Influence of the silicon surface treatment by plasma etching and scratching on the nucleation of diamond grown in HFCVD - a comparative study

A comparative study for the nucleation of diamond was carried out using surface treatment like (i) surface scratching with 1 μm diamond paste and (ii) surface etching using chlorine plasma at different RF powers (50, 100 and 150 W). Atomic force microscopic study shows variation in roughness from 31 nm to 110 nm. Scratching results in random scratches, whereas plasma etches a surface uniformly. Scanning electron microscopic observations show well faceted crystallites with a predominance of angular shaped grains corresponding to 〈100〉 and 〈110〉 crystallite surfaces for the scratched as well as plasma etched substrate. Surface etching at 150 W plasma power results in a better growth in comparison with 50 and 100 W plasma powers. Chlorine-radical is found responsible for the changes in the growth morphology. Raman spectroscopy shows a sharp peak at 1,332 cm⁻¹ and a peak at ∼1,580 cm⁻¹ for both samples.     

Using multiple endmember spectral mixture analysis to retrieve subpixel fire properties from MODIS

The Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on NASA's Terra and Aqua satellites image most of the Earth multiple times each day, providing useful data on fires that cannot be practically acquired using other means. Unfortunately, current fire products from MODIS and other sensors leave large uncertainties in measurements of fire sizes and temperatures, which strongly influence how fires spread, the amount and chemistry of their gas and aerosol emissions, and their impacts on ecosystems. In this study, we use multiple endmember spectral mixture analysis (MESMA) to retrieve subpixel fire sizes and temperatures from MODIS, possibly overcoming some limitations of existing methods for characterizing fire intensities such as estimating the fire radiative power (FRP). MESMA is evaluated using data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to assess the performance of FRP and MESMA retrievals of fire properties from a simultaneously acquired MODIS image, for a complex of fires in Ukraine from August 21, 2002. The MESMA retrievals of fire size described in this paper show a slightly stronger correlation than FRP does to fire pixel counts from the coincident ASTER image. Prior to this work, few studies, if any, had used MESMA for retrieving fire properties from a broad-band sensor like MODIS, or compared MESMA to higher-resolution fire data or other measures of fire properties like FRP. In the future, MESMA retrievals could be useful for fire spread modeling and forecasting, reducing hazards that fires pose to property and health, and enhancing scientific understanding of fires and their effects on ecosystems and atmospheric composition.     

The influence of epiphylls on remote sensing of humid forests

Epiphylls - lichens, fungi, liverworts, etc. infesting leaf surfaces - are found throughout humid forests of the world. It is well understood that epiphylls inhibit light interception by host plants, but their effect on remote sensing of colonized forests has not been examined. Incorporating leaf-level spectra from Terra Firme (primary forest) and Amazonian Caatinga (woodlands/forest growing on nutrient-deficient sandy soils), we used the GeoSAIL model to propagate leaf-level measurements to the canopy level and determine their effect on commonly used vegetation indices. In Caatinga, moderate infestations (50% leaf area epiphyll cover), lowered simulated Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) values by 6.1% and 20.4%, respectively, largely due to near infrared dampening. Heavy infestation (100% cover) simulations exhibited decreases 1.5-2 times greater than those of moderate infestations. For Terra Firme, which are generally less affected by epiphylls, moderate (20% leaf area) and heavy infestations (40%) lowered EVI by 4.4% (S.D. 0.8%) and 8.1% (S.D. 1.5%), respectively. Near infrared and green reflectance were most affected at the canopy level, showing mean decreases of 10.6% (S.D. 2.25%) and 9.5% (S.D. 3.49%), respectively, in heavy Terra Firme infestations. Time series of Moderate Resolution Imaging Spectrometer (MODIS) data corroborated the modeling results, suggesting a degree of coupling between epiphyll cover and the EVI and NDVI. These results suggest that, without explicit consideration of the presence of epiphylls, remote sensing-based methodologies may underestimate leaf area index, biomass and productivity in humid forests.     

Second-Order Stiffness Matrix and Loading Vector of a Beam-Column with Semirigid Connections on an Elastic Foundation

The second-order stiffness matrix and corresponding loading vector of a prismatic beam–column subjected to a constant axial load and supported on a uniformly distributed elastic foundation (Winkler type) along its span with its ends connected to elastic supports are derived in a classical manner. The stiffness coefficients are expressed in terms of the ballast coefficient of the elastic foundation, applied axial load, support conditions, bending, and shear deformations. These individual parameters may be dropped when the appropriate effect is not considered; therefore, the proposed model captures all the different models of beams and beam–columns including those based on the theories of Bernoulli–Euler, Timoshenko, Rayleigh, and bending and shear.The expressions developed for the load vector are also general for any type or combinations of transverse loads including concentrated and partially nonuniform distributed loads. In addition, the transfer equations necessary to determine the transverse deflections, rotations, shear, and bending moments along the member are also developed and presented.     

Optimization of abrasive water jet cutting of ductile materials

Full factorial design of experiments was developed in order to investigate the effects of jet pressure, abrasive mixing rate, cutting feed, and plate thickness upon three response variables, surface finish of cutting wear zone, percentage proportion of striation free area, and maximum width of cut. The set of sixteen experiments was performed on each of the following two ductile materials: AISI 4340 (high strength low alloy steel, hardened to 49HRc) and Aluminum 2219. Analysis of Variance (ANOVA) was performed on experimental data in order to determine the significance of effects of different parameters on the performance measures. It was found that cutting feed and thickness were highly influential parameters, while abrasive mixing rate is influential upon surface roughness only. Strong interaction was found between jet pressure and workpiece material. Multi-criteria numerical optimization was performed in order to simultaneously maximize/minimize different combinations of performance measures.     

Crude oil aggregation by microscopy and dynamic light scattering

This research is focused on establishing a methodology to evaluate the aggregation state of Mexican crude oil solutions from two different sources and SARA compositions, by using Dynamic Light Scattering (DLS). Different crude oil concentrations were established and monitored through time in order to determine their effects on the aggregation state. DLS results indicate that the aggregation state of the studied solutions is influenced by crude oil composition, specifically by the amount of resins. Particle size and elemental analysis of the aggregates were performed by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX), respectively. Results from these techniques reveal particulated low-porosity smooth surfaces due to the presence of resin, as well as the determination of the characteristic elements found in asphaltenes. High-Resolution Transmission Electron Microscopy (HTEM) indicated the presence of asphaltene aggregates constituted by nanometric particles and asphaltene stacking as well as ultrafine nanocrystalline-oriented structures.     

Assessment of the bioavailability of toxic and non-toxic arsenic species in seafood samples

Bioavailability of total arsenic, toxic (arsenite, As(III); and arsenate, As(V)), and non-toxic (monomethylarsonic acid, MA; dimethylarsonic acid, DMA; arsenobetaine, AB; and arsenocholine, AC) arsenic species has been assessed in different raw seafood samples (white fish, cold water fish and molluscs) by using an in vitro model that combines simulated gastric and intestinal digestion/dialysis methods. Correlations between arsenic species bioavailability and seafood nutrient contents (fat and protein) have also been established. Total arsenic content in seafood samples, and dialyzable and non-dialyzable fractions, were analyzed by inductively coupled plasma – mass spectrometry (ICP–MS) after a microwave-assisted acid digestion treatment. The determination of the different arsenic species concentrations in the samples (after an optimised matrix solid phase dispersion (MSPD) approach) and in the dialyzable fraction was done by high performance liquid chromatography (HPLC) coupled to ICP-MS as a selective detector. Accuracy of the procedure (total arsenic determination) was assessed by analyzing DORM-2 and BCR-627 certified reference materials. The accuracy of the in vitro procedure was established through a mass-balance study. After statistical evaluation (95% confidence interval), good accuracy of the whole in vitro process, for total arsenic and for arsenic speciation, was observed. High dialyzability percentages for total arsenic and for arsenic species were found (i.e. from 84.6 ± 1.7% to 106 ± 2.6%). Bioavailability of arsenic exhibits a negative correlation with the fat content of the seafood. However, no correlation was observed between the bioavailable fraction of total arsenic and arsenic species and the protein content of the seafood studied.     

Parallel query execution over encrypted data in database-as-a-service (DaaS)

The Journal of Supercomputing - The main challenge in database-as-a-service is the security and privacy of data because service providers are not usually considered as trustworthy. So, the data...     

Process Capability Analysis for NonLinear Profiles Using Depth Functions

There are practical situations in which the quality of a process or product can be better characterized by a functional relationship between a response variable and one or more explanatory variables, which is called profile. Such profiles frequently can be represented adequately using linear or nonlinear models. While there are several studies in monitoring profiles, there are few studies to evaluate the capability of a process with profile quality characteristic; specifically, there is no method in the literature to analyze process capability characterized by nonlinear profiles. In this paper, we propose two methods to measure the capability of these processes, based on the concept of functional depth. These methods do not have distributional assumptions and extend to functional data the Process Capability Indexes proposed by Clements 1 to measure the capability of a process characterized by a random variable. Performance of the proposed methods is evaluated through simulation studies. An example illustrates the applicability of these methods. Copyright © 2013 John Wiley & Sons, Ltd.