Clustering Trajectories by Relevant Parts for Air Traffic Analysis

Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering

Visual analytics of flight trajectories for uncovering decision making strategies

In air traffic management and control, movement data describing actual and planned flights are used for planning, monitoring and post-operation analysis purposes with the goal of increased efficient utilization of air space capacities (in terms of delay reduction or flight efficiency), without compromising the safety of passengers and cargo, nor timeliness of flights. From flight data, it is possible to extract valuable information concerning preferences and decision making of airlines (e.g. route choice) and air traffic managers and controllers (e.g. flight rerouting or optimizing flight times), features whose understanding is intended as a key driver for bringing operational performance benefits. In this paper, we propose a suite of visual analytics techniques for supporting assessment of flight data quality and data analysis workflows centred on revealing decision making preferences

Geometrical dynamics of Born-Infeld objects

We present a geometrical inspired study of the dynamics of $Dp$-branes. We focus on the usual nonpolynomial Dirac-Born-Infeld action for the worldvolume swept out by the brane in its evolution in general background spacetimes. We emphasize the form of the resulting equations of motion which are quite simple and resemble Newton's second law, complemented with a conservation law for a worldvolume bicurrent. We take a closer look at the classical Hamiltonian analysis which is supported by the ADM framework of general relativity. The constraints and their algebra are identified as well as the geometrical role they play in phase space. In order to illustrate our results, we review the dynamics of a $D1$-brane immersed in a $AdS_3 \times S^3$ background spacetime. We exhibit the mechanical properties of Born-Infeld objects paving the way to a consistent quantum formulation.Comment: LaTex, 20 pages, no figure

Supporting Visual Exploration of Iterative Job Scheduling

We consider the general problem known as job shop scheduling, in which multiple jobs consist of sequential operations that need to be executed or served by appropriate machines having limited capacities. For example, train journeys (jobs) consist of moves and stops (operations) to be served by rail tracks and stations (machines). A schedule is an assignment of the job operations to machines and times where and when they will be executed. Developers of computational methods for job scheduling need tools enabling them to explore how their methods work. At a high level of generality, we define the system of pertinent exploration tasks and a combination of visualisations capable of supporting the tasks. We provide general descriptions of the purposes, contents, visual encoding, properties, and interactive facilities of the visualisations and illustrate them with images from an example implementation in air traffic management. We justify the design of the visualisations based on the tasks, principles of creating visualisations for pattern discovery, and scalability requirements. The outcomes of our research are sufficiently general to be of use in a variety of applications

Trastuzumab and pertuzumab without chemotherapy in early-stage HER2+ breast cancer: a plain language summary of the PHERGain study

This is a summary of a publication about the PHERGain study, which was published in The Lancet Oncology in May 2021. The study includes 376 women with a type of breast cancer called HER2-positive breast cancer that can be removed by surgery. In the study, researchers wanted to learn if participants could be treated with two medicines called trastuzumab and pertuzumab without the need for chemotherapy. To identify HER2-positive tumors with more sensitivity to anti-HER2 therapies, the researchers used a type of imaging called a FDG-PET scan to check how well the treatments were working.Participants took a treatment before surgery, consisting of either chemotherapy (docetaxel and carboplatin) plus trastuzumab and pertuzumab (group A) or trastuzumab and pertuzumab alone (plus hormone therapy if the tumor was hormone receptor-positive; group B). After two cycles of treatment, participants underwent a FDG-PET scan. Participants assigned to group A completed 6 cycles of treatment regardless of 18F-FDG-PET results. Participants in group B continued the same treatment until surgery if their FDG-PET scan showed the treatment was working. While participants who did not show a response started treatment with chemotherapy in addition to trastuzumab and pertuzumab. All participants then had surgery.The results revealed that, of the participants in group B who showed a response using FDG-PET scan, 37.9% achieved a disappearance of all invasive cancer in the breast and axillary lymph nodes. This rate appears to be higher than those reported in previous studies evaluating the same treatment. These participants also had less side effects and improved overall quality of life compared with participants taking chemotherapy plus trastuzumab and pertuzumab.Early monitoring of how well participants respond to treatment by FDG-PET scan seems to identify participants with operable HER2-positive breast cancer who were more likely to benefit from trastuzumab and pertuzumab without the need to have chemotherapy. The PHERGain study is still ongoing and results on long-term survival are expected to be released in 2023. Clinical Trial Registration: NCT03161353 (ClinicalTrials.gov)

The datAcron Ontology for the Specification of Semantic Trajectories

As the number of moving objects increases, the challenges for achieving operational goals w.r.t. the mobility in many domains that are critical to economy and safety emerge dramatically. In domains such as air traffic management, this dictates a shift of operations’ paradigm from location based, as it is today, to trajectory based, where trajectories are turned into “first-class citizens”. Additionally, the increasing amount of data from heterogenous and disparate data sources implies the need for advanced analysis methods that require exploiting spatio-temporal mobility data in appropriate forms and at varying levels of abstraction. All these call for an in-principle way for organising integrated views of mobility data, with trajectories playing the main role. In this paper, we propose an ontology for modelling semantic trajectories, integrating spatio-temporal information regarding mobility of objects, at multiple, interlinked levels of abstraction. Our work builds upon a comprehensive framework that identifies fundamental spatio-temporal data types and specific conversions among these types. We validate the ontological specifications towards satisfying the needs of visual analysis tasks in the complex air traffic management domain, using real-world data

Arginine deprivation alters microglia polarity and synergises with radiation to eradicate non arginine auxotrophic glioblastoma tumors

New approaches for the management of glioblastoma (GBM) are an urgent and unmet clinical need. Here, we illustrate that the efficacy of radiotherapy for GBM is strikingly potentiated by concomitant therapy with the arginine depleting agent ADI-PEG20 in a non-arginine auxotrophic cellular background (Arginine Succinate Synthetase 1 positive). Moreover, this combination led to durable and complete radiological and pathological response with extended disease-free survival in an orthotopic immune competent model of GBM with no significant toxicity. ADI-PEG20 not only enhances the cellular sensitivity of Arginine succinate synthetase 1 positive GBM to ionising radiation by elevated production of nitric oxide (NO) and hence generation of cytotoxic peroxynitrites, but also promotes glioma-associated macrophages/microglia infiltration into tumors and turns their classical anti-inflammatory (pro-tumor) phenotype into a pro-inflammatory (anti-tumor) phenotype. Our results provide an effective, well-tolerated and simple strategy to improve GBM treatment which merits consideration for early evaluation in clinical trials

Early efficacy evaluation of mesenchymal stromal cells (MSC) combined to biomaterials to treat long bone non-unions

Background and study aim: Advanced therapy medicinal products (ATMP) frequently lack of clinical data on efficacy to substantiate a future clinical use. This study aims to evaluate the efficacy to heal long bone delayed unions and non-unions, as secondary objective of the EudraCT 2011-005441-13 clinical trial, through clinical and radiological bone consolidation at 3, 6 and 12 months of follow-up, with subgroup analysis of affected bone, gender, tobacco use, and time since the original fracture. Patients and methods: Twenty-eight patients were recruited and surgically treated with autologous bone marrow derived mesenchymal stromal cells expanded under Good Manufacturing Practices, combined to bioceramics in the surgical room before implantation. Mean age was 39 ± 13 years, 57% were males, and mean Body Mass Index 27 ± 7. Thirteen (46%) were active smokers. There were 11 femoral, 4 humeral, and 13 tibial non-unions. Initial fracture occurred at a mean ± SD of 27.9 ± 31.2 months before recruitment. Efficacy results were expressed by clinical consolidation (no or mild pain if values under 30 in VAS scale), and by radiological consolidation with a REBORNE score over 11/16 points (value of or above 0.6875). Means were statistically compared and mixed models for repeated measurements estimated the mean and confidence intervals (95%) of the REBORNE Bone Healing scale. Clinical and radiological consolidation were analyzed in the subgroups with Spearman correlation tests (adjusted by Bonferroni). Results: Clinical consolidation was earlier confirmed, while radiological consolidation at 3 months was 25.0% (7/28 cases), at 6 months 67.8% (19/28 cases), and at 12 months, 92.8% (26/28 cases including the drop-out extrapolation of two failures). Bone biopsies confirmed bone formation surrounding the bioceramic granules. All locations showed similar consolidation, although this was delayed in tibial non-unions. No significant gender difference was found in 12-month consolidation (95% confidence). Higher consolidation scale values were seen in non-smoking patients at 6 (p = 0.012, t-test) and 12 months (p = 0.011, t-test). Longer time elapsed after the initial fracture did not preclude the occurrence of consolidation. Conclusion: Bone consolidation was efficaciously obtained with the studied expanded hBM-MSCs combined to biomaterials, by clinical and radiological evaluation, and confirmed by bone biopsies, with lower consolidation scores in smokers

Visual exploration of movement and event data with interactive time masks

We introduce the concept of time mask, which is a type of temporal filter suitable for selection of multiple disjoint time intervals in which some query conditions fulfil. Such a filter can be applied to time-referenced objects, such as events and trajectories, for selecting those objects or segments of trajectories that fit in one of the selected time intervals. The selected subsets of objects or segments are dynamically summarized in various ways, and the summaries are represented visually on maps and/or other displays to enable exploration. The time mask filtering can be especially helpful in analysis of disparate data (e.g., event records, positions of moving objects, and time series of measurements), which may come from different sources. To detect relationships between such data, the analyst may set query conditions on the basis of one dataset and investigate the subsets of objects and values in the other datasets that co-occurred in time with these conditions. We describe the desired features of an interactive tool for time mask filtering and present a possible implementation of such a tool. By example of analysing two real world data collections related to aviation and maritime traffic, we show the way of using time masks in combination with other types of filters and demonstrate the utility of the time mask filtering