Shear enhanced heterogeneous nucleation in some Mg- and Al- alloys

Intensive shearing was applied to alloy melts at temperatures above their liquidus by using a twinscrew mechanism. The sheared melt was then cast into a TP1 mould for microstructural examination. Alloy melts with or without shearing were also filtered using the Prefil technique developed by N-Tech Ltd in order to analyse oxides and other second phase particles. The experimental results showed a significant grain refinement through enhancement of heterogeneous nucleation. The intensive melt shearing converted oxide films and agglomerates into well dispersed fine particles with a narrow size distribution. It was confirmed that the fine oxide particles can act as potent sites for nucleation during the solidification of the sheared melt. This paper presents the experimental results and theoretical analysis of shear enhanced heterogeneous nucleation during solidification of Mg- and Al-alloys. A multi-step heterogeneous nucleation mechanism has been proposed and discussed

Differential subcellular localization and activity of kelch repeat proteins KLHDC1 and KLHDC2.

We have previously identified and characterized human KLHDC2/HCLP-1, a kelch repeat protein that interacts with and inhibits transcription factor LZIP. In this study, we identified and characterized a paralog of KLHDC2 called KLHDC1. KLHDC1 and KLHDC2 share about 50% identity at the level of amino acid sequence and both gene loci localize to human chromosome 14q21.3. This cluster of KLHDC1 and KLHDC2 genes is highly conserved in vertebrates ranging from pufferfish to human. Both genes are expressed highly in skeletal muscle, but weakly in various other tissues. While KLHDC2 was predominantly found in the nucleus, KLHDC1 is a cytoplasmic protein. Neither KLHDC1 nor KLHDC2 binds to actin. In addition, KLHDC1 was unable to inhibit LZIP/CREB3-mediated transcriptional activation. Thus, KLHDC1 and KLHDC2 have differential localization and activity in cultured mammalian cells.postprin

Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithms and model predictive control, suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. To circumvent this trade-off, a 2-step procedure is motivated: first learning of a controller during offline training based on an arbitrarily complicated mathematical system model, before online fast feedforward evaluation of the trained controller. The contribution of this paper is the proposition of a simple gradient-free and model-based algorithm for deep reinforcement learning using task separation with hill climbing (TSHC). In particular, (i) simultaneous training on separate deterministic tasks with the purpose of encoding many motion primitives in a neural network, and (ii) the employment of maximally sparse rewards in combination with virtual velocity constraints (VVCs) in setpoint proximity are advocated.Comment: 10 pages, 6 figures, 1 tabl

PAK4 phosphorylates p53 at serine 215 to promote liver cancer metastasis

PAK4 kinase contributes to signaling pathways controlling cancer cell transformation, invasion and survival, but its clinicopathological impact has begun to emerge only recently. Here we report that PAK4 overexpression in hepatocellular carcinoma (HCC) conveys aggressive metastatic properties. A novel nuclear splice isoform of PAK4 lacking exon 2 sequences was isolated as part of our studies. By stably overexpressing or silencing PAK4 in HCC cells we showed that it was critical for their migration. Mechanistic investigations in this setting revealed that PAK4 directly phosphorylated p53 at S215, which not only attenuated transcriptional transactivation activity but also inhibited p53-mediated suppression of HCC cell invasion. Taken together, our results showed how PAK4 overexpression in HCC promotes metastatic invasion by regulating p53 phosphorylation.postprin

Excitation Spectra And Hard-core Thermodynamics Of Bosonic Atoms In Optical Superlattices

A generalized double-well-basis coupled representation is proposed to investigate excitation spectra and thermodynamics of bosonic atoms in double-well optical superlattices. In the hard-core limit and with a filling factor of one, excitations describing the creation of pairs of a doubly occupied state and a simultaneous empty state, and those from a symmetric singly occupied state to an antisymmetric state are carefully analyzed and their excitation spectra are calculated within mean-field theory. Based on the hard-core statistics, the equilibrium properties such as heat capacity and particle populations are studied in detail. The cases with other filling factors are also briefly discussed.published_or_final_versio

Artificial interspecific hybridization between Macrobrachium species

Viable F-1 hybrids were obtained from crosses of female Macrobrachium nipponense and male Macrobrachium hainanense involving spermatophore transfer and artificial insemination. This represents the first successful known case of hybridization of two Macrobrachium species by means of artificial insemination. The hatching rate was over 90%. About 20-60% of newly hatched larvae metamorphosed to postlarvae. The morphological characteristics of the hybrids resembled a combination of features of both parents. Malate dehydrogenase (MDH) and esterase (EST) isozyme electrophoresis indicated parents and F-1 hybrids showed co-dominant expression of the paternal and maternal alleles controlling the isozymes and confirmed the hybridization. (C) 2004 Elsevier B.V. All rights reserved.Viable F-1 hybrids were obtained from crosses of female Macrobrachium nipponense and male Macrobrachium hainanense involving spermatophore transfer and artificial insemination. This represents the first successful known case of hybridization of two Macrobrachium species by means of artificial insemination. The hatching rate was over 90%. About 20-60% of newly hatched larvae metamorphosed to postlarvae. The morphological characteristics of the hybrids resembled a combination of features of both parents. Malate dehydrogenase (MDH) and esterase (EST) isozyme electrophoresis indicated parents and F-1 hybrids showed co-dominant expression of the paternal and maternal alleles controlling the isozymes and confirmed the hybridization. (C) 2004 Elsevier B.V. All rights reserved

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi

Variational Methods for Biomolecular Modeling

Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrostatics and solvation that includes the curvature energy of the molecular surface, the formation of microdomains on lipid membrane due to the geometric and molecular mechanics at the lipid interface, and the mean curvature driven protein localization on membrane surfaces. By further implicitly representing the interface using a phase field function over the entire domain, one can simulate the dynamics of the interface and the corresponding energy variation by evolving the phase field function, achieving significant reduction of the number of degrees of freedom and computational complexity. Strategies for improving the efficiency of computational implementations and for extending applications to coarse-graining or multiscale molecular simulations are outlined.Comment: 36 page

The degradation of p53 and its major E3 ligase Mdm2 is differentially dependent on the proteasomal ubiquitin receptor S5a.

p53 and its major E3 ligase Mdm2 are both ubiquitinated and targeted to the proteasome for degradation. Despite the importance of this in regulating the p53 pathway, little is known about the mechanisms of proteasomal recognition of ubiquitinated p53 and Mdm2. In this study, we show that knockdown of the proteasomal ubiquitin receptor S5a/PSMD4/Rpn10 inhibits p53 protein degradation and results in the accumulation of ubiquitinated p53. Overexpression of a dominant-negative deletion of S5a lacking its ubiquitin-interacting motifs (UIM)s, but which can be incorporated into the proteasome, also causes the stabilization of p53. Furthermore, small-interferring RNA (siRNA) rescue experiments confirm that the UIMs of S5a are required for the maintenance of low p53 levels. These observations indicate that S5a participates in the recognition of ubiquitinated p53 by the proteasome. In contrast, targeting S5a has no effect on the rate of degradation of Mdm2, indicating that proteasomal recognition of Mdm2 can be mediated by an S5a-independent pathway. S5a knockdown results in an increase in the transcriptional activity of p53. The selective stabilization of p53 and not Mdm2 provides a mechanism for p53 activation. Depletion of S5a causes a p53-dependent decrease in cell proliferation, demonstrating that p53 can have a dominant role in the response to targeting S5a. This study provides evidence for alternative pathways of proteasomal recognition of p53 and Mdm2. Differences in recognition by the proteasome could provide a means to modulate the relative stability of p53 and Mdm2 in response to cellular signals. In addition, they could be exploited for p53-activating therapies. This work shows that the degradation of proteins by the proteasome can be selectively dependent on S5a in human cells, and that this selectivity can extend to an E3 ubiquitin ligase and its substrate

Robust statistical frontalization of human and animal faces

The unconstrained acquisition of facial data in real-world conditions may result in face images with significant pose variations, illumination changes, and occlusions, affecting the performance of facial landmark localization and recognition methods. In this paper, a novel method, robust to pose, illumination variations, and occlusions is proposed for joint face frontalization and landmark localization. Unlike the state-of-the-art methods for landmark localization and pose correction, where large amount of manually annotated images or 3D facial models are required, the proposed method relies on a small set of frontal images only. By observing that the frontal facial image of both humans and animals, is the one having the minimum rank of all different poses, a model which is able to jointly recover the frontalized version of the face as well as the facial landmarks is devised. To this end, a suitable optimization problem is solved, concerning minimization of the nuclear norm (convex surrogate of the rank function) and the matrix ℓ1 norm accounting for occlusions. The proposed method is assessed in frontal view reconstruction of human and animal faces, landmark localization, pose-invariant face recognition, face verification in unconstrained conditions, and video inpainting by conducting experiment on 9 databases. The experimental results demonstrate the effectiveness of the proposed method in comparison to the state-of-the-art methods for the target problems