A SEED MUCILAGE-DEGRADING FUNGUS FROM THE RHIZOSPHERE STRENGTHENS THE PLANT-SOIL-MICROBE CONTINUUM AND POTENTIALLY REGULATES ROOT NUTRIENTS OF A COLD DESERT SHRUB

A Seed Mucilage-Degrading Fungus From the Rhizosphere Strengthens the Plant-Soil-Microbe Continuum and Potentially Regulates Root Nutrients of a Cold Desert Shrub

Seed mucilage plays important roles in the adaptation of desert plants to the stressful environment.Artemisia sphaerocephala is an important pioneer plant in the Central Asian cold desert, and it produces a large quantity of seed mucilage.Seed mucilage of A.sphaerocephala can be degraded by soil microbes, but it is unknown which microorganisms can

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ANALYSIS OF NOISE IMMUNITY OF RECEPTION OF SIGNALS WITH MULTIPLE PHASE SHIFT KEYING UNDER THE INFLUENCE OF SCANNING INTERFERENCE

Signals with multi-phase shift keying (M-PSK) have long been successfully used in digital information transmission systems with high bandwidth.Their use is regulated by various communication standards.The noise immunity characteristics of their reception against the background of white Gaussian noise are well studied.The article deals with the case

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Linguistic Processing of Accented Speech Across the Lifespan

In most of the world, people have regular exposure to multiple accents.Therefore, learning to quickly process accented speech is a prerequisite to successful communication.In this paper, we examine work on the perception of accented speech across the lifespan, from early infancy to late adulthood.Unfamiliar accents initially impair linguistic proce

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Effect of CNT on microstructure, dry sliding wear and compressive mechanical properties of AZ61 magnesium alloy

Carbon nanotubes (CNTs) reinforced AZ61 magnesium alloy was successfully fabricated through stir casting method with the concentration of (0, 0.1, 0.5, 1) wt.% CNTs followed by age heat treatments.The influence of the CNTs concentration on compressive mechanical properties, dry sliding wear behavior and microstructure of synthesized composites have

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An Efficient Distributed Reinforcement Learning Architecture for Long-Haul Communication Between Actors and Learner

A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning that uses DQN (Deep Q-Network).In distributed reinforcement learning, actor nodes acquire experiences by interacting with a given environment and a learner node optimizes the DQN model.When distributed reinforcement learning is use

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