Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Evolution of classifiers for pitch estimation of piano music using cartesian genetic programming

Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. The goal of Pitch Estimation is to find the pitch or fundamental frequency of a digital recording of a speech or musical notes. It plays an important role, because it is the key to identify which notes are being played and at what time. Pitch Estimation of real instruments is a very hard task to address. Each instrument has its own physical characteristics, which reflects in different spectral characteristics. Furthermore, the recording conditions can vary from studio to studio and background noises must be considered. This dissertation presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP).We take advantage of evolutionary algorithms, in particular CGP, to explore and evolve complex mathematical functions that act as classifiers. These classifiers are used to identify piano notes pitches in an audio signal. To help us with the codification of the problem, we built a highly flexible CGP Toolbox, generic enough to encode different kind of programs. The encoded evolutionary algorithm is the one known as 1 + , and we can choose the value for . The toolbox is very simple to use. Settings such as the mutation probability, number of runs and generations are configurable. The cartesian representation of CGP can take multiple forms and it is able to encode function parameters. It is prepared to handle with different type of fitness functions: minimization of f(x) and maximization of f(x) and has a useful system of callbacks. We trained 61 classifiers corresponding to 61 piano notes. A training set of audio signals was used for each of the classifiers: half were signals with the same pitch as the classifier (true positive signals) and the other half were signals with different pitches (true negative signals). F-measure was used for the fitness function. Signals with the same pitch of the classifier that were correctly identified by the classifier, count as a true positives. Signals with the same pitch of the classifier that were not correctly identified by the classifier, count as a false negatives. Signals with different pitch of the classifier that were not identified by the classifier, count as a true negatives. Signals with different pitch of the classifier that were identified by the classifier, count as a false positives. Our first approach was to evolve classifiers for identifying artifical signals, created by mathematical functions: sine, sawtooth and square waves. Our function set is basically composed by filtering operations on vectors and by arithmetic operations with constants and vectors. All the classifiers correctly identified true positive signals and did not identify true negative signals. We then moved to real audio recordings. For testing the classifiers, we picked different audio signals from the ones used during the training phase. For a first approach, the obtained results were very promising, but could be improved. We have made slight changes to our approach and the number of false positives reduced 33%, compared to the first approach. We then applied the evolved classifiers to polyphonic audio signals, and the results indicate that our approach is a good starting point for addressing the problem of Pitch Estimation.

On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.

Genetic Algorithms for Parameter Estimation in Circadian Model

This paper proposes an algorithm to estimate two parameter values vs, transcription of frq gene, and vd, maximum rate of FRQ protein degradation for an existing 3rd order Neurospora model in literature. Details of the algorithm with simulation results are shown in this paper.

Genetic Aspects Of Athletic Performance: The African Runners Phenomenon.

The current dominance of African runners in long-distance running is an intriguing phenomenon that highlights the close relationship between genetics and physical performance. Many factors in the interesting interaction between genotype and phenotype (eg, high cardiorespiratory fitness, higher hemoglobin concentration, good metabolic efficiency, muscle fiber composition, enzyme profile, diet, altitude training, and psychological aspects) have been proposed in the attempt to explain the extraordinary success of these runners. Increasing evidence shows that genetics may be a determining factor in physical and athletic performance. But, could this also be true for African long-distance runners? Based on this question, this brief review proposed the role of genetic factors (mitochondrial deoxyribonucleic acid, the Y chromosome, and the angiotensin-converting enzyme and the alpha-actinin-3 genes) in the amazing athletic performance observed in African runners, especially the Kenyans and Ethiopians, despite their environmental constraints.

Genetic Predictors Of Long-term Response To Growth Hormone (gh) Therapy In Children With Gh Deficiency And Turner Syndrome: The Influence Of A Socs2 Polymorphism.

There is great interindividual variability in the response to GH therapy. Ascertaining genetic factors can improve the accuracy of growth response predictions. Suppressor of cytokine signaling (SOCS)-2 is an intracellular negative regulator of GH receptor (GHR) signaling. The objective of the study was to assess the influence of a SOCS2 polymorphism (rs3782415) and its interactive effect with GHR exon 3 and -202 A/C IGFBP3 (rs2854744) polymorphisms on adult height of patients treated with recombinant human GH (rhGH). Genotypes were correlated with adult height data of 65 Turner syndrome (TS) and 47 GH deficiency (GHD) patients treated with rhGH, by multiple linear regressions. Generalized multifactor dimensionality reduction was used to evaluate gene-gene interactions. Baseline clinical data were indistinguishable among patients with different genotypes. Adult height SD scores of patients with at least one SOCS2 single-nucleotide polymorphism rs3782415-C were 0.7 higher than those homozygous for the T allele (P < .001). SOCS2 (P = .003), GHR-exon 3 (P= .016) and -202 A/C IGFBP3 (P = .013) polymorphisms, together with clinical factors accounted for 58% of the variability in adult height and 82% of the total height SD score gain. Patients harboring any two negative genotypes in these three different loci (homozygosity for SOCS2 T allele; the GHR exon 3 full-length allele and/or the -202C-IGFBP3 allele) were more likely to achieve an adult height at the lower quartile (odds ratio of 13.3; 95% confidence interval of 3.2-54.2, P = .0001). The SOCS2 polymorphism (rs3782415) has an influence on the adult height of children with TS and GHD after long-term rhGH therapy. Polymorphisms located in GHR, IGFBP3, and SOCS2 loci have an influence on the growth outcomes of TS and GHD patients treated with rhGH. The use of these genetic markers could identify among rhGH-treated patients those who are genetically predisposed to have less favorable outcomes.

Nat2, Xrcc1 And Hogg1 Polymorphisms, Cigarette Smoking, Alcohol Consumption And Risk Of Upper Aerodigestive Tract Cancer.

To evaluate associations between polymorphisms of the N-acetyltransferase 2 (NAT2), human 8-oxoguanine glycosylase 1 (hOGG1) and X-ray repair cross-complementing protein 1 (XRCC1) genes and risk of upper aerodigestive tract (UADT) cancer. A case-control study involving 117 cases and 224 controls was undertaken. The NAT2 gene polymorphisms were genotyped by automated sequencing and XRCC1 Arg399Gln and hOGG1 Ser326Cys polymorphisms were determined by Polymerase Chain Reaction followed by Restriction Fragment Length Polymorphism (PCR-RFLP) methods. Slow metabolization phenotype was significantly associated as a risk factor for the development of UADT cancer (p=0.038). Furthermore, haplotype of slow metabolization was also associated with UADT cancer (p=0.014). The hOGG1 Ser326Cys polymorphism (CG or GG vs. CC genotypes) was shown as a protective factor against UADT cancer in moderate smokers (p=0.031). The XRCC1 Arg399Gln polymorphism (GA or AA vs. GG genotypes), in turn, was a protective factor against UADT cancer only among never-drinkers (p=0.048). Interactions involving NAT2, XRCC1 Arg399Gln and hOGG1 Ser326Cys polymorphisms may modulate the risk of UADT cancer in this population.

Transmission Of Intra-cellular Genetic Information: A System Proposal.

One of the great challenges of the scientific community on theories of genetic information, genetic communication and genetic coding is to determine a mathematical structure related to DNA sequences. In this paper we propose a model of an intra-cellular transmission system of genetic information similar to a model of a power and bandwidth efficient digital communication system in order to identify a mathematical structure in DNA sequences where such sequences are biologically relevant. The model of a transmission system of genetic information is concerned with the identification, reproduction and mathematical classification of the nucleotide sequence of single stranded DNA by the genetic encoder. Hence, a genetic encoder is devised where labelings and cyclic codes are established. The establishment of the algebraic structure of the corresponding codes alphabets, mappings, labelings, primitive polynomials (p(x)) and code generator polynomials (g(x)) are quite important in characterizing error-correcting codes subclasses of G-linear codes. These latter codes are useful for the identification, reproduction and mathematical classification of DNA sequences. The characterization of this model may contribute to the development of a methodology that can be applied in mutational analysis and polymorphisms, production of new drugs and genetic improvement, among other things, resulting in the reduction of time and laboratory costs.

Characterization Of Microsatellite Markers Developed From Prosopis Rubriflora And Prosopis Ruscifolia (leguminosae - Mimosoideae), Legume Species That Are Used As Models For Genetic Diversity Studies In Chaquenian Areas Under Anthropization In South America.

Prosopis rubriflora and Prosopis ruscifolia are important species in the Chaquenian regions of Brazil. Because of the restriction and frequency of their physiognomy, they are excellent models for conservation genetics studies. The use of microsatellite markers (Simple Sequence Repeats, SSRs) has become increasingly important in recent years and has proven to be a powerful tool for both ecological and molecular studies. In this study, we present the development and characterization of 10 new markers for P. rubriflora and 13 new markers for P. ruscifolia. The genotyping was performed using 40 P. rubriflora samples and 48 P. ruscifolia samples from the Chaquenian remnants in Brazil. The polymorphism information content (PIC) of the P. rubriflora markers ranged from 0.073 to 0.791, and no null alleles or deviation from Hardy-Weinberg equilibrium (HW) were detected. The PIC values for the P. ruscifolia markers ranged from 0.289 to 0.883, but a departure from HW and null alleles were detected for certain loci; however, this departure may have resulted from anthropic activities, such as the presence of livestock, which is very common in the remnant areas. In this study, we describe novel SSR polymorphic markers that may be helpful in future genetic studies of P. rubriflora and P. ruscifolia.

The Crystal-t Algorithm: A New Approach To Calculate The Sle Of Lipidic Mixtures Presenting Solid Solutions.

Lipidic mixtures present a particular phase change profile highly affected by their unique crystalline structure. However, classical solid-liquid equilibrium (SLE) thermodynamic modeling approaches, which assume the solid phase to be a pure component, sometimes fail in the correct description of the phase behavior. In addition, their inability increases with the complexity of the system. To overcome some of these problems, this study describes a new procedure to depict the SLE of fatty binary mixtures presenting solid solutions, namely the Crystal-T algorithm. Considering the non-ideality of both liquid and solid phases, this algorithm is aimed at the determination of the temperature in which the first and last crystal of the mixture melts. The evaluation is focused on experimental data measured and reported in this work for systems composed of triacylglycerols and fatty alcohols. The liquidus and solidus lines of the SLE phase diagrams were described by using excess Gibbs energy based equations, and the group contribution UNIFAC model for the calculation of the activity coefficients of both liquid and solid phases. Very low deviations of theoretical and experimental data evidenced the strength of the algorithm, contributing to the enlargement of the scope of the SLE modeling.

Cognitive And Behavioral Heterogeneity In Genetic Syndromes.

this study aimed to investigate the cognitive and behavioral profiles, as well as the psychiatric symptoms and disorders in children with three different genetic syndromes with similar sociocultural and socioeconomic backgrounds. thirty-four children aged 6 to 16 years, with Williams-Beuren syndrome (n=10), Prader-Willi syndrome (n=11), and Fragile X syndrome (n=13) from the outpatient clinics of Child Psychiatry and Medical Genetics Department were cognitively assessed through the Wechsler Intelligence Scale for Children (WISC-III). Afterwards, a full-scale intelligence quotient (IQ), verbal IQ, performance IQ, standard subtest scores, as well as frequency of psychiatric symptoms and disorders were compared among the three syndromes. significant differences were found among the syndromes concerning verbal IQ and verbal and performance subtests. Post-hoc analysis demonstrated that vocabulary and comprehension subtest scores were significantly higher in Williams-Beuren syndrome in comparison with Prader-Willi and Fragile X syndromes, and block design and object assembly scores were significantly higher in Prader-Willi syndrome compared with Williams-Beuren and Fragile X syndromes. Additionally, there were significant differences between the syndromes concerning behavioral features and psychiatric symptoms. The Prader-Willi syndrome group presented a higher frequency of hyperphagia and self-injurious behaviors. The Fragile X syndrome group showed a higher frequency of social interaction deficits; such difference nearly reached statistical significance. the three genetic syndromes exhibited distinctive cognitive, behavioral, and psychiatric patterns.

Ssr-based Genetic Diversity And Structure Of Garlic Accessions From Brazil.

Garlic is a spice and a medicinal plant; hence, there is an increasing interest in 'developing' new varieties with different culinary properties or with high content of nutraceutical compounds. Phenotypic traits and dominant molecular markers are predominantly used to evaluate the genetic diversity of garlic clones. However, 24 SSR markers (codominant) specific for garlic are available in the literature, fostering germplasm researches. In this study, we genotyped 130 garlic accessions from Brazil and abroad using 17 polymorphic SSR markers to assess the genetic diversity and structure. This is the first attempt to evaluate a large set of accessions maintained by Brazilian institutions. A high level of redundancy was detected in the collection (50 % of the accessions represented eight haplotypes). However, non-redundant accessions presented high genetic diversity. We detected on average five alleles per locus, Shannon index of 1.2, HO of 0.5, and HE of 0.6. A core collection was set with 17 accessions, covering 100 % of the alleles with minimum redundancy. Overall FST and D values indicate a strong genetic structure within accessions. Two major groups identified by both model-based (Bayesian approach) and hierarchical clustering (UPGMA dendrogram) techniques were coherent with the classification of accessions according to maturity time (growth cycle): early-late and midseason accessions. Assessing genetic diversity and structure of garlic collections is the first step towards an efficient management and conservation of accessions in genebanks, as well as to advance future genetic studies and improvement of garlic worldwide.

Genetic Breeding And Diversity Of The Genus Passiflora: Progress And Perspectives In Molecular And Genetic Studies.

Despite the ecological and economic importance of passion fruit (Passiflora spp.), molecular markers have only recently been utilized in genetic studies of this genus. In addition, both basic genetic researches related to population studies and pre-breeding programs of passion fruit remain scarce for most Passiflora species. Considering the number of Passiflora species and the increasing use of these species as a resource for ornamental, medicinal, and food purposes, the aims of this review are the following: (i) to present the current condition of the passion fruit crop; (ii) to quantify the applications and effects of using molecular markers in studies of Passiflora; (iii) to present the contributions of genetic engineering for passion fruit culture; and (iv) to discuss the progress and perspectives of this research. Thus, the present review aims to summarize and discuss the relationship between historical and current progress on the culture, breeding, and molecular genetics of passion fruit.

Molecular Genetic Variability Of Commercial And Wild Accessions Of Passion Fruit (passiflora Spp.) Targeting Ex Situ Conservation And Breeding.

Passiflora species are distributed throughout Latin America, and Brazil and Colombia serve as the centers of diversity for this genus. We performed cross-species amplification to evaluate 109 microsatellite loci in 14 Passiflora species and estimated the diversity and genetic structure of Passiflora cincinnata, Passiflora setaceae and Passiflora edulis. A total of 127 accessions, including 85 accessions of P. edulis, a commercial species, and 42 accessions of 13 wild species, were examined. The cross-species amplification was effective for obtaining microsatellite loci (average cross-amplification of 70%). The average number of alleles per locus (five) was relatively low, and the average diversity ranged from 0.52 in P. cincinnata to 0.32 in P. setacea. The Bayesian analyses indicated that the P. cincinnata and P. setacea accessions were distributed into two groups, and the P. edulis accessions were distributed into five groups. Private alleles were identified, and suggestions for core collections are presented. Further collections are necessary, and the information generated may be useful for breeding and conservation.

Genetic Diversity Of Giardia Duodenalis: Multilocus Genotyping Reveals Zoonotic Potential Between Clinical And Environmental Sources In A Metropolitan Region Of Brazil.

Giardia duodenalis is a flagellate protozoan that parasitizes humans and several other mammals. Protozoan contamination has been regularly documented at important environmental sites, although most of these studies were performed at the species level. There is a lack of studies that correlate environmental contamination and clinical infections in the same region. The aim of this study is to evaluate the genetic diversity of a set of clinical and environmental samples and to use the obtained data to characterize the genetic profile of the distribution of G. duodenalis and the potential for zoonotic transmission in a metropolitan region of Brazil. The genetic assemblages and subtypes of G. duodenalis isolates obtained from hospitals, a veterinary clinic, a day-care center and important environmental sites were determined via multilocus sequence-based genotyping using three unlinked gene loci. Cysts of Giardia were detected at all of the environmental sites. Mixed assemblages were detected in 25% of the total samples, and an elevated number of haplotypes was identified. The main haplotypes were shared among the groups, and new subtypes were identified at all loci. Ten multilocus genotypes were identified: 7 for assemblage A and 3 for assemblage B. There is persistent G. duodenalis contamination at important environmental sites in the city. The identified mixed assemblages likely represent mixed infections, suggesting high endemicity of Giardia in these hosts. Most Giardia isolates obtained in this study displayed zoonotic potential. The high degree of genetic diversity in the isolates obtained from both clinical and environmental samples suggests that multiple sources of infection are likely responsible for the detected contamination events. The finding that many multilocus genotypes (MLGs) and haplotypes are shared by different groups suggests that these sources of infection may be related and indicates that there is a notable risk of human infection caused by Giardia in this region.