Model and algorithm for computer-aided inventive problem analysis

The paper presents the research activity developed by the authors in the field of computer-aided inventive problem solving: an original model and a dialogue-based software application have been developed by integrating the logic of ARIZ (Algorithm for the Inventive Problem Solving) with some OTSM-TRIZ (General Theory of Powerful Thinking) models in order to guide a user also with no TRIZ education to the analysis of inventive problems. The paper demonstrates that through a dialogue-based interaction it is possible to guide the user towards a proper formulation of the problem statement, which is an essential step of any conceptual design activity. The proposed software system, although still at a prototype stage, has been tested with students at Politecnico di Milano and at the University of Florence. The paper details the structure of the algorithm and the results of the first validation activity; then, it discusses about the possibility to integrate the proposed approach into a new generation of CAD systems.     

Single-ion-conducting nanocomposite polymer electrolytes based on PEG400 and anionic nanoparticles: Part 2. Electrical characterization

Molecular relaxation and polarization phenomena of twelve single-ion-conducting nanocomposite polymer electrolytes (nCPEs) are studied using Broadband Electrical Spectroscopy (BES). The electrolytes are obtained by combining PEG400 oligomers with increasing amounts of anionic nanofiller comprised of fluorinated-TiO₂ associated with Li⁺ cations (LiFT^®), resulting in [PEG400/(LiFT)_y] systems with 0 ≤ y ≤ 26.4. This new class of [PEG400/(LiFT)_y] electrolytes allows us to achieve a significant single-ion conductivity (1.1·10⁻⁵ S cm⁻¹ at 30 °C for n_Li/n_O = 0.113) without the addition of lithium salts. To the best of our knowledge, this is the highest conductivity value reported for this class of electrolytes. This study, in conjunction with the results reported in Part 1, leads us to hypothesize a conduction mechanism in terms of two types of long-range charge-transfer processes. The first charge-transfer occurs at the interface between the filler nanoparticles and filler-PEG domains, while the second occurs through the PEG400 matrix with the assistance of polymer segmental motion. The measured Li⁺ transference numbers confirm that the studied materials are single-ion conductors.     

Caffeic Acid Enhances the Anti-Leukemic Effect of Imatinib on Chronic Myeloid Leukemia Cells and Triggers Apoptosis in Cells Sensitive and Resistant to Imatinib

Among the phenolic acids tested on the K562 cell line, a model of chronic myeloid leukemia (CML), caffeic acid (CA) was biologically active on sensitive and imatinib (IM)-resistant cells at micro-molar concentration, either in terms of reduction of cell proliferation or triggering of apoptosis. The CA treatment provoked mitochondrial membrane depolarization, genomic DNA fragmentation and phosphatidylserine exposure, hallmarks of apoptosis. Cell cycle analysis following the treatment with comparable cytotoxic concentrations of IM or CA showed marked differences in the distribution profiles. The reduction of cell proliferation by CA administration was associated with increased expression of two cell cycle repressor genes, CDKN1A and CHES1, while IM at a cytotoxic concentration increased the CHES1 but not the CDKN1A expression. In addition, CA treatment affected the proliferation and triggered the apoptosis in IM-resistant cells. Taken together, these data suggested that CA induced the anti-proliferative effect and triggered apoptosis of CML cells by a different mechanism than IM. Finally, the combined administration of IM and CA at suboptimal concentrations evidenced a synergy of action in determining the anti-proliferative effect and triggering apoptosis. The ability of CA to potentiate the anti-leukemic effect of IM highlighted the nutraceutical potential of CA in CML.     

Process noise covariance estimation via stochastic approximation

Kalman filtering for linear systems is known to provide the minimum variance estimation error, under the assumption that the model dynamics is known. While many system identification tools are available for computing the system matrices from experimental data, estimating the statistics of the output and process noises is still an open problem. Correlation-based approaches are very fast and sufficiently accurate, but there are typically restrictions on the number of noise covariance elements that can be estimated. On the other hand, maximum likelihood methods estimate all elements with high accuracy, but they are computationally expensive, and they require the use of external optimization solvers. In this paper, we propose an alternative solution, tailored for process noise covariance estimation and based on stochastic approximation and gradient-free optimization, that provides a good trade-off in terms of performance and computational load, and is also easy to implement. The effectiveness of the method as compared to the state of the art is shown on a number of recently proposed benchmark examples.     

Quantitative Measurements of the Critical Impeller Speed for Solid‐Liquid Suspensions

A quantitative methodology for particle suspension assessment is presented. A new parameter, f_mov/tot, the ratio of the mean number of moving particles to the total number of particles, is introduced to evaluate the minimum speed required to just suspend solids. This approach is tested to investigate the impact of impeller clearance on the minimum impeller speed, N_js, in a vessel when using a radial flow Rushton turbine. Flow patterns and power numbers obtained experimentally and computationally support the suspension findings. Image analysis is an appropriate method for determining N_js. Lowering the impeller clearance reduces the speed required for particle suspension with a change of flow pattern from a radial discharge with two loops to a single loop scouring the vessel base. The power number also falls markedly at the two‐to‐one loop transition as does the strain rate near the base.     

Anelastic reorganisation of fibre-reinforced biological tissues

In this work, we contribute to the study of the structural reorganisation of biological tissues in response to mechanical stimuli. We specialise our investigation to a class of hydrated soft tissues, whose internal structure features reinforcing fibres. These are oriented statistically within the tissue, and their pattern of orientation is such that, at each material point, the tissue is anisotropic. From its natural, stress-free state, the tissue can be distorted anelastically into a global reference configuration, and then deformed under the action of external mechanical loads. The anelastic distortions are responsible for changing irreversibly the internal structure of the tissue, which, in the present context, occurs through both the rearrangement of the bonds among the tissue cells and the deformation-driven reorientation of the fibres. The anelastic strains, in addition, are assumed to model the onset and evolution of microcracks in the tissue, which may be triggered by the mechanical loads applied to the tissue in the case of traumatic events, or diseases. For our purposes, we formulate an anisotropic model of remodelling and we consider a fully isotropic model of structural reorganisation for comparison, with the aim to study if, how, and to what extent the evolution of anelastic distortions is influenced by the tissue’s anisotropy.