Using Sparse Parts in Fused Information to Enhance Performance in Latent Low-Rank Representation-Based Fusion of Visible and Infrared Images.

Latent Low-Rank Representation (LatLRR) has emerged as a prominent approach for fusing visible and infrared images. In this approach, images are decomposed into three fundamental components: the base part, salient part, and sparse part. The aim is to blend the base and salient features to reconstruct images accurately. However, existing methods often focus more on combining the base and salient parts, neglecting the importance of the sparse component, whereas we advocate for the comprehensive inclusion of all three parts generated from LatLRR image decomposition into the image fusion process, a novel proposition introduced in this study. Moreover, the effective integration of Convolutional Neural Network (CNN) technology with LatLRR remains challenging, particularly after the inclusion of sparse parts. This study utilizes fusion strategies involving weighted average, summation, VGG19, and ResNet50 in various combinations to analyze the fusion performance following the introduction of sparse parts. The research findings show a significant enhancement in fusion performance achieved through the inclusion of sparse parts in the fusion process. The suggested fusion strategy involves employing deep learning techniques for fusing both base parts and sparse parts while utilizing a summation strategy for the fusion of salient parts. The findings improve the performance of LatLRR-based methods and offer valuable insights for enhancement, leading to advancements in the field of image fusion.

Bacterial composition, function and the enrichment of plant growth promoting rhizobacteria (PGPR) in differential rhizosphere compartments of Al-tolerant soybean in acidic soil.

Low pH with aluminum (Al) toxicity are the main limiting factors affecting crop production in acidic soil. Selection of legume crops with acid tolerance and nitrogen-fixation ability should be one of the effective measures to improve soil quality and promote agricultural production. The role of the rhizosphere microorganisms in this process has raised concerns among the research community. In this study, BX10 (Al-tolerant soybean) and BD2 (Al-sensitive soybean) were selected as plant materials. Acidic soil was used as growth medium. The soil layers from the outside to the inside of the root are bulk soil (BS), rhizosphere soil at two sides (SRH), rhizosphere soil after brushing (BRH) and rhizosphere soil after washing (WRH), respectively. High-throughput sequencing of 16S rDNA amplicons of the V4 region using the Illumina MiSeq platform was performed to compare the differences of structure, function and molecular genetic diversity of rhizosphere bacterial community of different genotypes of soybean. The results showed that there was no significant difference in alpha diversity and beta diversity in rhizosphere bacterial community among the treatments. PCA and PCoA analysis showed that BRH and WRH had similar species composition, while BS and SRH also had similar species composition, which indicated that plant mainly affected the rhizosphere bacterial community on sampling compartments BRH and WRH. The composition and abundance of rhizosphere bacterial community among the treatments were then compared at different taxonomic levels. The ternary diagram of phylum level showed that Cyanobacteria were enriched in WRH. Statistical analysis showed that the roots of Al-tolerant soybean BX10 had an enrichment effect on plant growth promoting rhizobacteria (PGPR), which included Cyanobacteria, Bacteroides, Proteobacteria and some genera and species related to the function of nitrogen fixation and aluminum tolerance. The rhizosphere bacterial community from different sampling compartments of the same genotype soybean also were selectively enriched in different PGPR. In addition, the functional prediction analysis showed that there was no significant difference in the classification and abundance of COG (clusters of orthologous groups of proteins) function among different treatments. Several COGs might be directly related to nitrogen fixation, including COG0347, COG1348, COG1433, COG2710, COG3870, COG4656, COG5420, COG5456 and COG5554. Al-sensitive soybean BD2 was more likely to be enriched in these COGs than BX10 in BRH and WRH, and the possible reason remains to be further investigated in the future.

Correlation of the second to fourth digit ratio with the body mass index of infertile men / 中华男科学杂志

<p><b>OBJECTIVE</b>To investigate the relationship between the second to the fourth digit ratio (2D:4D) and body mass index (BMI) in infertile men of the Han ethnic group in Ningxia.</p><p><b>METHODS</b>Using anthropometry, we calculated the mean ratio of 2D:4D and BMI of 197 infertile men and 148 normal healthy male controls, followed by analysis of their relationship.</p><p><b>RESULTS</b>The BMI was correlated positively with the 2D:4D ratio of the left hand in the infertile men (P < 0.05) and in the patients with a higher 2D:4D ratio of the left hand (P < 0.05), but negatively with the 2D:4D ratio of the righ/left (Dr-1) (left: P < 0.01; Dr-l: P < 0.05). The mean 2D: 4D ratio and BMI were both lower in the normal control than in the infertile men, with statistically significant differences in BMI (P < 0.05) and the 2D:4D ratio of the left hand (P < 0.05).</p><p><b>CONCLUSION</b>There is a correlation between the 2D:4D ratio and BMI in infertile men.</p>