Time complexity analysis of the stochastic diffusion search

The Stochastic Diffusion Search algorithm -an integral part of Stochastic Search Networks is investigated. Stochastic Diffusion Search is an alternative solution for invariant pattern recognition and focus of attention. It has been shown that the algorithm can be modelled as an ergodic, finite state Markov Chain under some non-restrictive assumptions. Sub-linear time complexity for some settings of parameters has been formulated and proved. Some properties of the algorithm are then characterised and numerical examples illustrating some features of the algorithm are presented.

Designing flexible procurement systems

The systems used for the procurement of buildings are organizational systems. They involve people in a series of strategic decisions, and a pattern of roles, responsibilities and relationships that combine to form the organizational structure of the project. To ensure effectiveness of the building team, this organizational structure needs to be contingent upon the environment within which the construction project takes place. In addition, a changing environment means that the organizational structure within a project needs to be responsive, and dynamic. These needs are often not satisfied in the construction industry, due to the lack of analytical tools with which to analyse the environment and to design appropriate temporary organizations. This paper presents two techniques. First is the technique of "Environmental Complexity Analysis", which identifies the key variables in the environment of the construction project. These are classified as Financial, Legal, Technological, Aesthetic and Policy. It is proposed that their identification will set the parameters within which the project has to be managed. This provides a basis for the project managers to define the relevant set of decision points that will be required for the project. The Environmental Complexity Analysis also identifies the project's requirements for control systems concerning Budget, Contractual, Functional, Quality and Time control. The process of environmental scanning needs to be done at regular points during the procurement process to ensure that the organizational structure is adaptive to the changing environment. The second technique introduced is the technique of "3R analysis", being a graphical technique for describing and modelling Roles, Responsibilities and Relationships. A list of steps is introduced that explains the procedure recommended for setting up a flexible organizational structure that is responsive to the environment of the project. This is by contrast with the current trend towards predetermined procurement paths that may not always be in the best interests of the client.

Independent component analysis of climate data: A new look at EOF rotation

The complexity inherent in climate data makes it necessary to introduce more than one statistical tool to the researcher to gain insight into the climate system. Empirical orthogonal function (EOF) analysis is one of the most widely used methods to analyze weather/climate modes of variability and to reduce the dimensionality of the system. Simple structure rotation of EOFs can enhance interpretability of the obtained patterns but cannot provide anything more than temporal uncorrelatedness. In this paper, an alternative rotation method based on independent component analysis (ICA) is considered. The ICA is viewed here as a method of EOF rotation. Starting from an initial EOF solution rather than rotating the loadings toward simplicity, ICA seeks a rotation matrix that maximizes the independence between the components in the time domain. If the underlying climate signals have an independent forcing, one can expect to find loadings with interpretable patterns whose time coefficients have properties that go beyond simple noncorrelation observed in EOFs. The methodology is presented and an application to monthly means sea level pressure (SLP) field is discussed. Among the rotated (to independence) EOFs, the North Atlantic Oscillation (NAO) pattern, an Arctic Oscillation–like pattern, and a Scandinavian-like pattern have been identified. There is the suggestion that the NAO is an intrinsic mode of variability independent of the Pacific.

GC/multiple collector-ICPMS method for chlorine stable isotope analysis of chlorinated aliphatic hydrocarbons

Stable isotopic characterization of chlorine in chlorinated aliphatic pollution is potentially very valuable for risk assessment and monitoring remediation or natural attenuation. The approach has been underused because of the complexity of analysis and the time it takes. We have developed a new method that eliminates sample preparation. Gas chromatography produces individually eluted sample peaks for analysis. The He carrier gas is mixed with Ar and introduced directly into the torch of a multicollector ICPMS. The MC-ICPMS is run at a high mass resolution of >= 10 000 to eliminate interference of mass 37 ArH with Cl. The standardization approach is similar to that for continuous flow stable isotope analysis in which sample and reference materials are measured successively. We have measured PCE relative to a laboratory TCE standard mixed with the sample. Solvent samples of 200 nmol to 1.3 mu mol ( 24- 165 mu g of Cl) were measured. The PCE gave the same value relative to the TCE as measured by the conventional method with a precision of 0.12% ( 2 x standard error) but poorer precision for the smaller samples.

An analysis of the management of a public sector project: a systems-based case study

The management of a public sector project is analysed using a model developed from systems theory. Linear responsibility analysis is used to identify the primary and key decision structure of the project and to generate quantitative data regarding differentiation and integration of the operating system, the managing system and the client/project team. The environmental context of the project is identified. Conclusions are drawn regarding the project organization structure's ability to cope with the prevailing environmental conditions. It is found that the complexity of the managing system imposed on the project was unable to achieve this and created serious deficiencies in the outcome of the project.

The influence of project complexity on estimating accuracy

With the rapid development in technology over recent years, construction, in common with many areas of industry, has become increasingly complex. It would, therefore, seem to be important to develop and extend the understanding of complexity so that industry in general and in this case the construction industry can work with greater accuracy and efficiency to provide clients with a better service. This paper aims to generate a definition of complexity and a method for its measurement in order to assess its influence upon the accuracy of the quantity surveying profession in UK new build office construction. Quantitative data came from an analysis of twenty projects of varying size and value and qualitative data came from interviews with professional quantity surveyors. The findings highlight the difficulty in defining and measuring project complexity. The correlation between accuracy and complexity was not straightforward, being subjected to many extraneous variables, particularly the impact of project size. Further research is required to develop a better measure of complexity. This is in order to improve the response of quantity surveyors, so that an appropriate level of effort can be applied to individual projects, permitting greater accuracy and enabling better resource planning within the profession.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes. Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes, Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Subspace system identification framework for the analysis of multimoded propagation of THz-transient signals

We provide a system identification framework for the analysis of THz-transient data. The subspace identification algorithm for both deterministic and stochastic systems is used to model the time-domain responses of structures under broadband excitation. Structures with additional time delays can be modelled within the state-space framework using additional state variables. We compare the numerical stability of the commonly used least-squares ARX models to that of the subspace N4SID algorithm by using examples of fourth-order and eighth-order systems under pulse and chirp excitation conditions. These models correspond to structures having two and four modes simultaneously propagating respectively. We show that chirp excitation combined with the subspace identification algorithm can provide a better identification of the underlying mode dynamics than the ARX model does as the complexity of the system increases. The use of an identified state-space model for mode demixing, upon transformation to a decoupled realization form is illustrated. Applications of state-space models and the N4SID algorithm to THz transient spectroscopy as well as to optical systems are highlighted.

Thermodynamic analysis of snowball Earth hysteresis experiment: Efficiency, entropy production and irreversibility

We present an extensive thermodynamic analysis of a hysteresis experiment performed on a simplified yet Earth-like climate model. We slowly vary the solar constant by 20% around the present value and detect that for a large range of values of the solar constant the realization of snowball or of regular climate conditions depends on the history of the system. Using recent results on the global climate thermodynamics, we show that the two regimes feature radically different properties. The efficiency of the climate machine monotonically increases with decreasing solar constant in present climate conditions, whereas the opposite takes place in snowball conditions. Instead, entropy production is monotonically increasing with the solar constant in both branches of climate conditions, and its value is about four times larger in the warm branch than in the corresponding cold state. Finally, the degree of irreversibility of the system, measured as the fraction of excess entropy production due to irreversible heat transport processes, is much higher in the warm climate conditions, with an explosive growth in the upper range of the considered values of solar constants. Whereas in the cold climate regime a dominating role is played by changes in the meridional albedo contrast, in the warm climate regime changes in the intensity of latent heat fluxes are crucial for determining the observed properties. This substantiates the importance of addressing correctly the variations of the hydrological cycle in a changing climate. An interpretation of the climate transitions at the tipping points based upon macro-scale thermodynamic properties is also proposed. Our results support the adoption of a new generation of diagnostic tools based on the second law of thermodynamics for auditing climate models and outline a set of parametrizations to be used in conceptual and intermediate-complexity models or for the reconstruction of the past climate conditions. Copyright © 2010 Royal Meteorological Society

Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

Resource allocation analysis of the stochastic diffusion search

The Stochastic Diffusion Search (SDS) was developed as a solution to the best-fit search problem. Thus, as a special case it is capable of solving the transform invariant pattern recognition problem. SDS is efficient and, although inherently probabilistic, produces very reliable solutions in widely ranging search conditions. However, to date a systematic formal investigation of its properties has not been carried out. This thesis addresses this problem. The thesis reports results pertaining to the global convergence of SDS as well as characterising its time complexity. However, the main emphasis of the work, reports on the resource allocation aspect of the Stochastic Diffusion Search operations. The thesis introduces a novel model of the algorithm, generalising an Ehrenfest Urn Model from statistical physics. This approach makes it possible to obtain a thorough characterisation of the response of the algorithm in terms of the parameters describing the search conditions in case of a unique best-fit pattern in the search space. This model is further generalised in order to account for different search conditions: two solutions in the search space and search for a unique solution in a noisy search space. Also an approximate solution in the case of two alternative solutions is proposed and compared with predictions of the extended Ehrenfest Urn model. The analysis performed enabled a quantitative characterisation of the Stochastic Diffusion Search in terms of exploration and exploitation of the search space. It appeared that SDS is biased towards the latter mode of operation. This novel perspective on the Stochastic Diffusion Search lead to an investigation of extensions of the standard SDS, which would strike a different balance between these two modes of search space processing. Thus, two novel algorithms were derived from the standard Stochastic Diffusion Search, ‘context-free’ and ‘context-sensitive’ SDS, and their properties were analysed with respect to resource allocation. It appeared that they shared some of the desired features of their predecessor but also possessed some properties not present in the classic SDS. The theory developed in the thesis was illustrated throughout with carefully chosen simulations of a best-fit search for a string pattern, a simple but representative domain, enabling careful control of search conditions.

Deciphering the complexity of sainfoin (Onobrychis viciifolia) proanthocyanidins by MALDI-TOF mass spectrometry with a judicious choice of isotope patterns and matrixes

Use of superdihydroxybenzoic acid as the matrix enabled the analysis of highly complex mixtures of proanthocyanidins from sainfoin (Onobrychis viciifolia) by MALDI-TOF mass spectrometry. Proanthocyanidins contained predominantly B-type homopolymers and heteropolymers up to 12- mers (3400 Da). Use of another matrix, 2,6-dihydroxyacetophenone, revealed the presence of A-type glycosylated dimers. In addition, we report here how a comparison of the isotopic adduct patterns, which resulted from Li and Na salts as MALDI matrix additives, could be used to confirm the presence of A-type linkages in complex proanthocyanidin mixtures. Preliminary evidence suggested the presence of A-type dimers in glycosylated prodelphinidins and in tetrameric procyanidins and prodelphinidins.

Evolutionary analysis of novel serine proteases in the venom gland transcriptome of Bitis gabonica rhinoceros

Background: Serine proteases are major components of viper venom and target various stages of the blood coagulation system in victims and prey. A better understanding of the diversity of serine proteases and other enzymes present in snake venom will help to understand how the complexity of snake venom has evolved and will aid the development of novel therapeutics for treating snake bites. Methodology and Principal Findings: Four serine protease-encoding genes from the venom gland transcriptome of Bitis gabonica rhinoceros were amplified and sequenced. Mass spectrometry suggests the four enzymes corresponding to these genes are present in the venom of B. g. rhinoceros. Two of the enzymes, rhinocerases 2 and 3 have substitutions to two of the serine protease catalytic triad residues and are thus unlikely to be catalytically active, though they may have evolved other toxic functions. The other two enzymes, rhinocerases 4 and 5, have classical serine protease catalytic triad residues and thus are likely to be catalytically active, however they have glycine rather than the more typical aspartic acid at the base of the primary specificity pocket (position 189). Based on a detailed analysis of these sequences we suggest that alternative splicing together with individual amino acid mutations may have been involved in their evolution. Changes within amino acid segments which were previously proposed to undergo accelerated change in venom serine proteases have also been observed. Conclusions and Significance: Our study provides further insight into the diversity of serine protease isoforms present within snake venom and discusses their possible functions and how they may have evolved. These multiple serine protease isoforms with different substrate specificities may enhance the envenomation effects and help the snake to adapt to new habitats and diets. Our findings have potential for helping the future development of improved therapeutics for snake bites.