An extended minimax disparity to determine the OWA operator weights

This paper contributes to extend the minimax disparity to determine the ordered weighted averaging (OWA) model based on linear programming. It introduces the minimax disparity approach between any distinct pairs of the weights and uses the duality of linear programming to prove the feasibility of the extended OWA operator weights model. The paper finishes with an open problem. © 2006 Elsevier Ltd. All rights reserved.

Zero weights and non-zero slacks:different solution to the same problem

This paper re-assesses three independently developed approaches that are aimed at solving the problem of zero-weights or non-zero slacks in Data Envelopment Analysis (DEA). The methods are weights restricted, non-radial and extended facet DEA models. Weights restricted DEA models are dual to envelopment DEA models with restrictions on the dual variables (DEA weights) aimed at avoiding zero values for those weights; non-radial DEA models are envelopment models which avoid non-zero slacks in the input-output constraints. Finally, extended facet DEA models recognize that only projections on facets of full dimension correspond to well defined rates of substitution/transformation between all inputs/outputs which in turn correspond to non-zero weights in the multiplier version of the DEA model. We demonstrate how these methods are equivalent, not only in their aim but also in the solutions they yield. In addition, we show that the aforementioned methods modify the production frontier by extending existing facets or creating unobserved facets. Further we propose a new approach that uses weight restrictions to extend existing facets. This approach has some advantages in computational terms, because extended facet models normally make use of mixed integer programming models, which are computationally demanding.

Structure and dynamics of multiple cationic vectors-siRNA complexation by all-atomic molecular dynamics simulations

Understanding the molecular mechanism of gene condensation is a key component to rationalizing gene delivery phenomena, including functional properties such as the stability of the gene-vector complex and the intracellular release of the gene. In this work, we adopt an atomistic molecular dynamics simulation approach to study the complexation of short strand duplex RNA with four cationic carrier systems of varying charge and surface topology at different charge ratios. At lower charge ratios, polymers bind quite effectively to siRNA, while at high charge ratios, the complexes are saturated and there are free polymers that are unable to associate with RNA. We also observed reduced fluctuations in RNA structures when complexed with multiple polymers in solution as compared to both free siRNA in water and the single polymer complexes. These novel simulations provide a much better understanding of key mechanistic aspects of gene-polycation complexation and thereby advance progress toward rational design of nonviral gene delivery systems.

Determining more realistic OWA weights

The concept of ordered weighted averaging (OWA) operator weights arises in uncertain decision making problems, however some weights may have a specific relationship with other. This information about the weights can be obtained from decision makers (DMs). This paper intends to introduce a theory of weight restrictions into the existing OWA operator weight models. Based on the DMs' value judgment the obtained OWA operator weights could be more realistic.

A method for automatically eliciting node weights in a hierarchical knowledge-based structure for reasoning with uncertainty

Hierarchical knowledge structures are frequently used within clinical decision support systems as part of the model for generating intelligent advice. The nodes in the hierarchy inevitably have varying influence on the decisionmaking processes, which needs to be reflected by parameters. If the model has been elicited from human experts, it is not feasible to ask them to estimate the parameters because there will be so many in even moderately-sized structures. This paper describes how the parameters could be obtained from data instead, using only a small number of cases. The original method [1] is applied to a particular web-based clinical decision support system called GRiST, which uses its hierarchical knowledge to quantify the risks associated with mental-health problems. The knowledge was elicited from multidisciplinary mental-health practitioners but the tree has several thousand nodes, all requiring an estimation of their relative influence on the assessment process. The method described in the paper shows how they can be obtained from about 200 cases instead. It greatly reduces the experts’ elicitation tasks and has the potential for being generalised to similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.

Atomic structure of the two intermediate phase glasses SiSe4 and GeSe4

The microscopic origin of the intermediate phase in two prototypical covalently bonded AxB1-x network glass forming systems, where A=Ge or Si, B=Se, and 0=x=1, was investigated by combining neutron diffraction with first-principles molecular-dynamics methods. Specifically, the structure of glassy GeSe4 and SiSe4 was examined, and the calculated total structure factor and total pair-correlation function for both materials are in good agreement with experiment. The structure of both glasses differs markedly from a simple model comprising undefective AB4 corner-sharing tetrahedra in which all A atoms are linked by B2 dimers. Instead, edge-sharing tetrahedra occur and the twofold coordinated Se atoms form three distinct structural motifs, namely, Se-Se2, Se-SeGe (or Se-SeSi), and Se-Ge2 (or Se-Si2). This identifies several of the conformations that are responsible for the structural variability in GexSe1-x and SixSe1-x glasses, a quantity that is linked to the finite width of the intermediate phase window.

A new fuzzy additive model for determining the common set of weights in Data Envelopment Analysis

The main advantage of Data Envelopment Analysis (DEA) is that it does not require any priori weights for inputs and outputs and allows individual DMUs to evaluate their efficiencies with the input and output weights that are only most favorable weights for calculating their efficiency. It can be argued that if DMUs are experiencing similar circumstances, then the pricing of inputs and outputs should apply uniformly across all DMUs. That is using of different weights for DMUs makes their efficiencies unable to be compared and not possible to rank them on the same basis. This is a significant drawback of DEA; however literature observed many solutions including the use of common set of weights (CSW). Besides, the conventional DEA methods require accurate measurement of both the inputs and outputs; however, crisp input and output data may not relevant be available in real world applications. This paper develops a new model for the calculation of CSW in fuzzy environments using fuzzy DEA. Further, a numerical example is used to show the validity and efficacy of the proposed model and to compare the results with previous models available in the literature.

Evolving weights for a new United Kingdom Divisia

Divisia money is a monetary aggregate that gives each component asset an assigned weight. We use an evolutionary neural network to calculate new Divisia weights for each component utilising the Bank of England monetary data for the U.K. We propose a new monetary aggregate using our newly derived weights to carry out quantitative inflation prediction. The results show that this new monetary aggregate has better inflation forecasting performance than the traditionally constructed Bank of England Divisa money. This result is important for monetary policymakers, as improved construction of monetary aggregates will yield tighter relationships between key macroeconomic variables and ultimately, greater macroeconomic control. Research is ongoing to establish the extent of the increased information content and parameter stability of this new monetary aggregate.

A molecular dynamics model of the atomic structure of dysprosium alumino-phosphate glass

Molecular dynamics (MD) has been used to identify the relative distribution of dysprosium in the phosphate glass DyAl0.30P3.05O9.62. The MD model has been compared directly with experimental data obtained from neutron diffraction to enable a detailed comparison beyond the total structure factor level. The MD simulation gives Dy ... Dy correlations at 3.80(5) and 6.40(5) angstrom with relative coordination numbers of 0.8(1) and 7.3(5), thus providing evidence of minority rare-earth clustering within these glasses. The nearest neighbour Dy-O peak occurs at 2.30 angstrom with each Dy atom having on average 5.8 nearest neighbour oxygen atoms. The MD simulation is consistent with the phosphate network model based on interlinked PO4 tetrahedra where the addition of network modifiers Dy3+ depolymerizes the phosphate network through the breakage of P-(O)-P bonds whilst leaving the tetrahedral units intact. The role of aluminium within the network has been taken into explicit account, and A1 is found to be predominantly (78 tetrahedrally coordinated. In fact all four A1 bonds are found to be to P (via an oxygen atom) with negligible amounts of Al-O-Dy bonds present. This provides an important insight into the role of Al additives in improving the mechanical properties of these glasses.

Analysis of powder caking in multicomponent powders using atomic force microscopy to examine particle properties

Atomic force microscopy has been used to study the surface properties of model spray dried powders. Phase imaging, nanoindentation and force modulation microscopy have differentiated between the different surface material properties of the particles, revealing a regular dispersion of soft, oil rich areas distributed across the particles' surface. Humidity and temperature cycling effects on the caking behavior of the particles have also been investigated, with significant morphology changes and onset of caking found to occur within relatively short periods of time.

The use of atomic force microscopy in investigating particle caking mechanisms

Spray-dried materials are being used increasingly in industries such as food, detergent and pharmaceutical manufacture. Spray-dried sodium carbonate is an important product that has a great propensity to cake; its moisture-sorption properties are very different to the crystalline and amorphous species, with a great affinity for atmospheric moisture. This work demonstrates how the noncontact surface analysis of individual particles using atomic force microscopy can highlight the possible mechanisms of unwanted agglomeration. The nondestructive nature of this method allows cycling of localised humidity in situ and repeated scanning of the same particle area. The resulting topography and phase scans showed that humidity cycling caused changes in the distribution of material phases that were not solely dependent on topographical changes. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving minimax disparity model to determine the OWA operator weights

Determining the Ordered Weighted Averaging (OWA) operator weights is important in decision making applications. Several approaches have been proposed in the literature to obtain the associated weights. This paper provides an alternative disparity model to identify the OWA operator weights. The proposed mathematical model extends the existing disparity approaches by minimizing the sum of the deviation between two distinct OWA weights. The proposed disparity model can be used for a preference ranking aggregation. A numerical example in preference ranking and an application in search engines prove the usefulness of the generated OWA weights.