The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data

Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

Intercalation of dodecylamine into kaolinite and its layering structure investigated by molecular dynamics simulation

Dodecylamine was successfully intercalated into the layer space of kaolinite by utilizing the methanol treated kaolinite–dimethyl sulfoxide (DMSO) intercalation complex as an intermediate. The basal spacing of kaolinite, measured by X-ray diffraction (XRD), increased from 0.72 nm to 4.29 nm after the intercalation of dodecylamine. Also, the significant variation observed in the Fourier Transform Infrared Spectroscopy (FTIR) spectra of kaolinite when intercalated with dodecylamine verified the feasibility of intercalation of dodecylamine into kaolinite. Isothermal-isobaric (NPT) molecular dynamics simulation with the use of Dreiding force field was performed to probe into the layering behavior and structure of nanoconfined dodecylamine in the kaolinite gallery. The concentration profiles of the nitrogen atom, methyl group and methylene group of intercalated dodecylamine molecules in the direction perpendicular to the kaolinite basal surface indicated that the alkyl chains within the interlayer space of kaolinite exhibited an obvious layering structure. However, the unified bilayer, pseudo-trilayer, or paraffin-type arrangements of alkyl chains deduced based on their chain length combined with the measured basal spacing of organoclays were not found in this study. The alkyl chains aggregated to a mixture of ordered paraffin-type-like structure and disordered gauche conformation in the middle interlayer space of kaolinite, and some alkyl chains arranged in two bilayer structures, in which one was close to the silica tetrahedron surface, and the other was close to the alumina octahedron surface with their alkyl chains parallel to the kaolinite basal surface.

Semiparametric estimation of count regression models

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. © 1999 Elsevier Science S.A. All rights reserved.

Cheating prevention in secret sharing over GF(pt)

The work investigates cheating prevention in secret sharing. It is argued that cheating is immune against cheating if the cheaters gain no advantage over honest participants by submitting invalid shares to the combiner. This work addresses the case when shares and the secret are taken from GF(pt). Two models are considered. The first one examines the case when cheaters consistently submit always invalid shares. The second modeldeal s with cheaters who submit a mixture of valid and invalid shares. For these two models, cheating immunity is defined, properties of cheating immune secret sharing are investigated and their constructions are given.

Constructions of cheating immune secret sharing

The work addresses the problem of cheating prevention in secret sharing. Two cheating scenarios are considered. In the first one, the cheaters always submit invalid shares to the combiner. In the second one, the cheaters collectively decide which shares are to be modified so the combiner gets a mixture of valid and invalid shares from the cheaters. The secret scheme is said to be k-cheating immune if any group of k cheaters has no advantage over honest participants. The paper investigates cryptographic properties of the defining function of secret sharing so the scheme is k-cheating immune. Constructions of secret sharing immune against k cheaters are given.

Surface chemical modification of carbon nanowalls for wide-range control of surface wettability

Carbon nanowalls (CNWs) are self-assembled, free-standing, few-layered graphenenano-structures with large surface area, and thin graphene edges. For their application to nanobiotechnology, the effects of chemisorbed species on surface wettability were investigated. The surfaces of as-grown CNWs obtained using CH4/H2 mixture were hydrophilic. After Ar atmospheric pressure plasma treatments for up to 30 s, the contact angles of water droplets on the CNWs decreased from 51° to 5°, owing to a result of oxidation only at edges and surface defects. They increased up to 147° by CF4 plasma treatment at low pressure. The wide-range control of surface wettability of CNWs was realized by post-growth plasma treatments. We also demonstrated detection of bovine serum albumin using surface-modified CNWs as electrodes.

Plasma-enabled, catalyst-free growth of carbon nanotubes on mechanically-written Si features with arbitrary shape

Simple, rapid, catalyst-free synthesis of complex patterns of long, vertically aligned multiwalled carbon nanotubes, strictly confined within mechanically-written features on a Si(1 0 0) surface is reported. It is shown that dense arrays of the nanotubes can nucleate and fully fill the features when the low-temperature microwave plasma is in a direct contact with the surface. This eliminates additional nanofabrication steps and inevitable contact losses in applications associated with carbon nanotube patterns. Using metal catalyst has long been considered essential for the nucleation and growth of surface-supported carbon nanotubes (CNTs) [1] and [2]. Only very recently, the possibility of CNT growth using non-metallic (e.g., oxide [3] and SiC [4]) catalysts or artificially created carbon-enriched surface layers [5] has been demonstrated. However, successful integration of carbon nanostructures into Si-based nanodevice platforms requires catalyst-free growth, as the catalyst nanoparticles introduce contact losses, and their catalytic activity is very difficult to control during the growth [6]. Furthermore, in many applications in microfluidics, biological and molecular filters, electronic, sensor, and energy conversion nanodevices, the CNTs need to be arranged in specific complex patterns [7] and [8]. These patterns need to contain the basic features (e.g., lines and dots) written using simple procedures and fully filled with dense arrays of high-quality, straight, yet separated nanotubes. In this paper, we report on a completely metal or oxide catalyst-free plasma-based approach for the direct and rapid growth of dense arrays of long vertically-aligned multi-walled carbon nanotubes arranged into complex patterns made of various combinations of basic features on a Si(1 0 0) surface written using simple mechanical techniques. The process was conducted in a plasma environment [9] and [10] produced by a microwave discharge which typically generates the low-temperature plasmas at the discharge power below 1 kW [11]. Our process starts from mechanical writing (scribing) a pattern of arbitrary features on pre-treated Si(1 0 0) wafers. Before and after the mechanical feature writing, the Si(1 0 0) substrates were cleaned in an aqueous solution of hydrofluoric acid for 2 min to remove any possible contaminations (such as oil traces which could decompose to free carbon at elevated temperatures) from the substrate surface. A piece of another silicon wafer cleaned in the same way as the substrate, or a diamond scriber were used to produce the growth patterns by a simple arbitrary mechanical writing, i.e., by making linear scratches or dot punctures on the Si wafer surface. The results were the same in both cases, i.e., when scratching the surface by Si or a diamond scriber. The procedure for preparation of the substrates did not involve any possibility of external metallic contaminations on the substrate surface. After the preparation, the substrates were loaded into an ASTeX model 5200 chemical vapour deposition (CVD) reactor, which was very carefully conditioned to remove any residue contamination. The samples were heated to at least 800 °C to remove any oxide that could have formed during the sample loading [12]. After loading the substrates into the reactor chamber, N2 gas was supplied into the chamber at the pressure of 7 Torr to ignite and sustain the discharge at the total power of 200 W. Then, a mixture of CH4 and 60% of N2 gases were supplied at 20 Torr, and the discharge power was increased to 700 W (power density of approximately 1.49 W/cm3). During the process, the microwave plasma was in a direct contact with the substrate. During the plasma exposure, no external heating source was used, and the substrate temperature (∼850 °C) was maintained merely due to the plasma heating. The features were exposed to a microwave plasma for 3–5 min. A photograph of the reactor and the plasma discharge is shown in Fig. 1a and b.

Real-time monitoring of nucleation-growth cycle of carbon nanoparticles in acetylene plasmas

Quantum cascade laserabsorption spectroscopy was used to measure the absolute concentration of acetylene in situ during the nanoparticle growth in Ar + C2H2 RF plasmas. It is demonstrated that the nanoparticle growth exhibits a periodical behavior, with the growth cycle period strongly dependent on the initial acetylene concentration in the chamber. Being 300 s at 7.5% of acetylene in the gas mixture, the growth cycle period decreases with the acetylene concentration increasing; the growth eventually disappears when the acetylene concentration exceeds 32%. During the nanoparticle growth, the acetylene concentration is small and does not exceed 4.2% at radio frequency (RF) power of 4 W, and 0.5% at RF power of 20 W. An injection of a single acetylene pulse into the discharge also results in the nanoparticlenucleation and growth. The absorption spectroscopy technique was found to be very effective for the time-resolved measurement of the hydrocarbon content in nanoparticle-generatingplasmas.

Single-step, rapid low-temperature synthesis of Si quantum dots embedded in an amorphous SiC matrix in high-density reactive plasmas

A simple, effective and innovative approach based on low-pressure, thermally nonequilibrium, high-density inductively coupled plasmas is proposed to rapidly synthesize Si quantum dots (QDs) embedded in an amorphous SiC (a-SiC) matrix at a low substrate temperature and without any commonly used hydrogen dilution. The experimental results clearly demonstrate that uniform crystalline Si QDs with a size of 3-4 nm embedded in the silicon-rich (carbon content up to 10.7at.%) a-SiC matrix can be formed from the reactive mixture of silane and methane gases, with high growth rates of ∼1.27-2.34 nm s-1 and at a low substrate temperature of 200 °C. The achievement of the high-rate growth of Si QDs embedded in the a-SiC without any commonly used hydrogen dilution is discussed based on the unique properties of the inductively coupled plasma-based process. This work is particularly important for the development of the all-Si tandem cell-based third generation photovoltaic solar cells.

Inductively coupled plasma-assisted RF magnetron sputtering deposition of boron-doped microcrystalline Si films

An innovative custom-designed inductively coupled plasma-assisted RF magnetron sputtering deposition system has been developed to synthesize B-doped microcrystalline silicon thin films using a pure boron sputtering target in a reactive silane and argon gas mixture. Films were deposited using different boron target powers ranging from 0 to 350 W at a substrate temperature of 250 °C. The effect of the boron target power on the structural and electrical properties of the synthesized films was extensively investigated using X-ray diffraction, Raman spectroscopy, scanning electron microscopy, and Hall-effect system. It is shown that, with an initial increase of the boron target power from 0 to 300 W, the structural and electrical properties of the B-doped microcrystalline films are improved. However, when the target power is increased too much (e.g. to 350 W), these properties become slightly worse. The variation of the structural and electrical properties of the synthesized B-doped microcrystalline thin films is related to the incorporation of boron atoms during the crystallization and doping of silicon in the inductively coupled plasma-based process. This work is particularly relevant to the microcrystalline silicon-based p-i-n junction solar cells.

Effect of gas pressure on electron field emission from carbon nanotube forests

This article quantifies the effect of the operating pressure of the H 2 + C 2H 4 gas mixture on the current density and threshold voltage of the electron emission from dense forests of multiwalled carbon nanotubes synthesized using thermal catalytic Chemical Vapor Deposition under near atmospheric pressure process conditions. The results suggest that in the pressure range of interest 400-700 Torr the field emission properties can be substantially improved by operating the process at lower gas pressures when the nanostructure aspect ratios are higher. The obtained threshold voltage ∼1.75 V/μm and the emission current densities ∼10 mA/cm 2 offer competitive advantages compared with the results reported by other authors. Copyright

Tailoring carbon nanotips in the plasma-assisted chemical vapor deposition: Effect of the process parameters

Carbon nanotips have been synthesized from a thin carbon film deposited on silicon by bias-enhanced hot filament chemical vapor deposition under different process parameters. The results of scanning electron microscopy indicate that high-quality carbon nanotips can only be obtained under conditions when the ion flux is effectively drawn from the plasma sustained in a CH4 + NH3 + H2 gas mixture. It is shown that the morphology of the carbon nanotips can be controlled by varying the process parameters such as the applied bias, gas pressure, and the NH3 / H2 mass flow ratios. The nanotip formation process is examined through a model that accounts for surface diffusion, in addition to sputtering and deposition processes included in the existing models. This model makes it possible to explain the major difference in the morphologies of the carbon nanotips formed without and with the aid of the plasma as well as to interpret the changes of their aspect ratio caused by the variation in the ion/gas fluxes. Viable ways to optimize the plasma-based process parameters to synthesize high-quality carbon nanotips are suggested. The results are relevant to the development of advanced plasma-/ion-assisted methods of nanoscale synthesis and processing.

p-type doping of ZnO by means of high-density inductively coupled plasmas

A custom-designed inductively coupled plasma assisted radio-frequency magnetron sputtering deposition system has been used to fabricate N-doped p-type ZnO (ZnO:N) thin films on glass substrates from a sintered ZnO target in a reactive Ar + N2 gas mixture. X-ray diffraction and scanning electron microscopy analyses show that the ZnO:N films feature a hexagonal crystal structure with a preferential (002) crystallographic orientation and grow as vertical columnar structures. Hall effect and X-ray photoelectron spectroscopy analyses show that N-doped ZnO thin films are p-type with a hole concentration of 3.32 × 1018 cm- 3 and mobility of 1.31 cm2 V- 1 s- 1. The current-voltage measurement of the two-layer structured ZnO p-n homojunction clearly reveals the rectifying ability of the p-n junction. The achievement of p-type ZnO:N thin films is attributed to the high dissociation ability of the high-density inductively coupled plasma source and effective plasma-surface interactions during the growth process.