Effects of unidirectional flow shear stresses on the formation, fractal microstructure and rigidity of incipient whole blood clots and fibrin gels

Incipient clot formation in whole blood and fibrin gels was studied by the rheometric techniques of controlled stress parallel superposition (CSPS) and small amplitude oscillatory shear (SAOS). The effects of unidirectional shear stress on incipient clot microstructure, formation kinetics and elasticity are reported in terms of the fractal dimension (df ) of the fibrin network, the gel network formation time (TGP ) and the shear elastic modulus, respectively. The results of this first haemorheological application of CSPS reveal the marked sensitivity of incipient clot microstructure to physiologically relevant levels of shear stress, these being an order of magnitude lower than have previously been studied by SAOS. CSPS tests revealed that exposure of forming clots to increasing levels of shear stress produces a corresponding elevation in df , consistent with the formation of tighter, more compact clot microstructures under unidirectional flow. A corresponding increase in shear elasticity was recorded. The scaling relationship established between shear elasticity and df for fibrin clots and whole blood confirms the fibrin network as the dominant microstructural component of the incipient clot in terms of its response to imposed stress. Supplementary studies of fibrin clot formation by rheometry and microscopy revealed the substantial additional network mass required to increase df and provide evidence to support the hypothesis that microstructural changes in blood clotted under unidirectional shear may be attributed to flow enhanced thrombin generation and activation. CSPS also identified a threshold value of unidirectional shear stress above which no incipient clot formation could be detected. CSPS was shown to be a valuable haemorheological tool for the study of the effects of physiological and pathological levels of shear on clot properties

Chiral Dynamics and Fermion Mass Generation in Three Dimensional Gauge Theory

We examine the possibility of fermion mass generation in 2+1- dimensional gauge theory from the current algebra point of view.In our approach the critical behavior is governed by the fluctuations of pions which are the Goldstone bosons for chiral symmetry breaking. Our analysis supports the existence of an upper critical number of Fermion flavors and exhibits the explicit form of the gap equation as well as the form of the critical exponent for the inverse correlation lenght of the order parameterComment: Latex,10 pages,DFUPG 70/9

Disclosure, Privacy and Workplace Accommodation of Episodic Disabilities: Organizational Perspectives on Disability Communication-Support Processes to Sustain Employment

© 2020, The Author(s). Purpose Employers increasingly are asked to accommodate workers living with physical and mental health conditions that cause episodic disability, where periods of wellness are punctuated by intermittent and often unpredictable activity limitations (e.g., depression, anxiety, arthritis, colitis). Episodic disabilities may be challenging for workplaces which must comply with legislation protecting the privacy of health information while believing they would benefit from personal health details to meet a worker’s accommodation needs. This research aimed to understand organizational perspectives on disability communication-support processes. Methods Twenty-seven participants from diverse employment sectors and who had responsibilities for supporting workers living with episodic disabilities (e.g., supervisors, disability managers, union representatives, occupational health representatives, labour lawyers) were interviewed. Five participants also had lived experience of a physical or mental health episodic disability. Participants were recruited through organizational associations, community networks and advertising. Semi-structured interviews and qualitative content analysis framed data collection and analyses, and mapped communication-support processes. Results Seven themes underpinned communication-support process: (1) similarities and differences among physical and mental health episodic disabilities; (2) cultures of workplace support, including contrasting medical and biopsychosocial perspectives; (3) misgivings about others and their role in communication-support processes; (4) that subjective perceptions matter; (5) the inherent complexity of the response process; (6) challenges arising when a worker denies a disability; and (7) casting disability as a performance problem. Conclusions This study identifies a conceptual framework and areas where workplace disability support processes could be enhanced to improve inclusion and the sustainability of employment among workers living with episodic disabilities

Essays in international trade and organisational economics

This thesis contains three chapters that examine various facets of how the market and technological environment shapes firms – and how firms shape their environments. The first chapter studies how multinational manufacturing firms organise production in parallel processing supply chains. Using confidential data on international sourcing of French manufacturing firms and an instrumental variables strategy based on selfconstructed input-output tables, the chapter shows that inputs that account for a high cost share – i.e. that are more important for technological reasons – are more likely to be produced by a multinational for itself, while unimportant ones are outsourced to third parties. It provides additional empirical evidence that this main finding is consistent with a property rights model of the boundary of the firm. The second chapter produces empirical facts on how exogenous changes in tariffs on intermediate goods have affected vertical integration patterns in France over the period 1996-2006 and evaluates them in light of the current literature. Using a long differences approach and detailed information on supply relationships, it shows that more protectionist policies by other countries and by the EU discouraged integrated relationships from shifting towards outsourcing and that initial market structure mattered for the impact of trade policy. The third chapter provides rare causal evidence for the relevance of endowment driven comparative advantage. It uses the fracking boom in the US following 2006 as a source of exogenous variation in the endowment of natural gas – and therefore in energy: fracking made energy considerably cheaper in the US compared to the rest of the world. The chapter studies factor, output, and international trade responses across sectors. It finds that energy intensive sectors expand along all dimensions and, most importantly, export more, which validates one of the most important neo-classical theories of why countries trade with each other

Non-linear Dynamics in QED_3 and Non-trivial Infrared Structure

In this work we consider a coupled system of Schwinger-Dyson equations for self-energy and vertex functions in QED_3. Using the concept of a semi-amputated vertex function, we manage to decouple the vertex equation and transform it in the infrared into a non-linear differential equation of Emden-Fowler type. Its solution suggests the following picture: in the absence of infrared cut-offs there is only a trivial infrared fixed-point structure in the theory. However, the presence of masses, for either fermions or photons, changes the situation drastically, leading to a mass-dependent non-trivial infrared fixed point. In this picture a dynamical mass for the fermions is found to be generated consistently. The non-linearity of the equations gives rise to highly non-trivial constraints among the mass and effective (`running') gauge coupling, which impose lower and upper bounds on the latter for dynamical mass generation to occur. Possible implications of this to the theory of high-temperature superconductivity are briefly discussed.Comment: 29 pages LATEX, 7 eps figures incorporated, uses axodraw style. Discussion on the massless case (section 2) modified; no effect on conclusions, typos correcte

Soil hydrologic grouping guide which soil and weather properties best estimate corn nitrogen need

Nitrogen fertilizer recommendations in corn (Zea mays L.) that match the economically optimal nitrogen fertilizer rate (EONR) are imperative for profitability and minimizing environmental degradation. However, the amount of soil N available for the crop depends on soil and weather factors, making it difficult to know the EONR from year-to-year and from field-to-field. Our objective was to explore, within the framework of hydrologic soil groups and drainage classifications (HGDC), which site-specific soil and weather properties best estimated corn N needs (i.e., EONR) for two application timings (at-planting and side-dress). Included in this investigation was a validation step using an independent dataset. Forty-nine N response trials conducted across the U.S. Midwest Corn Belt over three growing seasons (2014–2016) were used for recommendation model development, and 181 independent site-years were used for validation. For HGDC models, soil organic matter (SOM), clay content, and evenness of rainfall distribution before side-dress N application were the properties generally most helpful in predicting EONR. Using the validation data, model recommendations were within 34 kg N ha–1 of EONR for 37 and 42% of the sites with a root mean square error (RMSE) of 70 and 68 kg N ha–1 for at-planting and side-dress applications, respectively. Compared to state-specific recommendations, sites needing ha–1 or no N were better estimated with HGDC models. In contrast, for sites where EONR was \u3e150 kg N ha–1, HGDC models underestimated N needs compared to state specific. These results show HGDC groupings could aid in developing tools for N fertilizer recommendations

Corn Nitrogen Nutrition Index Prediction Improved by Integrating Genetic, Environmental, and Management Factors with Active Canopy Sensing Using Machine Learning

Accurate nitrogen (N) diagnosis early in the growing season across diverse soil, weather, and management conditions is challenging. Strategies using multi-source data are hypothesized to perform significantly better than approaches using crop sensing information alone. The objective of this study was to evaluate, across diverse environments, the potential for integrating genetic (e.g., comparative relative maturity and growing degree units to key developmental growth stages), environmental (e.g., soil and weather), and management (e.g., seeding rate, irrigation, previous crop, and preplant N rate) information with active canopy sensor data for improved corn N nutrition index (NNI) prediction using machine learning methods. Thirteen site-year corn (Zea mays L.) N rate experiments involving eight N treatments conducted in four US Midwest states in 2015 and 2016 were used for this study. A proximal RapidSCAN CS-45 active canopy sensor was used to collect corn canopy reflectance data around the V9 developmental growth stage. The utility of vegetation indices and ancillary data for predicting corn aboveground biomass, plant N concentration, plant N uptake, and NNI was evaluated using singular variable regression and machine learning methods. The results indicated that when the genetic, environmental, and management data were used together with the active canopy sensor data, corn N status indicators could be more reliably predicted either using support vector regression (R2 = 0.74–0.90 for prediction) or random forest regression models (R2 = 0.84–0.93 for prediction), as compared with using the best-performing single vegetation index or using a normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE) together (R2 \u3c 0.30). The N diagnostic accuracy based on the NNI was 87% using the data fusion approach with random forest regression (kappa statistic = 0.75), which was better than the result of a support vector regression model using the same inputs. The NDRE index was consistently ranked as the most important variable for predicting all the four corn N status indicators, followed by the preplant N rate. It is concluded that incorporating genetic, environmental, and management information with canopy sensing data can significantly improve in-season corn N status prediction and diagnosis across diverse soil and weather conditions

Mixed Hodge polynomials of character varieties

We calculate the E-polynomials of certain twisted GL(n,C)-character varieties M_n of Riemann surfaces by counting points over finite fields using the character table of the finite group of Lie-type GL(n,F_q) and a theorem proved in the appendix by N. Katz. We deduce from this calculation several geometric results, for example, the value of the topological Euler characteristic of the associated PGL(n,C)-character variety. The calculation also leads to several conjectures about the cohomology of M_n: an explicit conjecture for its mixed Hodge polynomial; a conjectured curious Hard Lefschetz theorem and a conjecture relating the pure part to absolutely indecomposable representations of a certain quiver. We prove these conjectures for n = 2.Comment: with an appendix by Nicholas M. Katz; 57 pages. revised version: New definition for homogeneous weight in Definition 4.1.6, subsequent arguments modified. Some other minor changes. To appear in Invent. Mat

Expression of Inhibitory Receptors on T and NK Cells Defines Immunological Phenotypes of HCV Patients with Advanced Liver Fibrosis

Chronic HCV can result in advanced liver disease, including cirrhosis. Patients with advanced fibrosis experience poor clinical outcomes and increased risk for hepatocellular carcinoma (HCC). These outcomes are, in part, a consequence of immune dysfunction. Increased inhibitory receptor and Galectin-9 (GAL-9) expression is a possible mechanism promoting lymphocyte dysfunction. In this study, we measured the expression of inhibitory receptors and GAL-9 on T/NK cells of patients with chronic HCV with no to moderate fibrosis (F0-F2) and advanced fibrosis (F3-F4). To analyze their co-expression, we employed t-SNE analysis. Notably, we found that F3-F4 patients had higher frequencies of >3 inhibitory receptor co-expression on NK cells. Moreover, F3-F4 patients manifest a higher frequency of NK cells co-expressing TIGIT and TIM-3, and CD4/NK cells co-expressing LAG-3 and GAL-9. In conclusion, we identified phenotypes of immune dysregulation that could explain the increased susceptibility to infection and HCC in patients with chronic HCV with advanced fibrosis.Virology; Immunolog

A Public–Industry Partnership for Enhancing Corn Nitrogen Research and Datasets: Project Description, Methodology, and Outcomes

Due to economic and environmental consequences of N lost from fertilizer applications in corn (Zea mays L.), considerable public and industry attention has been devoted to the development of N decision tools. Needed are research and databases and associated metadata, at numerous locations and years to represent a wide geographic range of soil and weather scenarios, for evaluating tool performance. The goals of this research were to conduct standardized corn N rate response field studies to evaluate the performance of multiple public-domain N decision tools across diverse soils and environmental conditions, develop and publish new agronomic science for improved crop N management, and train new scientists. The geographic scope, scale, and unique collaborative arrangement warrant documenting details of this research. The objectives of this paper are to describe how the research was undertaken, reasons for the methods, and the project’s anticipated value. The project was initiated in a partnership between eight U.S. Midwest land-grant universities, USDA-ARS, and DuPont Pioneer. Research using a standardized protocol was conducted over the 2014 through 2016 growing seasons, yielding a total of 49 sites. Preliminary observations of soil and crop variables measured from each site revealed a magnitude of differences in soil properties (e.g., texture and organic matter) as well as differences in agronomic and economic responses to applied N. The project has generated a valuable dataset across a wide array of weather and soils that allows investigators to perform robust evaluation of N use in corn and N decision tools