Feasibility Study of a Thick-Film PZT Resonant Pressure Sensor Made on a PreFired 3D LTCC Structure

This paper discusses the feasibility of a piezoelectric resonant pressure sensor made of lead–zirconate–titanate (PZT) thick films on a preprocessed 3D low-temperature co-fired ceramic structure with a deformable diaphragm. Numerical and experimental analyses were carried out. Two different thick-film PZT compositions were characterized. Using experimentally evaluated material properties, a finite-element analysis showed the trends and facilitated the decisions in the design phase of the sensor.     

Low temperature fast-neutron and gamma irradiation of glass fiber-epoxy composite. Part 2: Structure and chemistry

Structure and chemistry of S2-glass fiber-epoxy composite to fast-neutron and gamma irradiation at 4.2 K have been studied. Fast-neutron fluence ranged from 0.9 × 10²² to 1 × 10²³ n/m². At the neutron fluence of 3.1 × 10²² n/m², ordering of the amorphous S2-glass structure intervened. Ordering was followed by partial crystallization at the neutron fluence of 1 × 10²³ n/m². Although the epoxy matrix retained its amorphous structure, reactor irradiation induced crosslink formation and hydrogen evolution. These processes became significant at neutron fluences equal to or higher than 1.8 × 10²² n/m². No evidence has been found for hydrogen bubble or void nucleation at the glass-epoxy interface at the neutron fluence of 3.1 × 10²² n/m². Futhermore, sharp compositional changes measured at the glass-epoxy interface preclude an extended irradiation-induced atom mixing at this neutron fluence.     

Laccase-initiated reaction between phenolic acids and chitosan

Phenolic acids are known to possess antioxidant activities whilst chitosan is a biocompatible polymer with antibacterial activity against a broad spectrum of bacteria. Merging both types of molecules could therefore provide several potential applications. In this work, antioxidant properties of phenolic acid–functionalized-chitosan were investigated after being prepared from structurally-different phenolic acids (caffeic and gallic acids) and chitosan using the laccase from Trametes versicolor as the reaction initiator. A laccase-mediated oxidation kinetic of phenolic acids was monitored by UV–vis spectroscopy and cyclic voltammetry, as well as spin-trapping electron paramagnetic resonance spectroscopy (ST-EPR). The pH was shown to have a significant effect on the degree of phenolic acid self-polymerization, indicating the involvement of phenolate anions within the formations of coupled polyphenol products, and their functionalities, i.e. antioxidant activity. All the phenolic acid-functionalized-chitosans displayed greatly improved ABTS radical cation scavenging capacities, compared with the untreated chitosan.     

Prediction of Chronic Inflammation for Inhaled Particles: the Impact of Material Cycling and Quarantining in the Lung Epithelium

On a daily basis, people are exposed to a multitude of health-hazardous airborne particulate matter with notable deposition in the fragile alveolar region of the lungs. Hence, there is a great need for identification and prediction of material-associated diseases, currently hindered due to the lack of in-depth understanding of causal relationships, in particular between acute exposures and chronic symptoms. By applying advanced microscopies and omics to in vitro and in vivo systems, together with in silico molecular modeling, it is determined herein that the long-lasting response to a single exposure can originate from the interplay between the newly discovered nanomaterial quarantining and nanomaterial cycling between different lung cell types. This new insight finally allows prediction of the spectrum of lung inflammation associated with materials of interest using only in vitro measurements and in silico modeling, potentially relating outcomes to material properties for a large number of materials, and thus boosting safe-by-design-based material development. Because of its profound implications for animal-free predictive toxicology, this work paves the way to a more efficient and hazard-free introduction of numerous new advanced materials into our lives.     

Population size reduction for the differential evolution algorithm

This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.     

Relative survival analysis in R

Relative survival techniques are used to compare the survival experience in a study cohort with the one expected should they follow the background population mortality rates. The techniques are especially useful when the cause-specific death information is not accurate or not available since they provide a measure of excess mortality in a group of patients with a certain disease. There are several approaches to modeling relative survival, but there is no widely used statistical package that would incorporate the relevant techniques. The existing software was mostly written by the authors of different methods, in different computer languages and with different requirements for the data input, which makes it almost impossible for a user to choose between available models. We describe our R package relsurv that provides functions for easy and flexible fitting of several relative survival regression models.     

Flow through packed bed reactors: 1. Single-phase flow

Single-phase pressure drop was studied in a region of flow rates that is of particular interest to trickle bed reactors . Bed packings were made of uniformly sized spherical and non-spherical particles (cylinders, rings, trilobes, and quadralobes). Particles were packed by means of two methods: random close or dense packing (RCP) and random loose packing (RLP) obtaining bed porosities in the range of 0.37–0.52. It is shown that wall effects on pressure drop are negligible as long as the column-to-particle diameter ratio is above 10. Furthermore, the capillary model approach such as the Ergun equation is proven to be a sufficient approximation for typical values of bed porosities encountered in packed bed reactors. However, it is demonstrated that the original Ergun equation is only able to accurately predict the pressure drop of single-phase flow over spherical particles, whereas it systematically under predicts the pressure drop of single-phase flow over non-spherical particles. Special features of differently shaped non-spherical particles have been taken into account through phenomenological and empirical analyses in order to correct/upgrade the original Ergun equation. With the proposed upgraded Ergun equation one is able to predict single-phase pressure drop in a packed bed of arbitrary shaped particles to within ±10% on average. This approach has been shown to be far superior to any other available at this time.     

An Edit-Distance Model for the Approximate Matching of Timed Strings

An edit-distance model that can be used for the approximate matching of contiguous and non-contiguous timed strings is presented. The model extends the concept of the weighted string-edit distance by introducing timed edit operations and by making the edit costs time dependent. Special attention is paid to the timed null symbols that are associated with the timed insertions and deletions. The usefulness of the presented model is demonstrated on the classification of phone-recognition errors using the TIMIT speech database.     

The Polaron: Ground State, Excited States, and Far from Equilibrium

We describe a variational approach for solving the Holstein polaron model with dynamical quantum phonons on an infinite lattice. The method is simple, fast, extremely accurate, and gives ground and excited state energies and wavefunctions at any momentum k. The method can also be used to calculate coherent quantum dynamics for inelastic tunneling and for strongly driven polarons far from equilibrium.     

Comparative Analysis of System Dynamics and Object-Oriented Bayesian Networks Modelling for Water Systems Management

This paper presents a comparative analysis of System Dynamics Modelling (SDM) and Object-Oriented Bayesian Networks (OOBN). Both techniques are extensively used for water resources modelling due to their flexibility, effectiveness in assessing different management options, ease of operation and suitability for encouraging stakeholder involvement. Conversely, both approaches have several important differences that make them complementary. For example, while SDM is more suitable for simulating the feedback dynamics of processes, OOBN modelling is a powerful tool for modelling systems with uncertain inputs (or outputs) characterised by probability distributions. This comparative analysis is applied to the Kairouan aquifer system, Tunisia, where the aquifer plays an essential role for socio-economic development in the region. Both models produced comparable results using baseline data, and show their complementarity through a suite of scenario tests. It is shown that reducing pumping of groundwater to coastal cities may prove the key to reducing the current aquifer deficit, though local demand reduction must be considered to preserve the agricultural economy. It is suggested that water management assessment should be tackled using both approaches to complement each other, adding depth and insight, and giving a more coherent picture of the problem being addressed, allowing for robust policy decisions to be made.