Exploiting the Power of Human-Robot Collaboration: Coupling and Scale Effects in Bricklaying

As an important contributor to GDP growth, the construction industry is suffering from labor shortage due to population ageing, COVID-19 pandemic, and harsh environments. Considering the complexity and dynamics of construction environment, it is still challenging to develop fully automated robots. For a long time in the future, workers and robots will coexist and collaborate with each other to build or maintain a facility efficiently. As an emerging field, human-robot collaboration (HRC) still faces various open problems. To this end, this pioneer research introduces an agent-based modeling approach to investigate the coupling effect and scale effect of HRC in the bricklaying process. With multiple experiments based on simulation, the dynamic and complex nature of HRC is illustrated in two folds: 1) agents in HRC are interdependent due to human factors of workers, features of robots, and their collaboration behaviors; 2) different parameters of HRC are correlated and have significant impacts on construction productivity (CP). Accidentally and interestingly, it is discovered that HRC has a scale effect on CP, which means increasing the number of collaborated human-robot teams will lead to higher CP even if the human-robot ratio keeps unchanged. Overall, it is argued that more investigations in HRC are needed for efficient construction, occupational safety, etc.; and this research can be taken as a stepstone for developing and evaluating new robots, optimizing HRC processes, and even training future industrial workers in the construction industry

Adaptive Control of Resource Flow to Optimize Construction Work and Cash Flow via Online Deep Reinforcement Learning

Due to complexity and dynamics of construction work, resource, and cash flows, poor management of them usually leads to time and cost overruns, bankruptcy, even project failure. Existing approaches in construction failed to achieve optimal control of resource flow in a dynamic environment with uncertainty. Therefore, this paper introducess a model and method to adaptive control the resource flows to optimize the work and cash flows of construction projects. First, a mathematical model based on a partially observable Markov decision process is established to formulate the complex interactions of construction work, resource, and cash flows as well as uncertainty and variability of diverse influence factors. Meanwhile, to efficiently find the optimal solutions, a deep reinforcement learning (DRL) based method is introduced to realize the continuous adaptive optimal control of labor and material flows, thereby optimizing the work and cash flows. To assist the training process of DRL, a simulator based on discrete event simulation is also developed to mimic the dynamic features and external environments of a project. Experiments in simulated scenarios illustrate that our method outperforms the vanilla empirical method and genetic algorithm, possesses remarkable capability in diverse projects and external environments, and a hybrid agent of DRL and empirical method leads to the best result. This paper contributes to adaptive control and optimization of coupled work, resource, and cash flows, and may serve as a step stone for adopting DRL technology in construction project management

To overcome the scalability limitation of passive optical interconnects in datacentres

We propose to add optical amplifier(s) to passive optical interconnect (POI) at top-of-rack in datacentres and validate this approach by introducing impairment constraints into POIs design. It is shown that one amplifier can improve scalability by a factor of 16

Polarization-based cyclic weak value metrology for angular velocity measurement

Weak value has been proved to amplify the detecting changes of the meters at the cost of power due to post-selection. Previous power-recycling schemes enable the failed post-selection photons to be reselected repeatedly, thus surpassing the upper noise limit and improving the precision of interferometric systems. Here we introduce three cyclic methods to improve the sensitivity of polarization-based weak-value-based angular velocity measurement: power-, signal- and dual-recycling schemes. By inserting one or two partially transmitting mirrors inside the system, both the power and precision of detected signals are greatly enhanced, and the dual-recycling scheme has wider optimal region than that of power- or signal-recycling schemes. Compared to non-polarization schemes, polarization-based schemes enjoy lower optical loss and unique cyclic directions. These reduce the crosstalk among different paths of light and, theoretically, eliminate the walk-off effect, thus towering in both theoretical performance and application.Comment: 7 pages, 3 figure

The complete mitochondrial genomes for three Toxocara species of human and animal health significance

<p>Abstract</p> <p>Background</p> <p>Studying mitochondrial (mt) genomics has important implications for various fundamental areas, including mt biochemistry, physiology and molecular biology. In addition, mt genome sequences have provided useful markers for investigating population genetic structures, systematics and phylogenetics of organisms. <it>Toxocara canis, Toxocara cati </it>and <it>Toxocara malaysiensis </it>cause significant health problems in animals and humans. Although they are of importance in human and animal health, no information on the mt genomes for any of <it>Toxocara </it>species is available.</p> <p>Results</p> <p>The sizes of the entire mt genome are 14,322 bp for <it>T. canis</it>, 14029 bp for <it>T. cati </it>and 14266 bp for <it>T. malaysiensis</it>, respectively. These circular genomes are amongst the largest reported to date for all secernentean nematodes. Their relatively large sizes relate mainly to an increased length in the AT-rich region. The mt genomes of the three <it>Toxocara </it>species all encode 12 proteins, two ribosomal RNAs and 22 transfer RNA genes, but lack the ATP synthetase subunit 8 gene, which is consistent with all other species of Nematode studied to date, with the exception of <it>Trichinella spiralis</it>. All genes are transcribed in the same direction and have a nucleotide composition high in A and T, but low in G and C. The contents of A+T of the complete genomes are 68.57% for <it>T. canis</it>, 69.95% for <it>T. cati </it>and 68.86% for <it>T. malaysiensis</it>, among which the A+T for <it>T. canis </it>is the lowest among all nematodes studied to date. The AT bias had a significant effect on both the codon usage pattern and amino acid composition of proteins. The mt genome structures for three <it>Toxocara </it>species, including genes and non-coding regions, are in the same order as for <it>Ascaris suum </it>and <it>Anisakis simplex</it>, but differ from <it>Ancylostoma duodenale</it>, <it>Necator americanus </it>and <it>Caenorhabditis elegans </it>only in the location of the AT-rich region, whereas there are substantial differences when compared with <it>Onchocerca volvulus</it>,<it>Dirofiliria immitis </it>and <it>Strongyloides stercoralis</it>. Phylogenetic analyses based on concatenated amino acid sequences of 12 protein-coding genes revealed that the newly described species <it>T. malaysiensis </it>was more closely related to <it>T. cati </it>than to <it>T. canis</it>, consistent with results of a previous study using sequences of nuclear internal transcribed spacers as genetic markers.</p> <p>Conclusion</p> <p>The present study determined the complete mt genome sequences for three roundworms of human and animal health significance, which provides mtDNA evidence for the validity of <it>T. malaysiensis </it>and also provides a foundation for studying the systematics, population genetics and ecology of these and other nematodes of socio-economic importance.</p