866 resultados para INDEPENDENT COMPONENT ANALYSIS (ICA)
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Background: This multicentre, open-label, randomized, controlled phase II study evaluated cilengitide in combination with cetuximab and platinum-based chemotherapy, compared with cetuximab and chemotherapy alone, as first-line treatment of patients with advanced non-small-cell lung cancer (NSCLC). Patients and methods: Patients were randomized 1:1:1 to receive cetuximab plus platinum-based chemotherapy alone (control), or combined with cilengitide 2000 mg 1×/week i.v. (CIL-once) or 2×/week i.v. (CIL-twice). A protocol amendment limited enrolment to patients with epidermal growth factor receptor (EGFR) histoscore ≥200 and closed the CIL-twice arm for practical feasibility issues. Primary end point was progression-free survival (PFS; independent read); secondary end points included overall survival (OS), safety, and biomarker analyses. A comparison between the CIL-once and control arms is reported, both for the total cohorts, as well as for patients with EGFR histoscore ≥200. Results: There were 85 patients in the CIL-once group and 84 in the control group. The PFS (independent read) was 6.2 versus 5.0 months for CIL-once versus control [hazard ratio (HR) 0.72; P = 0.085]; for patients with EGFR histoscore ≥200, PFS was 6.8 versus 5.6 months, respectively (HR 0.57; P = 0.0446). Median OS was 13.6 for CIL-once versus 9.7 months for control (HR 0.81; P = 0.265). In patients with EGFR ≥200, OS was 13.2 versus 11.8 months, respectively (HR 0.95; P = 0.855). No major differences in adverse events between CIL-once and control were reported; nausea (59% versus 56%, respectively) and neutropenia (54% versus 46%, respectively) were the most frequent. There was no increased incidence of thromboembolic events or haemorrhage in cilengitide-treated patients. αvβ3 and αvβ5 expression was neither a predictive nor a prognostic indicator. Conclusions: The addition of cilengitide to cetuximab/chemotherapy indicated potential clinical activity, with a trend for PFS difference in the independent-read analysis. However, the observed inconsistencies across end points suggest additional investigations are required to substantiate a potential role of other integrin inhibitors in NSCLC treatment.
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Children s participation has been a subject in the international research since past ten years. This research has explored participation from the standpoint of the UN s Convention of the Rights of the Child and focused mainly on schoolchildren or on the working youth s chances in developing countries to have impact on their own lives (eg. Sinclair, 2004 and Thomas, 2002). In Finland there has been less research about the children s rights while the main focus has been on the customers of the child welfare system. This study examines children s participation in Helsinki metropolitan area via the views and the practices of the personnel of early childhood education. The adopted viewpoint is Shier s level model of participation (2001), in which the children s participation process is building in phases, is observed via the everyday actions of the kindergarten personnel. Attention has been paid on the special characteristics of the Finnish early childhood education. This study was part of VKK-Metro s research project. The inquiry in May 2010 was directed to all working teams in the kindergartens of the Helsinki metropolitan area. Of these 56.59 % (1116 teams) answered. The quantitative data analyzed by principal component analysis gave four principal components, from which three were named after Shier s participation model. The fourth component included variables about rules and power. The level model of participation fit well to assess early childhood education in the Helsinki metropolitan area. The professionalism of the personnel became emphasized in the area of everyday interactions between the personnel and the children. Important aspects of the children s participation are to become heard, to get support in the play and in interaction and to be able to share both power and responsibility with personnel of the early childhood education.
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Nanotechnology is a new technology which is generating a lot of interest among academicians, practitioners and scientists. Critical research is being carried out in this area all over the world.Governments are creating policy initiatives to promote developments it the nanoscale science and technology developments. Private investment is also seeing a rising trend. Large number of academic institutions and national laboratories has set up research centers that are workingon the multiple applications of nanotechnology. Wide ranges of applications are claimed for nanotechnology. This consists of materials, chemicals, textiles, semiconductors, to wonder drug delivery systems and diagnostics. Nanotechnology is considered to be a next big wave of technology after information technology and biotechnology. In fact, nanotechnology holds the promise of advances that exceed those achieved in recent decades in computers and biotechnology. Much interest in nanotechnology also could be because of the fact that enormous monetary benefits are expected from nanotechnology based products. According to NSF, revenues from nanotechnology could touch $ 1 trillion by 2015. However much of the benefits are projected ones. Realizing claimed benefits require successful development of nanoscience andv nanotechnology research efforts. That is the journey of invention to innovation has to be completed. For this to happen the technology has to flow from laboratory to market. Nanoscience and nanotechnology research efforts have to come out in the form of new products, new processes, and new platforms.India has also started its Nanoscience and Nanotechnology development program in under its 10(th) Five Year Plan and funds worth Rs. One billion have been allocated for Nanoscience and Nanotechnology Research and Development. The aim of the paper is to assess Nanoscience and Nanotechnology initiatives in India. We propose a conceptual model derived from theresource based view of the innovation. We have developed a structured questionnaire to measure the constructs in the conceptual model. Responses have been collected from 115 scientists and engineers working in the field of Nanoscience and Nanotechnology. The responses have been analyzed further by using Principal Component Analysis, Cluster Analysis and Regression Analysis.
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Migraine is the common cause of chronic episodic headache, affecting 12%-15% of the Caucasian population (41 million Europeans and some half a million Finns), and causes considerable loss of quality of life to its sufferers, as well as being linked to increased risk for a wide range of conditions, from depression to stroke. Migraine is the 19th most severe disease in terms of disability-adjusted life years, and 9th among women. It is characterized by attacks of headache accompanied by sensitivity to external stimuli lasting 4-72 hours, and in a third of cases by neurological aura symptoms, such as loss of vision, speech or muscle function. The underlying pathophysiology, including what triggers migraine attacks and why they occur in the first place, is largely unknown. The aim of this study was to identify genetic factors associated with the hereditary susceptibility to migraine, in order to gain a better understanding of migraine mechanisms. In this thesis, we report the results of genetic linkage and association analyses on a Finnish migraine patient collection as well as migraineurs from Australia, Denmark, Germany, Iceland and the Netherlands. Altogether we studied genetic information of nearly 7,000 migraine patients and over 50,000 population-matched controls. We also developed a new migraine analysis method called the trait component analysis, which is based on individual patient responses instead of the clinical diagnosis. Using this method, we detected a number of new genetic loci for migraine, including on chromosome 17p13 (HLOD 4.65) and 10q22-q23 (female-specific HLOD 7.68) with significant evidence of linkage, along with five other loci (2p12, 8q12, 4q28-q31, 18q12-q22, and Xp22) detected with suggestive evidence of linkage. The 10q22-q23 locus was the first genetic finding in migraine to show linkage to the same locus and markers in multiple populations, with consistent detection in six different scans. Traditionally, ion channels have been thought to play a role in migraine susceptibility, but we were able to exclude any significant role for common variants in a candidate gene study of 155 ion transport genes. This was followed up by the first genome-wide association study in migraine, conducted on 2,748 migraine patients and 10,747 matched controls followed by a replication in 3,209 patients and 40,062 controls. In this study, we found interesting results with genome-wide significance, providing targets for future genetic and functional studies. Overall, we found several promising genetic loci for migraine providing a promising base for future studies in migraine.
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Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.
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While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.
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FTIR-spektroskopia (Fourier-muunnosinfrapunaspektroskopia) on nopea analyysimenetelmä. Fourier-laitteissa interferometrin käyttäminen mahdollistaa koko infrapunataajuusalueen mittaamisen muutamassa sekunnissa. ATR-liitännäisellä varustetun FTIR-spektrometrin käyttö ei edellytä juuri näytteen valmistusta ja siksi menetelmä on käytössä myös helppo. ATR-liitännäinen mahdollistaa myös monien erilaisten näytteiden analysoinnin. Infrapunaspektrin mittaaminen onnistuu myös sellaisista näytteistä, joille perinteisiä näytteenvalmistusmenetelmiä ei voida käyttää. FTIR-spektroskopian avulla saatu tieto yhdistetään usein tilastollisiin monimuuttuja-analyyseihin. Klusterianalyysin avulla voidaan spektreistä saatu tieto ryhmitellä samanlaisuuteen perustuen. Hierarkkisessa klusterianalyysissa objektien välinen samanlaisuus määritetään laskemalla niiden välinen etäisyys. Pääkomponenttianalyysin avulla vähennetään datan ulotteisuutta ja luodaan uusia korreloimattomia pääkomponentteja. Pääkomponenttien tulee säilyttää mahdollisimman suuri määrä alkuperäisen datan variaatiosta. FTIR-spektroskopian ja monimuuttujamenetelmien sovellusmahdollisuuksia on tutkittu paljon. Elintarviketeollisuudessa sen soveltuvuutta esimerkiksi laadun valvontaan on tutkittu. Menetelmää on käytetty myös haihtuvien öljyjen kemiallisten koostumusten tunnistukseen sekä öljykasvien kemotyyppien havaitsemiseen. Tässä tutkimuksessa arvioitiin menetelmän käyttöä suoputken uutenäytteiden luokittelussa. Tutkimuksessa suoputken eri kasvinosien uutenäytteiden FTIR-spektrejä vertailtiin valikoiduista puhdasaineista mitattuihin FTIR-spektreihin. Puhdasaineiden FTIR-spektreistä tunnistettiin niiden tyypilliset absorptiovyöhykkeet. Furanokumariinien spektrien intensiivisten vyöhykkeiden aaltolukualueet valittiin monimuuttuja-analyyseihin. Monimuuttuja-analyysit tehtiin myös IR-spektrin sormenjälkialueelta aaltolukualueelta 1785-725 cm-1. Uutenäytteitä pyrittiin luokittelemaan niiden keräyspaikan ja kumariinipitoisuuden mukaan. Keräyspaikan mukaan ryhmittymistä oli havaittavissa, mikä selittyi vyöhykkeiden aaltolukualueiden mukaan tehdyissä analyyseissa pääosin kumariinipitoisuuksilla. Näissä analyyseissa uutenäytteet pääosin ryhmittyivät ja erottuivat kokonaiskumariinipitoisuuksien mukaan. Myös aaltolukualueen 1785-725 cm-1 analyyseissa havaittiin keräyspaikan mukaan ryhmittymistä, mitä kumariinipitoisuudet eivät kuitenkaan selittäneet. Näihin ryhmittymisiin vaikuttivat mahdollisesti muiden yhdisteiden samanlaiset pitoisuudet näytteissä. Analyyseissa käytettiin myös muita aaltolukualueita, mutta tulokset eivät juuri poikenneet aiemmista. 2. kertaluvun derivaattaspektrien monimuuttuja-analyysit sormenjälkialueelta eivät myöskään muuttaneet tuloksia havaittavasti. Jatkotutkimuksissa nyt käytettyä menetelmää on mahdollista edelleen kehittää esimerkiksi tutkimalla monimuuttuja-analyyseissa 2. kertaluvun derivaattaspektreistä suppeampia, tarkkaan valittuja aaltolukualueita.
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Tiivistelmä ReferatAbstract Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.
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Species identification forms the basis for understanding the diversity of the living world, but it is also a prerequisite for understanding many evolutionary patterns and processes. The most promising approach for correctly delimiting and identifying species is to integrate many types of information in the same study. Our aim was to test how cuticular hydro- carbons, traditional morphometrics, genetic polymorphisms in nuclear markers (allozymes and DNA microsatellites) and DNA barcoding (partial mitochondrial COI gene) perform in delimiting species. As an example, we used two closely related Formica ants, F. fusca and F. lemani, sampled from a sympatric population in the northern part of their distribu- tion. Morphological characters vary and overlap in different parts of their distribution areas, but cuticular hydrocarbons include a strong taxonomic signal and our aim is to test the degree to which morphological and genetic data correspond to the chemical data. In the morphological analysis, species were best separated by the combined number of hairs on pro- notum and mesonotum, but individual workers overlapped in hair numbers, as previously noted by several authors. Nests of the two species were separated but not clustered according to species in a Principal Component Analysis made on nuclear genetic data. However, model-based Bayesian clustering resulted in perfect separation of the species and gave no indication of hybridization. Furthermore, F. lemani and F. fusca did not share any mitochondrial haplotypes, and the species were perfectly separated in a phylogenetic tree. We conclude that F. fusca and F. lemani are valid species that can be separated in our study area relatively well with all methods employed. However, the unusually small genetic differen- tiation in nuclear markers (FST = 0.12) shows that they are closely related, and occasional hybridization between F. fusca and F. lemani cannot be ruled out.
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It has been found usually to talk in the early childhood education in connection with the creativity about arts and skills and about play. In this treatise, the creativity is approached besides play but also from the point of view of the creativity of the everyday. The starting point for the study is the view according to which the creativity is complex interaction between a creative person and an environment. The theoretical body of the study is the Componential theory of creativity of Amabile (1996). The process which is open and product which is new and suitable or acceptable were defined creative. In the opinion of many researchers, the creativity is a phenomenon that has determined in a certain time and place so the creativity is examined from the point of view of the social constructionism. As creative processes in the day nursery it has been defined pretend play, child´s involvement and children´s agentive perception which is based on the Children´s agentive perception theory of Reunamo (2007). The purpose of the study is to clarify how the child's personal factors and the social environment affect the creative processes of children in the day nursery. This Master's thesis is based on the Children' s agentive perception uncovered study led by Jyrki Reunamo (2010) which was carried out in the spring of 2010 in Keski-Uusimaa and in Hämeenlinna and Taiwan. From the study, a name has also been used "on the sources of Orientation", a research project and development project. The study includes the children's evaluation sector, the observation sector, the children's interview sector and the evaluation sector of the pedagogic environment. 891 Children 1-7 year-old by age participated in the study. All the sectors which belong to the study of Reunamo were utilized in this treatise and the Finnish day nurseries or preschool groups which had participated in the study were marked off as the target group. The main component analysis, sum variables, the correlation coefficients, Mann-Whitney s U-test and Kruskall-Wallas test were used for the statistical examination of the quantitative material. In this treatise it was noticed, both the personal properties of the child and a social environment, that they affected all the examined creative processes which also had a significant connection with each other statistically. The definition of creativity was filled best by the participative answers. However, the number of the participative answers was only 8% in the questions concerning adults. That raised the question whether an attempt should be made to have effect so that the children's better participation also in the interaction with the adults would be possible in the educational culture of the day nursery. In the further study, the conscious building of the social environment which supports the creativity from a social constructionism point of view could indeed be an interesting task. The treatise is suitable for an examination of the interaction between the child's person and a social environment especially from the point of view of the creativity.
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Community diversity and the population abundance of a particular group of species are controlled by immediate environment, inter-and intra-species interactions, landscape conditions, historical events and evolutionary processes. Nestedness is a measure of order in an ecological system, referring to the order in which the number of species is related to area or other factors. In this study we have studied the nestedness pattern in stream diatom assemblages in 24 stream sites of central Western Ghats, and report 98 taxa from the streams of central Western Ghats region. The communities show highly significant nested pattern. The Mantel test of matrix revealed a strong relationship between species assemblages and environmental conditions at the sites. A significant relationship between species assemblage and environmental condition was observed. Principal component analysis (PCA) indicated that environmental conditions differed markedly across the sampling sites, with the first three components explaining 78% of variance. Species composition of diatoms is significantly correlated with environmental distance across geographical extent. The current pattern suggests that micro-environment at regional levels influences the species composition of epilithic diatoms in streams. The nestedness shown by the diatom community was highly significant, even though it had a high proportion of idiosyncratic species, characterized with high numbers of cosmopolitan species, whereas the nested species were dominated by endemic species. PCA identifies ionic parameters and nutrients as the major features which determine the characteristics of the sampling sites. Hence the local water quality parameters are the major factors in deciding the diatom species assemblages.
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The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.
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Feature extraction in bilingual OCR is handicapped by the increase in the number of classes or characters to be handled. This is evident in the case of Indian languages whose alphabet set is large. It is expected that the complexity of the feature extraction process increases with the number of classes. Though the determination of the best set of features that could be used cannot be ascertained through any quantitative measures, the characteristics of the scripts can help decide on the feature extraction procedure. This paper describes a hierarchical feature extraction scheme for recognition of printed bilingual (Tamil and Roman) text. The scheme divides the combined alphabet set of both the scripts into subsets by the extraction of certain spatial and structural features. Three features viz geometric moments, DCT based features and Wavelet transform based features are extracted from the grouped symbols and a linear transformation is performed on them for the purpose of efficient representation in the feature space. The transformation is obtained by the maximization of certain criterion functions. Three techniques : Principal component analysis, maximization of Fisher's ratio and maximization of divergence measure have been employed to estimate the transformation matrix. It has been observed that the proposed hierarchical scheme allows for easier handling of the alphabets and there is an appreciable rise in the recognition accuracy as a result of the transformations.
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Sandalwood is an economically important aromatic tree belonging to the family Santalaceae. The trees are used mainly for their fragrant heartwood and oil that have immense potential for foreign exchange. Very little information is available on the genetic diversity in this species. Hence studies were initiated and genetic diversity estimated using RAPD markers in 51 genotypes of Santalum album procured from different geographcial regions of India and three exotic lines of S. spicatum from Australia. Eleven selected Operon primers (10mer) generated a total of 156 consistent and unambiguous amplification products ranging from 200bp to 4kb. Rare and genotype specific bands were identified which could be effectively used to distinguish the genotypes. Genetic relationships within the genotypes were evaluated by generating a dissimilarity matrix based on Ward's method (Squared Euclidean distance). The phenetic dendrogram and the Principal Component Analysis generated, separated the 51 Indian genotypes from the three Australian lines. The cluster analysis indicated that sandalwood germplasm within India constitutes a broad genetic base with values of genetic dissimilarity ranging from 15 to 91 %. A core collection of 21 selected individuals revealed the same diversity of the entire population. The results show that RAPD analysis is an efficient marker technology for estimating genetic diversity and relatedness, thereby enabling the formulation of appropriate strategies for conservation, germplasm management, and selection of diverse parents for sandalwood improvement programmes.
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Land-use changes influence local biodiversity directly, and also cumulatively, contribute to regional and global changes in natural systems and quality of life. Consequent to these, direct impacts on the natural resources that support the health and integrity of living beings are evident in recent times. The Western Ghats being one of the global biodiversity hotspots, is reeling under a tremendous pressure from human induced changes in terms of developmental projects like hydel or thermal power plants, big dams, mining activities, unplanned agricultural practices,monoculture plantations, illegal timber logging, etc. This has led to the once contiguous forest habitats to be fragmented in patches, which in turn has led to the shrinkage of original habitat for the wildlife, change in the hydrological regime of the catchment, decreased inflow in streams,human-animal conflicts, etc. Under such circumstances, a proper management practice is called for requiring suitable biological indicators to show the impact of these changes, set priority regions and in developing models for conservation planning. Amphibians are regarded as one of the best biological indicators due to their sensitivity to even the slightest changes in the environment and hence they could be used as surrogates in conservation and management practices. They are the predominating vertebrates with a high degree of endemism (78%) in Western Ghats. The present study is an attempt to bring in the impacts of various land-uses on anuran distribution in three river basins. Sampling was carried out for amphibians during all seasons of 2003-2006 in basins of Sharavathi, Aghanashini and Bedthi. There are as many as 46 species in the region, one of which is new to science and nearly 59% of them are endemic to the Western Ghats. They belong to nine families, Dicroglossidae being represented by 14 species,followed by Rhacophoridae (9 species) and Ranidae (5 species). Species richness is high in Sharavathi river basin, with 36 species, followed by Bedthi 33 and Aghanashini 27. The impact of land-use changes, was investigated in the upper catchment of Sharavathi river basin. Species diversity indices, relative abundance values, percentage endemics gave clear indication of differences in each sub-catchment. Karl Pearson’s correlation coefficient (r) was calculated between species richness, endemics, environmental descriptors, land-use classes and fragmentation metrics. Principal component analysis was performed to depict the influence of these variables. Results show that sub-catchments with lesser percentage of forest, low canopy cover, higher amount of agricultural area, low rainfall have low species richness, less endemic species and abundant non-endemic species, whereas endemism, species richness and abundance of endemic species are more in the sub-catchments with high tree density, endemic trees, canopy cover, rainfall and lower amount of agriculture fields. This analysis aided in prioritising regions in the Sharavathi river basin for further conservation measures.