Crystallization Characteristics of CaO-Al2O3-Based Mold Flux and Their Effects on In-Mold Performance during High-Aluminum TRIP Steels Continuous Casting

Crystallization behaviors of the newly developed lime-alumina-based mold fluxes for high-aluminum transformation induced plasticity (TRIP) steels casting were experimentally studied, and compared with those of lime-silica-based mold fluxes. The effects of mold flux crystallization characteristics on heat transfer and lubrication performance in casting high-Al TRIP steels were also evaluated. The results show that the crystallization temperatures of lime-alumina-based mold fluxes are much lower than those of lime-silica-based mold fluxes. Increasing B2O3 addition suppresses the crystallization of lime-alumina-based mold fluxes, while Na2O exhibits an opposite effect. In continuous cooling of lime-alumina-based mold fluxes with high B2O3 contents and a CaO/Al2O3 ratio of 3.3, faceted cuspidine precipitates first, followed by needle-like CaO center dot B2O3 or 9CaO center dot 3B(2)O(3)center dot CaF2. In lime-alumina-based mold flux with low B2O3 content (5.4 mass pct) and a CaO/Al2O3 ratio of 1.2, the formation of fine CaF2 takes place first, followed by blocky interconnected CaO center dot 2Al(2)O(3) as the dominant crystalline phase, and rod-like 2CaO center dot B2O3 precipitates at lower temperature during continuous cooling of the mold flux. In B2O3-free mold flux, blocky interconnected 3CaO center dot Al2O3 precipitates after CaF2 and 3CaO center dot 2SiO(2) formation, and takes up almost the whole crystalline fraction. The casting trials show that the mold heat transfer rate significantly decreases near the meniscus during the continuous casting using lime-alumina-mold fluxes with higher crystallinity, which brings a great reduction of surface depressions on cast slabs. However, excessive crystallinity of mold flux causes poor lubrication between mold and solidifying steel shell, which induces various defects such as drag marks on cast slab. Among the studied mold fluxes, lime-alumina-based mold fluxes with higher B2O3 contents and a CaO/Al2O3 ratio of 3.3 show comparatively improved performance.open113133sciescopu

Crystallization Kinetics and Mechanism of CaO-Al2O3-Based Mold Flux for Casting High-Aluminum TRIP Steels

Non-isothermal crystallization of the newly developed lime-alumina-based mold fluxes was investigated using differential scanning calorimetry. The crystallization kinetic parameters were determined by Ozawa equation, the combined Avrami-Ozawa equation, and the differential iso-conversional method of Friedman. It was found that Ozawa method failed to describe the non-isothermal crystallization behavior of the mold fluxes. The Avrami exponent determined by the combined Avrami-Ozawa equation indicates that the crystallization of cuspidine occurs through bulk nucleation and reaction-controlled three-dimensional growth, and then transforms to reaction-controlled two-dimensional growth at the crystallization later stage in lime-alumina-based mold fluxes with higher B2O3 content. For the mold fluxes with lower B2O3 content (10.8 mass pct), the crystallization of cuspidine is bulk nucleation and reaction-controlled two-dimensional growth at the crystallization primary stage followed by a diffusion-controlled two-dimensional growth process. The crystallization of CaF2 in mold flux originates from bulk nucleation and diffusion-controlled three-dimensional growth, which then transforms to two-dimensional growth. FE-SEM observations support these kinetic analysis results. The effective activation energy for cuspidine crystallization in the mold flux with higher B2O3 and Na2O contents increases as the crystallization progresses, and then decreases at the relative degree of crystallinity greater than 60 pct. The transition point of this trend approximately corresponds to the relative degree of crystallinity at which the crystallization mode of cuspidine transforms. For the mold fluxes with lower B2O3 and Na2O contents, the effective activation energy for cuspidine formation varies monotonically with the increase in the relative degree of crystallinity.open11149sciescopu

Evaluation of Matusita Equation and Its Modified Expression for Determining Activation Energy Associated with Melt Crystallization

Both the Matusita equation and the modified Matusita equation for estimating the activation energy associated with non-isothermal crystallization were critically evaluated. The derivation for melts crystallization on cooling indicates that, unlike for the crystallization that occurs on heating, the term 1 - exp (-Delta G/RT) in the basic rate equation of crystal growth and the term depending on the initial temperature of the cooling process cannot be neglected. It is demonstrated that both the Matusita equation and its modified expression are only valid to estimate the activation energy associated with the crystallization that occurs on heating, but are inapplicable for the melt crystallization that occurs on cooling. It is suggested that the isoconversional methods of Friedman and Vyazovkin should be alternative to determine effective activation energy for melt crystallization that occurs on cooling.open1133sciescopu

Reducing combinatorial uncertainties: A new technique based on MT2 variables

We propose a new method to resolve combinatorial ambiguities in hadron collider events involving two invisible particles in the final state. This method is based on the kinematic variable MT2 and on the MT2-assisted-on-shell reconstruction of invisible momenta, that are reformulated as `test' variables Ti of the correct combination against the incorrect ones. We show how the efficiency of the single Ti in providing the correct answer can be systematically improved by combining the different Ti and/or by introducing cuts on suitable, combination-insensitive kinematic variables. We illustrate our whole approach in the specific example of top anti-top production, followed by a leptonic decay of the W on both sides. However, by construction, our method is also directly applicable to many topologies of interest for new physics, in particular events producing a pair of undetected particles, that are potential dark-matter candidates. We finally emphasize that our method is apt to several generalizations, that we outline in the last sections of the paper.Comment: 1+23 pages, 8 figures. Main changes in v3: (1) discussion at the end of sec. 2 improved; (2) added sec. 4.2 about the method's dependence on mass information. Matches journal versio

Novel associations for hypothyroidism include known autoimmune risk loci

Hypothyroidism is the most common thyroid disorder, affecting about 5% of the general population. Here we present the first large genome-wide association study of hypothyroidism, in 2,564 cases and 24,448 controls from the customer base of 23andMe, Inc., a personal genetics company. We identify four genome-wide significant associations, two of which are well known to be involved with a large spectrum of autoimmune diseases: rs6679677 near _PTPN22_ and rs3184504 in _SH2B3_ (p-values 3.5e-13 and 3.0e-11, respectively). We also report associations with rs4915077 near _VAV3_ (p-value 8.3e-11), another gene involved in immune function, and rs965513 near _FOXE1_ (p-value 3.1e-14). Of these, the association with _PTPN22_ confirms a recent small candidate gene study, and _FOXE1_ was previously known to be associated with thyroid-stimulating hormone (TSH) levels. Although _SH2B3_ has been previously linked with a number of autoimmune diseases, this is the first report of its association with thyroid disease. The _VAV3_ association is novel. These results suggest heterogeneity in the genetic etiology of hypothyroidism, implicating genes involved in both autoimmune disorders and thyroid function. Using a genetic risk profile score based on the top association from each of the four genome-wide significant regions in our study, the relative risk between the highest and lowest deciles of genetic risk is 2.1

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Approaching disorder-free transport in high-mobility conjugated polymers.

Conjugated polymers enable the production of flexible semiconductor devices that can be processed from solution at low temperatures. Over the past 25 years, device performance has improved greatly as a wide variety of molecular structures have been studied. However, one major limitation has not been overcome; transport properties in polymer films are still limited by pervasive conformational and energetic disorder. This not only limits the rational design of materials with higher performance, but also prevents the study of physical phenomena associated with an extended π-electron delocalization along the polymer backbone. Here we report a comparative transport study of several high-mobility conjugated polymers by field-effect-modulated Seebeck, transistor and sub-bandgap optical absorption measurements. We show that in several of these polymers, most notably in a recently reported, indacenodithiophene-based donor-acceptor copolymer with a near-amorphous microstructure, the charge transport properties approach intrinsic disorder-free limits at which all molecular sites are thermally accessible. Molecular dynamics simulations identify the origin of this long sought-after regime as a planar, torsion-free backbone conformation that is surprisingly resilient to side-chain disorder. Our results provide molecular-design guidelines for 'disorder-free' conjugated polymers.We gratefully acknowledge financial support from the Engineering and Physical Sciences Research Council (EPSRC) through a programme grant (EP/G060738/1) and the Technology Strategy Board (TSB) (PORSCHED project). D. Venkateshvaran acknowledges financial support from the Cambridge Commonwealth Trust through a Cambridge International Scholarship. K. Broch acknowledges post-doctoral fellowship support from the German Research Foundation (DFG). Mateusz Zelazny acknowledges funding from the NanoDTC in Cambridge. The work in Mons was supported by the European Commission / Région Wallonne (FEDER – Smartfilm RF project), the Interuniversity Attraction Pole program of the Belgian Federal Science Policy Office (PAI 7/05), Programme d’Excellence de la Région Wallonne (OPTI2MAT project) and FNRS-FRFC. D.B. and J.C. are FNRS Research Fellows.This is the accepted manuscript. The final version's available from Nature at http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13854.html

Efficient derivation of NPCs, spinal motor neurons and midbrain dopaminergic neurons from hESCs at 3% oxygen

This protocol has been designed to generate neural precursor cells (NPCs) from human embryonic stem cells (hESCs) using a physiological oxygen (O(2)) level of 3% and chemically defined conditions. The first stage involves suspension culture of hESC colonies at 3% O(2), where they acquire a neuroepithelial identity over two weeks. This timescale is comparable to that at 20% O(2), but survival is enhanced. Sequential application of retinoic acid (RA) and purmorphamine (PM), from day 14 to 28, directs differentiation towards spinal motor neurons. Alternatively, addition of FGF-8 and PM generates midbrain dopaminergic neurons. OLIG2 induction in motor neuron precursors is 2-fold greater than at 20% O(2), whereas EN1 is 5-fold enhanced. 3% NPCs can be differentiated into all three neural lineages, and such cultures can be maintained long-term in the absence of neurotrophins. The ability to generate defined cell types at 3% O(2) should represent a significant advance for in vitro disease modelling and potentially cell-based therapies

An anatomy-based lumped parameter model of cerebrospinal venous circulation: can an extracranial anatomical change impact intracranial hemodynamics?

Background The relationship between extracranial venous system abnormalities and central nervous system disorders has been recently theorized. In this paper we delve into this hypothesis by modeling the venous drainage in brain and spinal column areas and simulating the intracranial flow changes due to extracranial morphological stenoses. Methods A lumped parameter model of the cerebro-spinal venous drainage was created based on anatomical knowledge and vessels diameters and lengths taken from literature. Each vein was modeled as a hydraulic resistance, calculated through Poiseuille’s law. The inputs of the model were arterial flow rates of the intracranial, vertebral and lumbar districts. The effects of the obstruction of the main venous outflows were simulated. A database comprising 112 Multiple Sclerosis patients (Male/Female = 42/70; median age ± standard deviation = 43.7 ± 10.5 years) was retrospectively analyzed. Results The flow rate of the main veins estimated with the model was similar to the measures of 21 healthy controls (Male/Female = 10/11; mean age ± standard deviation = 31 ± 11 years), obtained with a 1.5 T Magnetic Resonance scanner. The intracranial reflux topography predicted with the model in cases of internal jugular vein diameter reduction was similar to those observed in the patients with internal jugular vein obstacles. Conclusions The proposed model can predict physiological and pathological behaviors with good fidelity. Despite the simplifications introduced in cerebrospinal venous circulation modeling, the key anatomical feature of the lumped parameter model allowed for a detailed analysis of the consequences of extracranial venous impairments on intracranial pressure and hemodynamics

Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design

Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables