Extraction of Avgamasya asphaltite with sub- and supercritical solvents

The yields and the nature of the products from the solvent extraction of Avgamasya asphaltite of SE Turkey with benzene and toluene under Soxhlet, subcritical (up to 292 °C) and supercritical (350–450 °C) conditions are reported. The subcritical yield increases with temperature but also depends on pressure; the extra yield is mainly of asphaltenes. The 350 °C supercritical toluene extract shows little evidence of thermal degradation and is similar in yield and chemical nature to that obtained under subcritical conditions except that it contains more pentane-soluble material. At 450 °C the yield is increased and a number of pyrolytic effects are observed, including reduction in molecular mass, loss of heterocyclic and alkyl groups and the presence of toluene decomposition products.     

Modeling arbitrary polynomial bispectra in one and two dimensions

The authors propose a novel model, called a system with multiplicity (SWM), which is a refinement of the model proposed by Sakaguchi and Sakai (1989), to represent arbitrary polynomial bispectra. It is shown that an arbitrary polynomial bispectrum of a 1-D signal can always be realized using an SWM with FIR (finite impulse response) components. An algorithm is then developed for the identification of SWM that will match a given polynomial bispectrum. The authors address the problem of simultaneously matching an arbitrary polynomial bispectrum and a rational power spectrum function using an SWM. It is shown that this can always be accomplished by including another LSI component that is driven by a Gaussian input to the system. Experimental results for matching an estimated bispectrum as well as simultaneously matching a polynomial bispectrum and a power spectrum of some 1-D signals are presented. It is shown that in two dimensions an arbitrary polynomial bispectrum cannot always be uniquely modeled using an SWM with 2-D FIR components having different extents     

Analysis of Carrier Transport in <Emphasis Type="Italic">n</Emphasis>-Type Hg<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>Cd<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>Te with Ultra-Low Doping Concentration

Mercury cadmium telluride (HgCdTe, or MCT) with low n-type indium doping concentration offers a means for obtaining high performance infrared detectors. Characterizing carrier transport in materials with ultra low doping (N_D?=?10¹⁴ cm^?3 and lower), and multi-layer material structures designed for infrared detector devices, is particularly challenging using traditional methods. In this work, Hall effect measurements with a swept B-field were used in conjunction with a multi-carrier fitting procedure and Fourier-domain mobility spectrum analysis to analyze multi-layered MCT samples. Low temperature measurements (77 K) were able to identify multiple carrier species, including an epitaxial layer (x?=?0.2195) with n-type carrier concentration of n?=?1?×?10¹⁴ cm^?3 and electron mobility of μ?=?280000 cm²/Vs. The extracted electron mobility matches or exceeds prior empirical models for MCT, illustrating the outstanding material quality achievable using current epitaxial growth methods, and motivating further study to revisit previously published material parameters for MCT carrier transport. The high material quality is further demonstrated via observation of the quantum Hall effect at low temperature (5 K and below).     

Analyzing lifetime of energy harvesting underwater wireless sensor nodes

Underwater Wireless Sensor Networks (UWSNs) are utilized to monitor underwater environments that pose many challenges to researchers. One of the key complications of UWSNs is the difficulty of changing node batteries after their energy is depleted. This study aims to diminish the issues related to battery replacement by improving node lifetime. For this goal, three energy harvesting devices (turbine harvester, piezoelectric harvester, and hydrophone harvester) are analyzed to quantitate their impacts on node lifetime. In addition, two different power management schemes (schedule‐driven and event‐driven power management schemes) are combined with energy harvesters for further lifetime improvement. Performance evaluations via simulations show that energy harvesting methods joined by power management schemes can improve node lifetime substantially when actual conditions of Istanbul Bosporus Strait are considered. In this respect, turbine harvester makes the biggest impact and provides lifetime beyond 2000 days for most cases, while piezoelectric harvester can perform the same only for low duty cycle or event arrival values at short transmission ranges.     

The Effect of <Emphasis Type="Italic">Ar</Emphasis> Ambient Pressure and Annealing Duration on the Microstructure,Superconducting Properties and Activation Energies of MgB<Subscript>2</Subscript> Superconductors

MgB₂ samples are produced by ex situ reaction method under vacuum, and various (0, 10, 20 Bar) Ar pressure for 0.5 and 1 h. The effect of ambient pressure and annealing duration on the microstructure and electrical properties of bulk samples are investigated. XRD, SEM, and magnetoresistance measurements are made. The a and c lattice parameters and the grain size values are the highest for the samples produced under vacuum and their values decrease with increasing Ar pressure. Moreover, these values increase when the annealing duration increases from 0.5 to 1 h. The increasing pressure reduces the bond lengths between the atoms thus the grain sizes decrease. Smaller grain size promotes the connection between grains which results in an increase of the critical current density (J _c ). SEM micrographs reveal that the produced samples have granular structure which is a characteristic feature of MgB₂. The decrease of grain sizes and thus enhancement in grain connectivity with increasing pressure is also confirmed by SEM images. Magneto resistivity measurements show that T _c values of the samples produced under vacuum are the highest. T _c values decrease with increasing ambient pressure and applied magnetic field. The activation energies (U ₀) of the samples are calculated using Arrhenius plots due to thermally activated flux flow theory. Existence and increase of Ar pressure causes increase of activation energies. The samples produced with 0.5-h annealing have higher activation energies than the ones produced with 1-h annealing.     

Incremental <Emphasis Type="Italic">k</Emphasis>-core decomposition: algorithms and evaluation

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that is guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. For a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms.     

Satisfying agent goals by executing different task semantics: HTN, OWL-S or plug one yourself

In this paper, we propose a plan execution architecture which supports different task semantics. This way, each goal that is identified during the deliberation cycle of an agent can be satisfied through tasks defined in different semantics. The capability of supporting different task semantics provides two main advantages. The first advantage is the reuse of legacy artifacts within agent plans. The second advantage is simplifying the adaptation of an agent architecture to different standards of a business organization. In order to integrate various task semantics within a plan execution architecture, we have used a smoothly revised version of a previously articulated workflow model into which different task semantics would be reduced before execution. We have integrated hierarchical task network and OWL-S semantics into our plan execution architecture to test the strength of it in terms of support for executing different task semantics in an agent architecture. We think that such a plan execution architecture will contribute to the industrialization of agent architectures.     

A comparison of clustering-based privacy-preserving collaborative filtering schemes

Privacy-preserving collaborative filtering (PPCF) methods designate extremely beneficial filtering skills without deeply jeopardizing privacy. However, they mostly suffer from scalability, sparsity, and accuracy problems. First, applying privacy measures introduces additional costs making scalability worse. Second, due to randomness for preserving privacy, quality of predictions diminishes. Third, with increasing number of products, sparsity becomes an issue for both CF and PPCF schemes.In this study, we first propose a content-based profiling (CBP) of users to overcome sparsity issues while performing clustering because the very sparse nature of rating profiles sometimes do not allow strong discrimination. To cope with scalability and accuracy problems of PPCF schemes, we then show how to apply k-means clustering (KMC), fuzzy c-means method (FCM), and self-organizing map (SOM) clustering to CF schemes while preserving users’ confidentiality. After presenting an evaluation of clustering-based methods in terms of privacy and supplementary costs, we carry out real data-based experiments to compare the clustering algorithms within and against traditional CF and PPCF approaches in terms of accuracy. Our empirical outcomes demonstrate that FCM achieves the best low cost performance compared to other methods due to its approximation-based model. The results also show that our privacy-preserving methods are able to offer precise predictions.     

News from the field: Visual planning and urbanism in the mid‐twentieth century conference,Newcastle, UK, 11–13 September 2007

Gjirokastra, a century-old small city in southern Albania (now a UNESCO World Heritage site), provides an outstanding example of a Classical and Late Ottoman urban centre. At the same time, it is a special example of urban and architectural design based on self-defence by individual family units. Through an excursion of Gjirokastra's residential neighbourhoods, this article discusses how defence concerns guided its urban morphology and building typology until the collapse of the Ottoman Empire. The idea of war, feuds, and fear has pervaded the residents' self-identity for centuries. The military character of their houses owes much to the local ‘warrior’ mentality that prevailed in times of war and peace.