Recently, new semantic segmentation and object detection methods have been proposed for direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information and its robustness to dynamic changes in the environment. In addition, the cost of LiDAR sensors has decreased in recent years, which is an important factor for many application scenarios. The challenge with 3D LiDAR sensors like the Velodyne HDL-64E S2 is that they can output large 3D data at up to 1,300,000 points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real-time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed, but although it is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, we propose a new approach to semantic segmentation in forestry that uses a systematic sampling method in which the local neighbors of each point are retained to preserve geometric details. Our approach has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation in large datasets such as Semantic3D. We also present a preliminary study on the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.

Background: To identify and appraise the impacts and effectiveness of counseling interventions based on the 5A model on indicators of physical activity in adults. Methods: In May, 2022, a systematic review was carried out. Searches were performed in Embase, Lilacs, Pubmed, Scielo, Scopus, Sportdiscus and Web of Science. To avoid potential losses searches also were made in Google Scholar and in reference lists. Assessment of studies, data extraction and synthesis took place independently by two researchers. Results: Four studies composed the synthesis, which involved people with an average age between 40 and 55 years, being women in the majority of the samples. It was observed that counseling was carried out in conjunction with other strategies, such as drawing up an action plan, sending text messages and offering educational material. Only one study showed a statistically significant difference between the intervention and control groups in the “daily number of steps” indicator. Conclusions: counseling based on the 5A model did not reflect significant findings in relation to physical activity. Considering that behavior change for many people is neither a simple nor a quick process and that the 5A model is promising for other behavioral indicators, we indicate the need to carry out new intervention studies, with an expanded focus in relation to themes related to physical activity (e.g., types, dos-es, risks, benefits, identification of barriers and assessment) and, in parallel, the offer of practices in the Primary Health Care setting.

(1) Background: The HIV subtype D is generally associated with a faster decline in CD4+ T cell counts, a higher viral load, and a faster progression to AIDS. However, it is still poorly characterized in Brazil. In this study, we used genomics and epidemiological data to investigate the transmission dynamics of HIV subtype D in the state of Bahia, Northeast Brazil. (2) Methods: to achieve this goal, we obtained four novel HIV-1 subtype D partial pol genome sequences using the Sanger method. To understand the emergence of this novel subtype in the state of Bahia, we used phylodynamic analysis on a dataset comprising 3,704 pol genome sequences downloaded from the Los Alamos database. (3) Results: Our analysis revealed three branching patterns, indicating multiple introductions of the HIV-1 subtype D in Brazil from the late 1980s to the late 2000s and a single introduction event in the state of Bahia. Our data further suggest that these introductions most likely originated from European, Eastern African, Western African and Southern African countries. (4) Conclusion: Understanding the distribution of HIV-1 viral strains and their temporal dynamics is crucial for monitoring the real-time evolution of circulating subtypes and recombinant forms, as well as for designing novel diagnostic and vaccination strategies. We advocate for a shift to active surveillance, to ensure adequate preparedness for future epidemics mediated by emerging viral strains.