Estimation of soil dispersivity using soft computing approaches

The accurate estimation of soil dispersivity (α) is required for characterizing the transport of contaminants in soil. The in situ measurement of α is costly and time-consuming. Hence, in this study, three soft computing methods, namely adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and gene expression programming (GEP), are used to estimate α from more readily measurable physical soil variables, including travel distance from source of pollutant (L), mean grain size (D ₅₀), soil bulk density (ρ _b), and contaminant velocity (V _c). Based on three statistical metrics [i.e., mean absolute error, root-mean-square error (RMSE), and coefficient of determination (R ²)], it is found that all approaches (ANN, ANFIS, and GEP) can accurately estimate α. Results also show that the ANN model (with RMSE = 0.00050 m and R ² = 0.977) performs better than the ANFIS model (with RMSE = 0.00062 m and R ² = 0.956), and the estimates from GEP are almost as accurate as those from ANFIS. The performance of ANN, ANFIS, and GEP models is also compared with the traditional multiple linear regression (MLR) method. The comparison indicates that all of the soft computing methods outperform the MLR model. Finally, the sensitivity analysis shows that the travel distance from source of pollution (L) and bulk density (ρ _b) have, respectively, the most and the least effect on the soil dispersivity.

     

Metal and Metal Oxide Electrocatalysts for Redox Flow Batteries

Redox flow batteries (RFBs) are one of the promising technologies for large‐scale energy storage applications. For practical implementation of RFBs, it is of great interest to improve their efficiency and reduce their cost. One of the key components of RFBs that can greatly influence the efficiency and final cost is the electrode. The chemical and structural nature of electrodes can modify the kinetics of redox reactions and the accessibility of the electroactive species to available active sites. The ideal electrocatalyst for RFBs must have good activity for the desirable redox reaction, provide a high surface area, and exhibit sufficient conductivity and durability over repeated use. One strategy is to coat the electrode with metal and metal oxide electrocatalysts. Metal electrocatalysts have the advantage of high conductivity, while metal oxide catalysts are usually less expensive and so more economically attractive. In order to gain a better understanding of the performance of the electrocatalysts in RFBs, a comprehensive review of the progress in the development of metal and metal oxide electrocatalysts for RFBs is provided and a critical comparison of the latest developments is presented. Finally, practical recommendations for advancement of electrocatalysts and effective transfer of knowledge in this field are provided.     

An Extremely Stable,Highly Soluble Monosubstituted Anthraquinone for Aqueous Redox Flow Batteries

An extremely stable, energy-dense (53.6 Ah L⁻¹, 2 m transferrable electrons), low crossover (permeability of <1 × 10⁻¹³ cm² s⁻¹ using Nafion 212 (Nafion is a trademark polymer from DuPont)), and potentially inexpensive anthraquinone with 2-2-propionate ether anthraquinone structure (abbreviated 2-2PEAQ) is synthesized and extensively evaluated under practically relevant conditions for use in the negolyte of an aqueous redox flow battery. 2-2PEAQ shows a high stability with a fade rate of 0.03–0.05% per day at different applied current densities, cut-off voltage windows, and concentrations (0.1 and 1.0 m ) in both a full cell paired with a ferro/ferricyanide posolyte as well as a symmetric cell. 2-2PEAQ is further shown to have extreme long-term stability, losing only ≈0.01% per day when an electrochemical rejuvenation strategy is employed. From post-mortem analysis (nuclear magnetic resonance (NMR), liquid chromatography–mass spectrometry (LC-MS), and cyclic voltammetry (CV)) two degradation mechanisms are deduced: side chain loss and anthrone formation. 2-2PEAQ with the ether linkages attached on carbons non-adjacent to the central ring is found to have three times lower fade rate compared to its isomer with ether linkages on the carbon adjacent to the central quinone ring. The present study introduces a viable negolyte candidate for grid-scale aqueous organic redox flow batteries.     

A review of predictive policing from the perspective of fairness

Machine Learning has become a popular tool in a variety of applications in criminal justice, including sentencing and policing. Media has brought attention to the possibility of predictive policing systems causing disparate impacts and exacerbating social injustices. However, there is little academic research on the importance of fairness in machine learning applications in policing. Although prior research has shown that machine learning models can handle some tasks efficiently, they are susceptible to replicating systemic bias of previous human decision-makers. While there is much research on fair machine learning in general, there is a need to investigate fair machine learning techniques as they pertain to the predictive policing. Therefore, we evaluate the existing publications in the field of fairness in machine learning and predictive policing to arrive at a set of standards for fair predictive policing. We also review the evaluations of ML applications in the area of criminal justice and potential techniques to improve these technologies going forward. We urge that the growing literature on fairness in ML be brought into conversation with the legal and social science concerns being raised about predictive policing. Lastly, in any area, including predictive policing, the pros and cons of the technology need to be evaluated holistically to determine whether and how the technology should be used in policing.

     

Deformation Rate-Adaptive Conducting Polymers and Composites

Materials are more easily damaged during accidents that involve rapid deformation. Here, a design strategy is described for electronic materials comprised of conducting polymers that defies this orthodox property, making their extensibility and toughness dynamically adaptive to deformation rates. This counterintuitive property is achieved through a morphology of interconnected nanoscopic core–shell micelles, where the chemical interactions are stronger within the shells than the cores. As a result, the interlinked shells retain material integrity under strain, while the rate of dissociation of the cores controls the extent of micelle elongation, which is a process that adapts to deformation rates. A prototype based on polyaniline shows a 7.5-fold increase in ultimate elongation and a 163-fold increase in toughness when deformed at increasing rates from 2.5 to 10 000% min⁻¹. This concept can be generalized to other conducting polymers and highly conductive composites to create “self-protective” soft electronic materials with enhanced durability under dynamic movement or deformation.     

Comparative study on the influence of surface characteristics on de-icing evaluation

Journal of Materials Science - A comparative study of de-icing evaluation methods was conducted in this work, and their variations in response to surface characteristics were investigated. The...     

Correction to: A review of predictive policing from the perspective of fairness

Artificial Intelligence and Law - An amendment to this paper has been published and can be accessed via a link at the top of the paper.     

Evaluation of antimicrobial activity of synthesised silver nanoparticles using Thymus kotschyanus aqueous extract

Development of a green chemistry process for the synthesis of silver nanoparticles (AgNPs) has become a focus of interest. Characteristics of AgNPs were determined using techniques, such as ultraviolet–visible spectroscopy (UV–vis), Fourier transform infrared (FTIR) analysis, scanning electron microscopy (SEM), energy‐dispersive X‐ray spectroscopy and X‐ray diffraction (XRD). The synthesised AgNPs using Thymus kotschyanus had the most growth inhibition against gram‐positive bacteria such as Staphylococcus aureus and Bacillus subtilise, while the growth inhibition of AgNPs at 1000–500 µg/ml occurred against Klebsiella pneumonia and at 1000–250 µg/ml of AgNPs was observed against E. coli. The UV–vis absorption spectra confirmed the formation of the AgNPs with the characteristic peak at 415 nm and SEM micrograph acknowledged spherical particles in a nanosize range. FTIR measured the possible biomolecules that are responsible for stabilisation of AgNPs. XRD analysis exhibited the crystalline nature of AgNPs and showed face‐centred cubic structure. The synthesised AgNPs revealed significant antibacterial activity against gram‐positive bacteria.Inspec keywords: visible spectra, microorganisms, ultraviolet spectra, biomedical materials, nanofabrication, nanoparticles, X‐ray diffraction, scanning electron microscopy, molecular biophysics, X‐ray chemical analysis, nanomedicine, silver, antibacterial activity, Fourier transform infrared spectraOther keywords: green chemistry process, ultraviolet–visible spectroscopy, gram‐positive bacteria, silver nanoparticles, Thymus kotschyanus aqueous extract, UV–vis spectroscopy, Fourier transform infrared spectroscopy, FTIR analysis, scanning electron microscopy, energy‐dispersive X‐ray spectroscopy, SEM micrograph, X‐ray diffraction, XRD, Staphylococcus aureus, Bacillus subtilise, Klebsiella pneumonia, E. coli, UV–vis absorption spectra, face‐centred cubic structure, antibacterial activity, antimicrobial activity, wavelength 415.0 nm, Ag