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Ultra-high voltage (UHV) power grid is a new transmission and transformation technology, which has the advantages of large transmission capacity, long transmission distance, low line loss, saving land resources and obvious economic benefits. Taking the Zhangbei-xiongan 1000kv AC high voltage power transmission and transformation project as an example, this paper constructs the eco-environmental index system of the UHV transmission and transformation project by using the pressure-state-response model, and constructs a set of 18 indexes eco-environmental index system, it mainly includes three aspects: the eco-environmental pressure index caused by the construction behavior in different construction stages of power transmission and transformation projects, and the eco-environmental state index given by on-the-spot investigation and study of projects, based on the construction unit on the ecological environment impact management response measures given indicators. The index system provides a basis for comprehensive and systematic evaluation of the impact of power transmission and distribution projects on the ecological environment, and finally draws the corresponding project construction evaluation conclusions. In this paper, the eco-environmental impact assessment index system of power transmission and transformation engineering has certain universality, and it has certain reference and guiding significance for the ecological environment evaluation of power transmission and transformation engineering.

Simple Summary: The knowledge base surrounding digital dermatitis (DD) primarily relies on research pertaining to the dairy industry, little of which can be extrapolated to DD development in feedlot cattle. This study represents the largest retrospective study, to date, on the diagnosis of DD in western Canadian feedlot cattle. Utilizing records from western Canadian feedlots this study revealed associations between sex, placement quarter, and acquisition source, and DD at the animal-level, alongside an association between feedlot population size and the presence or absence of diagnosed DD cases at the feedlot level. These findings will drive future research related to understanding the development and transmission of DD in feedlot cattle as it pertains to these risk factors. Digital dermatitis (DD) is an emerging disease in feedlot cattle. Our objective was to identify animal- and feedlot-level risk factors for DD by analyzing individual animal health records (n = 1,209,883) and feedlot-level records from western Canadian feedlots (n = 28) between 2014 and 2018, inclusive. The risk of a DD diagnosis was higher (incidence rate ratio (IRR) = 2.08, 95% CI 1.52 to 2.86) in cattle sourced from confined background operations (CB) versus cattle sourced from auction markets (AM). Conversely, ranch direct (RD) cattle were (IRR = 0.02, 95% CI 0.04 to 0.30) lower risk than AM cattle of being diagnosed with DD. The risk of being diagnosed with DD was higher in females than in males. The magnitude of the risk in females over males was influenced by annual DD incidence in low morbidity years (2014, 2017, and 2018) (IRR = 2.02, 95% CI 1.27 to 3.19), medium morbidity years (2016) (IRR = 2.95, 95% CI 1.64 to 5.33), and high morbidity years (2015) (IRR = 5.41, 95% CI 3.27 to 8.95). At the feedlot-level, the risk of a diagnosis of DD was lower in small capacity (SCF) versus large capacity feedlots (LCF) (IRR = 0.24, 95% CI 0.05 to 0.76). Future research should focus on identifying factors that may propagate disease transmission between cattle of different sexes and from different acquisition sources. [ABSTRACT FROM AUTHOR]

In the advancing field of 5G technologies, particularly at the 60 GHz band, dielectric resonator antennas (DRAs) stand out for their low conduction loss and high radiation efficiency. However, the traditional design process for DRAs, predominantly reliant on intuitive reasoning and trial‐and‐error methods, is notably inefficient and resource‐intensive. Addressing this critical challenge, our research introduces a pioneering approach: a generative adversarial network (GAN)‐based model specifically tailored for automating DRA structure design. This novel model represents the first of its kind in the domain, marking a significant departure from conventional methods. Our GAN model uniquely integrates a simulator for DRA modeling and a generator for DRA structure design, streamlining the design process. To effectively train this model, we created a simulated data set comprising pattern–annotation pairs of geometric shapes and S11 parameters. This data set enabled the GAN to capture the intrinsic principles underlying DRA design. The practical impact of our model is profound; it significantly expedites the DRA design process, aligning it more closely with specific user requirements while conserving valuable time and resources. This breakthrough approach not only enhances the efficiency of DRA design but also sets a new standard in antenna technology development for future wireless communications. [ABSTRACT FROM AUTHOR]