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In the case of a weak signal from a photon counting lidar and strong noise from the solar background, the signal is completely submerged by noise, potentially resulting in the appearance of multiple peaks in the denoising algorithm of photon counting entropy. Consequently, a clear distinction between the signal and noise may become challenging, leading to significant fluctuation in the ranging error. To solve this problem, this paper proposes an improved offset parameter optimization algorithm under the framework of photon counting entropy, aiming to effectively eliminate peak interference caused by noise and enhancing ranging accuracy. The algorithm includes two aspects. First, we introduce the solar irradiance prediction of an MLP network and least squares linear conversion to accurately estimate the noise rate of the solar background noise. Then, we propose the offset parameter optimization method to effectively mitigate the interference caused by noise. In simulation and experimental analyses, the ranging error of our proposed method is within 5 and 30 cm , respectively. Compared with the denoising method of photon counting entropy, the average ranging error is increased by 81.99% and 73.76%. Furthermore, compared to other anti-noise methods, it exhibits superior ranging capability. [ABSTRACT FROM AUTHOR]

Building operations account for a large amount of energy use and CO2 emissions, and the morphology of buildings in residential clusters strongly impacts energy efficiency performance. However, little research has focused on the morphology and energy electricity usage of high-rise residential clusters in hot summer and cold winter (HSCW) regions. We investigated 96 residential clusters in Hangzhou, China, and established a corresponding morphology database. Additionally, we obtained annual electricity consumption for 16 of these residential clusters. With this database, we performed optimization of morphological parameters upon energy use intensity (EUI) using a genetic algorithm (GA). Specifically, the cooling, heating, and lighting EUIs of high-rise residential clusters were studied. After implementing the optimized morphological parameters, there was a reduction of up to 7.73% in EUI. According to regression analysis, the average aspect ratio was the most significant factor influencing EUI (r = −0.907), followed by floor area ratio (r = −0.755), average orientation (r = 0.502), and average number of floors (r = −0.453). These results indicate that a higher intensity of land development with a greater floor area ratio, average aspect ratio, and average number of floors can reduce total energy consumption. Additionally, we found that an average building orientation of southwest 15° (with respect to south) is optimal. The findings of this study can assist urban planners and designers in developing more sustainable residential clusters, leading to decreased energy costs and CO2 emissions. [ABSTRACT FROM AUTHOR]

In this work, we introduce a novel coherent perfect absorber, accentuating its novelty by emphasizing the broad bandwidth, reduced thickness, tunable property, and straightforward design achieved through the use of an asymmetric graphene metasurface. This design incorporates both square and circular graphene patches arranged on either side of a silicon substrate. With an optimized structural design, this absorber consistently captures over 90% of incoming waves across the frequency range of 1.65 to 4.49 THz, with a graphene Fermi level of 0.8 eV, and the whole device measures just 1.5 um thick. This makes our absorber significantly more effective and compact than previous designs. The absorber's effectiveness can be significantly enhanced by combining the metasurface's geometric design with the graphene Fermi level. It is anticipated that this ultrathin, wideband coherent perfect absorption device will play a crucial role in emerging on-chip THz communication technologies, including light modulators, photodetectors, and so on. [ABSTRACT FROM AUTHOR]

To address the challenges faced in the prediction of rolling bearing life, where temporal signals are affected by noise, making fault feature extraction difficult and resulting in low prediction accuracy, a method based on optimal time–frequency spectra and the DenseNet-ALSTM network is proposed. Firstly, a signal reconstruction method is introduced to enhance vibration signals. This involves using the CEEMDAN deconvolution method combined with the Teager energy operator for signal reconstruction, aiming to denoise the signals and highlight fault impacts. Subsequently, a method based on the snake optimizer (SO) is proposed to optimize the generalized S-transform (GST) time–frequency spectra of the enhanced signals, obtaining the optimal time–frequency spectra. Finally, all sample data are transformed into the optimal time–frequency spectrum set and input into the DenseNet-ALSTM network for life prediction. The comparison experiment and ablation experiment show that the proposed method has high prediction accuracy and ideal prediction performance. The optimization terms used in different contexts in this paper are due to different optimization methods, specifically the CEEMDAN method. [ABSTRACT FROM AUTHOR]

Most of the domestic wholesale markets have many operating entities, and the level of organization and scale is not high; therefore, at this stage, building a shared business platform and carrying out common distribution is an important way to improve the overall efficiency of the wholesale market distribution operations and the level of the intensive utilization of key resources such as vehicles. Carrying out common distribution requires the formation of a good synergy mechanism among the participating subjects, in which the design of a scientific and reasonable benefit distribution scheme, especially in balancing the relationship between government resources and social resources, is particularly important. As the benefit distribution of cooperation is affected by the dynamic changes of the resource input ratio, the distribution operation scale, the risk taking, and other factors, this paper establishes a multi-weight interval Shapley value method benefit distribution model, which reflects the effect of the key parameter variables. Through the empirical analysis of Beijing's wholesale markets for agricultural products, the results show that the revised benefit distribution is more in line with the interest demands among multiple subjects and is positively correlated with the contribution degree among the participating subjects, which can better mobilize the cooperation enthusiasm of the participating enterprises and provide a new methodological path to solve the problem of common distribution in wholesale markets. The distribution model constructed in this paper further enriches the relevant research content in the field of common distribution and is of reference value for the benefit distribution problem that requires comprehensive consideration of the dynamic change in the multiple parameters affecting the relationship. [ABSTRACT FROM AUTHOR]

Leptospirosis is an important zoonosis that is caused by pathogenic Leptospira, which is considered to be a re-emerging infectious disease in many countries. Rodents are the most important reservoirs for both human and animal infection. An epidemiological survey of pathogenic Leptospira in rodents is important for the prevention and control of leptospirosis. In this study, a total of 964 rodents were captured from six cities in Hubei Province, and two pathogenic Leptospira species (L. interrogans and L. borgpetersenii) were detected using nested PCR with an overall prevalence of 4.8%. L. interrogans was distributed in five sampling sites, which may be the dominant species of pathogenic Leptospira in Hubei Province. In addition, Rattus norvegicus showed a relatively high infection rate, which may play an important role in the transmission and infection of pathogenic Leptospira. This study reveals the prevalence of pathogenic Leptospira in wild rodents in Hubei Province, suggesting that the risk of leptospirosis infection in Hubei Province still exists. [ABSTRACT FROM AUTHOR]

A new kind of low-carbon bainite steel with excellent strength and toughness was developed, serving as the bogie of the next-generation high-speed train. However, the softening of the heat-affected zone (HAZ) in laser-arc hybrid welding (LAHW) needs to be overcome. In this study, the effect of the cooling rate of the LAHW process on the microstructure and mechanical properties in the HAZ was explored via thermal simulation. The results showed that with increased cooling rate, the grain size increased, the content of lath martensite decreased, and the lath bainite gradually changed to a granular shape in the thermal simulation specimen. With the decrease in the cooling rate, i.e., with the increase of t8/5, the strength–toughness matching of the material showed a downward trend. The thermal simulation specimen with a t8/5 of 6~8 s had higher strength and good toughness, which can be considered a potential welding parameter reference. The content of martensitic austenite (M-A) constituents was the main factor that determined the strength and toughness of the joint. During the tensile test, the axial force caused the material to tighten, and the transverse stress as obvious in the part of the M-A constituents that are prone to microcracks and many defects, resulting in cracks, paths, and multi-component layers in the center. As a result, the thermal cycle specimens had mixed fracture characteristics. [ABSTRACT FROM AUTHOR]

This paper overviews high-speed permanent magnet (HSPM) machines, accounting for stator structures, winding configurations, rotor constructions, and parasitic effects. Firstly, single-phase and three-phase PM machines are introduced for high-speed applications. Secondly, for three-phase HSPM machines, applications, advantages, and disadvantages of slotted/slotless stator structures, non-overlapping/overlapping winding configurations, different rotor constructions, i.e., interior PM (IPM), surface-mounted PM (SPM), and solid PM, are summarised in detail. Thirdly, parasitic effects due to high-speed operation are presented, including various loss components, rotor dynamic and vibration, and thermal aspects. Overall, three-phase PM machines have no self-starting issues, and exhibit high power density, high efficiency, high critical speed, together with low vibration and noise, which make them a preferred choice for high-performance, high-speed applications. [ABSTRACT FROM AUTHOR]