Generation of novel high quality HMW-GS genes in two introgression lines of Triticum aestivum/Agropyron elongatum

<p>Abstract</p> <p>Background</p> <p>High molecular weight glutenin subunits (HMW-GS) have been proved to be mostly correlated with the processing quality of common wheat (<it>Triticum aestivum</it>). But wheat cultivars have limited number of high quality HMW-GS. However, novel HMW-GS were found to be present in many wheat asymmetric somatic hybrid introgression lines of common wheat/<it>Agropyron elongatum</it>.</p> <p>Results</p> <p>To exploit how these new subunits were generated, we isolated HMW-GS genes from two sib hybrid lines (II-12 and 11-4-6) and compared them with those from their parents. The result shows that two genes of hybrid (<it>H11-3-3 </it>and <it>H11-4-3</it>) are directly introgressed from the donor parent <it>Agropyron elongatum</it>; one hybrid gene (<it>H1Dx5</it>) comes from point mutation of a parental wheat gene (<it>1Dx2.1</it>); two other hybrid genes (<it>H1By8 </it>and <it>H1By16</it>) are likely resulting from unequal crossover or slippage of a parental wheat gene (<it>1By9.1</it>); and the sixth novel hybrid gene (<it>H1Dy12</it>) may come from recombination between two parental genes.</p> <p>Conclusion</p> <p>Therefore, we demonstrate that novel HMW-GS genes can be rapidly created through asymmetric somatic hybridization in a manner similar with the evolution mechanism of these genes supposed before. We also described gene shuffling as a new mechanism of novel HMW-GS gene formation in hybrids. The results suggest that asymmetric somatic hybridization is an important approach for widening HMW-GS genebank of wheat quality improvement.</p

A Programmable ROADM System for SDM/WDM Networks

This paper proposed and evaluated a programmable ROADM system for MCF-based SDM/WDM networks. The proposed ROADM system employing both bypass connection and Route-and-Select wavelength switching enables adaptable virtual topology in optical networks by dynamically configuring bypass connection cores. The simulation results confirmed this ROADM system could provide acceptable performance with an around 10–20% reduction in the total cost including the number of ports and WSSs by comparing with a fully flexible SDM/WDM ROADM system, which cannot be implemented due to the required extremely high-port-count WSSs

Recent Advances in Transition-Metal-Based Catalytic Material for Room-Temperature Sodium–Sulfur Batteries

Room-temperature sodium–sulfur (RT Na–S) batteries have emerged as a promising candidate for next-generation scalable energy storage systems, due to their high theoretical energy density, low cost, and natural abundance. However, the practical applications of these batteries are hindered by the notorious shuttle effect of soluble sodium polysulfides (NaPSs) and sluggish reaction kinetics, which result in fast performance loss. To address this issue, recent studies have reported impressive achievements of transition metal nanoparticles/single atoms/cluster/compounds (TM)-based host materials with strong adsorption and catalyzation to NaPSs. These materials can significantly improve the electrochemical performance of RT Na–S batteries. In this review, the recent progress on TM-based host materials for RT Na–S batteries, including iron (Fe)-, cobalt (Co)-, nickel (Ni)-, molybdenum (Mo)-, titanium (Ti)-, vanadium (V)-, manganese (Mn)-, and other TM-based materials are summarized. The design, fabrication, and properties of these host materials are comprehensively summarized and systematically analyzed the underlying chemical inhibition and electrocatalysis mechanism between NaPSs and TM-based catalytic materials. At last, the challenges and prospects for designing efficient TM-based catalytic materials for high-performance RT Na–S batteries are discussed

Adaptive Resource Management for Edge Network Slicing using Incremental Multi-Agent Deep Reinforcement Learning

Multi-access edge computing provides local resources in mobile networks as the essential means for meeting the demands of emerging ultra-reliable low-latency communications. At the edge, dynamic computing requests require advanced resource management for adaptive network slicing, including resource allocations, function scaling and load balancing to utilize only the necessary resources in resource-constraint networks. Recent solutions are designed for a static number of slices. Therefore, the painful process of optimization is required again with any update on the number of slices. In addition, these solutions intend to maximize instant rewards, neglecting long-term resource scheduling. Unlike these efforts, we propose an algorithmic approach based on multi-agent deep deterministic policy gradient (MADDPG) for optimizing resource management for edge network slicing. Our objective is two-fold: (i) maximizing long-term network slicing benefits in terms of delay and energy consumption, and (ii) adapting to slice number changes. Through simulations, we demonstrate that MADDPG outperforms benchmark solutions including a static slicing-based one from the literature, achieving stable and high long-term performance. Additionally, we leverage incremental learning to facilitate a dynamic number of edge slices, with enhanced performance compared to pre-trained base models. Remarkably, this approach yields superior reward performance while saving approximately 90% of training time costs

Design and integration of a parallel, soft robotic end-effector for extracorporeal ultrasound

Objective: In this work we address limitations in state-of-the-art ultrasound robots by designing and integrating a novel soft robotic system for ultrasound imaging. It employs the inherent qualities of soft fluidic actuators to establish safe, adaptable interaction between ultrasound probe and patient. Methods: We acquire clinical data to determine the movement ranges and force levels required in prenatal foetal ultrasound imaging and design the soft robotic end-effector accordingly. We verify its mechanical characteristics, derive and validate a kinetostatic model and demonstrate controllability and imaging capabilities on an ultrasound phantom. Results: The soft robot exhibits the desired stiffness characteristics and is able to reach 100% of the required workspace when no external force is present, and 95% of the workspace when considering its compliance. The model can accurately predict the end-effector pose with a mean error of 1.18+/-0.29mm in position and 0.92+/-0.47deg in orientation. The derived controller is, with an average position error of 0.39mm, able to track a target pose efficiently without and with externally applied loads. Ultrasound images acquired with the system are of equally good quality compared to a manual sonographer scan. Conclusion: The system is able to withstand loads commonly applied during foetal ultrasound scans and remains controllable with a motion range similar to manual scanning. Significance: The proposed soft robot presents a safe, cost-effective solution to offloading sonographers in day-to-day scanning routines. The design and modelling paradigms are greatly generalizable and particularly suitable for designing soft robots for physical interaction tasks

A scaling law for distinct electrocaloric cooling performance in low-dimensional organic, relaxor and anti-ferroelectrics.

Electrocaloric (EC) materials show promise in eco-friendly solid-state refrigeration and integrable on-chip thermal management. While direct measurement of EC thin-films still remains challenging, a generic theoretical framework for quantifying the cooling properties of rich EC materials including normal-, relaxor-, organic- and anti-ferroelectrics is imperative for exploiting new flexible and room-temperature cooling alternatives. Here, we present a versatile theory that combines Master equation with Maxwell relations and analytically relates the macroscopic cooling responses in EC materials with the intrinsic diffuseness of phase transitions and correlation characteristics. Under increased electric fields, both EC entropy and adiabatic temperature changes increase quadratically initially, followed by further linear growth and eventual gradual saturation. The upper bound of entropy change (∆Smax) is limited by distinct correlation volumes (V cr ) and transition diffuseness. The linearity between V cr and the transition diffuseness is emphasized, while ∆Smax = 300 kJ/(K.m3) is obtained for Pb0.8Ba0.2ZrO3. The ∆Smax in antiferroelectric Pb0.95Zr0.05TiO3, Pb0.8Ba0.2ZrO3 and polymeric ferroelectrics scales proportionally with V cr-2.2, owing to the one-dimensional structural constraint on lattice-scale depolarization dynamics; whereas ∆Smax in relaxor and normal ferroelectrics scales as ∆Smax ~ V cr-0.37, which tallies with a dipolar interaction exponent of 2/3 in EC materials and the well-proven fractional dimensionality of 2.5 for ferroelectric domain walls

Molybdenum-Based Catalytic Materials for Li–S Batteries: Strategies, Mechanisms, and Prospects

Lithium–sulfur (Li–S) batteries are regarded as promising candidates for high-energy storage devices because of their high theoretical energy density (2600 Wh kg−1). However, their practical applications are still hindered by a multitude of key challenges, especially the shuttle effect of soluble lithium polysulfides (LiPSs) and the sluggish sulfur redox kinetics. To address these challenges, varieties of catalytic materials have been exploited to prevent the shuttle effect and accelerate the LiPSs conversion. Recently, molybdenum-based (Mo-based) catalytic materials are widely used as sulfur host materials, modified separators, and interlayers for Li–S batteries. They include the Mo sulfides, diselenides, carbides, nitrides, oxides, phosphides, borides, and metal/single atoms/clusters. Here, recent advances in these Mo-based catalytic materials are comprehensively summarized, and the current challenges and prospects for designing highly efficient Mo-based catalytic materials are highlighted, with the aim to provide a fundamental understanding of the sulfur reaction mechanism, and to guide the rational design of cathode catalysts for high-energy and long-life Li–S batteries

A scaling law for distinct electrocaloric cooling performance in low-dimensional organic, relaxor and anti-ferroelectrics

Electrocaloric (EC) materials show promise in eco-friendly solid-state refrigeration and integrable on-chip thermal management. While direct measurement of EC thin-films still remains challenging, a generic theoretical framework for quantifying the cooling properties of rich EC materials including normal-, relaxor-, organic- and anti-ferroelectrics is imperative for exploiting new flexible and room-temperature cooling alternatives. Here, we present a versatile theory that combines Master equation with Maxwell relations and analytically relates the macroscopic cooling responses in EC materials with the intrinsic diffuseness of phase transitions and correlation characteristics. Under increased electric fields, both EC entropy and adiabatic temperature changes increase quadratically initially, followed by further linear growth and eventual gradual saturation. The upper bound of entropy change (∆Smax) is limited by distinct correlation volumes (V cr ) and transition diffuseness. The linearity between V cr and the transition diffuseness is emphasized, while ∆Smax = 300 kJ/(K.m3) is obtained for Pb0.8Ba0.2ZrO3. The ∆Smax in antiferroelectric Pb0.95Zr0.05TiO3, Pb0.8Ba0.2ZrO3 and polymeric ferroelectrics scales proportionally with V cr −2.2, owing to the one-dimensional structural constraint on lattice-scale depolarization dynamics; whereas ∆Smax in relaxor and normal ferroelectrics scales as ∆Smax ~ V cr −0.37, which tallies with a dipolar interaction exponent of 2/3 in EC materials and the well-proven fractional dimensionality of 2.5 for ferroelectric domain walls