The Application of Robotic Drilling Systems in Extreme Environments

Vibrations in the aircraft assembly building will affect the precision of the robotic drilling system. A variable stiffness and damping semiactive vibration control mechanism with quasi-zero stiffness characteristics is developed. The quasi-zero stiffness of the mechanism is realized by the parallel connection of four vertically arranged bearing springs and two symmetrical horizontally arranged negative stiffness elements. Firstly, the quasi-zero stiffness parameters of the mechanism at the static equilibrium position are obtained through analysis. Secondly, the harmonic balance method is used to deal with the differential equations of motion. The effects of every parameter on the displacement transmissibility are analyzed, and the variable parameter control strategies are proposed. Finally, the system responses of the passive and semiactive vibration isolation mechanisms to the segmental variable frequency excitations are compared through virtual prototype experiments. The results show that the frequency range of vibration isolation is widened, and the stability of the vibration control system is effectively improved without resonance through the semiactive vibration control method. It is of innovative significance for ambient vibration control in robotic drilling systems.

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Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

Safety in Extreme Environments ◽

10.1007/s42797-021-00025-1 ◽

2021 ◽

Author(s):

Petar Radanliev ◽

David De Roure ◽

Kevin Page ◽

Max Van Kleek ◽

Omar Santos ◽

...

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Real Time ◽

Cyber Security ◽

Extreme Environments ◽

Learning Technologies ◽

Cyber Attacks ◽

Edge Computing ◽

Mathematical Formulas ◽

Cyber Risk

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

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Advancement of Mechanical Engineering in Extreme Environments

International Journal of Precision Engineering and Manufacturing-Green Technology ◽

10.1007/s40684-020-00295-3 ◽

2021 ◽

Author(s):

Zhen Qin ◽

Yu-Ting Wu ◽

Amre Eizad ◽

Sung-Ki Lyu ◽

Choon-Man Lee

Keyword(s):

Mechanical Engineering ◽

Extreme Environments

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Comprehensive analysis of SSRs and database construction using all complete gene-coding sequences in major horticultural and representative plants

Horticulture Research ◽

10.1038/s41438-021-00562-7 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Xiaoming Song ◽

Qihang Yang ◽

Yun Bai ◽

Ke Gong ◽

Tong Wu ◽

...

Keyword(s):

Higher Plants ◽

Extreme Environments ◽

Gene Families ◽

Comprehensive Analysis ◽

Whole Genome ◽

Flowering Genes ◽

Database Construction ◽

Myb Gene ◽

Gene Coding ◽

Lower Plants

AbstractSimple sequence repeats (SSRs) are one of the most important genetic markers and widely exist in most species. Here, we identified 249,822 SSRs from 3,951,919 genes in 112 plants. Then, we conducted a comprehensive analysis of these SSRs and constructed a plant SSR database (PSSRD). Interestingly, more SSRs were found in lower plants than in higher plants, showing that lower plants needed to adapt to early extreme environments. Four specific enriched functional terms in the lower plant Chlamydomonas reinhardtii were detected when it was compared with seven other higher plants. In addition, Guanylate_cyc existed in more genes of lower plants than of higher plants. In our PSSRD, we constructed an interactive plotting function in the chart interface, and users can easily view the detailed information of SSRs. All SSR information, including sequences, primers, and annotations, can be downloaded from our database. Moreover, we developed Web SSR Finder and Batch SSR Finder tools, which can be easily used for identifying SSRs. Our database was developed using PHP, HTML, JavaScript, and MySQL, which are freely available at http://www.pssrd.info/. We conducted an analysis of the Myb gene families and flowering genes as two applications of the PSSRD. Further analysis indicated that whole-genome duplication and whole-genome triplication played a major role in the expansion of the Myb gene families. These SSR markers in our database will greatly facilitate comparative genomics and functional genomics studies in the future.

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Extremofiles 2.0

Microorganisms ◽

10.3390/microorganisms9040784 ◽

2021 ◽

Vol 9 (4) ◽

pp. 784

Author(s):

Ricardo Amils ◽

Felipe Gómez

Keyword(s):

Extreme Environments

The exploration of extreme environments has led to the discovery of numerous environments that were, until recently, considered uninhabitable [...]

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