Enhancing airplane boarding procedure using vision based passenger classification

This paper presents the implementation of a new boarding strategy that exploits passenger and hand-luggage detection and classification to reduce the boarding time onto an airplane. A vision system has the main purpose of providing passengers data, in terms of agility coefficient and hand-luggage size to a seat assignment algorithm. The software is able to dynamically generate the passenger seat that reduces the overall boarding time while taking into account the current airplane boarding state. The motivation behind this work is to speed up of the passenger boarding using the proposed online procedure of seat assignment based on passenger and luggage classification. This method results in an enhancement of the boarding phase, in terms of both time and passenger experience. The main goal of this work is to demonstrate the usability of the proposed system in real conditions proving its performances in terms of reliability. Using a simple hardware and software setup, we performed several experiments recreating a gate entrance mock up and comparing the measurements with ground truth data to assess the reliability of the system

A fast airplane boarding strategy using online seat assignment based on passenger classification

The minimization of the turnaround time, the duration which an aircraft must remain parked at the gate, is an important goal of airlines to increase their profitability. This work introduces a procedure to minimize of the turnaround time by speeding up the boarding time in passenger aircrafts. This is realized by allocating the seat numbers adaptively to passengers when they pass the boarding gate and not before. Using optical sensors, an agility measure is assigned to each person and also a measure to characterize the size of her/his hand-luggage. Based on these two values per passenger and taking into account additional constraints, like reserved seats and the belonging to a group, a novel seat allocation algorithm is introduced to minimize the boarding time. Extensive simulations show that a mean reduction of the boarding time with approximately 15% is achieved compared to existing boarding strategies. The costs of introducing the proposed procedure are negligible, while the savings of reducing the turnaround time are enormous, considering that the costs generated by inactive planes on an airport are estimated to be about 30 $ per minute

Non-rigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS

With the recent introduction of the MR-LINAC, an MR-scanner combined with a radiotherapy LINAC, MR-based motion estimation has become of increasing interest to (retrospectively) characterize tumor and organs-at-risk motion during radiotherapy. To this extent, we introduce low-rank MR-MOTUS, a framework to retrospectively reconstruct time-resolved non-rigid 3D+t motion-fields from a single low-resolution reference image and prospectively undersampled k-space data acquired during motion. Low-rank MR-MOTUS exploits spatio-temporal correlations in internal body motion with a low-rank motion model, and inverts a signal model that relates motion-fields directly to a reference image and k-space data. The low-rank model reduces the degrees-of-freedom, memory consumption and reconstruction times by assuming a factorization of space-time motion-fields in spatial and temporal components. Low-rank MR-MOTUS was employed to estimate motion in 2D/3D abdominothoracic scans and 3D head scans. Data were acquired using golden-ratio radial readouts. Reconstructed 2D and 3D respiratory motion-fields were respectively validated against time-resolved and respiratory-resolved image reconstructions, and the head motion against static image reconstructions from fully-sampled data acquired right before and right after the motion. Results show that 2D+t respiratory motion can be estimated retrospectively at 40.8 motion-fields-per-second, 3D+t respiratory motion at 7.6 motion-fields-per-second and 3D+t head-neck motion at 9.3 motion-fields-per-second. The validations show good consistency with image reconstructions. The proposed framework can estimate time-resolved non-rigid 3D motion-fields, which allows to characterize drifts and intra and inter-cycle patterns in breathing motion during radiotherapy, and could form the basis for real-time MR-guided radiotherapy.Comment: 18 pages main text, 8 main figures, 1 main table, 12 supporting videos, 2 supporting figures, 1 supporting information PDF. Submitted to Magnetic Resonance in Medicine as Full Pape

Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy

Respiratory motion during radiotherapy causes uncertainty in the tumor's location, which is typically addressed by an increased radiation area and a decreased dose. As a result, the treatments' efficacy is reduced. The recently proposed hybrid MR-linac scanner holds the promise to efficiently deal with such respiratory motion through real-time adaptive MR-guided radiotherapy (MRgRT). For MRgRT, motion-fields should be estimated from MR-data and the radiotherapy plan should be adapted in real-time according to the estimated motion-fields. All of this should be performed with a total latency of maximally 200 ms, including data acquisition and reconstruction. A measure of confidence in such estimated motion-fields is highly desirable, for instance to ensure the patient's safety in case of unexpected and undesirable motion. In this work, we propose a framework based on Gaussian Processes to infer 3D motion-fields and uncertainty maps in real-time from only three readouts of MR-data. We demonstrated an inference frame rate up to 69 Hz including data acquisition and reconstruction, thereby exploiting the limited amount of required MR-data. Additionally, we designed a rejection criterion based on the motion-field uncertainty maps to demonstrate the framework's potential for quality assurance. The framework was validated in silico and in vivo on healthy volunteer data (n=5) acquired using an MR-linac, thereby taking into account different breathing patterns and controlled bulk motion. Results indicate end-point-errors with a 75th percentile below 1mm in silico, and a correct detection of erroneous motion estimates with the rejection criterion. Altogether, the results show the potential of the framework for application in real-time MR-guided radiotherapy with an MR-linac.Comment: This manuscript has supplementary files which can be downloaded at https://surfdrive.surf. nl/files/index.php/s/scLts9nJYXfbLMx. The files include videos that show reconstructed motion-fields and spatial uncertainty maps. See the Appendix for a description of all individual file

The effect of quarantine due to Covid-19 pandemic on seizure frequency in 102 adult people with epilepsy from Apulia and Basilicata regions, Southern Italy

Objective: following the COVID-19 pandemic, a quarantine was imposed to all of regions Italy by 9th March until 3rd May 2020. We investigated the effect of COVID-19 infection and quarantine on seizure frequency in adult people with epilepsy (PwE) of Apulia and Basilicata regions, Southern Italy. Methods: This is an observational, retrospective study based on prospective data collection of 102 successive PWE. The frequency of seizures was evaluated during pre-quarantine (January- February), quarantine (March-April), and post-quarantine period (May-June), while PwE were divided into A) cases responding to treatment with ≤ 1 seizure per year; B) cases responding to treatment with 2-5 seizure per year; C) cases with drug-resistant epilepsy with ≤ 4 seizures per month; D) cases with drug-resistant epilepsy with 5-10 seizures per month. PwE underwent several self-report questionnaires regarding therapeutic compliance, mood, stress and sleep during quarantine period. Results: Approximately 50 % of PwE showed seizure frequency changes (22.55 % an increase and 27.45 % a reduction) during quarantine. Seizure frequency significantly (p < 0.05) increased in PwE responding to treatment with ≤ 1 seizure per year, while significantly (p < 0.05) reduced in PwE with drug-resistant epilepsy with 5-10 seizures per month. The data was not influenced by therapeutic adherence, sleep and depression. The analysis of anxiety showed a moderate level of anxiety in PwE responding to treatment with < 1 seizure per year, while moderate stress was perceived by all PwE. Seizure frequency changes were related to quarantine, but not to COVID-19 infection. In fact, unlike other regions of Italy, particularly Northern Italy, Apulia and Basilicata regions were less affected by COVID-19 infection, and almost all PwE recognized the quarantine as a stressful event. Emotional distress and anxiety due to social isolation, but also the relative reduction of triggers for epileptic seizures were the most important factors for changes in seizure frequency. Conclusions: Our study adds to the growing concern that the indirect effects of COVID-19 pandemic will far outstrip the direct consequences of the infection

Real-time myocardial landmark tracking for MRI-guided cardiac radio-ablation using Gaussian Processes

The high speed of cardiorespiratory motion introduces a unique challenge for cardiac stereotactic radio-ablation (STAR) treatments with the MR-linac. Such treatments require tracking myocardial landmarks with a maximum latency of 100 ms, which includes the acquisition of the required data. The aim of this study is to present a new method that allows to track myocardial landmarks from few readouts of MRI data, thereby achieving a latency sufficient for STAR treatments. We present a tracking framework that requires only few readouts of k-space data as input, which can be acquired at least an order of magnitude faster than MR-images. Combined with the real-time tracking speed of a probabilistic machine learning framework called Gaussian Processes, this allows to track myocardial landmarks with a sufficiently low latency for cardiac STAR guidance, including both the acquisition of required data, and the tracking inference. The framework is demonstrated in 2D on a motion phantom, and in vivo on volunteers and a ventricular tachycardia (arrhythmia) patient. Moreover, the feasibility of an extension to 3D was demonstrated by in silico 3D experiments with a digital motion phantom. The framework was compared with template matching - a reference, image-based, method - and linear regression methods. Results indicate an order of magnitude lower total latency (<10 ms) for the proposed framework in comparison with alternative methods. The root-mean-square-distances and mean end-point-distance with the reference tracking method was less than 0.8 mm for all experiments, showing excellent (sub-voxel) agreement. The high accuracy in combination with a total latency of less than 10 ms - including data acquisition and processing - make the proposed method a suitable candidate for tracking during STAR treatments

Open and Hidden Charm Production in 920 GeV Proton-Nucleus Collisions

The HERA-B collaboration has studied the production of charmonium and open charm states in collisions of 920 GeV protons with wire targets of different materials. The acceptance of the HERA-B spectrometer covers negative values of xF up to xF=-0.3 and a broad range in transverse momentum from 0.0 to 4.8 GeV/c. The studies presented in this paper include J/psi differential distributions and the suppression of J/psi production in nuclear media. Furthermore, production cross sections and cross section ratios for open charm mesons are discussed.Comment: 5 pages, 9 figures, to be published in the proceedings of the 6th International Conference on Hyperons, Charm & Beauty Hadrons (BEACH04), Chicago, IL, June 27 - July 3, 200

Search for the Flavor-Changing Neutral Current Decay D0→μ+μ−D^0 \to \mu^+\mu^- with the HERA-B Detector

We report on a search for the flavor-changing neutral current decay $D^0 \to \mu^+\mu^-$ using $50 \times 10^6$ events recorded with a dimuon trigger in interactions of 920 GeV protons with nuclei by the HERA-B experiment. We find no evidence for such decays and set a 90% confidence level upper limit on the branching fraction $Br(D^0 \to \mu^+\mu^-) <2.0 \times 10^{-6}$.Comment: 17 pages, 4 figures (of which 1 double), paper to be submitted to Physics Letters

Measurement of the J/Psi Production Cross Section in 920 GeV/c Fixed-Target Proton-Nucleus Interactions

The mid-rapidity (dsigma_(pN)/dy at y=0) and total sigma_(pN) production cross sections of J/Psi mesons are measured in proton-nucleus interactions. Data collected by the HERA-B experiment in interactions of 920 GeV/c protons with carbon, titanium and tungsten targets are used for this analysis. The J/Psi mesons are reconstructed by their decay into lepton pairs. The total production cross section obtained is sigma_(pN)(J/Psi) = 663 +- 74 +- 46 nb/nucleon. In addition, our result is compared with previous measurements