A study on the influence of community spiritual comfort service on the mental health of older people.

Background: China is experiencing rapid population aging, with the proportion of older adult people aged 60 and above reaching 19. 8% of the total population in 2022. With the growth of age, the physical function of older adults declines and their mental health is getting worse, with the increasing trend of empty nesting and childlessness, older adults lack information and social interaction with others and fall into social isolation, loneliness and some mental health problems, the proportion of older adults with mental health problems gradually rises and the mortality rate increases incrementally, requiring effective ways to intervene in the mental health of older adults and promote healthy aging.

Resection or Biopsy: The Efficacy of Different Surgical Approaches for Primary Central Nervous System Lymphoma.

Aim: To analyze the efficacy of surgical resection versus brain biopsy combined with postoperative chemotherapy for primary central nervous system lymphoma (PCNSL) and to discuss a clinically standardized treatment protocol.

Material And Methods: Patients with a pathological diagnosis of PCNSL and subsequent chemotherapy between 2016 and 2021 at Northern Jiangsu People?s Hospital were selected and divided into groups according to whether they underwent microsurgical resection or stereotactic needle biopsy. Statistical analyses were performed to compare efficacy and safety in the two groups.

Point Cloud Semantic Segmentation Network Based on Multi-Scale Feature Fusion.

The semantic segmentation of small objects in point clouds is currently one of the most demanding tasks in photogrammetry and remote sensing applications. Multi-resolution feature extraction and fusion can significantly enhance the ability of object classification and segmentation, so it is widely used in the image field. For this motivation, we propose a point cloud semantic segmentation network based on multi-scale feature fusion (MSSCN) to aggregate the feature of a point cloud with different densities and improve the performance of semantic segmentation.

Spatial Aggregation Net: Point Cloud Semantic Segmentation Based on Multi-Directional Convolution.

Semantic segmentation of 3D point clouds plays a vital role in autonomous driving, 3D maps, and smart cities, etc. Recent work such as PointSIFT shows that spatial structure information can improve the performance of semantic segmentation. Motivated by this phenomenon, we propose Spatial Aggregation Net (SAN) for point cloud semantic segmentation.