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To reduce the computational complexity per step from O(n²) to O(n) for optimization based on quadratic surrogates, where n is the number of design variables.

Applying nonlinear optimization strategies directly to complex multidisciplinary systems can be prohibitively expensive when the complexity of the simulation codes is large. Increasingly, response surface approximations (RSAs), and specifically quadratic approximations, are being integrated with nonlinear optimizers in order to reduce the CPU time required for the optimization of complex multidisciplinary systems. For evaluation by the optimizer, RSAs provide a computationally inexpensive lower fidelity representation of the system performance. The curse of dimensionality is a major drawback in the implementation of these approximations as the amount of required data grows quadratically with the number n of design variables in the problem. In this paper a novel technique to reduce the magnitude of the sampling from O(n²) to O(n) is presented.

The technique uses prior information to approximate the eigenvectors of the Hessian matrix of the RSA and only requires the eigenvalues to be computed by response surface techniques. The technique is implemented in a sequential approximate optimization algorithm and applied to engineering problems of variable size and characteristics. Results demonstrate that a reduction in the data required per step from O(n²) to O(n) points can be accomplished without significantly compromising the performance of the optimization algorithm.

A reduction in the time (number of system analyses) required per step from O(n²) to O(n) is significant, even more so as n increases. The novelty lies in how only O(n) system analyses can be used to approximate a Hessian matrix whose estimation normally requires O(n²) system analyses.

This paper's objective is to investigate consumers' and producers' expectations towards geographical indications (GIs) in a German context, where this certification scheme has not been widely used so far.

Data for the consumer side were obtained by a structured questionnaire. A total of 741 consumers were asked online with respect to their knowledge and expectations towards geographical indications in general and Hessian apple wine in particular. The collected data were analysed by an explorative factor analysis and a binary logit model. Additionally, data for the producer side were collected via an in‐depth interview with one major producer of Hessian apple wine.

The consumer side results indicate that Hessian consumers' awareness and knowledge about GIs is very limited. Moreover, it is found that the quality warranty dimension is not as important as the economic support dimension and perceived authenticity of the product. A hypothetical willingness to pay for protection is mainly driven by consumer perceptions and expectations towards the positive impacts of geographical indications on the local economy. The producer side results highlight that the most important motivation to apply for a protected G1 (PGI) is to secure the established reputation against misuse by competing producers in order to ensure the quality level of Hessian apple wine.

The findings indicate that a PGI is by no means a self‐runner. The positive impacts of this certification scheme have to be communicated to consumers in order to be successful.

Empirical evidence regarding consumers' knowledge and expectations towards geographical indications in a non‐Mediterranean context is limited. The present paper contributes to the existing literature by providing empirical evidence for a German case study.

The purpose of this study is to enhance the functional properties of Hessian fabric through resin finishing. Hessian bags made of lignocellulosic jute fiber are commonly used to pack, store and transport agro-commodities, including horticultural crops such as rice, potato, onion and wheat. However, because of high water affinity, these bags undergo degradation in properties due to moisture release by the stored commodities themselves. Exposure to natural elements, e.g. rain and dew, also causes moisture absorption in hessian bags. Once the bag gets moistened, degradation of jute bags starts due to microbial attack, leading to loss in tensile strength and change in extensibility, leading to ultimate breakage in warp and weft directions of the fabric.

To overcome the degradation in the functional properties of hessian fabric due to exposure to moisture and microbial attack, the application of semi-synthetic polymeric materials was carried out.

Tenacity, bursting strength, puncture resistance, tear strength and breaking load, as well as life cycle of resin-treated jute fabric was found to be better than control jute.

To the best of the authors’ knowledge, no recent reports of resin finishing on jute (hessian) fabric with semi-synthetic resins are presently available, other than coating with rubber.

The purpose of the paper is to explore the structural feasibility of substituting traditional thick joint mortars with earth slurry mortars modified with varying amounts of sand. Thin jointing of earth blocks would reduce the cost of sustainable earth construction.

Compressive strength of earth‐block cubes was determined. Flexural strength was measured using the BRE electronic bond wrench, which enables block couplets to be tested quickly and accurately. Three samples of earth block, one from southwest England and two from East Anglia, together with nine examples of earth slurry mortar jointing were studied, including the effect of reinforcing the joint and or the block using hessian.

The 28‐day cube characteristic compressive strengths were determined for Appley soil, Norfolk lump and Beeston soil, the last with 0 per cent sand, 25 per cent sand and with 25 per cent sand with hessian. The flexural strengths of Appley and Beeston earth slurries were determined, along with Thermalite thin jointed cement and cement mortar for comparison. The Beeston soil flexural strength increased with increasing sand content. Earth slurry with 40 per cent sand and hessian present in the joint gave the greatest strength. It is important to use blocks and slurry mortars of the same soil. Extruded and compressed earth blocks are best suited to slurry jointing.

This work successfully demonstrates the structural feasibility of carefully reducing the thickness of earth mortars when constructing sustainable earth block walling. Characteristic flexural strengths are suggested where the test results were sufficiently consistent, and of a magnitude likely to be useful in design.

This paper begins by framing the concept of historical agency as a complex relationship between structural forces and individual actions. We then describe general features of historical fiction and consider ways of using this type of text in classrooms. Using the concept of historical agency, we examine three historical fiction texts for upper elementary or middle level readers (Roll of Thunder, Hear My Cry, The Fighting Ground, and Dragon's Gate). The analysis reveals the similarities and differences in the ways the authors construct historical agency. The paper concludes with a set of four key questions that teachers and students can apply to historical fiction to help students refigure the ways in which they construct knowledge about the past.

Using duality theory, we give a simple mathematical proof of some well‐known theorems of international trade theory. The two‐sector production model is described by a joint cost function from which the standard comparative statics results can be derived with little difficulty: all that is basically needed is the inversion of a Hessian matrix. This representation of the technology emphasises the importance of the assumption of non‐joint production, and it is useful for generalisation to many goods and factors, for treatment of intermediate products, and for empirical implementation.

To propose a new algorithmic platform (minlp_machine) for complex mixed‐integer non‐linear programming (MINLP) problems.

The platform combines features from classical non‐linear optimization methodology with novel innovations in computational techniques. The system constructs discrete search zones around non‐integer discrete‐valued variables of local solutions, which reduces the search process significantly. In complicated problems fast feasibility restoration is achieved through concentrated Hessians. The system is programmed in strict ANSI C and can be run either stand alone or as a support library for other programs. File I/O is designed to recognize possible usage in both single and parallel processor environments.

The system has been tested on Alpha and Sun mainframes and – as a support library for a Genetic Hybrid Algorithm (GHA()) – in Linux and IBM parallel supercomputer environments. The constrained problem can, for example, be solved through a sequence of first order Taylor approximations of the non‐linear constraints and occasional feasibility restoration through Hessian information of the Lagrangian of the MINLP problem, or by invoking a nonlinear solver like SQP directly in the branch and bound tree. The system has been successfully tested on a small sample of representative continuous‐valued non‐linear programming problems.

It is demonstrated that – through zone‐constrained search – minlp_machine() outperforms some recent competing approaches with respect to the number of nodes in the branch and bound tree.

The purpose of this paper is the introduction of a globally convergent algorithm into a framework for global derivative‐free optimization, such as particle swarm optimization (PSO) for which a full proof of convergence is currently missing.

The substitution of the classical PSO iteration by the Newton method is suggested when the global minimum is not improved. Use of surrogate models for the computation of the Hessian of the objective function is a key point for the overall computational effort. Adoption of a trust‐region approach guarantees the consistency of the present approach with the original formulation.

The approach proposed is mostly found to be an improvement of the classical PSO method. The use of surrogate models and the trust‐region approach maintains the overall computational effort at the same level as the original algorithm.

Although the number of algebraic test functions is pretty large, a single practical example is provided. Further numerical experiments are needed in order to increase the generality of the conclusions.

The proposed method improves the efficiency of the standard PSO algorithm.

Previous literature does not provide comprehensive systematic studies for coupling PSO with local search algorithms. This paper is a contribution for closing the gap.

This article examines the history, development, and application of the sandwich estimate of variance. In describing this estimator, we pay attention to applications that have appeared in the literature and examine the nature of the problems for which this estimator is used. We describe various adjustments to the estimate for use with small samples, and illustrate the estimator’s construction for a variety of models. Finally, we discuss interpretation of results.