99 research outputs found
A Learning-Based Approach for Distributed Planning and Coordination of Airport Surface Movement Operations
No full textAgent-based distributed planning and coordination has shown promising results in controlling operations in complex systems such as those present at airports. Distributed planning differs from centralised approaches because it is performed by several agents, which coordinate plans with each other in order to meet a global objective. In this research, we examine airport surface movement operations and focus specifically on improving the conflict detection abilities of a Multi-Agent Path Finding (MAPF) approach for distributed planning and coordination using machine learning. Our MAPF proposal is built on top of a distributed CBS-based algorithm implemented in an existing Multi-Agent System (MAS) model of Amsterdam Schiphol Airport (AAS). In the proposed approach, we use a delegated Multi-Agent System (dMAS), firstly, to propagate information related to the intended aircraft paths and, secondly, to perform the conflict detection task of the CBS algorithm. To achieve these, the dMAS accesses a set of Artificial Neural Networks (ANNs), each allocated to specific taxiway segments to obtain traversal time estimates of aircraft intending to use those segments. Propagated aircraft intentions are used as predictors for future traversal time predictions either during the intention propagation phase or during CBS conflict detection. The proposed planning and coordination model and three of its variants were tested on a real-world flight schedule extracted from ADS-B ground tracks. Comparisons with a baseline approach that implements a forward kinematic simulation for conflict detection revealed that dMAS-CBS offered more precise conflict predictions while being less prone to Type I errors. More specifically, under scenarios where the airport operates at peak capacity, dMAS-CBS was twice as precise and produced up to five times fewer false positives predictions than the baseline approach.Aerospace Engineerin
7D supersymmetric Yang-Mills on curved manifolds
No full textWe study 7D maximally supersymmetric Yang-Mills theory on curved manifolds that admit Killing spinors. If the manifold admits at least two Killing spinors (Sasaki-Einstein manifolds) we are able to rewrite the supersymmetric theory in terms of a cohomological complex. In principle this cohomological complex makes sense for any K-contact manifold. For the case of toric Sasaki-Einstein manifolds we derive explicitly the perturbative part of the partition function and speculate about the non-perturbative part. We also briefly discuss the case of 3-Sasaki manifolds and suggest a plausible form for the full non-perturbative answer
Endoscopic retrograde cholangiopancreatography-related perforations: Diagnosis and management
No full textExpanding the boundaries of minimally invasive surgery: the feasibility of robotic natural orifice transluminal extraction colectomy and robotic no-incision colectomy in colorectal practice
No full textPurpose Minimally invasive surgery offers reduced trauma, accelerated recovery, and shorter hospital stays. Robotic technology further enhances laparoscopic precision, particularly in colorectal procedures. This study investigated the safety and effectiveness of robotic natural orifice transluminal extraction colectomy (R-NOTEC) and robotic no-incision colectomy (R-NIC), comparing these techniques to the conventional robotic colectomy. Methods Outcomes of patients undergoing robotic-assisted colorectal resection—either conventional robotic colectomy or R-NOTEC/R-NIC—using a single docking technique at a tertiary hospital over 3 years were analyzed. All patients were managed according to established Enhanced Recovery After Surgery protocols. Results In total, 100 patients were included, with 25 receiving R-NOTEC or R-NIC. The median age was 65 years (range, 30–82 years), and the median body mass index was 31.0 kg/m2 (range, 20.1–43.0 kg/m2). The median length of stay was significantly shorter in the R-NOTEC/R-NIC group than in the conventional robotic group (2.0 days vs. 3.4 days, P=0.021). Other outcomes, such as circumferential resection margin status, lymph node yield, and mortality, were similar between groups. The R-NOTEC/R-NIC group exhibited a slightly lower complication rate, as well as less opioid use. No conversions to open surgery occurred in either group. Conclusion R-NOTEC/R-NIC offer significant promise in colorectal surgery by minimizing trauma, expediting recovery, and maintaining oncologic safety. Nevertheless, these procedures require specialized surgical expertise and careful patient selection. Further research should focus on long-term outcomes and standardization of these techniques
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