Integrative and Comprehensive Pancancer Analysis of Regulator of Chromatin Condensation 1 (RCC1)

Regulator of Chromatin Condensation 1 (RCC1) is the only known guanine nucleotide exchange factor that acts on the Ras-like G protein Ran and plays a key role in cell cycle regulation. Although there is growing evidence to support the relationship between RCC1 and cancer, detailed pancancer analyses have not yet been performed. In this genome database study, based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases, the potential role of RCC1 in 33 tumors’ entities was explored. The results show that RCC1 is highly expressed in most human malignant neoplasms in contrast to healthy tissues. RCC1 expression is closely related to the prognosis of a broad variety of tumor patients. Enrichment analysis showed that some tumor-related pathways such as “cell cycle” and “RNA transport” were involved in the functional mechanism of RCC1. In particular, the conducted analysis reveals the relation of RCC1 to multiple immune checkpoint genes and suggests that the regulation of RCC1 is closely related to tumor infiltration of cancer-associated fibroblasts and CD8⁺ T cells. Coherent data demonstrate the association of RCC1 with the tumor mutation burden and microsatellite instability in various tumors. These findings provide new insights into the role of RCC1 in oncogenesis and tumor immunology in various tumors and indicate its potential as marker for therapy prognosis and targeted treatment strategies.     

Enforcing Effective Rates for Packet-Level QoS Control in IP Networks: Theory and Validation Based on Real Traffic Data

This paper presents experimental results aiming at underpinning a traffic engineering framework for traffic control and resource management in IP-based networks, which has significant theoretical qualities. Initially, the paper reviews the major components of a packet level traffic control framework: (a) a general traffic shaping algorithm for effective rate enforcement (b) mechanisms for aggregating, splitting and policing streams shaped with this algorithm, and (c) a calculus for quantitative end-to-end QoS. Following the illustration of the theoretical concepts the paper focuses on aspects pertaining to the applicability of the framework. Specifically, we study the impact of the shaping delay and we provide insight into the issue of enforcing effective rates to traffic streams. These studies take into account results from simulating the shaping algorithm, which are based on analyzing, processing and simulating real traffic traces collected from an HTTP server. Moreover, traffic modeling conclusions related to the proposed shaping algorithm, are derived and presented.     

Built-In Contract Testing in Component Integration Testing

Assembling new software systems from prefabricated components is an attractive alternative to traditional software engineering practices which promises to increase reuse and reduce development costs. However, these benefits will only occur if separately developed components can be made to work effectively together with reasonable effort. Lengthy and costly in-situ verification and acceptance testing directly undermines the benefits of independent component fabrication and late system integration. This position paper outlines and introduces an approach for reducing manual system verification effort by equipping components with the ability to check their execution environments at run-time. When deployed in new systems, built-in tester components check the contract-compliance of their server components, including the run-time system, and thus automatically verify their ability to fulfill their own obligations. This comprises functional/behavioural contracts as well as quality-of-service contracts between individual components. Enhancing traditional component-based development methods with built-in contract testing in this way reduces the costs associated with component assembly, and thus makes the “plug-and-play” vision of component-based development closer to practical reality.     

Observability-based consistent EKF estimators for multi-robot cooperative localization

In this paper, we investigate the consistency of extended Kalman filter (EKF)-based cooperative localization (CL) from the perspective of observability. We analytically show that the error-state system model employed in the standard EKF-based CL always has an observable subspace of higher dimension than that of the actual nonlinear CL system. This results in unjustified reduction of the EKF covariance estimates in directions of the state space where no information is available, and thus leads to inconsistency. To address this problem, we adopt an observability-based methodology for designing consistent estimators in which the linearization points are selected to ensure a linearized system model with observable subspace of correct dimension. In particular, we propose two novel observability-constrained (OC)-EKF estimators that are instances of this paradigm. In the first, termed OC-EKF 1.0, the filter Jacobians are calculated using the prior state estimates as the linearization points. In the second, termed OC-EKF 2.0, the linearization points are selected so as to minimize their expected errors (i.e., the difference between the linearization point and the true state) under the observability constraints. The proposed OC-EKFs have been tested in simulation and experimentally, and have been shown to significantly outperform the standard EKF in terms of both accuracy and consistency.     

Sojourn time distributions and time scale separation results for multiclass state-dependent processor sharing systems with a finite service pool and exponential service requirements

The paper addresses multiclass processor sharing systems with general state-dependent service rates, exponential service requirements and a finite service pool. By considering the amount of service received by a permanent customer and associating this service with the evolution of a Markov Reward process, the sojourn time distribution is formulated in terms of a matrix exponential expression. When the service rates are balanced, this expression can be diagonalized. Tail asymptotics are also discussed. The matrix exponential expression is subsequently exploited towards the study of time scale separation regimes. Unlike the standard practice of assuming a distinct time scale per class, the paper groups more realistically all customer classes in two time scales. Provably tight approximations, of a known, small degree of error, are developed for the sojourn time distribution of a given class (with either fast or slow dynamics), in terms of reduced models containing only the customer classes operating in the same time scale. The approximation for the fast classes gives rise to further characterization of the tail behavior. Additionally, the paper studies another, more specialized variant of the time scale separation regime, in which the service rates take a special form that leads to even simpler approximations. Finally, it is shown that the essence of the main results applies also to the more general setting of service requirement distributions with Markovian phase-type form.     

Substrate‐Dependent Molecular and Nanostructural Orientation of Nafion Thin Films

The effects of film thickness and substrate composition on the ionomer structure in porous electrodes are critical in understanding pathways toward developing higher performance electrochemical devices, including fuel cells and batteries. Insights are gained into the molecular and nanostructural orientation dependence for thin Nafion films (12–300 nm thick) on gold, platinum, and SiO₂ model substrates. Molecular orientation is determined from the birefringence measured using spectroscopic ellipsometry, while the nanostructural orientation of the ionic domains is measured using grazing‐incidence small‐angle X‐ray scattering. Density functional theory calculations for the molecular polarizability of the Nafion backbone and side chain show complimentary contributions to the measured birefringence values for the material. Nafion films prepared on SiO₂ substrates exhibit a nearly isotropic molecular and nanostructural orientation. Films on gold and platinum display parallel backbone orientations, relative to the substrate, with decreasing film thickness. However, a birefringence transition toward molecular isotropy is observed for 30 nm thick films on Au and Pt; while the ionic nanostructured domains continuously align parallel to the substrate. This apparent isotropic molecular orientation with increasing domain orientation highlights the difference between the backbone and side chain orientation, a key finding for elucidating transport in confined films at the interfaces.     

Competition between surface energy and elastic anisotropies in the growth of coherent solid-state dendrites

A new phase-field model of microstructural evolution is presented that includes the effects of elastic strain energy. The model’s thin interface behavior is investigated by mapping it onto a recent model developed by Echebarria et al. [Echebarria B, Folch R, Karma A, Plapp M. Phys Rev E 2004;70:061604]. Exploiting this thin interface analysis, the growth of solid-state dendrites are simulated with diffuse interfaces and the phase-field and mechanical equilibrium equations are solved in real space on an adaptive mesh. A morphological competition between surface energy anisotropy and elastic anisotropy is examined. Two dimensional simulations are reported that show that solid-state dendritic structures undergo a transition from a surface-dominated [Meiron DI. Phys Rev A 1986;33:2704] growth direction to an elastically driven [Steinbach I, Apel M. Phys D – Nonlinear Phenomena 2006;217:153] growth direction due to changes in the elastic anisotropy, the surface anisotropy and the supersaturation. Using the curvature and strain corrections to the equilibrium interfacial composition and linear stability theory for isotropic precipitates as calculated by Mullins and Sekerka, the dominant growth morphology is predicted.     

Quantifying adsorption of heparin on a PVC substrate using ATR‐FTIR

The surface modification of poly(vinyl chloride) (PVC) tubing by heparin was performed to increase its blood compatibility. A solution of benzalkonium heparinate was used in the treatment of two types of plasticized PVC. The modification of the PVC surface was monitored after various treatment conditions, and quantitative results were obtained by using ATR‐FTIR spectroscopy. The treatment times and the PVC type have a strong influence on the observed amount of heparin. A partial removal (20–30 %) of heparin was observed after rinsing the PVC surface with a 0.9 wt% NaCl aqueous solution. The more flexible PVC tubing, having a lower T_g, had a higher concentration of heparin. Final heparin concentrations on the PVC surfaces were found to be in the range 1–17 µg cm^?2. Copyright © 2004 Society of Chemical Industry     

Thick membrane, solid contact ion selective electrode for the detection of lead at picomolar levels

A new approach for decreasing the lower detection limit of a lead ion selective electrode (ISE) is presented. The ISE is designed using nonfunctionalized porous glassy carbon loaded with ionophore/plasticizer/additive cocktail. This material acts both as the support for the liquid polymeric membrane and as the signal transducer of the ISE. The high purity of the glassy carbon, together with its high conductivity, allows for the development of a thick, low-resistance composite membrane. This sensor element enables the continuous measurement of lead down to picomolar levels, with very small detection limit deterioration due to the lead ion transport within the bulk of the thick membrane.     

A support vector machine approach for detection of microcalcifications

In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive enhancement learning scheme for improved performance. SVM is a machine-learning method, based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate MC detection as a supervised-learning problem and apply SVM to develop the detection algorithm. We use the SVM to detect at each location in the image whether an MC is present or not. We tested the proposed method using a database of 76 clinical mammograms containing 1120 MCs. We use free-response receiver operating characteristic curves to evaluate detection performance, and compare the proposed algorithm with several existing methods. In our experiments, the proposed SVM framework outperformed all the other methods tested. In particular, a sensitivity as high as 94% was achieved by the SVM method at an error rate of one false-positive cluster per image. The ability of SVM to out perform several well-known methods developed for the widely studied problem of MC detection suggests that SVM is a promising technique for object detection in a medical imaging application.