Comparison of environmental and genetic factors for Parkinson's disease between Chinese and Caucasians

This review paper compares the differences in prevalence, and environmental and genetic risk factors for Parkinson's disease between Chinese and Caucasian subjects. Comparison of age-specific prevalence between Chinese people and Caucasians suggests that the prevalence is lower in the Chinese ( at least in the past), although the prevalence rate in China appears to be rising. Distinctions in environmental risk factors and genetic factors are discussed. The difference in prevalence may be due to distinctions in environmental and genetic risk factors as well as the complex interaction between these environmental and genetic factors, although discrepancies in methodology for prevalence surveys can also be an explanation. Copyright (C) 2004 S. Karger AG, Basel.

The effects of habitat fragmentation due to forestry plantation establishment on the demography and genetic variation of a marsupial carnivore, Antechinus agilis

We conducted a demographic and genetic study to investigate the effects of fragmentation due to the establishment of an exotic softwood plantation on populations of a small marsupial carnivore, the agile antechinus (Antechinus agilis), and the factors influencing the persistence of those populations in the fragmented habitat. The first aspect of the study was a descriptive analysis of patch occupancy and population size, in which we found a patch occupancy rate of 70% among 23 sites in the fragmented habitat compared to 100% among 48 sites with the same habitat characteristics in unfragmented habitat. Mark-recapture analyses yielded most-likely population size estimates of between 3 and 85 among the 16 occupied patches in the fragmented habitat. Hierarchical partitioning and model selection were used to identify geographic and habitat-related characteristics that influence patch occupancy and population size. Patch occupancy was primarily influenced by geographic isolation and habitat quality (vegetation basal area). The variance in population size among occupied sites was influenced primarily by forest type (dominant Eucalyptus species) and, to a lesser extent, by patch area and topographic context (gully sites had larger populations). A comparison of the sex ratios between the samples from the two habitat contexts revealed a significant deficiency of males in the fragmented habitat. We hypothesise that this is due to male-biased dispersal in an environment with increased dispersal-associated mortality. The population size and sex ratio data were incorporated into a simulation study to estimate the proportion of genetic diversity that would have been lost over the known timescale since fragmentation if the patch populations had been totally isolated. The observed difference in genetic diversity (gene diversity and allelic richness at microsatellite and mitochondrial markers) between 16 fragmented and 12 unfragmented sites was extremely low and inconsistent with the isolation of the patch populations. Our results show that although the remnant habitat patches comprise approximately 2% of the study area, they can support non-isolated populations. However, the distribution of agile antechinus populations in the fragmented system is dependent on habitat quality and patch connectivity. (C) 2004 Elsevier Ltd. All rights reserved.

Genetic variability of Tomato spotted wilt virus in Australia and validation of real time RT-PCR for its detection in single and bulked leaf samples

The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy (R) or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to I infected in 800 samples with pepper but never detecting more than I infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

Genetic structure and male-mediated gene flow in the ghost bat (Macroderma gigas)

The Australian ghost bat is a large, opportunistic carnivorous species that has undergone a marked range contraction toward more mesic, tropical sites over the past century. Comparison of mitochondrial DNA (mtDNA) control region sequences and six nuclear microsatellite loci in 217 ghost bats from nine populations across subtropical and tropical Australia revealed strong population subdivision (mtDNA phi(ST) = 0.80; microsatellites URST = 0.337). Low-latitude (tropical) populations had higher heterozygosity and less marked phylogeographic structure and lower subdivision among sites within regions (within Northern Territory [NT] and within North Queensland [NQ]) than did populations at higher latitudes (subtropical sites; central Queensland [CQ]), although sampling of geographically proximal breeding sites is unavoidably restricted for the latter. Gene flow among populations within each of the northern regions appears to be male biased in that the difference in population subdivision for mtDNA and microsatellites (NT phi(ST) = 0.39, URST = 0.02; NQ phi(ST) = 0.60, URST = -0.03) is greater than expected from differences in the effective population size of haploid versus diploid loci. The high level of population subdivision across the range of the ghost bat contrasts with evidence for high gene flow in other chiropteran species and may be due to narrow physiological tolerances and consequent limited availability of roosts for ghost bats, particularly across the subtropical and relatively arid regions. This observation is consistent with the hypothesis that the contraction of the species' range is associated with late Holocene climate change. The extreme isolation among higher-latitude populations may predispose them to additional local extinctions if the processes responsible for the range contraction continue to operate.

Genetic algorithm based distance spectrum technique for performance union bound of space-time trellis coded OFDM

This paper derives the performance union bound of space-time trellis codes in orthogonal frequency division multiplexing system (STTC-OFDM) over quasi-static frequency selective fading channels based on the distance spectrum technique. The distance spectrum is the enumeration of the codeword difference measures and their multiplicities by exhausted searching through all the possible error event paths. Exhaustive search approach can be used for low memory order STTC with small frame size. However with moderate memory order STTC and moderate frame size the computational cost of exhaustive search increases exponentially, and may become impractical for high memory order STTCs. This requires advanced computational techniques such as Genetic Algorithms (GAS). In this paper, a GA with sharing function method is used to locate the multiple solutions of the distance spectrum for high memory order STTCs. Simulation evaluates the performance union bound and the complexity comparison of non-GA aided and GA aided distance spectrum techniques. It shows that the union bound give a close performance measure at high signal-to-noise ratio (SNR). It also shows that GA sharing function method based distance spectrum technique requires much less computational time as compared with exhaustive search approach but with satisfactory accuracy.

The dynamics of a genetic algorithm for a simple learning problem

A formalism for describing the dynamics of Genetic Algorithms (GAs) using method s from statistical mechanics is applied to the problem of generalization in a perceptron with binary weights. The dynamics are solved for the case where a new batch of training patterns is presented to each population member each generation, which considerably simplifies the calculation. The theory is shown to agree closely to simulations of a real GA averaged over many runs, accurately predicting the mean best solution found. For weak selection and large problem size the difference equations describing the dynamics can be expressed analytically and we find that the effects of noise due to the finite size of each training batch can be removed by increasing the population size appropriately. If this population resizing is used, one can deduce the most computationally efficient size of training batch each generation. For independent patterns this choice also gives the minimum total number of training patterns used. Although using independent patterns is a very inefficient use of training patterns in general, this work may also prove useful for determining the optimum batch size in the case where patterns are recycled.

The dynamics of a genetic algorithm under stabilizing selection

A formalism recently introduced by Prugel-Bennett and Shapiro uses the methods of statistical mechanics to model the dynamics of genetic algorithms. To be of more general interest than the test cases they consider. In this paper, the technique is applied to the subset sum problem, which is a combinatorial optimization problem with a strongly non-linear energy (fitness) function and many local minima under single spin flip dynamics. It is a problem which exhibits an interesting dynamics, reminiscent of stabilizing selection in population biology. The dynamics are solved under certain simplifying assumptions and are reduced to a set of difference equations for a small number of relevant quantities. The quantities used are the population's cumulants, which describe its shape, and the mean correlation within the population, which measures the microscopic similarity of population members. Including the mean correlation allows a better description of the population than the cumulants alone would provide and represents a new and important extension of the technique. The formalism includes finite population effects and describes problems of realistic size. The theory is shown to agree closely to simulations of a real genetic algorithm and the mean best energy is accurately predicted.

A hybrid genetic algorithm for the multi-depot vehicle routing problem

The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time. The distribution problem is generally formulated as the vehicle routing problem (VRP). Nevertheless, there is a rigid assumption that there is only one depot. In cases, for instance, where a logistics company has more than one depot, the VRP is not suitable. To resolve this limitation, this paper focuses on the VRP with multiple depots, or multi-depot VRP (MDVRP). The MDVRP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To deal with the problem efficiently, two hybrid genetic algorithms (HGAs) are developed in this paper. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method and the nearest neighbor heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different problem sizes. It is proved that the performance of HGA2 is superior to that of HGA1 in terms of the total delivery time.

A genetic algorithm for the generalised transportation problem

The generalised transportation problem (GTP) is an extension of the linear Hitchcock transportation problem. However, it does not have the unimodularity property, which means the linear programming solution (like the simplex method) cannot guarantee to be integer. This is a major difference between the GTP and the Hitchcock transportation problem. Although some special algorithms, such as the generalised stepping-stone method, have been developed, but they are based on the linear programming model and the integer solution requirement of the GTP is relaxed. This paper proposes a genetic algorithm (GA) to solve the GTP and a numerical example is presented to show the algorithm and its efficiency.

Genetic algorithms and investment strategies: A global perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: (1) help global investors determine the optimal selection and holding periods for momentum portfolios, (2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, (3) assess the investment strategy profits after considering transaction costs, and (4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

Genetic Algorithms and Investment Strategies: A Global Perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: 1) help global investors determine the optimal selection and holding periods for momentum portfolios, 2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, 3) assess the investment strategy profits after considering transaction costs, and 4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

Contemporary population genetic structure and phylogeography of pink salmon

Thesis (Master's)--University of Washington, 2016-06

Population genetic of three species of Clupeidae family Sardinella sindensis, Sardinella albella, Dussumieria acuta in the Persian Gulf & Oman Sea

Sardines and other Microfilidae have very important ecological role in marine ecosystems because they are first consumers in marine food chain and they are the main food of valuable species as tuna. So decries in their population will decline fishing of these spices. There are 10 genus of Clupeidae in south of Iran and Sardinella is the one of the most abundant of them. In this study we investigated about morphological and genetically differences in population of 3 species: Sardinella sindensis, Sardinella abella, Dussomieria acuta. About 65 specimens of Sardinella sindensis, 61 specimens of Sardinella albella and 63 specimens of, Dussomieria acuta from three regions of their distribution: Jask (Oman Sea), Qeshm (Hormoz) and Lengeh (Pearsian Gulf) have been collected. Morphological research of their characters and statistical studies were done. To determine the genetically structure of specie's population we sequenced 500 bp of mitochondrial control region. Genetical studies determine meaningful difference in alleles and heterozigosity frequency of Sardinella sindensis. This must be the result of divergence in population of this species. Morphological investigation of Sardinella albella shows the meaningful difference. But detailed studies diffused it. Genetical studies show a meaningful variance in allele and heterosigosity frequency. This may be an aspect of sardine tendency to live in estuaries. Morphological research of Dussomieria acuta in Jask and Lengeh show a meaningful variance in these regions. Such a situation might be result of Monsoon, upwelling and better weather which occur in Oman Sea in spite of Persian Gulf.

Genetic Characteristic of Indonesian Local Ducks Based on Single Nucleotide Polymorphism (SNP) Analysis in D-loop Region Mitochondria DNA

Abstract. The aim of the study was to know the genetic characteristic and polymorphysm of Indonesian local ducks including Magelang, Tegal, Mojosari, Bali and Alabio duck based on Single Nucleotide Polymorphism (SNP) analysis in D-loop region mtDNA. The long term aim was to set the spesific genetic marker based on SNP D-loop region mtDNA which could differentiate local ducks in Indonesia. In the future, it could be used as selection tool for local duck conservation, and refinement strategy as well as the improvement of genetic quality by utilizing the available native duck germplasm. There were 20 ducks for each duck population and were taken 3 ml of its blood as sample. DNA Isolation Kit high pure PCR template preparation (Geneaid) was uded for Genome DNA isolation.  Amplification with PCR technique used primer DL-AnasPF (L56) as forward and DL-AnasPR (H773) as reverse. Next, PCR product or amplicon were sequenced. Sequence result were analyzed with SNP technique and observed the similarity and difference of its nucleotide sequence between individual and population. The result of the study showed that genome DNA from local duck in Indonesia was successfully isolated. DNA fragment of 718 bp was amplified with primer pair of DL-AnasPF and DL-AnasPR. Nucleotide sequence was 469 nt and analyzed with SNP technique. It was compared with standard nucleotide sequence of Anas platyrhynchos (HM010684.1) in Gen Bank. The result of nucleotide sequence similarity percentage was 99.68±0.56%. Single Nucleotide Polymorphism D-loop region mtDNA Indonesian local duck was 0.32±0.56%.  Some SNP was found in Magelang duck C (Klawu blorok), F (Cemani black),  G (Gambiran), H (Jarakan kalung), I (Jowo plain) and K (Plain white) also Tegal duck 8, 1, 2, 5, 2, 8 and 2 SNP respectively. It could be concluded that polymorphic genetic characteristic similarity were existed in Indonesia local duck populations which was shown by its big standard deviation SNP in D-loop region mtDNA. Magelang duck with different feather color relatively more polymorphic to another local duck in Indonesia. Single Nucleotide Polymorphism which was achieved could be used as genetic marker that differentiate genetic characteristic of Indonesian local ducks.Key words:  genetic characteristic, local duck, Single Nucleotide Polymorphism (SNP), D-loop mtDNAAbstrak.  Penelitian ini bertujuan untuk mengetahui karakteristik genetik dan polimorfisme itik lokal Indonesia yaitu itik Magelang, Tegal, Mojosari, Bali dan Alabio berdasarkan analisis Single Nucleotide Polymorphism (SNP) daerah D-loop mtDNA. Tujuan jangka panjangnya adalah menetapkan marker atau penanda genetik berdasarkan SNP daerah D-loop mtDNA spesifik yang dapat membedakan itik-itik lokal yang ada di Indonesia. Selanjutnya digunakan sebagai  alat bantu seleksi untuk konservasi, pembibitan  dan pengembangbiakan itik lokal.  Populasi masing-masing jenis itik lokal yang digunakan sebanyak 20 ekor untuk diambil 3 ml sampel darahnya. Isolasi DNA genom menggunakan DNA Isolation Kithigh pure PCR template preparation (Geneaid). Amplifikasi dengan teknik PCR menggunakan pasangan primer DL-AnasPF (L56) sebagai forward dan DL-AnasPR (H773) sebagai reverse. Produk PCR atau amplikon yang diperoleh disekuensing. Hasil sekuensing dianalisis dengan teknik SNP dan diamati kesamaan dan perbedaan urutan nukleotida antar individu itik dan antar populasi.  Hasil penelitian menunjukkan bahwa DNA genom dari itik lokal di Indonesia berhasil diisolasi. Amplifikasi dengan teknik PCR berhasil memperoleh fragmen berukuran 718 bp. Urutan nukleotida hasil sekuensing sebesar 469 nt dianalisis dengan teknik SNP dan dibandingkan dengan urutan nukleotida standar dari itik Anas platyrhynchos (HM010684.1) yang ada di Gen Bank, diperoleh persentase kesamaan urutan nukleotid sebesar 99,68±0,56%. Single Nucleotide Polymorphism daerah D-loop mtDNA pada itik lokal di Indonesia sebesar 0,32±0,56%. Sejumlah SNP ditemukan pada itik Magelang C (Klawu blorok), F (Hitam cemani),  G (Gambiran), H (Jarakan kalung), I (Jowo polos) dan K (Putih polos) serta itik Tegal  masing-masing 8, 1, 2, 5, 2, 8 serta 2 SNP. Kesimpulan dari penelitian ini adalah terdapat karakteristik genetik yang polimorfik pada populasi itik lokal di Indonesia, ditunjukkan dengan adanya simpang baku SNP pada daerah D-loop mtDNA yang relatif besar. Itik Magelang dengan warna bulu yang berbeda relatif lebih polimorfik dibandingkan dengan itik lokal lainnya di Indonesia.  Single Nucleotide Polymorphism yang diperoleh dapat digunakan sebagai penanda genetik yang dapat membedakan karakteristik genetik yang dimiliki oleh itik lokal di Indonesia.Kata kunci:  karakteristik genetik, itik lokal, Single NucleotidePolymorphism (SNP),  D-loop mtDNA

Detailed analysis of a conservative difference approximation for the time fractional diffusion equation

Diffusion equations that use time fractional derivatives are attractive because they describe a wealth of problems involving non-Markovian Random walks. The time fractional diffusion equation (TFDE) is obtained from the standard diffusion equation by replacing the first-order time derivative with a fractional derivative of order α ∈ (0, 1). Developing numerical methods for solving fractional partial differential equations is a new research field and the theoretical analysis of the numerical methods associated with them is not fully developed. In this paper an explicit conservative difference approximation (ECDA) for TFDE is proposed. We give a detailed analysis for this ECDA and generate discrete models of random walk suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation. The stability and convergence of the ECDA for TFDE in a bounded domain are discussed. Finally, some numerical examples are presented to show the application of the present technique.