The ectomycorrhizal fungus Pisolithus microcarpus encodes a microRNA involved in cross-kingdom gene silencing during symbiosis

Small RNAs (sRNAs) are known to regulate pathogenic plant–microbe interactions. Emerging evidence from the study of these model systems suggests that microRNAs (miRNAs) can be translocated between microbes and plants to facilitate symbiosis. The roles of sRNAs in mutualistic mycorrhizal fungal interactions, however, are largely unknown. In this study, we characterized miRNAs encoded by the ectomycorrhizal fungus Pisolithus microcarpus and investigated their expression during mutualistic interaction with Eucalyptus grandis. Using sRNA sequencing data and in situ miRNA detection, a novel fungal miRNA, Pmic_miR-8, was found to be transported into E. grandis roots after interaction with P. microcarpus. Further characterization experiments demonstrate that inhibition of Pmic_miR-8 negatively impacts the maintenance of mycorrhizal roots in E. grandis, while supplementation of Pmic_miR-8 led to deeper integration of the fungus into plant tissues. Target prediction and experimental testing suggest that Pmic_miR-8 may target the host NB-ARC domain containing transcripts, suggesting a potential role for this miRNA in subverting host signaling to stabilize the symbiotic interaction. Altogether, we provide evidence of previously undescribed cross-kingdom sRNA transfer from ectomycorrhizal fungi to plant roots, shedding light onto the involvement of miRNAs during the developmental process of mutualistic symbioses.

Green Interactive Installations as Conceptual Experiments towards a New Meaning of Smart Design

Nature-based design process with its embedded concept of form that follows function can be materialized as products capable of incorporating aesthetics and functionality similar to the characteristics of its natural role models. The paper addresses the topic of green installations created through a design process that simulates nature’s smart developmental mechanisms. The aim is to create an interactive installation capable of receiving and interpreting external factors that would determine the ensemble’s behavior and influence its future development and evolution. The main challenge lies in the fact that the smart feature is often achieved by intensive use of technology, which often overshadows inventive ways in which the behavioral and aesthetic properties of the material can be reinterpreted. The interactive green installation “Modgrew” investigates the possibilities of obtaining smart features through the experimental testing of two main types of configurations. The results underline the fact that, by applying the principles of biomimetic design, technologies from different fields can be combined towards obtaining a smart product. The conclusions highlight the need for future studies cover subjects such as the efficiency of automation, the possible reconfiguration of modules, behavioral optimization over time, the identification of minimal tech alternatives and the reduction of maintenance necessities.

Application of Cascade Forward Backpropagation Neural Networks for Selecting Mining Methods

Decision-making is very important in many fields, such as mining engineering. In addition, there has been a growth of computer applications in all fields, especially mining operations. One of these application fields is mine design and the selection of suitable mining methods, and computer applications can help mine engineers to decide upon and choose more satisfactory methods. The selection of mining methods depends on the rock-layer specification. All rock characteristics should be classified in terms of technical and economic concerns related to mining rock specifications, such as mechanical and physical properties, and evaluated according to their weights and ratings. Methodologically, in this study, the criteria considered in the University of British Columbia (UBC) method were used as references to establish general criteria. These criteria consist of general shape, ore thickness, ore plunge, and grade distribution, in addition to the rock quality designation (ore zone, hanging wall, and foot wall) and rock substance strength (ore zone, hanging wall, and foot wall). The technique for order of preference by similarity to ideal solution (TOPSIS) was adopted, and an improved TOPSIS method was developed based on experimental testing and checked by means of the application of cascade forward backpropagation neural networks in mining method selection. The results provide indicators that decision makers can use to choose between different mining methods based on the total points given to all ore properties. The best mining method is cut and fill stopping, with a rank of 0.70, and the second is top slicing, with a rank of 0.67.

An SMA cable-based negative stiffness seismic isolator: Development, experimental characterization, and numerical modeling

Shape memory alloy (SMA)-based seismic isolation systems can successfully reduce the peak and residual displacements of bridges during strong earthquake, but they commonly lead to an increased force demands in substructure. This study explores the development of an SMA cable-based negative stiffness isolator to alleviate this problem. The proposed isolator is composed of superelastic SMA cables and a frictional sliding bearing with convex surfaces. The frictional sliding bearing limit the forces transferred to the superstructure and provides energy dissipation, while its built-in negative stiffness mechanism reduces the force demands in substructure. SMA cables provide critical restoring forces, additional energy dissipation, and displacement-limiting capacity. Based on the force balance, the negative stiffness and restoring requirements of the SMA cable-based negative stiffness isolator were analyzed first. Then, a prototype large-scale isolator was designed and fabricated. Next, the experimental testing of the developed isolator was performed under two different vertical load levels. Finally, finite element modeling of the proposed isolator was conducted, and the simulation results and experimental results were compared and discussed. The proposed isolator generates lower forces than the SMA-based zero and positive stiffness isolators and can exhibit stable energy dissipation capabilities with very good displacement-limiting and self-centering capabilities.

Applications of Nano-Zeolite in Wastewater Treatment: An Overview

Nano-zeolite is an innovative class of materials that received recognition for its potential use in water and tertiary wastewater treatment. These applications include ion-exchange/sorption, photo-degradation, and membrane separation. The aim of this work is to summarize and analyze the current knowledge about the utilization of nano-zeolite in these applications, identify the gaps in this field, and highlight the challenges that face the wide scale applications of these materials. Within this context, an introduction to water quality, water and wastewater treatment, utilization of zeolite in contaminant removal from water was addressed and linked to its structure and the advances in zeolite preparation techniques were overviewed. To have insights into the trends of the scientific interest in this field, an in-depth analysis of the variation in annual research distribution over the last decade was performed for each application. This analysis covered the research that addressed the potential use of both zeolites and nano-zeolites. For each application, the characterization, experimental testing schemes, and theoretical analysis methodologies were overviewed. The results of the most advanced research were collected, summarized, and analyzed to allow an easy visualization and comparison of these research results. Finally, the gaps and challenges that face these applications are concluded.