An Efficient Network Model for Determining the Effective Thermal Conductivity of Particulate Thermal Interface Materials

Particulate composites are commonly used in Microelectronics applications. One example of such materials is Thermal Interface Materials (TIMs) that are used to reduce the contact resistance between the chip and the heat sink. The existing analytical descriptions of thermal transport in particulate systems do not accurately account for the effect of inter-particle interactions, especially in the intermediate volume fractions of 30-80%. Another crucial drawback in the existing analytical as well as the network models is the inability to model size distributions (typically bimodal) of the filler material particles that are obtained as a result of the material manufacturing process. While full-field simulations (using, for instance, the finite element method) are possible for such systems, they are computationally expensive. In the present paper, we develop an efficient network model that captures the physics of inter-particle interactions and allows for random size distributions. Twenty random microstructural arrangements each of Alumina as well as Silver particles in Silicone and Epoxy matrices were generated using an algorithm implemented using a java language code. The microstructures were evaluated through both full-field simulations as well as the network model. The full-field simulations were carried out using a novel meshless analysis technique developed in the author’s (GS) research [26]. In all cases, it is shown that the random network models are accurate to within 5% of the full field simulations. The random network model simulations were efficient since they required two orders of magnitude smaller computation time to complete in comparison to the full field simulation

Estimating the Yield Strength of Thin Metal Films through Elastic-Plastic Buckling-Induced Debonding

In this paper, we propose a procedure to estimate the yield strength of thin films by debonding films from their substrate by elastic-plastic buckling under thermally-induced compressive loading. The out-of-plane displacement of the metal lines under conditions of elastic-plastic buckling is dependent on the yield strength of the film. Thus, an inverse estimate of the yield strength is made from measurements of the out-of-plane displacements of the buckled metal lines. The procedure is demonstrated to estimate the yield strength of aluminum lines consistent with measurements by other techniques

On QBF Proofs and Preprocessing

QBFs (quantified boolean formulas), which are a superset of propositional formulas, provide a canonical representation for PSPACE problems. To overcome the inherent complexity of QBF, significant effort has been invested in developing QBF solvers as well as the underlying proof systems. At the same time, formula preprocessing is crucial for the application of QBF solvers. This paper focuses on a missing link in currently-available technology: How to obtain a certificate (e.g. proof) for a formula that had been preprocessed before it was given to a solver? The paper targets a suite of commonly-used preprocessing techniques and shows how to reconstruct certificates for them. On the negative side, the paper discusses certain limitations of the currently-used proof systems in the light of preprocessing. The presented techniques were implemented and evaluated in the state-of-the-art QBF preprocessor bloqqer.Comment: LPAR 201

Tissue invasion and metastasis: molecular, biological and clinical perspectives

Cancer is a key health issue across the world, causing substantial patient morbidity and mortality. Patient prognosis is tightly linked with metastatic dissemination of the disease to distant sites, with metastatic diseases accounting for a vast percentage of cancer patient mortality. While advances in this area have been made, the process of cancer metastasis and the factors governing cancer spread and establishment at secondary locations is still poorly understood. The current article summarizes recent progress in this area of research, both in the understanding of the underlying biological processes and in the therapeutic strategies for the management of metastasis. This review lists the disruption of E-cadherin and tight junctions, key signaling pathways, including urokinase type plasminogen activator (uPA), phosphatidylinositol 3-kinase/v-akt murine thymoma viral oncogene (PI3K/AKT), focal adhesion kinase (FAK), β-catenin/zinc finger E-box binding homeobox 1 (ZEB-1) and transforming growth factor beta (TGF-β), together with inactivation of activator protein-1 (AP-1) and suppression of matrix metalloproteinase-9 (MMP-9) activity as key targets and the use of phytochemicals, or natural products, such as those from Agaricus blazei, Albatrellus confluens, Cordyceps militaris, Ganoderma lucidum, Poria cocos and Silybum marianum, together with diet derived fatty acids gamma linolenic acid (GLA) and eicosapentanoic acid (EPA) and inhibitory compounds as useful approaches to target tissue invasion and metastasis as well as other hallmark areas of cancer. Together, these strategies could represent new, inexpensive, low toxicity strategies to aid in the management of cancer metastasis as well as having holistic effects against other cancer hallmarks.W.G. Jiang ... S.K. Thompson ... et al

Upregulation of ASCL1 and inhibition of Notch signaling pathway characterize progressive astrocytoma

Astrocytoma is the most common type of brain cancer constituting more than half of all brain tumors. With an aim to identify markers describing astrocytoma progression, we have carried out microarray analysis of astrocytoma samples of different grades using cDNA microarray containing 1152 cancer-specific genes. Data analysis identified several differentially regulated genes between normal brain tissue and astrocytoma as well as between grades II/III astrocytoma and glioblastoma multiforme (GBM; grade IV). We found several genes known to be involved in malignancy including Achaete-scute complex-like 1 (Drosophila) (ASCL1; Hash 1). As ASCL has been implicated in neuroendocrine, medullary thyroid and small-cell lung cancers, we chose to examine the role of ASCL1 in the astrocytoma development. Our data revealed that ASCL1 is overexpressed in progressive astrocytoma as evidenced by increased levels of ASCL1 transcripts in 85.71% (6/7) of grade II diffuse astrocytoma (DA), 90% (9/10) of grade III anaplastic astrocytoma (AA) and 87.5% (7/8) of secondary GBMs, while the majority of primary de novo GBMs expressed similar to or less than normal brain levels (66.67%; 8/12). ASCL1 upregulation in progressive astrocytoma is accompanied by inhibition of Notch signaling as seen by uninduced levels of HES1, a transcriptional target of Notch1, increased levels of HES6, a dominant-negative inhibitor of HES1-mediated repression of ASCL1, and increased levels of Notch ligand Delta1, which is capable of inhibiting Notch signaling by forming intracellular Notch ligand autonomous complexes. Our results imply that inhibition of Notch signaling may be an important early event in the development of grade II DA and subsequent progression to grade III AA and secondary GBM. Furthermore, ASCL1 appears to be a putative marker to distinguish primary GBM from secondary GBM

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Automated Analysis in Feature Modelling and Product Configuration

The automated analysis of feature models is one of the thriving topics of research in the software product line and variability management communities that has attracted more attention in the last years. A recent literature review reported that more than 30 analysis operations have been identi ed and di erent analysis mechanisms have been proposed. Product con guration is a well established research eld with more than 30 years of successful applications in di erent industrial domains. Our hypothesis, that is not really new, is that these two independent areas of research have interesting synergies that have not been fully explored. To try to explore the potential synergies systematically, in this paper we provide a rapid review to bring together these previously disparate streams of work. We de ne a set of research questions and give a preliminary answer to some of them. We conclude that there are many research opportunities in the synergy of these independent areas.Ministerio de Ciencia e Innovación TIN2009- 07366Junta de Andalucía TIC-590

Tissue invasion and metastasis: Molecular, biological and clinical perspectives

Cancer is a key health issue across the world, causing substantial patient morbidity and mortality. Patient prognosis is tightly linked with metastatic dissemination of the disease to distant sites, with metastatic diseases accounting for a vast percentage of cancer patient mortality. While advances in this area have been made, the process of cancer metastasis and the factors governing cancer spread and establishment at secondary locations is still poorly understood. The current article summarizes recent progress in this area of research, both in the understanding of the underlying biological processes and in the therapeutic strategies for the management of metastasis. This review lists the disruption of E-cadherin and tight junctions, key signaling pathways, including urokinase type plasminogen activator (uPA), phosphatidylinositol 3-kinase/v-akt murine thymoma viral oncogene (PI3K/AKT), focal adhesion kinase (FAK), β-catenin/zinc finger E-box binding homeobox 1 (ZEB-1) and transforming growth factor beta (TGF-β), together with inactivation of activator protein-1 (AP-1) and suppression of matrix metalloproteinase-9 (MMP-9) activity as key targets and the use of phytochemicals, or natural products, such as those from Agaricus blazei, Albatrellus confluens, Cordyceps militaris, Ganoderma lucidum, Poria cocos and Silybum marianum, together with diet derived fatty acids gamma linolenic acid (GLA) and eicosapentanoic acid (EPA) and inhibitory compounds as useful approaches to target tissue invasion and metastasis as well as other hallmark areas of cancer. Together, these strategies could represent new, inexpensive, low toxicity strategies to aid in the management of cancer metastasis as well as having holistic effects against other cancer hallmarks

Multicomponent Domino Synthesis, Anticancer Activity and Molecular Modeling Simulation of Complex Dispirooxindolopyrrolidines

A series of spirooxindolopyrrolidine fused N -styrylpiperidone heterocyclic hybrids has been synthesized in excellent yield via a domino multicomponent protocol that involves one-pot three component 1,3-dipolar cycloaddition and concomitant enamine reactions performed in an inexpensive ionic liquid, namely 1-butyl-3-methylimidazolium bromide ([bmim]Br). Compounds thus synthesized were evaluated for their cytotoxicity against U-937 tumor cells. Interestingly; compounds 5i and 5m exhibited a better cytotoxicity than the anticancer drug bleomycin. In ddition; the effect of the synthesized compounds on the nuclear morphology of U937 FaDu cells revealed that treatment with compounds 5a–m led to their apoptotic cell death