An inverse problem for estimation of bending stiffness in Kirchhoff–Love plates

This work deals with the development of a numerical method for solving an inverse problem for bending stiffness estimation in a Kirchhoff–Love plate from overdetermined data. The coefficient is identified using a technique called the Method of Variational Imbedding, where the original inverse problem is replaced by a minimization problem. The Euler–Lagrange equations for minimization comprise higher-order equations for the solution of the displacement and an equation for the bending stiffness. The correctness of the embedded problem is discussed. A difference scheme and a numerical algorithm for solving the parameter identification problem are developed. Numerical results for the obtained values of the bending stiffness as an inverse problem are presented.     

Proteases to Improve the Mechanical Characteristics of Durable Press Finished Cotton Fabrics

N‐Methylol reagents are conventional crosslinking agents that are still widely used in textile industry to produce crease‐resistant cotton fabrics. In this work serine proteases were used to recover the strength of fabrics, cross‐linked with N‐hydroxymethylacrylamide. Nearly one half of the strength loss of crosslinked cotton fabrics could be restored after protease treatment, while the wrinkle recovery angle (WRA) decreased only slightly. The enzymatic hydrolysis of the amide cross‐links in the durable pressed cellulose was confirmed by FT‐IR analysis and dyeability with an acid dye.

Effect of protease concentration on the tensile strength recovery, WRA and acid dye dyeability at 30 min reaction time.     

Nutritional Management of Thyroiditis of Hashimoto

Since the thyroid gland is one of the organs most affected by autoimmune processes, many patients with thyroiditis of Hashimoto (TH) seek medical advice on lifestyle variance and dietary modifications to improve and maintain their hyroid function. In this review, we aim to present and discuss some challenges associated with the nutritional management of TH, focusing on environmental and dietary deficits, inflammatory and toxic nutrients, cyanotoxins, etc. We discuss the relationships among different diets, chronic inflammation, and microbiota, and their impact on the development and exacerbation of TH in detail. We share some novel insights into the role of vitamin D and melatonin for preserving thyroid function during chronic inflammation in autoimmune predisposed subjects. A comprehensive overview is provided on anti-inflammatory nutrients and ecological diets, including foods for cleansing and detoxification, which represent strategies to prevent relapses and achieve overall improvement of life quality. In conclusion, data from biomedical and clinical studies provide evidence that an appropriate dietary and lighting regimen could significantly improve the function of the thyroid gland and reduce the reactivity of autoantibodies in TH. Compliance with nutritional guidelines may help TH patients to reduce the need for medicines.     

Integrated eco-design decision-making for sustainable product development

This paper presents an integrated eco-design decision-making (IEDM) methodology that is formed using three stages: life cycle assessment, an eco-design process (Eco-Process) model and an enhanced eco-design quality function deployment process. All product sustainability considerations are conducted within a special eco-design house of quality. This brings together the analysis of factors relating to manufacturing processes, product usage and end-of-life strategy. The concentration of environmental considerations in one place insures that product sustainability is central to any design development and that the implications of change are fully identified and justified. The IEDM methodology utilises of a set of Eco-Process parameters and their associated relationships to allow users with complementary knowledge to enter and access information in a timely and controlled manner. They are then able to contribute their expertise to support decisions with the aim of providing more sustainable products. An application of the approach is presented in the context of a case study considering the redesign of a single-use medical forceps. The materials and production methods used are investigated with a view to quantifying their environmental impact. The resulting IEDM methodology can be seen to be widely and easily applicable.     

Identification of solitary-wave solutions as an inverse problem: Application to shapes with oscillatory tails

The propagation of stationary solitary waves on an infinite elastic rod on elastic foundation equation is considered. The asymptotic boundary conditions admit the trivial solution along with the solution of type of solitary wave, which is a bifurcation problem.     

Facet-Dependent Intrinsic Activity of Single Co3O4 Nanoparticles for Oxygen Evolution Reaction

Deciphering the influence of nanocatalyst morphology on their catalytic activity in the oxygen evolution reaction (OER), the limiting reaction in water splitting process, is essential to develop highly active precious metal-free catalysts, yet poorly understood. The intrinsic OER activity of Co₃O₄ nanocubes and spheroids is probed at the single particle level to unravel the correlation between exposed facets, (001) vs. (111), and activity. Single cubes with predominant (001) facets show higher activity than multi-faceted spheroids. Density functional theory calculations of different terminations and reaction sites at (001) and (111) surfaces confirm the higher activity of the former, expressed in lower overpotentials. This is rationalized by a change in the active site from octahedral to tetrahedral Co and the potential-determining step from *OH to *O for the cases with lowest overpotentials at the (001) and (111) surfaces, respectively. This approach enables the identification of highly active facets to guide shape-selective syntheses of improved metal oxide nanocatalysts for water oxidation.     

Feature Interaction Maximisation

Feature selection plays an important role in classification algorithms. It is particularly useful in dimensionality reduction for selecting features with high discriminative power. This paper introduces a new feature-selection method called Feature Interaction Maximisation (FIM), which employs three-way interaction information as a measure of feature redundancy. It uses a forward greedy search to select features which have maximum interaction information with the features already selected, and which provide maximum relevance. The experiments conducted to verify the performance of the proposed method use three datasets from the UCI repository. The method is compared with four other well-known feature-selection methods: Information Gain (IG), Minimum Redundancy Maximum Relevance (mRMR), Double Input Symmetrical Relevance (DISR), and Interaction Gain Based Feature Selection (IGFS). The average classification accuracy of two classifiers, Naïve Bayes and K-nearest neighbour, is used to assess the performance of the new feature-selection method. The results show that FIM outperforms the other methods.     

Rock Salt Ni/Co Oxides with Unusual Nanoscale‐Stabilized Composition as Water Splitting Electrocatalysts

The influence of nanoscale on the formation of metastable phases is an important aspect of nanostructuring that can lead to the discovery of unusual material compositions. Here, the synthesis, structural characterization, and electrochemical performance of Ni/Co mixed oxide nanocrystals in the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is reported and the influence of nanoscaling on their composition and solubility range is investigated. Using a solvothermal synthesis in tert ‐butanol ultrasmall crystalline and highly dispersible Ni _x Co_{1? x} O nanoparticles with rock salt type structure are obtained. The mixed oxides feature non‐equilibrium phases with unusual miscibility in the whole composition range, which is attributed to a stabilizing effect of the nanoscale combined with kinetic control of particle formation. Substitutional incorporation of Co and Ni atoms into the rock salt lattice has a remarkable effect on the formal potentials of NiO oxidation that shift continuously to lower values with increasing Co content. This can be related to a monotonic reduction of the work function of (001) and (111)‐oriented surfaces with an increase in Co content, as obtained from density functional theory (DFT+U) calculations. Furthermore, the electrocatalytic performance of the Ni _x Co_{1? x} O nanoparticles in water splitting changes significantly. OER activity continuously increases with increasing Ni contents, while HER activity shows an opposite trend, increasing for higher Co contents. The high electrocatalytic activity and tunable performance of the nonequilibrium Ni _x Co_{1? x} O nanoparticles in HER and OER demonstrate great potential in the design of electrocatalysts for overall water splitting.     

Knowledge acquisition techniques for feature recognition in CAD models

Automatic Feature Recognition (AFR) techniques are an important tool for achieving a true integration of design and manufacturing stages during the product development. In particular, AFR systems offer capabilities for recognising high-level geometrical entities, features, in Computer-Aided Design (CAD) models. However, the recognition performances of most of the existing AFR systems are limited to the requirements of specific applications. This paper presents automatic knowledge acquisition techniques to support the development of AFR systems that could be deployed in different application domains. In particular, a method to generate automatically feature recognition rules is proposed. These rules are formed by applying an inductive learning algorithm on training data consisting of feature examples. In addition, a technique for defining automatically feature hints from such rule sets is described. The knowledge acquisition techniques presented in this study are implemented within a prototype feature recognition system and its capabilities are verified on two benchmarking parts.