Selection of cowpea progenies with enhanced drought-tolerance traits using principal component analysis.

Vigna unguiculata (L.) Walp (cowpea) is a food crop with high nutritional value that is cultivated throughout tropical and subtropical regions of the world. The main constraint on high productivity of cowpea is water deficit, caused by the long periods of drought that occur in these regions. The aim of the present study was to select elite cowpea genotypes with enhanced drought tolerance, by applying principal component analysis to 219 first-cycle progenies obtained in a recurrent selection program. The experimental design comprised a simple 15 x 15 lattice with 450 plots, each of two rows of 10 plants. Plants were grown under water-deficit conditions by applying a water depth of 205 mm representing one-half of that required by cowpea. Variables assessed were flowering, maturation, pod length, number and mass of beans/pod, mass of 100 beans, and productivity/plot. Ten elite cowpea genotypes were selected, in which principal components 1 and 2 encompassed variables related to yield (pod length, beans/pod, and productivity/plot) and life precocity (flowering and maturation), respectively.

Assessment of heavy metals in soils of a vineyard region with the use of principal component analysis.

Agricultural management with chemicals may contaminate the soil with heavy metals. The objective of this study was to apply Principal Component Analysis and geoprocessing techniques to identify the origin of the metals Cu, Fe, Mn, Zn, Ni, Pb, Cr and Cd as potential contaminants of agricultural soils. The study was developed in an area of vineyard cultivation in the State of São Paulo, Brazil. Soil samples were collected and GPS located under different uses and coverings. The metal concentrations in the soils were determined using the DTPA method. The Cu and Zn content was considered high in most of the samples, and was larger in the areas cultivated with vineyards that had been under the application of fungicides for several decades. The concentrations of Cu and Zn were correlated. The geoprocessing techniques and the Principal Component Analysis confirmed the enrichment of the soil with Cu and Zn because of the use and management of the vineyards with chemicals in the preceding decades.

Inactivation and structural changes of E. Cloacae and B. Subtilis Endospores during IR laser water treatment

IR radiation has been studied for micro-organism inactivation of bacterial spores on metal substrates [1] and on metal and paper substrates [2]. A near-point near infrared laser water treatment apparatus for use in dental hand-pieces was also developed [3]. To date water sterilisation research using a mid-IR laser technique is very rare. According to the World Health Organisation [4], examinations for faecal indicator bacteria remain the most sensitive and specific way of assessing the hygienic quality of water. Bacteria that fall into this group are E. coli, other coliform bacteria (including E. cloacae) and to a lesser extent, faecal streptococci [5]. Protozoan cysts from organisms which cause giardiasis are the most frequently identified cause of waterborne diseases in developed countries [6,7]. The use of aerobic bacterial endospores to monitor the efficiency of various water treatments has been shown to provide a reliable and simple indicator of overall performance of water treatment[8,9].The efficacy of IR radiation for water disinfection compared to UV treatment has been further investigated in the present study. In addition FTIR spectroscopy in conjunction with Principle Component Analysis was used to characterise structural changes within the bacterial cells and endospores following IR laser treatment. Changes in carbohydrate content of E. cloacae following IR laser treatment were observed.

Separable and non-separable discrete wavelet transform based texture features and image classification of breast thermograms

Highly sensitive infrared cameras can produce high-resolution diagnostic images of the temperature and vascular changes of breasts. Wavelet transform based features are suitable in extracting the texture difference information of these images due to their scale-space decomposition. The objective of this study is to investigate the potential of extracted features in differentiating between breast lesions by comparing the two corresponding pectoral regions of two breast thermograms. The pectoral regions of breastsare important because near 50% of all breast cancer is located in this region. In this study, the pectoral region of the left breast is selected. Then the corresponding pectoral region of the right breast is identified. Texture features based on the first and the second sets of statistics are extracted from wavelet decomposed images of the pectoral regions of two breast thermograms. Principal component analysis is used to reduce dimension and an Adaboost classifier to evaluate classification performance. A number of different wavelet features are compared and it is shown that complex non-separable 2D discrete wavelet transform features perform better than their real separable counterparts.

Label-free SERS for natural product provenance

Introduction Natural product provenance is important in the food, beverage and pharmaceutical industries, for consumer confidence and with health implications. Raman spectroscopy has powerful molecular fingerprint abilities. Surface Enhanced Raman Spectroscopy’s (SERS) sharp peaks allow distinction between minimally different molecules, so it should be suitable for this purpose. Methods Naturally caffeinated beverages with Guarana extract, coffee and Red Bull energy drink as a synthetic caffeinated beverage for comparison (20 µL ea.) were reacted 1:1 with Gold nanoparticles functionalised with anti-caffeine antibody (ab15221) (10 minutes), air dried and analysed in a micro-Raman instrument. The spectral data was processed using Principle Component Analysis (PCA). Results The PCA showed Guarana sourced caffeine varied significantly from synthetic caffeine (Red Bull) on component 1 (containing 76.4% of the variance in the data). See figure 1. The coffee containing beverages, and in particular Robert Timms (instant coffee) were very similar on component 1, but the barista espresso showed minor variance on component 1. Both coffee sourced caffeine samples varied with red Bull on component 2, (20% of variance). ************************************************************ Figure 1 PCA comparing a naturally caffeinated beverage containing Guarana with coffee. ************************************************************ Discussion PCA is an unsupervised multivariate statistical method that determines patterns within data. Figure 1 shows Caffeine in Guarana is notably different to synthetic caffeine. Other researchers have revealed that caffeine in Guarana plants is complexed with tannins. Naturally sourced/ lightly processed caffeine (Monster Energy, Espresso) are more inherently different than synthetic (Red Bull) /highly processed (Robert Timms) caffeine, in figure 1, which is consistent with this finding and demonstrates this technique’s applicability. Guarana provenance is important because it is still largely hand produced and its demand is escalating with recognition of its benefits. This could be a powerful technique for Guarana provenance, and may extend to other industries where provenance / authentication are required, e.g. the wine or natural pharmaceuticals industries.

Experimental and statistical investigation of Australian native plants for second-generation biodiesel production

This work explores the potential of Australian native plants as a source of second-generation biodiesel for internal combustion engines application. Biodiesels were evaluated from a number of non-edible oil seeds which are grow naturally in Queensland, Australia. The quality of the produced biodiesels has been investigated by several experimental and numerical methods. The research methodology and numerical model developed in this study can be used for a broad range of biodiesel feedstocks and for the future development of renewable native biodiesel in Australia.

An assessment of the genetic relationship between sweet and grain sorghums, within Sorghum bicolor ssp. bicolor (L.) Moench, using AFLP markers

Compared to grain sorghums, sweet sorghums typically have lower grain yield and thick, tall stalks which accumulate high levels of sugar (sucrose, fructose and glucose). Unlike commercial grain sorghum (S. bicolor ssp. bicolor) cultivars, which are usually F1 hybrids, commercial sweet sorghums were selected as wild accessions or have undergone limited plant breeding. Although all sweet sorghums are classified within S. bicolor ssp. bicolor, their genetic relationship with grain sorghums is yet to be investigated. Ninety-five genotypes, including 31 sweet sorghums and 64 grain sorghums, representing all five races within the subspecies bicolor, were screened with 277 polymorphic amplified fragment length polymorphism (AFLP) markers. Cluster analysis separated older sweet sorghum accessions (collected in mid 1800s) from those developed and released during the early to mid 1900s. These groups were emphasised in a principle component analysis of the results such that sweet sorghum lines were largely distinguished from the others, particularly by a group of markers located on sorghum chromosomes SBI-08 and SBI-10. Other studies have shown that QTL and ESTs for sugar-related traits, as well as for height and anthesis, map to SBI-10. Although the clusters obtained did not group clearly on the basis of racial classification, the sweet sorghum lines often cluster with grain sorghums of similar racial origin thus suggesting that sweet sorghum is of polyphyletic origin within S. bicolor ssp. bicolor.

HR-MAS NMR spectroscopy shows regional metabolite variation in bovine articular cartilage

Mechanical stress is an important external factor effecting the development and maintenance of articular cartilage. The metabolite profile of diseased cartilage has been well studied but there is limited information about the variation in metabolite profile of healthy cartilage. With the importance of load in maintaining healthy cartilage, regional differences in metabolite profile associated with differences in load may provide information on how load contributes to the maintenance of healthy cartilage. HR-MAS NMR spectroscopy allows the assessment of tissue samples without modification and was used for assessing the difference in metabolic profile between the load bearing and non-load bearing regions of the bovine articular cartilage. In this preliminary study, we examined cartilage from tibia and femur of four knee joints. Sixteen pairs of 1D-NOESY spectra were acquired. Principle component analysis (PCA) identified chemical shifts responsible for variance. SBASE (AMIX) and the Human Metabolome Database were used in conjunction with previous reported cartilage data for identifying metabolites associated with the PCA results. The major contributors to load-related differences in metabolite profile were N-acetyl groups, lactate and phosphocholine peaks. Integrals of these regions were further analysed using a Student's t-test. In load bearing cartilage regions. N-acetyl groups and phosphocholine were found at significantly higher concentration (p < 0.05 and p < 0.005, respectively) in both femur and tibia, while lactate was reduced in load bearing cartilage (p < 0.005). The results of this pilot HR-MAS NMR study demonstrate its ability to provide useful metabolite information for healthy cartilage.

Estimation and inference for grasping and manipulation tasks using vision and kinesthetic sensors

This thesis presents a novel framework for state estimation in the context of robotic grasping and manipulation. The overall estimation approach is based on fusing various visual cues for manipulator tracking, namely appearance and feature-based, shape-based, and silhouette-based visual cues. Similarly, a framework is developed to fuse the above visual cues, but also kinesthetic cues such as force-torque and tactile measurements, for in-hand object pose estimation. The cues are extracted from multiple sensor modalities and are fused in a variety of Kalman filters.

A hybrid estimator is developed to estimate both a continuous state (robot and object states) and discrete states, called contact modes, which specify how each finger contacts a particular object surface. A static multiple model estimator is used to compute and maintain this mode probability. The thesis also develops an estimation framework for estimating model parameters associated with object grasping. Dual and joint state-parameter estimation is explored for parameter estimation of a grasped object's mass and center of mass. Experimental results demonstrate simultaneous object localization and center of mass estimation.

Dual-arm estimation is developed for two arm robotic manipulation tasks. Two types of filters are explored; the first is an augmented filter that contains both arms in the state vector while the second runs two filters in parallel, one for each arm. These two frameworks and their performance is compared in a dual-arm task of removing a wheel from a hub.

This thesis also presents a new method for action selection involving touch. This next best touch method selects an available action for interacting with an object that will gain the most information. The algorithm employs information theory to compute an information gain metric that is based on a probabilistic belief suitable for the task. An estimation framework is used to maintain this belief over time. Kinesthetic measurements such as contact and tactile measurements are used to update the state belief after every interactive action. Simulation and experimental results are demonstrated using next best touch for object localization, specifically a door handle on a door. The next best touch theory is extended for model parameter determination. Since many objects within a particular object category share the same rough shape, principle component analysis may be used to parametrize the object mesh models. These parameters can be estimated using the action selection technique that selects the touching action which best both localizes and estimates these parameters. Simulation results are then presented involving localizing and determining a parameter of a screwdriver.

Lastly, the next best touch theory is further extended to model classes. Instead of estimating parameters, object class determination is incorporated into the information gain metric calculation. The best touching action is selected in order to best discern between the possible model classes. Simulation results are presented to validate the theory.

Genetic diversity of Bartail flathead (Platycephalus indicus (Linnaeus,1758)) using AFLP markers in Persian Gulf

Platycephalus indicus is a large benthic fish that inhabits temperate and tropical coastal waters of the Indo-West Pacific and found on sand or mud bottom in vary shallow area of estuary and near shore to depth of 25m. This species is dominant species of platycephalidae family, in Khuzestan, Bushehr and Hormozgan provinces and mainly is captured by bottom trawl, gillnet and moshta in Hormozgan. This study was designed to evaluate population variation and differentiation of bartail flathead (Platycephalus indicus (Linnaeus, 1785))in the Iranian waters of Persian Gulf using the morphometric and meristic characters and by AFLP marker. . A total 180 fish specimens were collected by gill net from six station(khor mosa, bahrekan, shif, motaf, charak and bandar abbas) that was 30 individual related to every station in Iranian shores of Persian Gulf . 28 morphometric factors and 11meristic specialties were measured and morphometric factors was standardized with Beacham formula. Univariate analysis of variance (One-way ANOVA) revealed significant differences with varying degrees between the means for 21 standardized morphometric measurements and 6 meristic counts that showed high significant differences between the six stations sampling. Discriminate function analysis (DFA) or the overall random assignment of individuals into their original groups was for morphometric and meristic characters was 47.9% and 53.9% respectively. The data were subjected to a principle component analysis (PCA) which grouped in eight and four factors for morphometric and meristic charactersrespectively.. Genetic diversity of six populations of bartail flathead (Platycephalus indicus) was investigated using amplified fragment length polymorphism (AFLP). A total of 118 reproducible bands amplified with ten AFLP primer combinations were obtained from 42 fishes that were collected from six different locations in the northern of Persian Gulf. The percentage of polymorphic bands was 57.06%. Average of Nei’s genetic diversity was 0.200±0.008, and Average of Shannon’s index was 0.300±0.011. The results of AMOVA analysis indicated that 66% of the genetic variation contained within populations and 34% occurred among populations and gene flow was 0.6454.The estimated level of population differentiation asmeasured by average Fst value across all loci was 0.327. Plotting discriminant functions 1 and 2 and UPGMA dendrograms based on Euclidian distance and genetic distance also showed at least five separate populations of bartail flathead in the northern Persian Gulf.

滇池金线鲃形态度量学分析(Cypriniformes:Cyprinidae)

运用多变量形态度量学和框架结构形态学的方法,测量了采自滇池流域6个不同地点的149尾滇池金线鲃(Sinocyclocheilus grahami)的标本.应用多变量形态度量学分析,选择了20个框架结构性状和19个常规性状,进行主成成分分析.主成成分分析结果的散布图显示,6个不同地点的标本聚在一起没有分开,表明滇池金线鲃的各居群之间在可数性状和可量性状上均未表现出明显的差异,说明滇池金线鲃在形态上还未发生明显的种下分化.

Reproductive physiology of ribbon fish (Trichiurus lepturus)

The ribbon fishes ‘of the family Trichiuridac are represented as one of the most important food resources in Indian ocean. High density of the dominant species of ribbon fish (Trichiurus lepturus) in Oman sea and the 'Tillable catch in last yeas (more than 7000 tones per year) makes a trust area for studing their population biolog and stock assessment. As our knowledge on reproductive biology of this species has an important role on their fisheries management, as well as conservation of this stock from decline or over fishing, this research was held to determine some aspects of reproductive physiology of ribbon fish and the effects of environmental factors in gonadal cycle. The goals of the present thesis is to determine some aspects of reproductive physiology such as gonadosomatic index (GSI) , hepatosomatic index (HSI), condition factor (Ko, fecundity, sex ratio, size at first maturity, size at maturity (LM5O) and their relative hormonal & biochemical fluctuations. In this regards annual variation of sex hormones ic. estradiol 17-B, progestron, cortisol, testostrone and gonadotropins FSH (GTH-I) , LH (GTH-ll)I were measured ; gonadal histological studies were done by light & electron micrography. The research was carried out from April 1995 to January 19% in Ras Nleidani in the north part of Oman sea, and the environmental factors such as temperature, salinity, oxygen, rainfall and pH were measured. The effects of these parameters on reproductive cycle and hormonal fluctuationswere discussed by using correlation and principle component analysis (PCA). Female Ribbon fish reproductive strategy shows the same paterns of nonguarder marine teleosts. T. lepturus has more than one spawning season (existance of egges in different size in each month) and therfore it must have asynchronous ovaries and belong to continious spawners. GSI and HSI are good evidences for this type of reproductive patern. The testis of the lobular type , which is typical of most teleosts , is composed of numerous lobules which are separated from each other by a thin layer of fibrous connective tissue. GSI fluctuations revealed prolong- spawning time in males. There is significant increase in 17-13 estradiol. progestrone , cortisol and gonadotropins with maturity and prespawning period of female T lepturus. Plasma concentration of E2 and GTH II incresaed along with water temperature increasing (3300).. Spawning was observed from Nov. 1995 to Apr. 1996 in this species. Progestrone increased significantly with increasing rainfall in this season (P<0.01). Plasma cortisol levels increased with maturation and vitelpgenesis and also with the peak of spawning. From lenght-weight frequency and size distribution in each age groups and also minimum size at first maturity (52a cm) it would he concluded that T. lepturus must be matured at 2 years of age. Serum cholestrol and triglicerides significantly increased when maturation occured in this species. The relationship between alkaline phosphatase activity and hormonal fluctuations with maturity and vitelogenesis were discussed. Proximate compostion (muscle) shows significant variation with spawning period and maturity. Absolute individual fecundity (17420-159150) increased with body length and weight. Ultrastructural observations show dramatic variation in cell membrane (0ocyte membrane), yolk vesicles and, nucleolus dispersal in relation to maturity stages. fluctuations of gonadal hormones were discused in relation with vitelogenesis. Testosterone increased in males from Nov: to Mar. due to environmental impacts and spawning time. Sex ratio in different depth (10-40 m ,80-110 m) shows significnt differences in this ratio for two depths. In 10-40 m depth female shows dominant abundance to male in each months that may be due to their reproductive migration behaviour. The effects of temperature photoperiod and rainfall to maturity and spawning were discussed. According to -pawning period of T. leptunts in our sampling area it could be suggested that ribbon fish fi,theries must be restricted in the peak of spawning seasons (Feb. to Mar.) and in the spawning grounds (under 40 m depths). Other suggestions for population conservation have been mentioned.

Bayesian classification of acoustical waveforms under environmental variability

We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.

主成分分析和聚类分析在软件重构中的应用

重构是软件系统不断演化的关键之一,也是一项复杂而又困难的活动.传统的定位重构代码方法依赖开发者的观察和主观意识,耗时耗力,尤其在重构代码较多时.因此,提出了一套自动化定位重构的方法.该方法利用基于面向对象软件度量指标获取代码特征信息,使用相关性检验查验特征信息数据,应用主成分分析压缩和解释特征信息,应用聚类分析分类相似代码段,迅速准确定位重构.一个简单的实例表明该方法是简单有效的,并且优于传统方法.