Ratios of UV, PAR and NIR components to global solar radiation measured at Botucatu site in Brazil

The relationships between the four radiant fluxes are analyzed based on a 4 year data archive of hourly and daily global ultraviolet (I(UV)), photosynthetically active-PAR (I(PAR)), near infrared (I(NIR)) and broadband global solar radiation (I(G)) collected at Botucatu, Brazil. These data are used to establish both the fractions of spectral components to global solar radiation and the proposed linear regression models. Verification results indicated that the proposed regression models predict accurately the spectral radiant fluxes at least for the Brazilian environment. Finally, results obtained in this analysis agreed well with most published results in the literature. (c) 2010 Elsevier Ltd. All rights reserved.

Fibroelastic Components of the Vesicourethral Junction of Rats in the Aging Process

The vesicourethral junction comprising the vesical trigone, is relevant in setting and positioning of the urinary bladder, along with the vesical neck, fixed by lateral ligaments of the bladder and tendinous arch of the pelvis fascia. Namely, the puboprostatic ligament (men) and the pubovesical (women). The circular set elastic fibers in this junction are important and valuable in the elasticity and plasticity of the area, allowing quick expansion and withdrawal with the flow of urine, and associated to smooth muscle tissue and nerve control form an important collective to maintain urinary continence. The objective of the present study is to describe the elastic system in the vesicouretral junction in relation to aging and its involvement in the states of urinary continence and incontinence, as well as the study of the vesicouretral junction in various age groups while evaluating with electron transmission microscopy. To carry out the study, 12 Wistar rats were used, divided into groups: neonate (4 animals), adult group (4 animals) and aged group (4 animals). Electron transmission microscopy with use of tanic acid technique associated to glutaraldehyde fixation, satisfactorily showed the extreme structural differences between mature elaunin and oxytalan fibers present between intercelular spaces and bundles of collagen fibers. The phases of elastogenesis in neonate animals and degradation of the elastic system of older animals were also evaluated.

Maternal diabetes affects specific extracellular matrix components during placentation

During embryo implantation, invasive trophoblast cells mediate embryo invasion into the decidualized stroma, forming a rich network of lacunae that connect the embryonic tissues to the maternal blood vessels. Placentation is probably guided by the composition and organization of the endometrial extracellular matrix. Certain pathological conditions that occur during pregnancy, including diabetes, have been linked to abnormal placental morphology and consequent fetal morbidity. We used immunoperoxidase techniques to identify members of the collagen, proteoglycan and glycoprotein families in the various compartments of the rat placenta and to determine whether experimentally induced diabetes affects placental morphology and alters the distribution of these molecules during pregnancy. Single injections of alloxan (40 mg kg(-1) i.v.) were used to induce diabetes on day 2 of pregnancy in Wistar rats. Placentas were collected on days 14, 17, and 20. Type I and III collagen, as well as the proteoglycans decorin and biglycan, were found to be distributed throughout the placentas of control and diabetic rats. In both groups, laminin expression decreased at the end of pregnancy. In contrast, fibronectin was detected in the labyrinth region of diabetic rats at all gestational stages studied, whereas it was detected only at term pregnancy in the placentas of control rats. These results show for the first time that some extracellular matrix molecules are modulated during placental development. However, as diabetic rats presented increased fibronectin deposition exclusively in the labyrinth region, we speculate that diabetes alters the microenvironment at the maternal-fetal interface, leading to developmental abnormalities in the offspring.

Up-regulation of NADPH oxidase components and increased production of interferon-gamma by leukocytes from sickle cell disease patients

We have previously demonstrated that mononuclear leukocytes from patients with sickle cell disease (SCD) release higher amounts of superoxide compared with normal controls. The aim of this study was to further study the NADPH oxidase system in these patients by investigating gene expression of NADPH oxidase components, phosphorylation of p47(phox) component, and the release of cytokines related to NADPH oxidase activation in mononuclear leukocytes from patients with SCD. gp91(phox) gene expression was significantly higher in monocytes from SCD patients compared with normal controls (P = 0.036). Monocytes from SCD patients showed higher levels of p47 phox phosphorylation compared with normal controls. INF-gamma release by lymphocytes from SCD patients was significantly higher compared with normal controls, after 48 h culture with phytohemagglutinin (P = 0.02). The release of TNF-alpha by monocytes from SCD patients and normal controls was similar after 24 and 48 h culture with lipopolysaccharide (P > 0.05). We conclude that monocytes from SCD patients show higher levels of gp91(phox) gene expression and p47(phox) phosphorylation, along with increased IFN-gamma release by SCD lymphocytes. These findings help to explain our previous observation showing the increased respiratory burst activity of mononuclear leukocytes from SCD patients and may contribute to inflammation and tissue damage in these patients.

Components Separation Technique With Limited Subcutaneous Undermining A Cadaver Study

The purpose of this study is to evaluate the influence of the undermining of the subcutaneous tissue on the tension of the abdominal wall, after the components separation of the abdominal muscles. Twenty adult cadavers were studied. The resistance of the medial advancement of both anterior and posterior recti sheaths was represented by the traction index and measured in 2 levels-3 cm above and 2 cm below the umbilicus. Traction indices were compared in the following 3 consecutive dissection situations: (1) after the subcutaneous tissue undermining laterally to the semilunaris line; (2) after the dissection of the rectus muscle from its posterior sheath associated with the release of the external oblique muscle; (3) after the subcutaneous tissue undermining laterally to the anterior axillary line. Friedman and Spearman tests were used to compare the results. There was no statistical significant difference between the subcutaneous tissue undermining laterally to the semilunaris line and that laterally to the anterior axillary line, when associated with the musculoaponeurotic dissections. In conclusion, limited subcutaneous undermining does not influence the tension of closure of the musculoaponeurotic layer after the components separation technique in cadavers.

OntoMap: an ontology-based architecture to perform the semantic mapping between an interlingua and software components

This paper is about the use of natural language to communicate with computers. Most researches that have pursued this goal consider only requests expressed in English. A way to facilitate the use of several languages in natural language systems is by using an interlingua. An interlingua is an intermediary representation for natural language information that can be processed by machines. We propose to convert natural language requests into an interlingua [universal networking language (UNL)] and to execute these requests using software components. In order to achieve this goal, we propose OntoMap, an ontology-based architecture to perform the semantic mapping between UNL sentences and software components. OntoMap also performs component search and retrieval based on semantic information formalized in ontologies and rules.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Comparing finite state machine test coverage criteria

To plan testing activities, testers face the challenge of determining a strategy, including a test coverage criterion that offers an acceptable compromise between the available resources and test goals. Known theoretical properties of coverage criteria do not always help and, thus, empirical data are needed. The results of an experimental evaluation of several coverage criteria for finite state machines (FSMs) are presented, namely, state and transition coverage; initialisation fault and transition fault coverage. The first two criteria focus on FSM structure, whereas the other two on potential faults in FSM implementations. The authors elaborate a comparison approach that includes random generation of FSM, construction of an adequate test suite and test minimisation for each criterion to ensure that tests are obtained in a uniform way. The last step uses an improved greedy algorithm.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Reversible and irreversible magnetization components behavior in Ni nanowires

Polycrystalline Ni nanowires were electrodeposited in nanoporous anodized alumina membranes with mean diameter of approximately 42 nm. Their magnetic properties were studied at 300 K, by measurements of recoil curves from demagnetized state and also from saturated state. M(rev) and M(irr) components were obtained and M(rev)(M(irr)) H curves were constructed from the experimental data. These curves showed a behavior that suggests a non-uniform reversal mode influenced by the presence of dipolar interactions in the system. A qualitative approach to this behavior is obtained using a Stoner-Wohlfarth model modified by a mean field term and local interaction fields. (C) 2008 Elsevier B.V. All rights reserved.

Complex networks analysis of manual and machine translations

Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.

Using metrics from complex networks to evaluate machine translation

Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

Likelihood ratio tests for variance components in linear mixed models

Although the asymptotic distributions of the likelihood ratio for testing hypotheses of null variance components in linear mixed models derived by Stram and Lee [1994. Variance components testing in longitudinal mixed effects model. Biometrics 50, 1171-1177] are valid, their proof is based on the work of Self and Liang [1987. Asymptotic properties of maximum likelihood estimators and likelihood tests under nonstandard conditions. J. Amer. Statist. Assoc. 82, 605-610] which requires identically distributed random variables, an assumption not always valid in longitudinal data problems. We use the less restrictive results of Vu and Zhou [1997. Generalization of likelihood ratio tests under nonstandard conditions. Ann. Statist. 25, 897-916] to prove that the proposed mixture of chi-squared distributions is the actual asymptotic distribution of such likelihood ratios used as test statistics for null variance components in models with one or two random effects. We also consider a limited simulation study to evaluate the appropriateness of the asymptotic distribution of such likelihood ratios in moderately sized samples. (C) 2008 Elsevier B.V. All rights reserved.

Simple components of the center of FG/J(FG)

Let G be a finite group, F a field, FG the group ring of G over F, and J(FG) the Jacobson radical of FG. Using a result of Berman and Witt, we give a method to determine the structure of the center of FG/J(FG), provided that F satisfies a field theoretical condition.