Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

Ecosystem approach and the Fuzzy logic: a dialectical proposal for information on Environmental Health

The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.

Niobium Effects on the Recrystallization Behavior on a Full Austenitic 15Cr-15Ni Stainless Steel Investigated Using Adaptive Neural Networks (ANN)

A new series of austenitic stainless steels-Nb stabilized, without Mo additions, non-susceptible to delta ferrite formation and devoid of intemetallic phases (sigma and chi), without deformation induced martensite is being developed, aiming at high temperature applications as well as for corrosive environments. The base steel composition is a 15Cr-15Ni with normal additions of Nb of 0.5, 1.0 and 2 wt%. Mechanical properties, oxidation and corrosion resistance already have been invetigated in previous papers. In this paper, the effects of Nb on the SFE, strain hardening and recrystallization resistance are evaluated with the help of Adaptive Neural Networks (ANN).

Phase-disorder-induced firing activity in excitable neuronal networks with attractive and repulsive coupling

It has been revealed that the network of excitable neurons via attractive coupling can generate spikes under stimuli of subthreshold signals with disordered phases. In this paper, we explore the firing activity induced by phase disorder in excitable neuronal networks consisting of both attractive and repulsive coupling. By increasing the fraction of repulsive coupling, we find that, in the weak coupling strength case, the firing threshold of phase disorder is increased and the system response to subthreshold signals is decreased, indicating that the effect of inducing neuron firing by phase disorder is weakened with repulsive coupling. Interestingly, in the large coupling strength case, we see an opposite situation, where the coupled neurons show a rather large response to the subthreshold signals even with small phase disorder. The latter case implies that the effect of phase disorder is enhanced by repulsive coupling. A system of two-coupled excitable neurons is used to explain the role of repulsive coupling on phase-disorder-induced firing activity.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

Hierarchical multi-label classification using local neural networks

Hierarchical multi-label classification is a complex classification task where the classes involved in the problem are hierarchically structured and each example may simultaneously belong to more than one class in each hierarchical level. In this paper, we extend our previous works, where we investigated a new local-based classification method that incrementally trains a multi-layer perceptron for each level of the classification hierarchy. Predictions made by a neural network in a given level are used as inputs to the neural network responsible for the prediction in the next level. We compare the proposed method with one state-of-the-art decision-tree induction method and two decision-tree induction methods, using several hierarchical multi-label classification datasets. We perform a thorough experimental analysis, showing that our method obtains competitive results to a robust global method regarding both precision and recall evaluation measures.

Genetic variability and demographic history of Heliothis virescens (Lepidoptera: Noctuidae) populations from Brazil inferred by mtDNA sequences

Intra-and inter-population genetic variability and the demographic history of Heliothis virescens (F.) populations were evaluated by using mtDNA markers (coxI, coxII and nad6) with samples from the major cotton-and soybean-producing regions in Brazil in the growing seasons 2007/08, 2008/09 and 2009/10. AMOVA indicated low and non-significant genetic structure, regardless of geographical scale, growing season or crop, with most of genetic variation occurring within populations. Clustering analyzes also indicated low genetic differentiation. The haplotype network obtained with combined datasets resulted in 35 haplotypes, with 28 exclusive occurrences, four of them sampled only from soybean fields. The minimum spanning network showed star-shaped structures typical of populations that underwent a recent demographic expansion. The recent expansion was supported by other demographic analyzes, such as the Bayesian skyline plot, the unimodal distribution of paired differences among mitochondrial sequences, and negative and significant values of neutrality tests for the Tajima's D and Fu's F-S parameters. In addition, high values of haplotype diversity ((H) over cap) and low values of nucleotide diversity (pi), combined with a high number of low frequency haplotypes and values of theta(pi)<theta(W), suggested a recent demographic expansion of H. virescens populations in Brazil. This demographic event could be responsible for the low genetic structure currently found; however, haplotypes present uniquely at the same geographic regions and from one specific host plant suggest an initial differentiation among H. virescens populations within Brazil.

The genetic structure and mating system of Acrocomia aculeata (Arecaceae)

Acrocomia aculeata is a perennial, fruit-producing palm tree, native to tropical forests. Its fruits have spurred interest because of their significant potential for use in the cosmetic industry and as feedstock for biofuel. In the present study, the genetic structure and mating system in Acrocomia aculeata were analyzed, using eight nuclear microsatellite loci and samples from Sao Paulo and Minas Gerais states, Brazil. By means of Bayesian analysis, these populations were clustered into two or three groups. A high multilocus outcrossing rate suggests that outcrosses were predominant, although a certain degree of biparental inbreeding also occurred. Thus, although monoecious and self-compatible, there is every indication that A. aculeata bears a mixed reproductive system, with a predominance of outcrossing. Given the genetic structure revealed hereby, future conservation strategies and germplasm collecting should be focussed on sampling and preserving individuals from different clusters.

Genetic correlations and heritability estimates of reproductive traits of Nellore bulls

Estimates of phenotypic, genetics and residual variances for reproductive traits in 5903 Nellore bulls were obtained. The experimental model used was multiple trait derivative-free restricted maximum likelihood. The values obtained for heritability were 0.24 +/- 0.05 for scrotal circumference at 450 days of age and 0.37 +/- 0.05 at 21 months for age at the time of the breeding soundness evaluation; 0.24 +/- 0.05 and 0.26 +/- 0.05 for left and right testicle length; 0.29 +/- 0.05 and 0.31 +/- 0.05 for left and right testicle width; 0.12 +/- 0.04 for testicle format; 0.33 +/- 0.06 for testicle volume; 0.11 +/- 0.03 for gross motility; 0.08 +/- 0.03 for individual motility and 0.05 +/- 0.02 for spermatic vigor; 0.20 +/- 0.04, 0.03 +/- 0.02 and 0.19 +/- 0.04 for larger defects, smaller defects and total defects, respectively. The values for heritability for testicular biometric characteristics were moderate to high while the seminal characteristics, presented low values. Genetic correlations between scrotal circumference with all the reproductive traits were favorable, suggesting the scrotal circumference as a feature of choice in the selection of bulls.

Association study between the rs165599 catechol-O-methyltransferase genetic polymorphism and schizophrenia in a Brazilian sample

Schizophrenia is a severe psychiatric disorder with frequent recurrent psychotic relapses and progressive functional impairment. It results from a poorly understood gene-environment interaction. The gene encoding catechol-O-methyltransferase (COMT) is a likely candidate for schizophrenia. Its rs165599 (A/G) polymorphism has been shown to be associated with alteration of COMT gene expression. Therefore, the present study aimed to investigate a possible association between schizophrenia and this polymorphism. The distribution of the alleles and genotypes of this polymorphism was investigated in a Brazilian sample of 245 patients and 834 controls. The genotypic frequencies were in Hardy-Weinberg equilibrium and no statistically significant differences were found between cases and controls when analyzed according to gender or schizophrenia subtypes. There was also no difference in homozygosis between cases and controls. Thus, in the sample studied, there was no evidence of any association between schizophrenia and rs165599 (A/G) polymorphism in the non-coding region 3' of the COMT gene.

Neural mobilization reverses behavioral and cellular changes that characterize neuropathic pain in rats

Background: The neural mobilization technique is a noninvasive method that has proved clinically effective in reducing pain sensitivity and consequently in improving quality of life after neuropathic pain. The present study examined the effects of neural mobilization (NM) on pain sensitivity induced by chronic constriction injury (CCI) in rats. The CCI was performed on adult male rats, submitted thereafter to 10 sessions of NM, each other day, starting 14 days after the CCI injury. Over the treatment period, animals were evaluated for nociception using behavioral tests, such as tests for allodynia and thermal and mechanical hyperalgesia. At the end of the sessions, the dorsal root ganglion (DRG) and spinal cord were analyzed using immunohistochemistry and Western blot assays for neural growth factor (NGF) and glial fibrillary acidic protein (GFAP). Results: The NM treatment induced an early reduction (from the second session) of the hyperalgesia and allodynia in CCI-injured rats, which persisted until the end of the treatment. On the other hand, only after the 4th session we observed a blockade of thermal sensitivity. Regarding cellular changes, we observed a decrease of GFAP and NGF expression after NM in the ipsilateral DRG (68% and 111%, respectively) and the decrease of only GFAP expression after NM in the lumbar spinal cord (L3-L6) (108%). Conclusions: These data provide evidence that NM treatment reverses pain symptoms in CCI-injured rats and suggest the involvement of glial cells and NGF in such an effect.

GEOGRAPHICAL GENETIC STRUCTURING AND PHENOTYPIC VARIATION IN THE VELLOZIA HIRSUTA (VELLOZIACEAE) OCHLOSPECIES COMPLEX

Premise of the study: Vellozia hirsuta forms a complex presenting wide morphological and anatomical variation, resulting in five specific names and 14 morpho-anatomical patterns occurring in disjunct populations. We carried out a phylogeographical study to investigate the existence of correlation among the genetic and morphological patterns within this complex, and to determine whether it is composed of various species or should be treated as an ochlospecies, a species having widely polymorphic and weakly polytypic complex variation, with morphological characteristics varying independently. Methods: We carried out phylogeographical analyses using cpDNA rpl32F-trnL intergenic region. Key results: We found 20 haplotypes in 23 populations sampled. The populations are genetically structured (Phi(ST) = 0.818) into four phylogeographical groups demonstrating geographical structuring but with no correlation with morpho-anatomical patterns. Our analyses do not support recognizing any of the species now synonymized under Vellozia hirsuta. The northern populations were the most genetically differentiated and could be considered a distinct taxon, as they are also morphologically different. Conclusions: It is recommended that Vellozia hirsuta be considered a single enormously variable species. The patterns of variation within V. hirsuta probably are related to climatic changes that occurred during the Pleistocene Epoch in tropical Brazil when reductions in forest cover favored the expansion of V. hirsuta populations into extensive lowland areas. The expansion of forest cover at the end of the glaciations would have again restricted the occurrence of campos rupestres vegetation to high elevations, which constitute the current centers of diversity of this species.

Cash balance management: A comparison between genetic algorithms and particle swarm optimization

This work aimed to apply genetic algorithms (GA) and particle swarm optimization (PSO) in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.

Maternal iNOS genetic polymorphisms and hypertensive disorders of pregnancy

Increased expression and activity of inducible nitric oxide synthase (iNOS) may contribute to the pathogenesis of pre-eclampsia (PE) and gestational hypertension (GH). However, no previous study has examined whether genetic polymorphisms in the iNOS gene are associated with PE or GH. We examined whether two functional, clinically relevant iNOS genetic polymorphisms (the C(-1026)A polymorphism, rs2779249, in the promoter region, and the G2087A polymorphism, rs2297518, in exon 16) are associated with GH or with PE. We studied 565 pregnant women: 212 healthy pregnant (HP), 166 pregnant with GH and 187 pregnant with PE. Genotypes were determined by real-time PCR, using the Taqman allele discrimination assay. The PHASE 2.1 program was used to estimate haplotype distributions in the three study groups. We found no significant association between the C(-1026)A polymorphism and PE or GH (P>0.05). However, we found the GA genotype and the A allele for the G2087A polymorphism at higher frequency in PE, but not in GH, compared with HP (P<0.05). The haplotype analysis showed no significant intergroup differences (P>0.05). These findings suggest that iNOS genetic variants may affect the susceptibility to PE, but not to GH. Journal of Human Hypertension (2012) 26, 547-552; doi:10.1038/jhh.2011.65; published online 30 June 2011