A simulation tool to study methods of addressing of resources of a network operating system

In the paper a simulation tool to study an effectiveness of different methods of addressing of resources in network operating system and simulation experiments have been presented. This model makes it possible to study network operating systems with a static addressing of resources and network operating systems with admissible dynamic change of addresses of resources in a local area network. To carry on experiments the model of the network operating system has been extended adding a model of environment demands. The later has been constructed in such a way that it is not necessary to consider an influence of different methods of resource addressing on a distribution of arrival moments of those environment demands. The simulation tool presented here has been developed on the basis of a logical model of the network operating system constructed earlier [Gos 86]. The tool described in this paper could be treated as a basic one because it is possible to use many parts of it to construct other tools making possible simulation studies of other problems of network operating system (e.g., the effectiveness of distribution of resource management, synchronization). The simulation carried out shows that the simulation tool constructed can be effectively used to study the influence of different methods of resource addressing on a performance of network operating systems

A model of a distributed operating system

In this paper a logical model of a distributed operating system has been presented. This model of a distributed operating system contains a set of processes managing resources, connections between these processes, and mappings of events controlling this distributed operating system into processes managing resources. The fundamental types of resources introduced by the architecture of local computer networks, i.e., messages and data structures describing the location of resources in the network, have been defined. Operations on these resources and connections between the processes managing them and processes managing other resources of the distributed operating system have been presented. Addressing processes have been discussed. The model has been constructed in such a way that a synthesis of different simulation tools (models) to study distributed operating systems can be carried out. In particular, this model makes it possible to construct simulation tools to study the effectiveness of distributed operating systems with processes managing resources defined in different ways.That means that the model has been developed in such a way to be both a concept and a tool like the model developed by A. K. Jones. The later was treated by us as a background model

Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of Density Functional Theory (DFT). However, running large simulation cells with DFT is computationally demanding, while simulations of small cells are often plagued with non-physical effects that are a consequence of the system's finite size. Therefore, one is often forced to use empirical models that describe the physics of the material in terms of effective interaction terms, that are fitted using the results from DFT, to perform simulations that do not suffer from finite size effects. In this study we use a machine-learning (ML) potential trained on DFT, in combination with accelerated sampling techniques, to converge the thermodynamic properties of Barium Titanate (BTO) with first-principles accuracy and a full atomistic description. Our results indicate that the predicted Curie temperature depends strongly on the choice of DFT functional and system size, due to the presence of emergent long-range directional correlations in the local dipole fluctuations. Our findings demonstrate how the combination of ML models and traditional bottom-up modeling allow one to investigate emergent phenomena with the accuracy of first-principles calculations and the large size and time scales afforded by empirical models.Comment: 15 pages, 10 figure

Treatment of Correlation Effects in Electron Momentum Density: Density Fuctional Theory and Beyond

Recent high resolution Compton scattering experiments clearly reveal that there are fundamental limitations to the conventional local density approximation (LDA) based description of the ground state electron momentum density (EMD) in solids. In order to go beyond the framework of the density functional theory (DFT), we consider for the correlated system a BCS-like approach in which we start with a singlet pair wavefunction or a 'geminal' from which the many body wavefunction is then constructed by taking an antisymmetrized geminal product (AGP). A relatively simple practical implementation of the AGP method is developed where the one-particle orbitals are approximated by the Kohn-Sham solutions used in standard band computations, and the orbital-dependent BCS energy scale $\Delta_i$ is determined through a readily computed exchange-type integral. The methodology is illustrated by considering EMD and Compton profiles in Li, Be and Al. It is found that in Li the present scheme predicts a substantial renormalization of the LDA result for the EMD; in Be, the computed correlation effect is anisotropic, while in Al, the deviations from the LDA are relatively small. These theoretical predictions are in qualitative accord with the corresponding experimental observations on Li, Be and Al, and indicate the potential of the AGP method for describing correlation effects on the EMD in wide classes of materials.Comment: 4 figures, accepted for publication in J. Phys. Chem. Solid

Novel therapeutics for coronary artery disease from genome-wide association study data

BACKGROUND: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD. METHODS: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (http://www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatic modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD. RESULTS: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05). CONCLUSIONS: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies

Compton scattering beyond the impulse approximation

We treat the non-relativistic Compton scattering process in which an incoming photon scatters from an N-electron many-body state to yield an outgoing photon and a recoil electron, without invoking the commonly used frameworks of either the impulse approximation (IA) or the independent particle model (IPM). An expression for the associated triple differential scattering cross section is obtained in terms of Dyson orbitals, which give the overlap amplitudes between the N-electron initial state and the (N-1) electron singly ionized quantum states of the target. We show how in the high energy transfer regime, one can recover from our general formalism the standard IA based formula for the cross section which involves the ground state electron momentum density (EMD) of the initial state. Our formalism will permit the analysis and interpretation of electronic transitions in correlated electron systems via inelastic x-ray scattering (IXS) spectroscopy beyond the constraints of the IA and the IPM.Comment: 7 pages, 1 figur

Cancer-associated fibroblasts are positively correlated with metastatic potential of human gastric cancers

<p>Abstract</p> <p>Background</p> <p>The prognosis of gastric cancer patients is difficult to predict because of defects in establishing the surgical-pathological features. Cancer-associated fibroblasts (CAFs) have been found to play prominent role in promoting tumor growth, invasion and metastasis. Thus raises the hypothesis that the extent of CAFs prevalence may help to establish the prognosis of gastric cancer patients.</p> <p>Methods</p> <p>Immunochemistry and realtime-PCR experiments were carried out to compare the expression of proteins which are specific markers of CAFs or secreted by CAFs in the tumor and normal tissue specimens. The extent of CAFs' prevalence was graded according to immunochemical staining, and correlation was further analyzed between CAFs' prevalence and other tumor characteristics which may influence the prognosis of gastric cancer patients.</p> <p>Results</p> <p>Nearly 80 percent of normal gastric tissues were negative or weak positive for CAFs staining, while more than 60 percent of gastric cancer tissues were moderate or strong positive for CAFs staining. Realtime-PCR results also showed significant elevated expression of FAP, SDF-1 and TGF-β1 in gastric cancer tissues compared to normal gastric tissues. Further analysis showed that CAFs' prevalence was correlated with tumor size, depth of the tumor, lymph node metastasis, liver metastasis or peritoneum metastasis.</p> <p>Conclusions</p> <p>Reactive cancer associated fibroblasts (CAFs) were frequently accumulated in gastric cancer tissues, and the prevalence of CAFs was correlated with tumor size, depth of the tumor and tumor metastasis, thus give some supports for establishing the prognosis of the gastric cancer patients.</p

Phenotypic Overlap between MMP-13 and the Plasminogen Activation System during Wound Healing in Mice

BACKGROUND: Proteolytic degradation of extracellular matrix is a crucial step in the healing of incisional skin wounds. Thus, healing of skin wounds is delayed by either plasminogen-deficiency or by treatment with the broad-spectrum metalloproteinase (MP) inhibitor Galardin alone, while the two perturbations combined completely prevent wound healing. Both urokinase-type plasminogen activator and several matrix metallo proteinases (MMPs), such as MMP-3, -9 and -13, are expressed in the leading-edge keratinocytes of skin wounds, which may account for this phenotypic overlap between these classes of proteases. METHODOLOGY: To further test that hypothesis we generated Mmp13;Plau and Mmp13;Plg double-deficient mice in a cross between Mmp13- and Plau-deficient mice as well as Mmp13- and Plg-deficient mice. These mice were examined for normal physiology in a large cohort study and in a well-characterized skin wound healing model, in which we made incisional 20 mm-long full-thickness skin wounds. PRINCIPAL FINDINGS: While mice that are deficient in Mmp13 have a mean healing time indistinguishable to wild-type mice, wound healing in both Plau- and Plg-deficient mice is significantly delayed. Histological analysis of healed wounds revealed a significant increase in keratin 10/14 immunoreactive layers of kerationcytes in the skin surface in Mmp13;Plau double-deficient mice. Furthermore, we observe, by immunohistological analysis, an aberrant angiogenic pattern during wound healing induced by Plau-deficiency, which has not previously been described. CONCLUSIONS: We demonstrate a phenotypic overlap, defined as an additional delay in wound healing in the double-deficient mice compared to the individual single-deficient mice, between MMP-13 and the plasminogen activation system in the process of wound healing, but not during gestation and in postnatal development. Thus, a dual targeting of uPA and MMP-13 might be a possible future strategy in designing therapies aimed at tissue repair or other pathological processes, such as cancer invasion, where proteolytic degradation is a hallmark