A Study on Emotional Maturity of College Students

The Emotional maturity becomes important in the behaviour of individuals. As the students are the pillars of the future generations their Emotional maturity is vital one. So the present study intends to measure the Emotional Maturity of college students. Normative survey method and random sampling technique has been used in the present study. The “Emotional Maturity Scale†standardized by K.M.Roma Pal [5] was used for this study. The result of the study shows that the emotional maturity of college students is extremely unstable

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

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

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

RpoS Regulates a Novel Type of Plasmid DNA Transfer in Escherichia coli

Spontaneous plasmid transformation of Escherichia coli is independent of the DNA uptake machinery for single-stranded DNA (ssDNA) entry. The one-hit kinetic pattern of plasmid transformation indicates that double-stranded DNA (dsDNA) enters E. coli cells on agar plates. However, DNA uptake and transformation regulation remain unclear in this new type of plasmid transformation. In this study, we developed our previous plasmid transformation system and induced competence at early stationary phase. Despite of inoculum size, the development of competence was determined by optical cell density. DNase I interruption experiment showed that DNA was taken up exponentially within the initial 2 minutes and most transforming DNA entered E. coli cells within 10 minutes on LB-agar plates. A half-order kinetics between recipient cells and transformants was identified when cell density was high on plates. To determine whether the stationary phase master regulator RpoS plays roles in plasmid transformation, we investigated the effects of inactivating and over-expressing its encoding gene rpoS on plasmid transformation. The inactivation of rpoS systematically reduced transformation frequency, while over-expressing rpoS increased plasmid transformation. Normally, RpoS recognizes promoters by its lysine 173 (K173). We found that the K173E mutation caused RpoS unable to promote plasmid transformation, further confirming a role of RpoS in regulating plasmid transformation. In classical transformation, DNA was transferred across membranes by DNA uptake proteins and integrated by DNA processing proteins. At stationary growth phase, RpoS regulates some genes encoding membrane/periplasmic proteins and DNA processing proteins. We quantified transcription of 22 of them and found that transcription of only 4 genes (osmC, yqjC, ygiW and ugpC) encoding membrane/periplasmic proteins showed significant differential expression when wildtype RpoS and RpoSK173E mutant were expressed. Further investigation showed that inactivation of any one of these genes did not significantly reduce transformation, suggesting that RpoS may regulate plasmid transformation through other/multiple target genes

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