Slam

Immune checkpoint inhibitors have limited efficacy in hepatocellular carcinoma (HCC). Macrophages are the most abundant immune cells in HCC, suggesting that a better understanding of the intrinsic processes by which tumor cells regulate macrophages could help identify strategies to improve response to immunotherapy. As signaling lymphocytic activation molecule (SLAM) family members regulate various immune functions, we investigated the role of specific SLAM receptors in the immunobiology of HCC. Comparison of the transcriptomic landscapes of immunotherapy-responsive and non-responsive advanced HCC patients identified SLAMF7 upregulation in immunotherapy-responsive HCC, and HCC patients who responded to immunotherapy also displayed higher serum levels of SLAMF7...

β-barrel membrane proteins populate the outer membrane of Gram-negative bacteria, mitochondria, and chloroplasts, playing significant roles in multiple key cellular pathways. Characterizing the functions of these membrane proteins in vivo is often challenging due to the complex protein network in the periplasm of Gram-negative bacteria (or intermembrane space in mitochondria and chloroplasts) and the presence of other outer membrane proteins. In vitro reconstitution into lipid-bilayer-like environments such as nanodiscs or proteoliposomes provides an excellent method for examining the specific function and mechanism of these membrane proteins in an isolated system...

Temozolomide (TMZ) resistance remains the major obstacle in the treatment of glioblastoma (GBM). Lactylation is a novel post-translational modification that is involved in various tumors. However, whether lactylation plays a role in GBM TMZ resistance remains unclear. Here it is found that histone H3K9 lactylation (H3K9la) confers TMZ resistance in GBM via LUC7L2-mediated intron 7 retention of MLH1. Mechanistically, lactylation is upregulated in recurrent GBM tissues and TMZ-resistant cells, and is mainly concentrated in histone H3K9...

In the autonomous navigation of mobile robots, precise positioning is crucial. In forest environments with weak satellite signals or in sites disturbed by complex environments, satellite positioning accuracy has difficulty in meeting the requirements of autonomous navigation positioning accuracy for robots. This article proposes a vision SLAM/UWB tightly coupled localization method and designs a UWB non-line-of-sight error identification method using the displacement increment of the visual odometer. It utilizes the displacement increment of visual output and UWB ranging information as measurement values and applies the extended Kalman filtering algorithm for data fusion...

An optimized robot path-planning algorithm is required for various aspects of robot movements in applications. The efficacy of the robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms because of its heuristic approach. However, the performance of the conventional A* algorithm is suboptimal for the time, space, and number of search nodes, depending on the robot motion block (RMB). To address these challenges, this paper proposes an optimal RMB with an adaptive cost function to improve performance...

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network, GY, based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and the SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction...

An autonomous, power-assisted Turtlebot is presented in this paper in order to enhance human mobility. The turtlebot moves from its initial position to its final position at a predetermined speed and acceleration. We propose an intelligent navigation system that relies solely on individual instructions. When there is no individual present, the Turtlebot remains stationary. Turtlebot utilizes a rotating Kinect sensor in order to perceive its path. Various angles were examined in order to demonstrate the effectiveness of the system in experiments conducted on a U-shaped experimental pathway...

This study analysed critical movement demands of tennis match-play to better inform contemporary approaches to athlete preparation and training. HawkEye data from matches during the 2021 and 2022 Australian Open were utilised. Distance was aggregated for movement cycles, points, games, sets, and matches, alongside total shots played. Data was collated for males (best-of-five sets) and females (best-of-three sets) allowing comparisons both within and between sexes. Overall, no differences within sexes were evident for total distance, however males traversed further per match than females (MDE = 809 ± 139m, ES = 0...

IMPORTANCE: Image guidance is an important adjunct for endoscopic sinus and skull base surgery. However, current systems require bulky external tracking equipment, and their use can interrupt efficient surgical workflow. OBJECTIVE: To evaluate a trackerless surgical navigation system using 3-dimensional (3D) endoscopy and simultaneous localization and mapping (SLAM) algorithms in the anterior skull base. DESIGN, SETTING, AND PARTICIPANTS: This interventional deceased donor cohort study and retrospective clinical case study was conducted at a tertiary academic medical center with human deceased donor specimens and a patient with anterior skull base pathology...

As computer vision algorithms increase in capability, their applications in clinical systems will become more pervasive. These applications include: diagnostics, such as colonoscopy and bronchoscopy; guiding biopsies, minimally invasive interventions, and surgery; automating instrument motion; and providing image guidance using pre-operative scans. Many of these applications depend on the specific visual nature of medical scenes and require designing algorithms to perform in this environment. In this review, we provide an update to the field of camera-based tracking and scene mapping in surgery and diagnostics in medical computer vision...

Visual-inertial SLAM (VI-SLAM) is a key technology for Augmented Reality (AR), which allows the AR device to recover its 6-DoF motion in real-time in order to render the virtual content with the corresponding pose. Nowadays, smartphones are still the mainstream devices for ordinary users to experience AR. However the current VI-SLAM methods, although performing well on high-end phones, still face robustness challenges when deployed on a larger stock of mid- and low-end phones. Existing VI-SLAM datasets use either very ideal sensors or only a limited number of devices for data collection, which cannot reflect the capability gaps that VI-SLAM methods need to solve when deployed on a large variety of phone models...

The number of migrants entering the United States in 2023 shattered records. Despite prevailing narratives, immigrants, on average, contribute substantially to US society. Rather than slamming the door in the faces of newcomers, federal, state, and local policymakers should provide services to these individuals to ensure they have the maximum opportunity to thrive, both for their own benefit and for the greater social good. Public health and social science research provides ample rigorous evidence on the benefits of different types of investments in these vulnerable individuals upon their arrival in our country...

BACKGROUND: The database we introduce is a pivotal component of the LIFE SNAILS project (Support and Naturalisation in Areas of Importance for Land Snails). This initiative is dedicated to safeguarding three endangered species of terrestrial molluscs, specifically, two snails ( Oxychilusagostinhoi Martins 1981 and Leptaxisminor Backhuys, 1975) and a semi-slug ( Plutoniaangulosa (Morelet, 1860)), all of which are single island endemics from Santa Maria Island and face significant threats towards their populations...

Little is known about the difference of anthropometry and physical fitness between the finalist and eliminated player in the NBA all star slam dunk contest. This study aimed to compare the difference on anthropometric and physical fitness indicator in the combine draft between finalist and eliminated player in the national basketball association all star slam dunk contest. Draft data of 32 basketball players (N = 32, age in draft year: 20.69±2.28 years old, height without shoes: 196.75±8.68 cm, weight: 96...

Salmonella Typhimurium is a highly lethal pathogenic bacterium in weaned piglets, causing significant treatment costs and economic losses in the swine industry. Additionally, due to its ability to induce zoonotic diseases, resulting in harm to humans through the transmission of the pathogen from pork, it presents a serious public health issue. Bacteriophages (phages), viruses that infect specific bacterial strains, have been proposed as an alternative to antibiotics for controlling pathogenic bacteria. In this study, we isolated SLAM_phiST1N3, a phage infecting a multidrug-resistant (MDR) S...

We demonstrate a pre-chirp and gain jointly managed Yb-fiber laser that drives simultaneous label-free autofluorescence-multiharmonic (SLAM) medical imaging. We show that a gain managed Yb-fiber amplifier produces high-quality compressed pulses when the seeding pulses exhibit proper negative pre-chirp. The resulting laser source can generate 43-MHz, 34-fs pulses centered at 1110 nm with more than 90-nJ energy. We apply this ultrafast source to SLAM imaging of cellular and extracellular components in various human tissues of intestinal adenocarcinoma, lung adenocarcinoma, and liver...

Visual-inertial odometry (VIO) algorithms, fusing various features such as points and lines, are able to improve their performance in challenging scenes while the running time severely increases. In this paper, we propose a novel lightweight point-line visual-inertial odometry algorithm to solve this problem, called LRPL-VIO. Firstly, a fast line matching method is proposed based on the assumption that the photometric values of endpoints and midpoints are invariant between consecutive frames, which greatly reduces the time consumption of the front end...

As a fundamental issue in robotics academia and industry, indoor autonomous mobile robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information about their working environment and themselves, which can be realized through sensors and the extraction of corresponding information from the measurements of these sensors. The application of sensing technologies can enable mobile robots to perform localization, mapping, target or obstacle recognition, and motion tasks, etc. This paper reviews sensing technologies for autonomous mobile robots in indoor scenes...

Outdoor Location-Based Augmented Reality (LAR) applications require precise positioning for seamless integrations of virtual content into immersive experiences. However, common solutions in outdoor LAR applications rely on traditional smartphone sensor fusion methods, such as the Global Positioning System (GPS) and compasses, which often lack the accuracy needed for precise AR content alignments. In this paper, we introduce an innovative approach to enhance LAR anchor precision in outdoor environments. We leveraged Visual Simultaneous Localization and Mapping (VSLAM) technology, in combination with innovative cloud-based methodologies, and harnessed the extensive visual reference database of Google Street View (GSV) , to address the accuracy limitation problems...

Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics, enabling autonomous robots to navigate and create maps of unknown environments. Nevertheless, the SLAM methods that use cameras face problems in maintaining accurate localization over extended periods across various challenging conditions and scenarios. Following advances in neuroscience, we propose NeoSLAM, a novel long-term visual SLAM, which uses computational models of the brain to deal with this problem. Inspired by the human neocortex, NeoSLAM is based on a hierarchical temporal memory model that has the potential to identify temporal sequences of spatial patterns using sparse distributed representations...