A fuzzy queue-aware routing approach for wireless mesh networks

Recent advances in Wireless Mesh Networks (WMNs) have overcome the drawbacks of traditional wired and ad-hoc networks and now they are seen as a means of allowing last mile communications with quality level assurance in Future Multimedia Systems. However, new routing schemes are needed to provide end-to-end Quality of Service (QoS) and Quality of Experience (QoE) support for delay/loss/jitter-sensitive multimedia applications. The well-known OLSR (Optimized Link State Routing) protocol with ETX (Expected Transmission Count) metric brings many benefits to the path selection process, but has a drawback with regard to queue availability management, which reduces the system performance. This problem is caused when OLSR-EXT control messages are exchanged and the queues of mesh routers along the end-to-end communication path are overloaded. As a result, multimedia-related packets will suffer from loss/delay/jitter and the overall system performance will decrease. This paper proposes the Optimized Link State Routing-Fuzzy ETX Queue (OLSR-FEQ) protocol to overcome the limitations of OLSR-ETX regarding queue availability, QoS and QoE assurance. OLSR-FEQ optimizes network and user-based parameters by coordinating queue availability, QoS and fuzzy issues in the routing decision process as a way of allocating the best paths for multimedia applications. Performance evaluations were carried out with the Network Simulator (NS-2.34) to show the benefits of the proposed solution when compared with existing routing schemes, namely OLSR-ETX, OLSR-FLC, OLSR-MD and HWMP (IEEE 802.11s standard), regarding QoS (unsuccessful packet delivery and throughput) and QoE (PSNR, SSIM, VQM and MOS) parameters.     

Resistivity as a function of composition in the superconducting Nb-Pt A15 phase

The electrical resistivity of the A15 compound Nb_100–x Pt _x (20x28.9) is measured as a function of compositionx from room temperature to the superconducting transition temperatureT _c The residual resistivity ₀ is observed to be nearly independent of composition on the Nb-rich side of stoichiometry, but strongly dependent on the Pt-rich side. A closeT _c correlation with the resistivity sloped/dT at high temperatures and with the electronic specific heat coefficient , which are proportional to the superconducting coupling parameter , is noted. The results can be understood in terms of an order-disorder model.     

A random dipole model for spontaneous brain activity

The statistical properties of the EEG and the MEG are described mathematically as the result of randomly distributed dipoles. These dipoles represent the interactions of cortical neurons. For certain dipole distributions, the first- and second-order moments of the electric and magnetic fields are derived analytically. If the dipoles are in a spherical volume conductor and have no preference for any direction, the variance of a differentially measured EEG-signal is only a function of the electrode distance. In this paper, the theoretically derived variance function will be compared with EEG- and MEG-measurements. It is shown that a dipole with a fixed position and a randomly fluctuating amplitude is an adequate model for the alpha-rhythm. An expression for the covariance between the magnetic field and a differentially measured EEG-signal is derived. This covariance is considered as a function of the magnetometer position, and is compared with the measurements of Chapman et al. [23]. The theory can be used to obtain a (spatial) covariance matrix of the background noise, which occurs in evoked potential measurements. Such a covariance matrix can be used to obtain a maximum likelihood estimator of the dipole parameters in evoked potential studies, to evaluate the merits of the so-called "Laplacian derivation," and for the interpolation of electromagnetic data.     

The Chick Chorioallantoic Membrane Model: A New In Vivo Tool to Evaluate Breast Cancer Stem Cell Activity

The high plasticity of cancer stem-like cells (CSCs) allows them to differentiate and proliferate, specifically when xenotransplanted subcutaneously into immunocompromised mice. CSCs are highly tumorigenic, even when inoculated in small numbers. Thus, in vivo limiting dilution assays (LDA) in mice are the current gold standard method to evaluate CSC enrichment and activity. The chick embryo chorioallantoic membrane (CAM) is a low cost, naturally immune-incompetent and reproducible model widely used to evaluate the spontaneous growth of human tumor cells. Here, we established a CAM-LDA assay able to rapidly reproduce tumor specificities—in particular, the ability of the small population of CSCs to form tumors. We used a panel of organotropic metastatic breast cancer cells, which show an enrichment in a stem cell gene signature, enhanced CD44⁺/CD24^−/low cell surface expression and increased mammosphere-forming efficiency (MFE). The size of CAM-xenografted tumors correlate with the number of inoculated cancer cells, following mice xenograft growth pattern. CAM and mice tumors are histologically comparable, displaying both breast CSC markers CD44 and CD49f. Therefore, we propose a new tool for studying CSC prevalence and function—the chick CAM-LDA—a model with easy handling, accessibility, rapid growth and the absence of ethical and regulatory constraints.     

P16 and HPV Genotype Significance in HPV-Associated Cervical Cancer—A Large Cohort of Two Tertiary Referral Centers

The expression of p16 is a good surrogate of human papillomavirus (HPV) infection in HPV-associated cancers. The significance of p16 expression, HPV genotype and genera in the outcome of patients with HPV-associated cervical cancer (CC) is unclear. Our aim is to ascertain the prognostic significance of these factors. Data from 348 patients (median age: 47.5 years old) with CC, diagnosed in two referral centers, were retrospectively collected. Advanced disease (FIGO2018 IB2-IV) was present in 68% of patients. A single HPV genotype was identified in 82.8% of patients. The most common HPVs were HPV16 (69%) and HPV18 (14%). HPV genera reflected this distribution. HPV16 tumors presented at an earlier stage. P16 was negative in 18 cases (5.2%), 83.3% of which were squamous cell carcinomas. These cases occurred in older patients who tended to have advanced disease. In the univariate analysis, HPV16 (HR: 0.58; p = 0.0198), α-9 genera (HR: 0.37; p = 0.0106) and p16 overexpression (HR: 0.54; p = 0.032) were associated with better survival. HPV16 (HR: 0.63; p = 0.0174) and α-9 genera (HR: 0.57; p = 0.0286) were associated with less relapse. In the multivariate analysis, only the International Federation of Gynecology and Obstetrics (FIGO) stage retained an independent prognostic value. HPV16, α-9 genera and p16 overexpression were associated with better survival, although not as independent prognostic factors. Patients with p16-negative HPV-associated CC were older, presented with advanced disease and had worse prognosis.     

Color and COD retention by nanofiltration membranes

In the present study the application of the nanofiltration process was investigated mainly in the retention ofcolor and chemical oxygen demand (COD) present in textile industry wastewater. Nanofiltration experiments were carried out in a pilot unit, operating in crossflow. Three different types of spiral wound membranes, DK 1073, NF 45 and MPS 31 were used simultaneously in the same unit. The results of the tests showed that for color retention, the values were around 99% for the DK 1073 and NF 45 membranes and the 87% for COD retention for the DK 1073. The permeate flux for the different wastewaters varied from 30.5 to 70 L/h.m². Fouling was observed in all membranes due to the accumulation of molecular species close to the filtering surface. The process was efficient and promising for the reuse of wastewater from this type of industry.     

Effect of catalysts in the quality of syngas and by-products obtained by co-gasification of coal and wastes. 1. Tars and nitrogen compounds abatement

The aim of this work is to analyse the possibility of using co-gasification technology to process coal mixed with wastes to take profit of its energy content and at the same time to minimize the environmental impact associated with the use of wastes and to diminish the costs of flue gas treatment. The addition to coal of different types of materials, like: pine based waste, petcoke and polyethylene (PE), was not found to give rise to any operational problems, regarding both the feeding system and gasification process and led to higher energy conversions, however, the gas presented higher tars and hydrocarbons content. Several catalysts were tested, such as, dolomite, olivine, nickel and magnesium oxides, zinc oxides and cobalt and molybdenum oxides. Catalyst action was analysed in tars release and also in ammonia compounds reduction. The presence of catalysts allowed increasing hydrogen release, whilst there was a decrease in hydrocarbons and tars contents. A nickel-magnesium oxide was the catalyst that led to the highest reduction in hydrocarbons and tars. This catalyst also led to the lowest NH₃ content in the fuel gas produced, due to the catalyst efficiency in NH₃ destruction.     

Microporous anisotropic phase inversion membranes from bisphenol A polycarbonate: Effect of additives to the polymer solution

Phase inversion is a very flexible technique to obtain membranes with a large sort of morphologies. Membrane properties can vary greatly depending on the kind of polymer system used. Bisphenol A polycarbonate (PC) could be used as a phase inversion membrane base polymer, and presents very good properties. Nevertheless, very little information on membrane preparation using PC and the phase inversion process can be found in the literature. In this work flat‐sheet microporous membranes were obtained by the phase inversion process using the immersion precipitation technique. A new polymer system was studied, consisting of polycarbonate, N‐methyl‐2‐pyrrolidone as solvent, water as the nonsolvent, and an additive. The influence of some parameters on membrane morphology, such as polymer solution composition, exposition time before immersion into the precipitation bath, and the kind of additive was investigated. Precipitation was followed using light transmission experiments and membrane morphology was observed through Scanning Electron Microscopy (SEM). The viscosity and cloud points of all polymer solutions were also determined. The results were related to the studied synthesis parameters, using the basic principles of membrane formation by the phase inversion technique, looking forward to establishing criteria to control the morphology of flat‐sheet membranes using polycarbonate as the base polymer. The results showed that both additives were able to increase pore interconnectivity and even suppress macrovoid formation. The decrease in the miscibility region of the polymer system and increase in mass transfer resistance are found to be the determining factors during polymer solution precipitation. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3085–3096, 2002     

Inductive Model Generation for Text Classification Using a Bipartite Heterogeneous Network

Algorithms for numeric data classification have been applied for text classification. Usually the vector space model is used to represent text collections. The characteristics of this representation such as sparsity and high dimensionality sometimes impair the quality of general-purpose classifiers. Networks can be used to represent text collections, avoiding the high sparsity and allowing to model relationships among different objects that compose a text collection. Such network- based representations can improve the quality of the classification results. One of the simplest ways to represent textual collections by a network is through a bipartite heterogeneous network, which is composed of objects that represent the documents connected to objects that represent the terms. Heterogeneous bipartite networks do not require computation of similarities or relations among the objects and can be used to model any type of text collection. Due to the advantages of representing text collections through bipartite heterogeneous networks, in this article we present a text classifier which builds a classification model using the structure of a bipartite heterogeneous network. Such an algorithm, referred to as IMBHN （Inductive Model Based on Bipartite Heterogeneous Network）, induces a classification model assigning weights to objects that represent the terms for each class of the text collection. An empirical evaluation using a large amount of text collections from different domains shows that the proposed IMBHN algorithm produces significantly better results than k-NN, C4.5, SVM, and Naive Bayes algorithms.     

Towards adaptive learning with improved convergence of deep belief networks on graphics processing units

In this paper we focus on two complementary approaches to significantly decrease pre-training time of a deep belief network (DBN). First, we propose an adaptive step size technique to enhance the convergence of the contrastive divergence (CD) algorithm, thereby reducing the number of epochs to train the restricted Boltzmann machine (RBM) that supports the DBN infrastructure. Second, we present a highly scalable graphics processing unit (GPU) parallel implementation of the CD-k algorithm, which boosts notably the training speed. Additionally, extensive experiments are conducted on the MNIST and the HHreco databases. The results suggest that the maximum useful depth of a DBN is related to the number and quality of the training samples. Moreover, it was found that the lower-level layer plays a fundamental role for building successful DBN models. Furthermore, the results contradict the pre-conceived idea that all the layers should be pre-trained. Finally, it is shown that by incorporating multiple back-propagation (MBP) layers, the DBNs generalization capability is remarkably improved.