Fast Track Research Articles

Graph Based RFID Grouping for Fast and Robust Inventory Tracking

Graph Based RFID Grouping for Fast and Robust Inventory Tracking

Image-Based Fast Finite-Time Target Tracking Control of Onboard Inertially Stabilized Camera Platform

Image-Based Fast Finite-Time Target Tracking Control of Onboard Inertially Stabilized Camera Platform

Multi-nozzle thrust matching control of STOVL engine

Abstract A multi-nozzle thrust matching control method is proposed in this paper to provide the thrust vector required of lift-fan type short takeoff and vertical landing (STOVL) aircrafts during hover. Attitude-matched thrust commands for each nozzle of STOVL engine are generated based on a six-degree-of-freedom aircraft model. The thrust controller is divided into two blocks according to the coupling analysis. Based on the combination of linear matrix inequality and differential evolution algorithm, a multi-target controller parameters optimization method is proposed to achieve stable disturbance suppression and fast command tracking. Simulations results show that the proposed command generated model is effective and the decoupling control method can effectively suppress the coupling between the loops and realize the matching control of thrust.

Sensorless contact force estimation and robust impedance control for a quadrotor manipulation system

The research on aerial manipulation systems has been increased rapidly in recent years. These systems are very attractive for a wide range of applications due to their unique features. However, dynamics, control and manipulation tasks of such systems are quite challenging because they are naturally unstable, have very fast dynamics, have strong nonlinearities, are very susceptible to parameters variations due to carrying a payload besides the external disturbances, and have complex inverse kinematics. In addition, the manipulation tasks require estimating (applying) a certain force of (at) the end-effector as well as the accurate positioning of it. Thus, in this article, a robust force estimation and impedance control scheme is proposed to address these issues. The robustness is achieved based on the Disturbance Observer (DOb) technique. Then, a tracking and performance low computational linear controller is used. For teleoperation purpose, the contact force needs to be identified. However, the current developed techniques for force estimation have limitations because they are based on ignoring some dynamics and/or requiring of an indicator of the environment contact. Unlike these techniques, we propose a technique based on linearization capabilities of DOb and a Fast Tracking Recursive Least Squares (FTRLS) algorithm. The complex inverse kinematics problem of such a system is solved by a Jacobin based algorithm. The stability analysis of the proposed scheme is presented. The algorithm is tested to achieve tracking of task space reference trajectories besides the impedance control. The efficiency of the proposed technique is enlightened via numerical simulation.

Vehicle Motion Control for Overactuated Vehicles to Enhance Controllability and Path Tracking

The motion control of vehicles poses distinct challenges for both vehicle stability and path tracking, especially under critical environmental and driving conditions. Overactuated vehicles can effectively utilize the available tyre–road friction potential by leveraging additional actuators, thus enhancing their stability and controllability even in challenging scenarios. This paper introduces a novel modular upstream control architecture for overactuated vehicles, integrating a fast and robust linear time-varying model predictive path and speed tracking controller with a model following approach and nonlinear control allocation to form a holistic vehicle motion controller. The architecture decouples the path and speed tracking task from the actuator allocation, where torque vectoring and rear-wheel steering are applied to achieve linear understeer reference vehicle behavior. It allows for the use of a simpler path tracking controller, enabling long preview horizons and enhanced computational efficiency. Nonlinearities, such as the mutual influence of lateral and longitudinal tyre forces, are accounted for within the control allocation. The simulation results demonstrate that the proposed control architecture and overactuation improve vehicle stability in critical driving conditions and reduce path tracking errors compared to a dual-motor vehicle.

Impact of High-Intensity Interval Training (HIIT) on Patient Recovery After Myocardial Infarction and Stroke: A Fast Track to Fitness

Impact of High-Intensity Interval Training (HIIT) on Patient Recovery After Myocardial Infarction and Stroke: A Fast Track to Fitness

Application of machine learning for detecting and tracking turbulent structures in plasma fusion devices using ultra fast imaging

This study explores the application of machine learning techniques for detecting and tracking plasma filaments around the boundary of magnetically confined tokamak plasmas. Plasma filaments, also called blobs, are responsible for enhanced turbulent transport across magnetic field lines, and their accurate characterization is crucial for optimizing the performance of magnetic fusion devices. We present a novel approach that combines machine learning methods applied to data obtained from ultra-fast cameras, including YOLO (You Only Look Once) for object detection, semantic segmentation, and specific tracking methods. This approach enables fast and accurate detection and tracking of filaments while overcoming the limitations of conventional methods, which are time-consuming and prone to human subjectivity. A significant advance in our study lies in the development of a method for automatically labeling a large batch of data, which greatly facilitates the training of supervised machine learning algorithms. Using these techniques, we obtained promising results demonstrating a significant improvement over conventional tracking methods, achieving a detection accuracy of up to 98.8%, while reducing the inference time per frame by 15% to 31% compared to conventional Kalman filter tracking. These results open up new perspectives for investigating turbulent phenomena in tokamaks, and could have important implications for the development of controlled nuclear fusion.

Weld Seam Recognition and Tracking With Omnidirectional Wall-Climbing Robot for Spherical Tank Inspection

Abstract Weld seams of in-service pressure storage equipment, such as spherical tanks, require regular inspection to ensure safe operation. Wall-climbing robots can replace manual operations, increasing inspection efficiency and reducing maintenance costs. High precision and fast weld seam identification and tracking are beneficial for improving the automated navigation and spatial positioning of wall-climbing robots. This study proposes a weld seam recognition and tracking method with the omnidirectional wall-climbing robot for spherical tank inspection. Based on deep learning networks, the robot has a front-mounted camera to recognize weld seams and extract weld paths. Weld seam deviation data (drift angle and offset distance) were used in real time to provide feedback on the robot's relative position. For the robot to quickly correct deviations and track weld seams, a seam path-tracking controller based on sliding mode control was designed and simulated. Weld recognition experiments revealed that the robot can accurately recognize and extract weld paths, and the recognition time for each image was approximately 0.25 s. In the weld seam tracking experiments, the robot could successfully track longitudinal and transverse weld seams at different speeds (from 0.05 to 0.2 m/s). During the process of weld seam tracking, the robot angle error was kept within ±3 deg, and the maximum offset distance was less than ±35 mm. Field tests on a 3000-m3 spherical tank were conducted to verify the practicability and effectiveness of the weld seam tracking system. This robotic system can autonomously complete weld seam identification and tracking, which promotes the automation of spherical tank inspection and maintenance.

Adaptive Two-Degree-of-Freedom Robust Gain-Scheduling Control Strategy

This study introduces a novel tracking control strategy tailored to aeroengines, which are highly nonlinear and characterized by significant uncertainty. The proposed method entails a robust extended Kalman filter (REKF) enhanced by a forgetting factor for improved performance. An accompanying augmented, mixed onboard adaptive model based on the REKF precisely estimates and manages engine performance degradation. This advanced model effectively counters the degradation term in the perturbation block of the engine’s uncertain model. Using this strategic approach, a robust gain-scheduling controller was constructed and was found to outperform its predecessors, marking a notable advancement in control system design. Controlling twin rotor multi-input, multi-output (MIMO) systems is a highly complex process due to model uncertainties and unpredictable external disturbances. To address these challenges, we constructed an adaptive two-degree-of-freedom robust gain-scheduling controller (ATDF-RGSC) using a mixed sensitivity approach. Rigorous performance analysis confirms that this controller offers enhanced robustness, faster tracking, and more precise disturbance attenuation compared to other methods. These advanced control strategies successfully manage uncertainties and disturbances, improving performance metrics in both simulated and experimental scenarios. The proposed method may significantly enhance the safety and reliability of aeroengines and MIMO systems in practical applications.

CTIM-25. PHASE2B/3 STUDY OF NEOANTIGEN-SPECIFIC T CELL IMMUNOTHERAPY IN NEWLY DIAGNOSED O6 – METHYLGUANINE METHYLTRANSFERASE UNMETHYLATED (MGMT -) GLIOBLASTOMA

Abstract MGMT- glioblastoma (GBM) is the most common malignant primary brain tumor, yet outcomes have not improved in decades despite intensive investigations. TVI-AST-008 is a randomized clinical trial of a novel neoantigen-specific T cell immunotherapy regimen proven invariably curative in rodent models and clinically effective in trials of patients with relapsed/resistant GBM. TVAX neoantigen-specific T cell immunotherapy exploits the fact that cancer cells express neoantigens, and adoptive transfer can bypass the immunosuppressive milieu near the resection cavity. In this manner, TVAX effector T cells initiate apoptosis in any residual GBM. After pathologic confirmation, autologous GBM tumor tissue sent to the TVAX GMP manufacturing facility is irradiated and utilized for proprietary vaccine production. Patients are vaccinated with a series of two intradermal injections and the resulting cancer neoantigen-specific T cells are harvested by leukapheresis. These T cells are activated and proliferated ex vivo by TVAX manufacturing to generate effector T cells. These are re-infused following standard radio-chemotherapy, followed by low-dose interleukin-2 to further stimulate T cell proliferation. In the study, MGMT- GBM patients are randomly assigned to treatment or control arms. Patients in the treatment arm undergo vaccination, then standard concurrent IMRT-chemotherapy, followed by re-infusion of TVAX autologous effector T cells. Patients in the control arm undergo standard IMRT-chemotherapy followed by adjuvant chemotherapy with temozolomide. TVI-AST-008 is an ongoing, randomization-controlled study with Fast Track designation from the FDA. The primary end point is overall survival. Additional end points include progression free survival, safety and immune response. Patients are followed with physical exams and surveillance MRI for evidence of disease progression. The trial is targeted for 15 centers in the US.

A Machine Learning Approach for Breast Cancer Risk Prediction in Digital Mammography

Breast cancer is among the most prevalent cancers in the female population globally. Therefore, screening campaigns as well as approaches to identify patients at risk are particularly important for the early detection of suspect lesions. This study aims to propose a workflow for the automatic classification of patients based on one of the most relevant risk factors in breast cancer, which is represented by breast density. The proposed classification methodology takes advantage of the features automatically extracted from mammographic images, as digital mammography represents the major screening tool in women. Textural features were extracted from the breast parenchyma through a radiomics approach, and they were used to train different machine learning algorithms and neural network models to classify the breast density according to the standard Breast Imaging Reporting and Data System (BI-RADS) guidelines. Both binary and multiclass tasks have been carried out and compared in terms of performance metrics. Preliminary results show interesting classification accuracy (93.55% for the binary task and 82.14% for the multiclass task), which are promising compared to the current literature. As the proposed workflow relies on straightforward and computationally efficient algorithms, it could serve as a basis for a fast-track protocol for the screening of mammograms to reduce the radiologists’ workload.

Variable impedance control for synchronizer position tracking based on gain scheduling

Achieving fast and stable synchronizer position tracking control can greatly improve the power and comfort of transmission shifting. In order to further improve the shift speed and stability of the synchronizer, this article takes the synchronizer control of a three-speed seamless transmission as the research object and proposes a variable impedance control method based on gain scheduling. Firstly, dynamic models of the shift actuator and synchronizer was established. Then, an impedance outer loop controller and a position inner loop controller were designed. In the impedance outer loop, adjust the synchronizer reference position based on the difference between the reference shift force and the actual shift force. At the same time, based on the actual control requirements of different motion stages of the synchronizer, the optimal impedance control parameters for each stage are selected for gain scheduling control. In the position inner loop, a prescribed performance-active disturbance rejection control is adopted, which solves the problem of system disturbance while ensuring the instantaneous performance of position tracking. Finally, simulations and bench tests were conducted on the position tracking control of synchronizer. The simulation and bench test results show that the control strategy proposed achieves fast and stable synchronizer position tracking, with superior control performance, which preliminarily verifies the effectiveness of the control strategy.

Coinfections and iterative detection of respiratory viruses among 17,689 patients between March 2021 and December 2022 in Southern France

ObjectivesWe aimed to describe coinfections and iterative infections with respiratory viruses diagnosed over a 22-month period in 2021–2022 in public university hospitals of the second largest French city. Material and methodsRespiratory virus infections were diagnosed by qPCR with the Fast Track Diagnostics Respiratory Pathogens 21 on nasopharyngeal swabs collected between 01/03/2021–31/10/2022 and sent for routine diagnosis purpose to our clinical microbiology-virology laboratory at public university hospitals of Marseille, Southern France. ResultsNasopharyngeal swabs from 17,689 patients were tested, of which 8,133 (46 %) were positive for ≥1 respiratory virus and 1,255 (15%) were co-infected with ≥2 viruses including 213 (2.6 %) with 3–7 viruses. Among them, 1,005 (80 %) were younger than 5 years, and mean age was significantly lower for coinfected than monoinfected patients (6.6 versus 23.8 years; p < 0.0001). Viruses with the highest confection rates were HBoV (97 %), HPeV (97 %), EV (92 %), ADV (68 %), and HCoV-HKU1 (63 %). Iterative infections were observed in 96 patients and they involved 10 different viruses. ConclusionsOur study points out that coinfections with respiratory viruses vary over time in prevalence, involve majoritarily young children, and may involve concurrent acute infections or acute-on-chronic infections, which deserves further specific studies.

Emergency Care Efficiency vs. Quality: Uncovering Hidden Consequences of Fast-Track Routing Decisions

Problem definition: This work aims to examine the role of emergency department (ED) operational status related to congestion in fast-track (FT) routing decisions and the subsequent effects on patient outcomes. Methodology/results: In this paper, we utilize a two-year data set from two hospital EDs in Alberta, Canada, and adopt an instrumental variable approach to examine the effects of FT routing decisions on patient outcomes. Based on the empirical findings, we utilize a data-calibrated simulation to compare the performance of different routing policies. First, our study reveals that FT routing decisions are not purely clinically driven, and ED operational status is also associated with FT routing decisions. Second, being routed to FT can improve ED efficiency by reducing the average length of stay and left without being seen rates. However, this efficiency improvement comes at the cost of potential quality decline. In particular, being routed to the FT leads to an 8.2% increase in the 48-hour revisit rate for the high-complexity group and a 2.3% increase for the medium-complexity group. Third, we delve into the mechanisms behind observed patient outcomes and find that physicians in the FT area may prioritize expediting patient flow by simplifying patient diagnosis and treatment procedures. Consequently, the quality of care may be compromised for high- and medium-complexity patients. Finally, our simulation findings highlight the importance of selecting the “right” patients to be routed to the FT unit. To this end, the complexity-based classification method and dynamic routing policies emerge as promising avenues. Managerial implications: Our findings call for immediate attention from healthcare practitioners to carefully balance the trade-off between emergency care efficiency and quality, emphasizing the necessity of selecting the right patients for routing. Funding: This study is partially supported by the Hong Kong Research Grants Council [Grants GRF 11508921 and CRF C7162-20G]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0440 .

Sustainability and Performance Evaluation in Third Sector Partnerships: The Case of Turin Fast Track City

ABSTRACTCOVID‐19 radically changed how public services (activities of general interest) are pursued and administered. The search for resilient models has prompted public administration to test new regulatory approaches and to involve the third sector in the provision of primary services. This study investigates the sustainability and capacity of these models, specifically the implementation of a co‐planning and co‐design model aimed at measuring the possible creation of value and achieving common objectives. On the basis of an analysis of the development of the Turin Fast Track City project, the study employs a longitudinal method to identify not only the sustainability of the model but also new effective performance measurement tools, such as SIA analysis and integrated social accounting using financial and non‐financial elements. The study also highlights critical elements aimed at supporting future investigations.

Real-World Study on Implementation of Genomic Tests for Advanced Lung Adenocarcinoma in Brazil.

Tissue inadequacy and operational challenges may limit lung cancer comprehensive biomarker testing. Here, we describe the initial implementation of a tailored tissue molecular journey at Oncoclínicas Precision Medicine Laboratory in Brazil, which includes fast-track (FT) non-next-generation sequencing (NGS) assays combined with a broad NGS panel. From 2021 to 2023, all nonsquamous lung cancer samples eligible for the patient support program "Lung Mapping Consortium" at Oncoclínicas & Co were evaluated using the FT panel (immunohistochemistry for PD-L1 and anaplastic lymphoma kinase [ALK], polymerase chain reaction for EGFR and BRAF, and fluorescence in situ hybridization for ROS1) plus a broad DNA and RNA sequencing panel of 180 genes (custom ARCHER panel). From 1,272 samples received by the laboratory, 3% had no tissue for any molecular testing, 20% was not eligible for broad NGS panel as per pathologist assessment (tumor purity and quantity), additional 12% did not reach presequencing analytical thresholds (nucleic acid quantity and/or quality), and 3% had postsequencing failure. Most frequent alterations were KRAS mutations (28.4%, KRASG12C 9.7%), EGFR mutations (23.6%, exon20 insertions 2.9%), ALK fusions (6.4%), MET exon 14 skipping (4.4%), ERBB2 mutations (3.4%), ROS1 fusions (3.1%), and BRAFV600E (1.9%). In 35% of the samples, FT non-NGS tests were the only molecular diagnostics: EGFR mutations (14%), ALK fusions (4.4%), ROS1 fusions (1.8%), and BRAFV600E (0.7%). Overall, high PD-L1 expression (≥50%) was found in 12.3%. This study provides data on the molecular epidemiology of lung adenocarcinoma in Brazil, confirming high prevalence of EGFR mutations, ALK fusions, and MET exon 14 skipping alteration. Biomarker detection is largely affected by biospecimen collection and processing, with one third of the patients eligible for non-NGS testing only, which presents reduced coverage and sensitivity for actionable drivers.

Fast and Accurate Relative Motion Tracking for Dual Industrial Robots

Fast and Accurate Relative Motion Tracking for Dual Industrial Robots

Development of an optimized MRI protocol for a rapid preoperative identification of sentinel lymph nodes using superparamagnetic iron oxide – the Gothenburg Fast Acquisition Sentinel Lymph Node Tracking Magnetic Resonance Imaging Protocol (GO-FAST-MRI)

Development of an optimized MRI protocol for a rapid preoperative identification of sentinel lymph nodes using superparamagnetic iron oxide – the Gothenburg Fast Acquisition Sentinel Lymph Node Tracking Magnetic Resonance Imaging Protocol (GO-FAST-MRI)

Fast OCT-Based Needle Tracking for Retinal Microsurgery Using Dynamic Spiral Scanning

Fast OCT-Based Needle Tracking for Retinal Microsurgery Using Dynamic Spiral Scanning

AI Chatbots: Fast Tracking Sustainability Report Analysis for Enhanced Decision Making

AI Chatbots: Fast Tracking Sustainability Report Analysis for Enhanced Decision Making