renegotiation of the social contract between science and society, with society becoming a far more active partner in the creation of knowledge. On the one hand, new forms of knowledge production are emerging, and on the other, both science and society are experiencing a rapid acceleration in new forms of knowledge utilization. Concomitantly since the Second World War, the science underpinning the knowledge utilization field has had exponential growth. Few in-depth examinations of this field exist, and no comprehensive analyses have used bibliometric methods.</p> <p>Methods</p> <p>Using bibliometric analysis, specifically first author co-citation analysis, our group undertook a domain analysis of the knowledge utilization field, tracing its historical development between 1945 and 2004. Our purposes were to map the historical development of knowledge utilization as a field, and to identify the changing intellectual structure of its scientific domains. We analyzed more than 5,000 articles using citation data drawn from the Web of Science^®. Search terms were combinations of knowledge, research, evidence, guidelines, ideas, science, innovation, technology, information theory and use, utilization, and uptake.</p> <p>Results</p> <p>We provide an overview of the intellectual structure and how it changed over six decades. The field does not become large enough to represent with a co-citation map until the mid-1960s. Our findings demonstrate vigorous growth from the mid-1960s through 2004, as well as the emergence of specialized domains reflecting distinct collectives of intellectual activity and thought. Until the mid-1980s, the major domains were focused on innovation diffusion, technology transfer, and knowledge utilization. Beginning slowly in the mid-1980s and then growing rapidly, a fourth scientific domain, evidence-based medicine, emerged. The field is dominated in all decades by one individual, Everett Rogers, and by one paradigm, innovation diffusion.</p> <p>Conclusion</p> <p>We conclude that the received view that social science disciplines are in a state where no accepted set of principles or theories guide research (<it>i.e.</it>, that they are pre-paradigmatic) could not be supported for this field. Second, we document the emergence of a new domain within the knowledge utilization field, evidence-based medicine. Third, we conclude that Everett Rogers was the dominant figure in the field and, until the emergence of evidence-based medicine, his representation of the general diffusion model was the dominant paradigm in the field.</p

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution