Many studies have found that the correlation between species richness (SR) and morphological diversity (MD) is positive, but the correlation degree of these parameters is not always consistent due to differences in categories and various ecological factors in the living environment. Based on this, related studies have revealed the good performance of using higher taxa in biodiversity research, not only by shifting the testing group scale from local communities to worldwide datasets but also by adding different taxonomic levels, such as the genus level. However, it remains unclear whether this positive correlation can also be applied to other categories or groups. Here, we evaluated the applicability of higher taxa in the biodiversity study of darkling beetles by using 3407 species (9 subfamilies, 89 tribes, and 678 genera), based on the correlation between taxa richness and morphological diversity in the tribe/genus/species. In addition, the continuous features prevalent in the tenebrionids, pronotum and elytron, were selected, and the morphological diversity of various groups was obtained by the geometric morphometric approach to quantify the morphologic information of features. This study found that genus/species richness in subfamilies Pimelinae and Stenochiinae was positively correlated with the change trend of MD, and the correlation between the MD of elytron and taxa richness gradually decreased from the tribe-level to the genus-level to the species-level test. The results confirm the stable morphology and simple function of the elytron and the applicability of tribe level in biodiversity research.

This paper reports an efficient method for sound extraction from high-speed light spot videos reconstructed from the coded light spot images captured with a low-speed camera based on compressive sensing, but at the expense of consuming time. The proposed method first gets the high-speed video of the light spot that is illuminated on the vibrating target caused by sound. Then the centroid of the light spot is used to recover the sound. Simulations of the proposed method are carried out and experimental results are demonstrated. The results show that high-speed videos with a frame rate of 2000 Hz can be reconstructed with a low-speed (100 Hz) charge-coupled device (CCD) camera, which is randomly modulated by a digital micro-mirror device (DMD) 20 times during each exposure time. This means a speed improvement of 20 times is achieved. The effects of synchronization between CCD image recording and DMD modulation, the optimal sampling patterns of DMD, and sound vibration amplitudes on the performance of the proposed method are evaluated. Using this compressive camera, speech (counting from one to four in Chinese) was recovered well. This has been confirmed by directly listening to the recovered sound, and the intelligibility value (0–1) that evaluated the similarity between them was 0.8185. Although we use this compressive camera for sound detection, we expect it to be useful in applications related to vibration and motion.

Geomagnetic storms have a significant impact on Earth’s magnetosphere and ionosphere, as well as on the global atmospheric circuit. This study focuses on investigating the anomalous variations in the vertical atmospheric electric field at eight mid-latitude and low-latitude stations during a mega-geomagnetic storm on 24 April 2023. The majority of stations observed vertical atmospheric electric field increases, while only three nearby stations exhibited vertical atmospheric electric field decreases. The analysis revealed that vertical atmospheric electric field changes ranged from 19 to 370 V/m, and the time differences between extreme vertical atmospheric electric field values and the minimum Dst value ranged from 0 to 5.3 h. Other response patterns to this super magnetic storm at different latitudes are summarized, and the physical mechanisms of different effects of magnetic storms on the electric fields of stations at different latitudes are also discussed.

Depth cameras are closely related to our daily lives and have been widely used in fields such as machine vision, autonomous driving, and virtual reality. Despite their diverse applications, depth cameras still encounter challenges like multi-path interference and mixed pixels. Compared to traditional sensors, depth cameras have lower resolution and a lower signal-to-noise ratio. Moreover, when used in environments with scattering media, object information scatters multiple times, making it difficult for time-of-flight (ToF) cameras to obtain effective object data. To tackle these issues, we propose a solution that combines ToF cameras with second-order correlation transform theory. In this article, we explore the utilization of ToF camera depth information within a computational correlated imaging system under ambient light conditions. We integrate compressed sensing and non-training neural networks with ToF technology to reconstruct depth images from a series of measurements at a low sampling rate. The research indicates that by leveraging the depth data collected by the camera, we can recover negative depth images. We analyzed and addressed the reasons behind the generation of negative depth images. Additionally, under undersampling conditions, the use of reconstruction algorithms results in a higher peak signal-to-noise ratio compared to images obtained from the original camera. The results demonstrate that the introduced second-order correlation transformation can effectively reduce noise originating from the ToF camera itself and direct ambient light, thereby enabling the use of ToF cameras in complex environments such as scattering media.

In fair weather, the vertical atmospheric electric field is oriented downward (positive in the earth surface ordinate system) in the global atmospheric circuit. Some researchers have revealed the unique phenomenon whereby once an upward vertical atmospheric electric field is observed in fair weather, an earthquake (EQ) follows within 2–48 h regardless of the EQ magnitude. However, the mechanism has not been explained with a suitable physical model. In this paper, a physical model is presented considering four types of forces acting on charged particles in the air. It is demonstrated that the heavier positive ions and lighter negative ions are rapidly separated. Finally, a reversed fair weather electrostatic field is formed by the above charge separation process. The simulation results have instructive significance for future observations and hazard predictions and still need further research.

With the continuous development of science and technology, laser ranging technology will become more efficient, convenient, and widespread, and it has been widely used in the fields of medicine, engineering, video games, and three-dimensional imaging. A time-of-flight (ToF) camera is a three-dimensional stereo imaging device with the advantages of small size, small measurement error, and strong anti-interference ability. However, compared to traditional sensors, ToF cameras typically exhibit lower resolution and signal-to-noise ratio due to inevitable noise from multipath interference and mixed pixels during usage. Additionally, in environments with scattering media, the information about objects gets scattered multiple times, making it challenging for ToF cameras to obtain effective object information. To address these issues, we propose a solution that combines ToF cameras with single-pixel imaging theory. Leveraging intensity information acquired by ToF cameras, we apply various reconstruction algorithms to reconstruct the object’s image. Under undersampling conditions, our reconstruction approach yields higher peak signal-to-noise ratio compared to the raw camera image, significantly improving the quality of the target object’s image. Furthermore, when ToF cameras fail in environments with scattering media, our proposed approach successfully reconstructs the object’s image when the camera is imaging through the scattering medium. This experimental demonstration effectively reduces the noise and direct ambient light generated by the ToF camera itself, while opening up the potential application of ToF cameras in challenging environments, such as scattering media or underwater.