PCB-RandNet: Rethinking Random Sampling for LIDAR Semantic Segmentation in Autonomous Driving Scene

Fast and efficient semantic segmentation of large-scale LiDAR point clouds is a fundamental problem in autonomous driving. To achieve this goal, the existing point-based methods mainly choose to adopt Random Sampling strategy to process large-scale point clouds. However, our quantative and qualitative studies have found that Random Sampling may be less suitable for the autonomous driving scenario, since the LiDAR points follow an uneven or even long-tailed distribution across the space, which prevents the model from capturing sufficient information from points in different distance ranges and reduces the model's learning capability. To alleviate this problem, we propose a new Polar Cylinder Balanced Random Sampling method that enables the downsampled point clouds to maintain a more balanced distribution and improve the segmentation performance under different spatial distributions. In addition, a sampling consistency loss is introduced to further improve the segmentation performance and reduce the model's variance under different sampling methods. Extensive experiments confirm that our approach produces excellent performance on both SemanticKITTI and SemanticPOSS benchmarks, achieving a 2.8% and 4.0% improvement, respectively. The source code is available at https://github.com/huixiancheng/PCB-RandNet.Comment: Accepted by ICRA 2024. Code: https://github.com/huixiancheng/PCB-RandNe

Response of Soil Nitrogen Components and <i>nirK</i>- and <i>nirS</i>-Type Denitrifying Bacterial Community Structures to Drip Irrigation Systems in the Semi-Arid Area of Northeast China

Denitrification is a key process in soil available nitrogen (N) loss. However, the effects of different water-saving irrigation systems on soil N components and denitrifying bacterial communities are still unclear. In this study, quantitative fluorescence PCR and Illumina MiSeq sequencing were used to investigate the effects of three main irrigation systems, conventional flooding irrigation (FP), shallow buried drip irrigation (DI), and mulched drip irrigation (MF), on the abundance, community composition, and diversity of soil nirK- and nirS-type denitrifying bacteria in the semi-arid area of Northeast China, and to clarify the driving factors of nirK- and nirS-type denitrifying bacterial community variations. The results showed that, compared with FP, MF significantly increased soil moisture, alkaline hydrolyzed nitrogen (AHN), nitrate nitrogen (NO3−-N), non-acid hydrolyzed nitrogen (AIN), and amino sugar nitrogen (ASN), but significantly decreased the contents of ammonium nitrogen (NH4+-N) and acid hydrolyzed ammonium nitrogen (AN). The irrigation system changed the relative abundance of the dominant genera of denitrifying bacteria, DI and MF significantly increased nitrate reductase (NR) and nitrite reductase (NiR) activities, and MF significantly increased the diversity of nirK- and nirS-type denitrifying bacteria but significantly decreased the richness. The community structure of nirK- and nirS-type denitrifying bacteria was significantly different among the three irrigation systems. NO3−-N was the main driving factor affecting the community structure of nirS-type denitrifying bacteria, and moisture significantly affected the community structure of nirK-type denitrifying bacteria. DI and MF significantly increased the abundance of nirK- and nirS-type denitrifying bacteria and also increased the abundance ratio of nirS/nirK genes. Therefore, although DI and MF significantly increased the abundance of denitrifying microorganisms, they did not lead to an increase in the N2O emission potential

Effects of Balancing Exchangeable Cations Ca, Mg, and K on the Growth of Tomato Seedlings (<i>Solanum lycopersicum</i> L.) Based on Increased Soil Cation Exchange Capacity

(1) Background: Previous research has demonstrated that the cation exchange capacity (CEC) of soil and the balance of exchangeable cations Ca, Mg, and K are key factors affecting plant growth and development. We hypothesized that balancing exchangeable cations based on increased CEC would improve plant growth and development. (2) Methods: This study conducted a two-phase experiment to evaluate methods for increasing soil CEC and the effects of increasing CEC and balancing Ca, Mg, and K on plant growth. Therefore, we first conducted a soil culture experiment using organic fertilizer, montmorillonite, and humic acid to investigate fertilizers that can effectively increase CEC in the short term. Then, a tomato seedling pot experiment was conducted using the control (CK) and OMHA fertilizer-treated soils collected from soil culture experiments. The CK and OMHA treatment soils were constructed with balanced exchangeable cations and an unbalanced control, respectively. (3) Results: The soil culture experiments revealed that the combination of organic fertilizer, montmorillonite, and humic acid (OMHA treatment) had the most significant effect on increasing CEC. The CEC of the OMHA treatment increased by 41.07%, reaching 27.10 cmol·kg−1. The tomato pot experiments demonstrated that balancing the exchangeable cations in OMHA soil improved the Mg and K nutrition of tomato seedlings and significantly increased SPAD, leaf nitrogen content, and dry weight, while balancing the exchangeable cations in CK soil improved only the K nutrition of tomato seedlings. (4) Conclusions: Overall, balancing exchangeable cations based on increasing CEC can improve soil nutrient availability and alleviate the competition effects of Ca, Mg, and K cations. Low CEC and imbalanced exchangeable cations can be detrimental to tomato seedling growth