A critical assessment and summary on the low carbon energy pile technologies based on the life-cycle perspective: Challenges and prospects

Energy piles, a technology integrating the heat exchange component within building pile foundations for shallow geothermal energy utilization, have proven economically efficient. They outperform conventional ground source heat pumps by mitigating additional borehole costs and space requirements. This paper systematically examines low-carbon...

Self-assembly of ammonium assimilation microbiomes regulated by COD/N ratio

Marine microorganisms have an inherent advantage in the treatment of saline wastewater due to their halophilic properties. Ammonium assimilation is the most important and common nitrogen conversion pathway in the ocean, which means that it may be a suitable nitrogen removal strategy under high salinity conditions. However, the targeted...

Integrating the flow regime and water quality effects into a niche-based metacommunity dynamics model for river ecosystems

Aquatic community dynamics are closely dominated by flow regime and water quality conditions, which are increasingly threatened by dam regulation, water diversion, and nutrition pollution. However, further understanding of the ecological impacts of flow regime and water quality conditions on aquatic multi-population dynamics has rarely been...

A Flow Graph-Based Scalable Critical Branch Identification Approach for AC State Estimation Under Load Redistribution Attacks

This article offers a novel perspective on identifying the critical branches under load redistribution (LR) attacks. Compared to the existing literature that is largely disruption-driven and based on dc state estimation, we propose to address the threat from LR attacks on a more fundamental level by modeling and analyzing the circulation of...

Thickness-Independent Capacitive Performance of Holey Ti₃C₂T_x Film Prepared through a Mild Oxidation Strategy

The Ti₃C₂T_x film with metallic conductivity and high pseudo-capacitance holds profound promise in flexible high-rate supercapacitors. However, the restacking of Ti₃C₂T_x sheets hinders ion access to thick film electrodes. Herein, a mild yet green route has been developed to...

Temperature-sensing performance of polymer-derived SiAlCN ceramics up to 1000 °C

Temperature sensors that can operate in high-temperature and harsh environments are highly desired. However, this is a great challenge for sensing materials to operate under extreme working conditions because of oxidation and/or corrosion at high temperature. In this study, polymer-derived SiAlCN ceramics were prepared as sensing materials to...

Ammonium-assimilating microbiome: A halophilic biosystem rationally optimized by carbon to nitrogen ratios with stable nitrogen conversion and microbial structure

The contradiction between theoretical metabolism of ammonium assimilation and experiential understanding of conventional biosystems makes the rational optimization of the ammonium-assimilating microbiome through carbon to nitrogen (C/N) ratios perplexing. The effect of different C/N ratios on ammonium-assimilating biosystems was investigated...

New innovations in pavement materials and engineering: A review on pavement engineering research 2021

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges. In the past 10 years, the pavement infrastructure strongly supports the rapid development of the global social economy. New theories, new methods, new technologies and new materials related to pavement engineering are emerging....

High-Precision Detection Method for Structure Parameters of Catenary Cantilever Devices using 3D Point Cloud Data

This article proposes an automatic high-precision detection method for structure parameters of catenary cantilever devices (SPCCDs) using 3-D point cloud data. The steps of the proposed detection method are: 1) segmenting and recognizing the components of the catenary cantilever devices, 2) extracting the detection plane and backbone...

SlimML: Removing Non- critical Input Data in Large-scale Iterative Machine Learning

The core of many large-scale machine learning (ML) applications, such as neural networks (NN), support vector machine (SVM), and convolutional neural network (CNN), is the training algorithm that iteratively updates model parameters by processing massive datasets. From a plethora of studies aiming at accelerating ML, being data...