The rank and kernel of extended 1-perfect /spl Zopf//sub 4/-linear and additive non-/spl Zopf//sub 4/-linear codes

A binary extended 1-perfect code of length n + 1 = 2/sup t/ is additive if it is a subgroup of /spl Zopf//sub 2//sup /spl alpha// /spl times/ /spl Zopf//sub 4//sup /spl beta//. The punctured code by deleting a /spl Zopf//sub 2/ coordinate (if there is one) gives a perfect additive code. 1-perfect additive codes were completely characterized and by using that characterization we compute the possible parameters /spl alpha/, /spl beta/, rank, and dimension of the kernel for extended 1-perfect additive codes. A very special case is that of extended 1-perfect /spl Zopf//sub 4/-linear codes.     

Analysis of the essential oil of Mexican oregano (Lippia graveolens HBK)

The composition of the volatile oil of Mexican oregano (Lippia graveolens HBK) isolated by steam distillation was investigated by means of column chromatography, gas chromatography and mass spectrometry. A total of 33 components were identified including 22 hydrocarbons, 4 alcohols, 4 ethers, 2 phenols and 1 ketone. Of the 33 components observed in the present study 7 were identified in Mexican oregano for the first time.     

Ranking Pages by Topology and Popularity within Web Sites

We compare two link analysis ranking methods of web pages in a site. The first, called Site Rank, is an adaptation of PageRank to the granularity of a web site and the second, called Popularity Rank, is based on the frequencies of user clicks on the outlinks in a page that are captured by navigation sessions of users through the web site. We ran experiments on artificially created web sites of different sizes and on two real data sets, employing the relative entropy to compare the distributions of the two ranking methods. For the real data sets we also employ a nonparametric measure, called Spearman's footrule, which we use to compare the top-ten web pages ranked by the two methods. Our main result is that the distributions of the Popularity Rank and Site Rank are surprisingly close to each other, implying that the topology of a web site is very instrumental in guiding users through the site. Thus, in practice, the Site Rank provides a reasonable first order approximation of the aggregate behaviour of users within a web site given by the Popularity Rank.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

Study of the nozzle flow in a cross-flow turbine

An investigation of the flow inside the nozzle of a Cross-Flow turbine, which is a hydraulic turbine where the rectangular water jet issuing from the nozzle crosses the rotor blades twice, is presented here. Part of the investigation consisted in the experimental measurement of the static pressure distribution on the inside walls of two different nozzle configurations, both with the nozzle mounted alone and in the presence of a rotor. The tests performed in the presence of a rotor included the measurement of efficiency and covered a wide range of working conditions around the best efficiency point. The analysis of the results obtained in this way give us an indication of the influence of the turbine non-dimensional volume flow rate on the flow inside the nozzle and the way it affects the reaction degree of the machine and its efficiency level. Although most of the tests were carried out with a 25-blade rotor, one of the analysed nozzle configurations (that with an inside vane) was also tested with a 10-blade rotor, permitting the assessment of the effect the number of blades has on the flow in the nozzle.The flow inside the nozzle with no inside vane was numerically analysed using a method based on a Schwarz-Christoffel conformal transformation of variables. The numerical results show a fair agreement with the experimental data collected when the rotor was not present. A qualitative discussion of some of the losses occurring in the nozzle is advanced based on the computer results, and its conclusions are used for explaining the poor performance of the nozzle with no inside vane.     

On the impact of physical layer awareness on scheduling and resource allocation in broadband multicellular IEEE 802.16 systems [Radio Resource Management and Protocol Engineering for IEEE 802.16]

Multicellular networks based on the IEEE 802.16 standard appear to be very promising candidates to provide end users with broadband wireless access. However, they also pose interesting challenges in terms of radio resource management, where several design choices are not specified in the standard, intentionally left open to implementors. For this reason, we focus in this article on scheduling and resource allocation, and investigate how they could operate in a cross-layer fashion. In particular, we describe the principles of joint scheduling and resource allocation for IEEE 802.16 operating in AMC mode, and discuss the critical role played by physical layer considerations, especially intercell interference estimation and channel state awareness, in the obtained performance. This leads to identifying key open issues and possible general solutions     

Probabilistic Wind Farms Generation Model for Reliability Studies Applied to Brazilian Sites

This paper presents a computer model for the probabilistic representation of wind farms generation for reliability studies, which can provide an annual estimation of energy production and calculate several performance indexes. The model combines the stochastic characteristics of wind speed with the operational information of the turbines, such as the failure and repair rates, representing the wind farm by a Markov process. The simulations are made with real time series of wind speed of several Brazilian regions and actual turbine models. The influence of some wind farm and installation site characteristics on the results are evaluated, such as the wind speed statistical clustering technique, the number and type of the turbines, and the failure and repair rates. The results obtained reproduce successfully the behavior of the components considered in the model     

Surface tension as a limiting factor for aerobic n-alkane biodegradation

A new mathematical model for n-alkane biodegradation in crude oil, heavy oil and paraffinic mixtures is described. The pattern of n-alkane degradation as a function of the inverse of hydrocarbon chain length reported in this paper can be considered as general behaviour for many aerobic n-alkane biodegradation processes. A new interpretation of n-alkane biodegradation as a function of surface tension, is given. A mathematical expression was obtained starting from the degradation values of n-alkane and relative surface tension, which is a parameter independent of fermentation conditions. An interesting parameter, b, was identified which represented the accelerating conversion factor for n-alkane biodegradation. The findings suggested that the n-alkane biodegradation. The findings suggested that he n-alkane biodegradation rate may be affected by the fermentation condition (agitation, aeration, etc.) and by the strain of microorganism, while the behaviour pattern of n-alkane degradation was essentially linked to the substrate characteristics (molecular structure, molecular weight and density).