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...

FedViT: Federated continual learning of vision transformer at edge

Deep Neural Networks (DNNs) have been ubiquitously adopted in internet of things and are becoming an integral part of our daily life. When tackling the evolving learning tasks in real world, such as classifying different types of objects, DNNs face the challenge to continually retrain themselves according to the tasks on different edge...

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...

FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge

Deep Neural Networks (DNNs) have been ubiquitously adopted in internet of things and are becoming an integral of our daily life. When tackling the evolving learning tasks in real world, such as classifying different types of objects, DNNs face the challenge to continually retrain themselves according to the tasks on different edge devices....

EdgeVisionBench: A Benchmark of Evolving Input Domains for Vision Applications at Edge

Vision applications powered by deep neural networks (DNNs) are widely deployed on edge devices and solve the learning tasks of incoming data streams whose class label and input feature continuously evolve, known as domain shift. Despite its prominent presence in real-world edge scenarios, existing benchmarks used by domain adaptation methods...

A new reinforcement learning-based variable speed limit control approach to improve traffic efficiency against freeway jam waves

Conventional reinforcement learning (RL) models of variable speed limit (VSL) control systems (and traffic control systems in general) cannot be trained in real traffic process because new control actions are usually explored randomly, which may result in high costs (delays) due to exploration and learning. For this reason, existing RL-based...

Lightweight and Accurate DNN-Based Anomaly Detection at Edge

Deep neural networks (DNNs) have been showing significant success in various anomaly detection applications such as smart surveillance and industrial quality control. It is increasingly important to detect anomalies directly on edge devices, because of high responsiveness requirements and tight latency constraints. The accuracy of DNN-based...

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....

Knitting 4D garments with elasticity controlled for body motion

In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in...