953 resultados para Multi-population
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This paper is concerned with the development of an algorithm for pole placement in multi-input dynamic systems. The algorithm which uses a series of elementary transformations is believed to be simpler, computationally more efficient and numerically stable when compared with earlier methods. In this paper two methods have been presented.
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Males of some species included in the Bactrocera dorsalis complex are strongly attracted to methyl eugenol (ME) (1,2-dimethoxy-4-(2-propenyl) benzene), a natural compound occurring in a variety of plant species. ME feeding of males of the B. dorsalis complex is known to enhance their mating competitiveness. Within B. dorsalis, recent studies show that Asian and African populations of B. dorsalis are sexually compatible, while populations of B. dorsalis and Bactrocera carambolae are relatively incompatible. The objectives of this study were to examine whether ME feeding by males affects mating compatibility between Asian and African populations of B. dorsalis and ME feeding reduces male mating incompatibility between B. dorsalis (Asian population) and B. carambolae. The data confirmed that Asian and African populations of B. dorsalis are sexually compatible for mating and showed that ME feeding only increased the number of matings. Though ME feeding also increased the number of matings of B. dorsalis (Asian population) and B. carambolae males but the sexual incompatibility between both species was not reduced by treatment with ME. These results conform to the efforts resolving the biological species limits among B. dorsalis complex and have implications for fruit fly control programs in fields and horticultural trade.
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Eight polymorphic microsatellite loci were analysed in six population samples from four locations of the Australian endemic brown tiger prawn, Penaeus esculentus. Tests of Hardy-Weinberg equilibrium were generally in accord with expectations, with only one locus, in two samples, showing significant deviations. Three samples were taken in different years from the Exmouth Gulf. These showed no significant heterogeneity, and it was concluded that they were from a single panmictic population. A sample from Shark Bay, also on the west coast of Australia, showed barely detectable differentiation from Exmouth Gulf (F (ST) = 0 to 0.0014). A northeast sample from the Gulf of Carpentaria showed low (F (ST) = 0.008) but significant differentiation from Moreton Bay, on the east coast. However, Exmouth Gulf/Shark Bay samples were well differentiated from the Gulf of Carpentaria/Moreton Bay (F (ST) = 0.047-0.063). The data do not fit a simple isolation by distance model. It is postulated that the east-west differentiation largely reflects the isolation of east and west coast populations that occurred at the last glacial maximum when there was a land bridge between north-eastern Australia and New Guinea.
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We are addressing the problem of jointly using multiple noisy speech patterns for automatic speech recognition (ASR), given that they come from the same class. If the user utters a word K times, the ASR system should try to use the information content in all the K patterns of the word simultaneously and improve its speech recognition accuracy compared to that of the single pattern based speech recognition. T address this problem, recently we proposed a Multi Pattern Dynamic Time Warping (MPDTW) algorithm to align the K patterns by finding the least distortion path between them. A Constrained Multi Pattern Viterbi algorithm was used on this aligned path for isolated word recognition (IWR). In this paper, we explore the possibility of using only the MPDTW algorithm for IWR. We also study the properties of the MPDTW algorithm. We show that using only 2 noisy test patterns (10 percent burst noise at -5 dB SNR) reduces the noisy speech recognition error rate by 37.66 percent when compared to the single pattern recognition using the Dynamic Time Warping algorithm.
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This paper presents a Multi-Hypotheses Tracking (MHT) approach that allows solving ambiguities that arise with previous methods of associating targets and tracks within a highly volatile vehicular environment. The previous approach based on the Dempster–Shafer Theory assumes that associations between tracks and targets are unique; this was shown to allow the formation of ghost tracks when there was too much ambiguity or conflict for the system to take a meaningful decision. The MHT algorithm described in this paper removes this uniqueness condition, allowing the system to include ambiguity and even to prevent making any decision if available data are poor. We provide a general introduction to the Dempster–Shafer Theory and present the previously used approach. Then, we explain our MHT mechanism and provide evidence of its increased performance in reducing the amount of ghost tracks and false positive processed by the tracking system.
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Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.
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Background. Evidence of cognitive dysfunction in depressive and anxiety disorders is growing. However, the neuropsychological profile of young adults has received only little systematic investigation, although depressive and anxiety disorders are major public health problems for this age group. Available studies have typically failed to account for psychiatric comorbidity, and samples derived from population-based settings have also seldom been investigated. Burnout-related cognitive functioning has previously been investigated in only few studies, again all using clinical samples and wide age groups. Aims. Based on the information gained by conducting a comprehensive review, studies on cognitive impairment in depressive and anxiety disorders among young adults are rare. The present study examined cognitive functioning in young adults with a history of unipolar depressive or anxiety disorders in comparison to healthy peers, and associations of current burnout symptoms with cognitive functioning, in a population-based setting. The aim was also to determine whether cognitive deficits vary as a function of different disorder characteristics, such as severity, psychiatric comorbidity, age at onset, or the treatments received. Methods. Verbal and visual short-term memory, verbal long-term memory and learning, attention, psychomotor processing speed, verbal intelligence, and executive functioning were measured in a population-based sample of 21-35 year olds. Performance was compared firstly between participants with pure non-psychotic depression (n=68) and healthy peers (n=70), secondly between pure (n=69) and comorbid depression (n=57), and thirdly between participants with anxiety disorders (n=76) and healthy peers (n=71). The diagnostic procedure was based on the SCID interview. Fourthly, the associations of current burnout symptoms, measured with the Maslach Burnout Inventory General Survey, and neuropsychological test performance were investigated among working young adults (n=225). Results. Young adults with depressive or anxiety disorders, with or without psychiatric comorbidity, were not found to have major cognitive impairments when compared to healthy peers. Only mildly compromised verbal learning was found among depressed participants. Pure and comorbid depression groups did not differ in cognitive functioning, either. Among depressed participants, those who had received treatment showed more impaired verbal memory and executive functioning, and earlier onset corresponded with more impaired executive functioning. In anxiety disorders, psychotropic medication and low psychosocial functioning were associated with deficits in executive functioning, psychomotor processing speed, and visual short-term memory. Current burnout symptoms were associated with better performance in verbal working memory and verbal intelligence. However, lower examiner-rated social and occupational functioning was associated with problems in verbal attention, memory, and learning. Conclusions. Depression, anxiety disorders, or burnout symptoms may not be associated with major cognitive deficits among young adults derived from the general population. Even psychiatric comorbidity may not aggravate cognitive functioning in depressive or anxiety disorders among these young adults. However, treatment-seeking in depression was found to be associated with cognitive deficits, suggesting that these deficits relate to increased distress. Additionally, early-onset depression, found to be associated with executive dysfunction, may represent a more severe form of the disorder. In anxiety disorders, those with low symptom-related psychosocial functioning may have cognitive impairment. An association with self-reported burnout symptoms and cognitive deficits was not detected, but individuals with low social and occupational functioning may have impaired cognition.
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Root-lesion nematode (Pratylenchus thornei) is a serious pathogen of wheat in many countries. The International Triticeae Mapping Initiative (ITMI) population of recombinant inbred lines (RILs) was assessed for resistance to P. thornei to determine the chromosome locations of the resistance genes. The ITMI population is derived from a cross between the resistant synthetic hexaploid wheat W-7984 and a susceptible bread wheat cultivar Opata 85. Two years of phenotypic data for resistance to P. thornei were obtained in replicated glasshouse trials. Quantitative trait locus (QTL) analysis was performed using available segregation and map data for 114 RILs. A QTL on chromosome 6DS showed consistent effects for reduced nematode numbers (partial resistance) across years and accounted for 11% and 23% of the phenotypic variation. A second QTL for P. thornei resistance on chromosome 2BS accounted for an additional 19% and 5%. Restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers associated with the QTLs are physically located in regions rich in major genes at the distal ends of the short chromosome arms of 6D and 2B. SSR markers with potential for marker-assisted selection of P. thornei resistance effective in different genetic backgrounds have been identified.
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Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.
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Global amphibian decline by chytridiomycosis is a major environmental disaster that has been attributed to either recent fungal spread or environmental change that promotes disease. Here, we present a population genetic comparison of Batrachochytrium dendrobatidis isolates from an intensively studied region of frog decline, the Sierra Nevada of California. In support of a novel pathogen, we find low diversity, no amphibian-host specificity, little correlation between fungal genotype and geography, local frog extirpation by a single fungal genotype, and evidence of human-assisted fungus migration. In support of endemism, at a local scale, we find some diverse, recombining populations. Therefore neither epidemic spread nor endemism alone explains this particular amphibian decline. Recombination raises the possibility of resistant sporangia and a mechanism for rapid spread as well as persistence that could greatly complicate global control of the pathogen.
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Airborne particles, including both ultrafine and supermicrometric particles, contain various carcinogens. Exposure and risk-assessment studies regularly use particle mass concentration as dosimetry parameter, therefore neglecting the potential impact of ultrafine particles due to their negligible mass compared to supermicrometric particles. The main purpose of this study was the characterization of lung cancer risk due to exposure to polycyclic aromatic hydrocarbons and some heavy metals associated with particle inhalation by Italian non-smoking people. A risk-assessment scheme, modified from an existing risk model, was applied to estimate the cancer risk contribution from both ultrafine and supermicrometric particles. Exposure assessment was carried out on the basis of particle number distributions measured in 25 smoke-free microenvironments in Italy. The predicted lung cancer risk was then compared to the cancer incidence rate in Italy to assess the number of lung cancer cases attributed to airborne particle inhalation, which represents one of the main causes of lung cancer, apart from smoking. Ultrafine particles are associated with a much higher risk than supermicrometric particles, and the modified risk-assessment scheme provided a more accurate estimate than the conventional scheme. Great attention has to be paid to indoor microenvironments and, in particular, to cooking and eating times, which represent the major contributors to lung cancer incidence in the Italian population. The modified risk assessment scheme can serve as a tool for assessing environmental quality, as well as setting up exposure standards for particulate matter.
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This paper presents the architecture of a fault-tolerant, special-purpose multi-microprocessor system for solving Partial Differential Equations (PDEs). The modular nature of the architecture allows the use of hundreds of Processing Elements (PEs) for high throughput. Its performance is evaluated by both analytical and simulation methods. The results indicate that the system can achieve high operation rates and is not sensitive to inter-processor communication delay.
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The law provides rights for PWD for easy access of public goods, including education, social security, medical treatment, occupational and social rehabilitation and establishes an extent of responsibility of the government and its bodies for the creation of favourable conditions for the social adaptation of PWDs in market environment conditions.
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We present a new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi-objective optimization algorithm developed on the basis of the Quantum behaved Particle Swarm Optimization (QPSO) paradigm. QPSO is a co-variant of the popular Particle Swarm Optimization (PSO) and has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; Failure Mechanism based Failure criteria, Maximum stress failure criteria and the Tsai-Wu Failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences as well as fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Also, the performance of QPSO is compared with the conventional PSO.
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Ramp metering (RM) is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, RM algorithms fall into two categories by their effective scope: local control and coordinated control. Local control algorithm determines the metering rate based on the traffic condition on adjacent motorway mainline and the on-ramp. Conversely, coordinated RM strategies make use of measurements from the entire motorway network to operate individual ramp signals for optimal performance at the network level. This study proposes a multi-hierarchical strategy for on-ramp coordination. The strategy is structured in two layers. At the higher layer, a centralised, predictive controller plans the coordination control within a long update interval based on the location of high-risk breakdown flow. At the lower layer, reactive controllers determine the metering rates of those ramps involved in the ramp coordination with a short update interval. This strategy is modelled and applied to the northbound model of the Pacific Motorway in a micro-simulation platform (AIMSUN). The simulation results show that the proposed strategy effectively delays the onset of congestion and reduces total congestion with better managed on-ramp queues.