Nonequilibrium brittle fracture propagation: Steady state, oscillations and intermittency

A minimal model is constructed for two-dimensional fracture propagation. The heterogeneous process zone is presumed to suppress stress relaxation rate, leading to non-quasistatic behavior. Using the Yoffe solution, I construct and solve a dynamical equation for the tip stress. I discuss a generic tip velocity response to local stress and find that noise-free propagation is either at steady state or oscillatory, depending only on one material parameter. Noise gives rise to intermittency and quasi-periodicity. The theory explains the velocity oscillations and the complicated behavior seen in polymeric and amorphous brittle materials. I suggest experimental verifications and new connections between velocity measurements and material properties.Comment: To appear in Phys. Rev. Lett., 6 pages, self-contained TeX file, 3 postscript figures upon request from author at [email protected] or [email protected], http://cnls-www.lanl.gov/homepages/rafi/rafindex.htm

No self-similar aggregates with sedimentation

Two-dimensional cluster-cluster aggregation is studied when clusters move both diffusively and sediment with a size dependent velocity. Sedimentation breaks the rotational symmetry and the ensuing clusters are not self-similar fractals: the mean cluster width perpendicular to the field direction grows faster than the height. The mean width exhibits power-law scaling with respect to the cluster size, ~ s^{l_x}, l_x = 0.61 +- 0.01, but the mean height does not. The clusters tend to become elongated in the sedimentation direction and the ratio of the single particle sedimentation velocity to single particle diffusivity controls the degree of orientation. These results are obtained using a simulation method, which becomes the more efficient the larger the moving clusters are.Comment: 10 pages, 10 figure

The convective storm initiation project

Copyright @ 2007 AMSThe Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model. A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawin-sondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP. This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.This work is funded by the National Environment Research Council following an initial award from the HEFCE Joint Infrastructure Fund

A peridynamic based machine learning model for one-dimensional and two-dimensional structures

With the rapid growth of available data and computing resources, using data-driven models is a potential approach in many scientific disciplines and engineering. However, for complex physical phenomena that have limited data, the data-driven models are lacking robustness and fail to provide good predictions. Theory-guided data science is the recent technology that can take advantage of both physics-driven and data-driven models. This study presents a novel peridynamics based machine learning model for one and two-dimensional structures. The linear relationships between the displacement of a material point and displacements of its family members and applied forces are obtained for the machine learning model by using linear regression. The numerical procedure for coupling the peridynamic model and the machine learning model is also provided. The numerical procedure for coupling the peridynamic model and the machine learning model is also provided. The accuracy of the coupled model is verified by considering various examples of a one-dimensional bar and two-dimensional plate. To further demonstrate the capabilities of the coupled model, damage prediction for a plate with a pre-existing crack, a two-dimensional representation of a three-point bending test, and a plate subjected to dynamic load are simulated

Artesunate induces oncosis-like cell death in vitro and has antitumor activity against pancreatic cancer xenografts in vivo

Pancreatic cancer is highly resistant to the currently available chemotherapeutic agents. Less than 5% of patients diagnosed with this disease could survive beyond 5 years. Thus, there is an urgent need for the development of novel, efficacious drugs that can treat pancreatic cancer. Herein we report the identification of artesunate (ART), a derivative of artemisinin, as a potent and selective antitumor agent against human pancreatic cancer cells in vitro and in vivo. ART exhibits selective cytotoxic activity against Panc-1, BxPC-3 and CFPAC-1 pancreatic cancer cells with IC50 values that are 2.3- to 24-fold less than that of the normal human hepatic cells (HL-7702). The pan caspase inhibitor zVAD-fmk did not inhibit the cytotoxic activity of ART. Electron microscopy of ART-treated cells revealed severe cytoplasmic swelling and vacuolization, swollen and internally disorganized mitochondria, dilation (but not fragmentation) of the nuclei without chromatin condensation, and cell lysis, yielding a morphotype that is typical of oncosis. The ART-treated cells exhibited a loss of mitochondrial membrane potential (ΔΨm) and ART-induced cell death was inhibited in the presence of the reactive oxygen species (ROS) scavenger N-acetyl-cysteine (NAC). Importantly, ART produced a dose-dependent tumor regression in an in vivo pancreatic cancer xenografts model. The in vivo antitumor activity of ART was similar to that of gemcitabine. Taken together, our study suggests that ART exhibits antitumor activity against human pancreatic cancer via a novel form of oncosis-like cell death, and that ART should be considered a potential therapeutic candidate for treating pancreatic cancer

Liquid facets-Related (lqfR) Is Required for Egg Chamber Morphogenesis during Drosophila Oogenesis

Clathrin interactor 1 [CLINT1] (also called enthoprotin/EpsinR) is an Epsin N-terminal homology (ENTH) domain-containing adaptor protein that functions in anterograde and retrograde clathrin-mediated trafficking between the trans-Golgi network and the endosome. Removal of both Saccharomyces cerevisiae homologs, Ent3p and Ent5p, result in yeast that are viable, but that display a cold-sensitive growth phenotype and mistrafficking of various vacuolar proteins. Similarly, either knock-down or overexpression of vertebrate CLINT1 in cell culture causes mistrafficking of proteins. Here, we have characterized Drosophila CLINT1, liquid-facets Related (lqfR). LqfR is ubiquitously expressed throughout development and is localized to the Golgi and endosome. Strong hypomorphic mutants generated by imprecise P-element excision exhibit extra macrochaetae, rough eyes and are female sterile. Although essentially no eggs are laid, the ovaries do contain late-stage egg chambers that exhibit abnormal morphology. Germline clones reveal that LqfR expression in the somatic follicle cells is sufficient to rescue the oogenesis defects. Clones of mutant lqfR follicle cells have a decreased cell size consistent with a downregulation of Akt1. We find that while total Akt1 levels are increased there is also a significant decrease in activated phosphorylated Akt1. Taken together, these results show that LqfR function is required to regulate follicle cell size and signaling during Drosophila oogenesis

Lattice Boltzmann simulations of soft matter systems

This article concerns numerical simulations of the dynamics of particles immersed in a continuum solvent. As prototypical systems, we consider colloidal dispersions of spherical particles and solutions of uncharged polymers. After a brief explanation of the concept of hydrodynamic interactions, we give a general overview over the various simulation methods that have been developed to cope with the resulting computational problems. We then focus on the approach we have developed, which couples a system of particles to a lattice Boltzmann model representing the solvent degrees of freedom. The standard D3Q19 lattice Boltzmann model is derived and explained in depth, followed by a detailed discussion of complementary methods for the coupling of solvent and solute. Colloidal dispersions are best described in terms of extended particles with appropriate boundary conditions at the surfaces, while particles with internal degrees of freedom are easier to simulate as an arrangement of mass points with frictional coupling to the solvent. In both cases, particular care has been taken to simulate thermal fluctuations in a consistent way. The usefulness of this methodology is illustrated by studies from our own research, where the dynamics of colloidal and polymeric systems has been investigated in both equilibrium and nonequilibrium situations.Comment: Review article, submitted to Advances in Polymer Science. 16 figures, 76 page

Highly Pathogenic Avian Influenza Virus H5N1 Infection in a Long-Distance Migrant Shorebird under Migratory and Non-Migratory States

Corticosterone regulates physiological changes preparing wild birds for migration. It also modulates the immune system and may lead to increased susceptibility to infection, with implications for the spread of pathogens, including highly pathogenic avian influenza virus (HPAIV) H5N1. The red knot (Calidris canutus islandica) displays migratory changes in captivity and was used as a model to assess the effect of high plasma concentration of corticosterone on HPAIV H5N1 infection. We inoculated knots during pre-migration (N = 6), fueling (N = 5), migration (N = 9) and post-migration periods (N = 6). Knots from all groups shed similar viral titers for up to 5 days post-inoculation (dpi), peaking at 1 to 3 dpi. Lesions of acute encephalitis, associated with virus replication in neurons, were seen in 1 to 2 knots per group, leading to neurological disease and death at 5 to 11 dpi. Therefore, the risk of HPAIV H5N1 infection in wild birds and of potential transmission between wild birds and poultry may be similar at different times of the year, irrespective of wild birds' migratory status. However, in knots inoculated during the migration period, viral shedding levels positively correlated with pre-inoculation plasma concentration of corticosterone. Of these, knots that did not become productively infected had lower plasma concentration of corticosterone. Conversely, elevated plasma concentration of corticosterone did not result in an increased probability to develop clinical disease. These results suggest that birds with elevated plasma concentration of corticosterone at the time of migration (ready to migrate) may be more susceptible to acquisition of infection and shed higher viral titers—before the onset of clinical disease—than birds with low concentration of corticosterone (not ready for take-off). Yet, they may not be more prone to the development of clinical disease. Therefore, assuming no effect of sub-clinical infection on the likelihood of migratory take-off, this may favor the spread of HPAIV H5N1 by migratory birds over long distances