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Persistent surveillance is one of the major tasks envisioned for unmanned aerial vehicles in that some regions of interest need to be continuously surveyed. This distinction from the one-time coverage/exploration does not allow a straightforward application of the most exploration techniques to address the persistent surveillance problem. This article introduces and demonstrates a method of alterable artificial potential field to control a group of unmanned aerial vehicles to stay over the region of interest. We present attractive potential field to drive the unmanned aerial vehicles to desirable areas, obstacle potential field to move away from obstacles, collision avoidance potential field to control unmanned aerial vehicles not to collide with others, and formation of potential field to make unmanned aerial vehicles gather in a group. The simulation results show that the proposed approach could generate collision-free path for unmanned aerial vehicles staying over the region of interest for a long endurance.

To implement taxi route planning for aircrafts in Advanced Surface Movement Guidance and Control System (A-SMGCS), discrete event dynamic system (DEDS) modeling method is adopted. The surface movement model based on Petri Nets is proposed taking into account the runway, taxiways and apron running regulations. The surface movement controlling regulations are defined and the conflict detection and resolution is transformed into the state forbidden problem. To describe dynamic behaviors of aircraft surface movement model, the enabling, firing rule and the staying time window are defined. The dynamic route is optimized from static admissible routes. The result of planning indicates that dynamic route planned can decrease the potential conflicts, reduce waiting time of aircrafts and increase the capacity of airport.

Visual tracking in condition of occlusion has been a challenging task over years. Recently, part-based algorithms have made great progress in handling occlusion. However, the existing part-based methods neglect different importance between central parts and marginal parts. Besides, scale variation remains a difficulty for part-based tracking. In this paper, we propose a novel part-based tracker to solve the above problems. Specifically, we introduce a visual attention mechanism recurrently exploiting co-saliency of target to guide the sampling of parts, which aims to highlight the importance of salient parts and guarantee the semantic integrity so as to improve the robustness handling occlusion. Considering the drift of prediction caused by mutual influence of parts, we implement the non-maximum suppression operation to reduce the high overlaps between parts, and introduce an effective correlation filter as base tracker. To balance the global distribution and local partiality of parts, appropriate update strategy including scale estimation method inspired by particle filters and correlation filters, Hough-voting scheme for target's center prediction, and principles of part resampling are also fused into the algorithm. The experimental results on VOT 2017 and OTB-50 benchmarks showed that the proposed method is in comparison to the state-of-the-art trackers and good at dealing with occlusion situations particularly.

PurposeTo evaluate the prognostic value of metabolic syndrome (MetS) in upper tract urothelial carcinoma (UTUC) patients based on propensity score matching (PSM) analysis.Patients and MethodsA total of 573 patients with UTUC after radical nephroureterectomy were included at Peking University People’s Hospital from January 2007 to April 2021. MetS was diagnosed according to the criteria of Chinese Diabetes Society and was defined as the presence of 3 or more of the following 4 conditions (obesity, hyperglycemia, hypertension, high triglycerides and/or low high-density lipoprotein-cholesterol). Patients were divided into two groups based on whether they had MetS, whose variables were adjusted using 1:1 PSM analysis with a caliber of 0.02 to minimize selection bias. Univariate and multivariate Cox regression analysis were used to evaluate the association of MetS and its components with pathological outcomes after adjusting preoperative confounders by propensity score matching. The Kaplan-Meier method was used to estimate overall survival (OS), cancer-specific survival (CSS), and intravesical recurrence-free survival (IVRFS) after surgery.ResultsMetS was significantly correlated with older age, a history of coronary heart disease, high Charlson Comorbidity Index, low estimated Glomerular filtration rate, and low aspartate/alanine aminotransferase ratio (all P<0.05). Multivariate Cox regression analysis and Kaplan-Meier curves demonstrated that MetS showed no statistical correlation with lower OS or IVRFS and approaching significance with lower CSS (P=0.063) before PSM. After PSM, the 5-year OS, CSS, and IVRFS were 64.1%, 74.7%, and 77.2%, respectively, in the MetS group, compared with 67.4%, 78.8%, and 77.2%, respectively, in non-MetS group. Univariate Cox regression analyses showed that MetS and its components were not associated with decreased OS, CSS, or IVRFS (all P>0.05).ConclusionIn our study, no statistical difference was found between MetS and survival outcomes in UTUC, except a marginal association with lower CSS. Further studies are needed to evaluate the role of MetS and its each single component on UTUC.