Polychromatic Dyeing

The history and development of the ICI polychromatic dyeing process are outlineed The basic mechanics of the process and the applicator and its essential principles are described. The factors governing the control and reproduction of patterns are described, together with dye-fixation procedures. Reference is made to several important applications of this coloration technique, which is also compared with conventional pad-dyeing and textile-printing methods.     

Effect of catalyst type on the kinetics of the photoelectrochemical disinfection of water inoculated with E. coli

The rates of the photoelectrochemical disinfection of Escherichia coli at TiO₂ electrodes were measured as a function of concentration and applied potential. Two different TiO₂ photoelectrodes were used: a thermally treated titanium plate and a porous film prepared by a sol–gel hydrolysis technique. The kinetics of the disinfection process were found to depend upon the nature of the electrode material. For the thermal film they were first order, and half order for the sol–gel film. It was also found that the catalytic activity per unit surface area of catalyst is many orders of magnitude greater than that observed using TiO₂ slurries; this was attributed to the reduced rate of electron-hole recombination afforded by the application of a small potential bias (1 V vs Ag/AgCl), and hence the exploitation of the electric field enhancement (EFE) effect.     

Effect of Resins on Asphaltene Self‐Association and Solubility

In previous studies, asphaltenes and resins have been treated as two distinct fractions of a crude oil. The asphaltenes were assumed to be the only self‐associating fraction. However, there is evidence that resins also participate in this self‐association. In this study, molar masses of mixtures of asphaltenes and resins were measured with vapour pressure osmometry. Precipitation from the same mixtures dispersed in solutions of toluene and pentane were also measured. The data were modelled with previously developed self‐association and precipitation models. Model results with asphaltenes and resins characterized as a single distribution and as individual components are compared. The data and the modelling suggest that asphaltenes and resins are better characterized as a single distribution of self‐associating components.     

Implementation of the quadrature method of moments in CFD codes for aggregation-breakage problems

In this work the quadrature method of moments (QMOM) is implemented in a commercial computational fluid dynamics (CFD) code (FLUENT) for modeling simultaneous aggregation and breakage. Turbulent and Brownian aggregation kernels are considered in combination with different breakage kernels (power law and exponential) and various daughter distribution functions (symmetric, erosion, uniform). CFD predictions are compared with experimental data taken from other work in the literature and conclusions about CPU time required for the simulations and the advantages of this approach are drawn.     

Adaptive augmented Lagrangian methods: algorithms and practical numerical experience

In this paper, we consider augmented Lagrangian (AL) algorithms for solving large-scale nonlinear optimization problems that execute adaptive strategies for updating the penalty parameter. Our work is motivated by the recently proposed adaptive AL trust region method by Curtis et al. [An adaptive augmented Lagrangian method for large-scale constrained optimization, Math. Program. 152 (2015), pp. 201–245.]. The first focal point of this paper is a new variant of the approach that employs a line search rather than a trust region strategy, where a critical algorithmic feature for the line search strategy is the use of convexified piecewise quadratic models of the AL function for computing the search directions. We prove global convergence guarantees for our line search algorithm that are on par with those for the previously proposed trust region method. A second focal point of this paper is the practical performance of the line search and trust region algorithm variants in Matlab software, as well as that of an adaptive penalty parameter updating strategy incorporated into the Lancelot software. We test these methods on problems from the CUTEst and COPS collections, as well as on challenging test problems related to optimal power flow. Our numerical experience suggests that the adaptive algorithms outperform traditional AL methods in terms of efficiency and reliability. As with traditional AL algorithms, the adaptive methods are matrix-free and thus represent a viable option for solving large-scale problems.     

Subroutine based detection of APT malware

Statistical detection of mass malware has been shown to be highly successful. However, this type of malware is less interesting to cyber security officers of larger organizations, who are more concerned with detecting malware indicative of a targeted attack. Here we investigate the potential of statistically based approaches to detect such malware using a malware family associated with a large number of targeted network intrusions. Our approach is complementary to the bulk of statistical based malware classifiers, which are typically based on measures of overall similarity between executable files. One problem with this approach is that a malicious executable that shares some, but limited, functionality with known malware is likely to be misclassified as benign. Here a new approach to malware classification is introduced that classifies programs based on their similarity with known malware subroutines. It is illustrated that malware and benign programs can share a substantial amount of code, implying that classification should be based on malicious subroutines that occur infrequently, or not at all in benign programs. Various approaches to accomplishing this task are investigated, and a particularly simple approach appears the most effective. This approach simply computes the fraction of subroutines of a program that are similar to malware subroutines whose likes have not been found in a larger benign set. If this fraction exceeds around 1.5 %, the corresponding program can be classified as malicious at a 1 in 1000 false alarm rate. It is further shown that combining a local and overall similarity based approach can lead to considerably better prediction due to the relatively low correlation of their predictions.     

Evaluating the species energy relationship with the newest measures of ecosystem energy: NDVI versus MODIS primary production

Ecosystem energy has been shown to be a strong correlate with biological diversity at continental scales. Early efforts to characterize this association used the normalized difference vegetation index (NDVI) to represent ecosystem energy. While this spectral vegetation index covaries with measures of ecosystem energy such as net primary production, the covariation is known to degrade in areas of very low vegetation or in areas of dense forest. Two of the new vegetation products from the MODIS sensor, derived by integrating spectral reflectance, climate data, and land cover, are thought to better approximate primary productivity than NDVI. In this study, we determine if the new MODIS derived measures of primary production, gross primary productivity (GPP) and net primary productivity (NPP) better explain variation in bird richness than historically used NDVI. Moreover, we evaluate if the two productivity measures covary more strongly with bird diversity in those vegetation conditions where limitations of NDVI are well recognized.Biodiversity was represented as native landbird species richness derived from the North American Breeding Bird Survey. Analyses included correlation analyses among predictor variables, and univariate regression analyses between each predictor variable and bird species richness. Analyses were done at two levels: for all BBS routes across natural landscapes in North America; and for routes in 10 vegetation classes stratified by vegetated cover along a gradient from bare ground to herbaceous cover to tree cover. We found that NDVI, GPP and NPP were highly correlated and explained similar variation in bird species richness when analyzed for all samples across North America. However, when samples were stratified by vegetated cover, strength of correlation between NDVI and both productivity measures was low for samples with bare ground and for dense forest. The NDVI also explained substantially less variation in bird species richness than the primary production in areas with more bare ground and in areas of dense forest. We conclude that MODIS productivity measures have higher utility in studies of the relationship of species richness and productivity and that MODIS GPP and NPP improve on NDVI, especially for studies with large variation in vegetated cover and density.     

Runtime support for scalable programming in Java

The paper research is concerned with enabling parallel, high-performance computation—in particular development of scientific software in the network-aware programming language, Java. Traditionally, this kind of computing was done in Fortran. Arguably, Fortran is becoming a marginalized language, with limited economic incentive for vendors to produce modern development environments, optimizing compilers for new hardware, or other kinds of associated software expected of by today’s programmers. Hence, Java looks like a very promising alternative for the future. The paper will discuss in detail a particular environment called HPJava. HPJava is the environment for parallel programming—especially data-parallel scientific programming—in Java. Our HPJava is based around a small set of language extensions designed to support parallel computation with distributed arrays, plus a set of communication libraries. A high-level communication API, Adlib, is developed as an application level communication library suitable for our HPJava. This communication library supports collective operations on distributed arrays. We include Java Object as one of the Adlib communication data types. So we fully support communication of intrinsic Java types, including primitive types, and Java object types.