Evaluations of corporate sustainability indicators based on fuzzy similarity graphs

The paper deals with inconsistencies of composite sustainability indicators and their different subsets (economic, environmental, social, and corporate governance). Corporate sustainability performance is usually highly nonlinear, vague, partially inconsistent and multidimensional. The resulting models are often oversimplified. The key reason is an information shortage which eliminates the unsophisticated applications of classical statistical methods. Numbers are accurate and information intensive. Verbal quantifications are less accurate and therefore not that information intensive. Fuzzy sets and fuzzy reasoning are used to make verbal quantifiers suitable for computer applications. A fuzzy similarity graph is defined. A team of experts identified 17 relevant variables (e.g. Environmental costs, Occupational diseases, Number of complaints received from stakeholders) and 12 company data sets are available. Each company is presented as a fuzzy conditional statement. A set of fuzzy pairwise similarities is generated and used to evaluate five similarity graphs: a Total Graph (based on all 17 variables) and graphs based on relevant specific subsets of variables, Economic, Environmental, Social and Corporate Governance graphs. The topologies of these graphs are significantly different. No prior knowledge of fuzzy reasoning is required.     

Evolution and similarity evaluation of protein structures in contact map space

Prediction of fold from amino acid sequence of a protein has been an active area of research in the past few years, but the limited accuracy of existing techniques emphasizes the need to develop newer approaches to tackle this task. In this study, we use contact map prediction as an intermediate step in fold prediction from sequence. Contact map is a reduced graph-theoretic representation of proteins that models the local and global inter-residue contacts in the structure. We start with a population of random contact maps for the protein sequence and "evolve" the population to a "high-feasibility" configuration using a genetic algorithm. A neural network is employed to assess the feasibility of contact maps based on their 4 physically relevant properties. We also introduce 5 parameters, based on algebraic graph theory and physical considerations, that can be used to judge the structural similarity between proteins through contact maps. To predict the fold of a given amino acid sequence, we predict a contact map that will sufficiently approximate the structure of the corresponding protein. Then we assess the similarity of this contact map with the representative contact map of each fold; the fold that corresponds to the closest match is our predicted fold for the input sequence. We have found that our feasibility measure is able to differentiate between feasible and infeasible contact maps. Further, this novel approach is able to predict the folds from sequences significantly better than a random predictor.     

A graph spectral analysis of the structural similarity network of protein chains

We present a simple method for the analysis of large networks based on their graph spectral properties. One of the advantages of this method is that it uses a single numerical computation to identify subclusters in a connected graph, which can significantly simplify the complexity involved in analyzing large graphs. This is illustrated using a network of protein chains constructed on the basis of their structural similarities. The large-scale network properties and the cluster and subcluster organization of the protein chain network are presented. We summarize the results of structural and functional analyses of the nodes present in these clusters and elucidate the implications of structural similarity in the protein chain universe.     

Ancestral processes for non-neutral models of complex diseases

We consider non-neutral models for unlinked loci, where the fitness of a chromosome or individual is not multiplicative across loci. Such models are suitable for many complex diseases, where there are gene-interactions. We derive a genealogical process for such models, called the complex selection graph (CSG). This coalescent-type process is related to the ancestral selection graph, and is derived from the ancestral influence graph by considering the limit as the recombination rate between loci gets large. We analyse the CSG both theoretically and via simulation. The main results are that the gene-interactions do not produce linkage disequilibrium, but do produce dependencies in allele frequencies between loci. For small selection rates, the distributions of the genealogy and the allele frequencies at a single locus are well-approximated by their distributions under a single locus model, where the fitness of each allele is the average of the true fitnesses of that allele with respect to the distribution of alleles at other loci.     

A Theoretical Graph Method for Search and Analysis of Critical Phenomena in Biochemical Systems. II. Kinetic Models of Biochemical Oscillators Including Two and Three Substances

Four kinetic models of hypothetical complex reactions containing minimal two-substance or three-substance oscillators were constructed on the basis of the graphical rules suggested in the preceding work. The kinetic models are thought to be a part of one of four general biochemical systems: 1) system of mutual protein phosphorylation/dephosphorylation; 2) autophosphorylation of multisubunit protein; 3) association/dissociation of proteins or protein-containing structures during protein–protein or protein–ligand interaction; and 4) two-substrate enzymatic reaction with substrate inhibition by one substrate. Graphical rules of oscillator association with surrounding medium were considered. The graphical criteria of the oscillation generator elimination and criteria of oscillation damping were obtained. Both damped and undamped oscillations of reaction components were obtained by numerical integration of the mathematical models of these reactions. The areas of changes of model parameters and variables, within which the oscillations exist, were found.     

Experimental design for gene expression microarrays

We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.     

Feeding behaviour of the Asiatic citrus psyllid,Diaphorina citri,on healthy and huanglongbing‐infected citrus

Diaphorina citri Kuwayama (Hemiptera: Sternorrhyncha: Psyllidae) is a vector of huanglongbing, a disease of citrus that in Asia is caused by ‘Candidatus Liberibacter asiaticus’ (α‐Proteobacteria) (Las). Acquisition of Las by D. citri appears to be variable, and this variability may be due to the suitability of the host plants and their tissues for acquisition. Therefore, this study aimed to determine the effect of symptom severity of the disease on the feeding behaviour of D. citri. Use of an electrical penetration graph showed that the pathway phase of D. citri consisted of four waveforms, A, B, C, and D; waveforms A and B have not been reported for D. citri before. The remaining waveforms, E1, E2, and G, conform to those described before for D. citri. The duration of the non‐penetration period did not differ between healthy or infected plants. However, in moderately and severely symptomatic plants, the duration of the pathway phase increased, whereas the phloem phase was shorter. In all diseased plants, the times to first and sustained salivation in the phloem were longer than those in control plants, with the times being related to symptom severity. As symptom expression increased, the percentage of time spent by psyllids salivating during the phloem phase increased; however, the percentage of time spent in phloem activities reduced gradually from ca. 74% in the control plants to ca. 8% in the severely symptomatic plants. In contrast, the percentage of time spent on xylem activities increased, as did the proportion of psyllids feeding from xylem. The differences in the durations of the E waveforms on plants showing different levels of symptom expression may account for differences in acquisition found amongst studies; therefore, future work on the acquisition and transmission of Las needs to carefully document symptom expression.