Search

ObjectivesThe preliminary research device of magnetic confinement deuterium-deuterium fusion neutron source is a novel neutron source preliminary research device based on field-reversed configuration (FRC) cascade magnetic compression. It aims to leverage the experiences from the first-phase construction to enhance system design, significantly improve plasma parameters, and further expand research on magnetic compression fusion, laying the foundation for achieving a large-volume high-flux fusion neutron source in the third phase.MethodsThe preliminary research device control system optimized and reconstructed the control framework, provided safety interlocking, pulse control and comprehensive data services, coordinated and integrated each service into the automated discharge process through integrated control, and added a number of resources to expand applications and DevOps tool.ResultsThrough the reconfiguration design, the comprehensive performance of the control system in terms of safety, stability and efficiency had been significantly improved. The safety interlock system ensured the safety of personnel and equipment during the experiment process, the pulse control system achieved high-precision timing control, the comprehensive data service provided full process support from data collection to analysis, and resource expansion applications and DevOps tools further improved the system flexibility and operation and maintenance efficiency.ConclusionsBy optimizing the control framework and introducing advanced operation and maintenance tools, the design can better meet the needs of complex device structure and precise discharge flow, and provide an efficient control system construction plan for the subsequent long-term cooperation construction of the magnetically confined deuterium fusion neutron source preliminary research device.

Lodging causes a reduction in wheat (Triticum aestivum L.) yield and quality. A shorter plant height (PH) can reduce the incidence of lodging. The overuse of nitrogen promotes excessive vegetative growth, leads to taller plants, and increases lodging risk. Here, we utilized genome-wide association studies (GWASs) to explore the genetic basis of PH and the nitrogen effect index (NEI), a parameter to estimate the responses of PH under varying nitrogen conditions, using 21,201 SNP markers from the Illumina Wheat 90K SNP array. A total of 191 wheat varieties from Yellow and Huai Valley regions of China, as well as other global regions, were analyzed across two growing seasons under four nitrogen treatments, namely N0 (0 kg/ha), N150 (150 kg/ha), N210 (210 kg/ha), and N270 (270 kg/ha). GWAS results showed that 30 genetic markers were associated with PH, explaining phenotypic variance from 5.92% to 13.69%. Additionally, nine significant loci were associated with the NEI. Notably, markers on chromosomes 1A and 6B were linked to both PH and the NEI, which were insensitive to low- and high-nitrogen fertilizers. In addition, the PH of the three cultivars (Zhoumai16, Zhoumai13, and Bima1) showed little variation in four nitrogen fertilizer levels. This study identified key genetic markers associated with wheat PH and the NEI, providing insights for optimizing nitrogen use in wheat breeding. [ABSTRACT FROM AUTHOR]

The accurate evaluation of green innovation efficiency is a critical prerequisite for enterprises to achieve sustainable development goals and improve environmental performance and economic efficiency. This paper evaluates the green innovation efficiency of 72 new-energy enterprises by using a hybrid method of Data Envelopment Analysis (DEA) and a random forest model. The non-parametric DEA model is combined with the parametric SFA model to analyze the real green innovation efficiency on the basis of removing environmental factors and random factors. Then, the random forest model based on a nonlinear relationship is used to evaluate factors impacting green innovation efficiency. This paper proposes a comprehensive evaluation method designed to assess the green innovation efficiency of new-energy enterprises. By applying this method, companies can gain a comprehensive understanding of the current performance in green innovation, facilitating informed decision-making and accelerating sustainable development. [ABSTRACT FROM AUTHOR]

Electrochromic smart windows can achieve controllable modulation of color and transmittance under an external electric field with active light and thermal control capabilities, which helps reduce energy consumption caused by building cooling and heating. However, electrochromic smart windows often rely on external power circuits, which greatly affects the independence and portability of smart windows. Based on this, an electrochromic smart window driven by temperature-difference power generation was designed and implemented. This smart window provides automatic and manual control of the reversible cycle of electrochromic glass from light blue to dark blue according to user requirements and changes in the surrounding environment, achieving adaptive adjustment of visual comfort and reducing energy consumption. The infrared radiation rejection (from 780 to 2500 nm) of the electrochromic smart window is as high as 77.3%, and its transmittance (from 380 to 780 nm) fluctuates between 39.2% and 56.4% with changes in working state. Furthermore, the temperature in the indoor simulation device with electrochromic glass as the window was 15 °C lower than that with ordinary glass as the window after heating with a 250 W Philips infrared lamp for ten minutes. After 2000 cycles of testing, the performance of the smart window was basically maintained at its initial values, and it has broad application prospects in buildings, vehicles, and high-speed rail systems. [ABSTRACT FROM AUTHOR]

Nowadays, one of the main challenges facing green innovation management is how to enhance the performance of innovation processes by utilizing asymmetric input and output data. Therefore, this paper develops an improved SBM model analysis framework for evaluating the green innovation efficiency of asymmetric input and output data. The framework is applied to assess the technical (TE), managerial (PTE), and scale (SE) efficiencies of new energy companies under three input variables (R&D personnel input, R&D capital input, and comprehensive energy consumption input), two desirable output variables (green technology output and economic output), and one undesirable output variable (greenhouse gas emissions). Then, environmental factors and random factors are eliminated from the obtained input slack variables based on the SFA model, placing decision-making units in a homogeneous environment. The results demonstrate that TE, PTE, and SE are improved after eliminating environmental factors and random factors. Subsequently, based on the entropy method, this paper classifies companies' green innovation patterns into four categories and provides targeted solutions. The purpose of this paper is to provide an evaluation method for new energy companies to understand green innovation efficiency and assist decision makers in identifying the most optimal resource allocation approach. The proposed improved SBM model contributes to the literature and to industry practice by (1) providing a reliable evaluation of green innovation efficiency under asymmetric input and output data; (2) determining effective improvement actions based on a slack analysis of environmental variables and random variables that lead to improved process performance; and (3) making fuzzy innovation performance efficient to facilitate understanding and managing innovation resource allocation quality. [ABSTRACT FROM AUTHOR]

White light cavities with broadband resonance are usually filled with negative dispersion medium, which inevitably leads to gain. In this article, pure passive white light cavities are designed, in which negative dispersion medium is no longer necessary. Theoretically, if the reflection phase of the cavity wall can exhibit a negative dispersion slope, then it can also satisfy white light cavities conditions without medium. In practice, the negative dispersion property of the cavity wall can be realized by two metal coatings with different reflection coefficients. Therefore, our white light cavities are composite cavities, in which the main cavity provides resonance while the auxiliary cavity forms the cavity wall, providing negative dispersion reflection phase. Further, atomic gas can be employed to improve the performance of the white light cavities. Atomic gas exploits effects such as Electromagnetic Induced Transparency (EIT), enabling the white light cavities to be controlled by coherent driving field. With the passive characters, our design can be realized and implemented much more easily.