Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

Rate equation theory for the hydrogenation kinetics of Mg-based materials

A uniform solid product layer normally assumed in the shrinking-core model cannot predict the kinetic transition behavior of the H₂ adsorption reactions. In this study, the concept of a uniform solid product layer has been replaced by that of the inward growth of solid products on the solid surface. A rate equation is established to calculate the inward growth of the solid product and was implemented into the shrinking-core model to calculate the H₂ adsorption kinetics for various shapes of Mg-based materials. The prediction accuracy of the developed model is verified from the detailed experimental data. To account for the external gas diffusion around the particle and the intraparticle gas diffusion, an analytical equation is derived using the Thiele modulus method. This model can be used to analyze various kinetic aspects and to analyze the effect of change in the particle microstructure on intraparticle diffusion.     

Deacylation of Calcium-Dependent Antibiotics from Streptomyces violaceoruber in Co-culture with Streptomyces sp. MG7-G1

When Streptomyces violaceoruber grows together with Streptomyces sp. MG7-G1, it reacts with strongly induced droplet production on its aerial mycelium. Initially the metabolite profile of droplets from S. violaceoruber in co-culture with Streptomyces sp. MG7-G1 was compared to samples from S. violaceoruber in single-culture by using high-performance liquid chromatography-mass spectrometry (HPLC-MS). Then, the exudate from agar plates of co-cultures and single cultures (after freezing and thawing) was also analysed. Several compounds were only observed when S. violaceoruber was grown in co-culture. Based on their high-resolution ESI mass spectra and their comparable retention times to the calcium-dependent antibiotics (CDAs) produced by S. violaceoruber, the new compounds were suspected to be deacylated calcium-dependent antibiotics (daCDAs), lacking the 2,3-epoxyhexanoyl residue of CDAs. This was verified by detailed analysis of the MS/MS spectra of the daCDAs in comparison to the CDAs. The major CDA compounds present in calcium ion-supplemented agar medium of co-cultures were daCDAs, thus suggesting that Streptomyces sp. MG7-G1 expresses a deacylase that degrades CDAs.     

Remote Steering of Self‐Propelling Microcircuits by Modulated Electric Field

The principles and design of “active” self‐propelling particles that can convert energy, move directionally on their own, and perform a certain function is an emerging multidisciplinary research field, with high potential for future technologies. A simple and effective technique is presented for on‐demand steering of self‐propelling microdiodes that move electroosmotically on water surface, while supplied with energy by an external alternating (AC) field. It is demonstrated how one can control remotely the direction of diode locomotion by electronically modifying the applied AC signal. The swimming diodes change their direction of motion when a wave asymmetry (equivalent to a DC offset) is introduced into the signal. The data analysis shows that the ability to control and reverse the direction of motion is a result of the electrostatic torque between the asymmetrically polarized diodes and the ionic charges redistributed in the vessel. This novel principle of electrical signal‐coded steering of active functional devices, such as diodes and microcircuits, can find applications in motile sensors, MEMs, and microrobotics.     

Enhance cycling performance of LiMn2O4 cathode by Sr2+ and Cr3+ doping

Spinel LiSr_0·1Cr_0·1Mn_1·8O₄ was synthesised by high temperature solid state method in order to enhance the electrochemical performance. The LiSr_0·1Cr_0·1Mn_1·8O₄ (LSCMO) materials were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical tests. The XRD and SEM studies confirm that LSCMO had spinel crystal structure with a space group of Fd3m, and the particle of LSCMO shows irregular shape. The cyclic voltammetry data illustrated that the heavy current charge–discharge performance of LMO was improved by Sr²⁺ and Cr³⁺ doping. The galvanostatic charge–discharge of LSCMO cathode materials was measured at 1, 5, 10 and 20 C. The results indicated that LSCMO improved the capacity retention.     

Raman and X-ray photoelectron spectroscopy study on the influence of La2O3 on the melt structure of SiO2–CaO–Al2O3–MgO

In order to gain more insights into the influence of rare earth elements on the melt structure of SiO₂–CaO–Al₂O₃–MgO glass ceramics, Raman and X-ray photoelectron spectroscopy techniques were used to study the influence of La₂O₃ on the Si–O/Al–O tetrahedron structure within SiO₂–CaO–Al₂O₃–MgO–quenched glass samples in this study. Results showed that some Raman peak shapes at low frequencies (200–840 cm^?1) changed significantly after the addition of La₂O₃, compared to the high frequency (840–1200 cm^?1) region that corresponds to the [SiO₄] structure, suggesting that the depolymerization of the low-frequency T–O–T (T=Si or Al) structure was more prevalent with La³⁺ addition. Besides, the depolymerization extent of the Si–O/Al–O tetrahedral network varied when the melt composition altered. Most notably, depolymerization is the most significant at a low CaO/SiO₂ ratio (0.25) and a high Al₂O₃ content (8%). Meanwhile, La³⁺ can promote the transformation of Si–O–Si and Al–O–Al bonds to the Si–O–Al ones, thereby forming a complex ionic cluster network interwoven with Si–O and Al–O tetrahedrons.     

Epos – an instrument for the assessment of the ethical position in software development

Digital technology becomes more powerful, intelligent, pervasive and ubiquitous. Ethical aspects of this development have not yet drawn the appropriate attention of researchers and engineers. This paper presents an instrument that aims at measuring the individual ethical position with regard to the design and development of computer software. The development of the Epos tool was based on two data collections. The data of the first survey (n₁ = 147 participants) were used to select items and to determine the factorial structure of the questionnaire. Results show that the Epos instrument reliably assesses peoples’ ethical opinion with respect to five central components: (1) regulation, (2) data privacy, (3) domain specific knowledge, (4) societal responsibility and (5) company responsibility. In the second survey, we determined the stability of the instruments factor structure by assessing a sample of n₂?=?196 participants. A confirmatory factor analysis (CFA) supported the initial factor structure. Next steps and further implications are discussed regarding the final version of the questionnaire.     

A Complexing Agent to Enable a Wide-Temperature Range Bromine-Based Flow Battery for Stationary Energy Storage

Bromine-based flow batteries (Br-FBs) are considered one of the most promising energy storage systems due to their features of high energy density and low cost. However, they generally suffer from uncontrolled diffusion of corrosive bromine particularly at high temperatures. That is because the interaction between polybromide anions and the commonly used complexing agent (N–methyl–N–ethyl–pyrrolidinium bromide [MEP]) decreases with increasing temperatures, which causes serious self-discharge and capacity fade. Herein, a novel bromine complexing agent, 1–ethyl–2–methyl–pyridinium bromide (BCA), is introduced in Br-FBs to solve the above problems. It is proven that BCA can combine with polybromide anions very well even at a high temperature of 60 °C. Moreover, the BCA contributes to decreasing the electrochemical polarization of Br⁻/Br₂ couple, which in turn improves their power density. As a result, a zinc–bromine flow battery with BCA as the complexing agent can achieve a high energy efficiency of 84% at 40 mA cm⁻², even at high temperature of 60 °C and it can stably run for more than 400 cycles without obvious performance decay. This paper provides an effective complexing agent to enable a wide temperature range Br-FB.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.