TomTom (Netherlands)

The article analyses the existing communication systems of unmanned aerial vehicles designed for fire detection and extinguishing. Their disadvantages, such as limited data transmission speed, insufficient awareness in the communication system, lack of indication of the optimal communication channel range, focus on reducing and optimising information exchange without improving signal quality, as well as focus on use in marine conditions rather than on land areas, are revealed. An innovative method of natural fire detection and suppression is proposed as an alternative. Its structure and communication system are described, which is the most optimal, practical and capable of solving a wide range of tasks: from receiving and exchanging information between unmanned aerial vehicles and other aircraft or ground stations to collision avoidance and route optimisation.

The problem of delivery and dumping of fire extinguishing agent into the fire source is considered. Different types of fire extinguishing agents and systems are analyzed. The most effective way seems to be extinguishing with a blast wave. The author conducts a patent search for systems using a blast wave to extinguish a fire. The advantages and disadvantages of each method are determined. So, the main disadvantages are: the inability to completely extinguish a fire in the riding area, the risk of severe damage to trees, the high cost, and the high technology of the solution. A technical solution is proposed that takes into account the disadvantages of existing systems. As a fire extinguishing system, it is proposed to create an effective shock wave in the riding zone of a forest fire, created using supplied fire suppression devices with filler and a dispersing explosive charge. The essence of the system, the principle of operation and the device operation scheme are described.

Introduction: Retropharyngeal abscess (RPA) is deep neck space infection which requires prompt diagnosis and management due to its potential life-threatening nature. In paediatric group it is most common between 3-5 years of age with infants presenting it very rarely. We are reporting a case series of all the children who were diagnosed of RPA and managed successfully. Materials and methods: This is a single‑center, retrospective study conducted at the tertiary care hospital. Detailed data from the case files of patients who were diagnosed and managed for RPA from 2012 to 2022 were included. The demographic details, presenting complaints, site of involvement, CT findings, intra-operative findings, pus culture report and course of child during hospitalization was meticulously documented along with their follow up findings and analysed. Results: Total number of children who underwent treatment for RPA during the study period is 17. maximum number of cases were below 4 years of age accounting for 65%. 58.8 % had an episode of Upper respiratory tract infection before developing the RPA. 2 patients were diagnosed to have tuberculosis and had started on Anti tubercular treatment. One child had sustained injury to neck, and one had history of chicken bone ingestion. Five children showed the complications of which 60% of them were infant: Conclusion: The crucial step in infants with RPA is prompt diagnosis and aggressive management. Initial antibiotics should be a broad spectrum until the pus culture sensitivity reports are available. There is a recent trend is Methicillin resistant staphylococcus aureus especially in younger children. Paradoxical reaction of tubercular treatment is rare and should be borne in mind of its possibilities while treating.

Spatial scene understanding, including monocular depth estimation, is an important problem in various applications such as robotics and autonomous driving. While improvements in unsupervised monocular depth estimation have potentially allowed models to be trained on diverse crowd-sourced videos, this remains underexplored as most methods utilize the standard training protocol wherein the models are trained from scratch on all data after new data is collected. Instead, continual training of models on sequentially collected data would significantly reduce computational and memory costs. Nevertheless, naive continual training leads to catastrophic forgetting, where the model performance deteriorates on older domains as it learns on newer domains, highlighting the trade-off between model stability and plasticity. While several techniques have been proposed to address this issue in image classification, the high-dimensional and spatiotemporally correlated outputs of depth estimation make it a distinct challenge. To the best of our knowledge, no framework or method currently exists focusing on the problem of continual learning in depth estimation. Thus, we introduce a framework that captures the challenges of continual unsupervised depth estimation (CUDE), and define the necessary metrics to evaluate model performance. We propose a rehearsal-based dual-memory method MonoDepthCL, which utilizes spatiotemporal consistency for continual learning in depth estimation, even when the camera intrinsics are unknown. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">§</sup>

To operate safely, an automated vehicle (AV) must anticipate how the environment around it will evolve. For that purpose, it is important to know which prediction models are most appropriate for every situation. Currently, assessment of prediction models is often performed over a set of trajectories without distinction of the type of movement they capture, resulting in the inability to determine the suitability of each model for different situations. In this work we illustrate how standardized evaluation methods result in wrong conclusions regarding a model's predictive capabilities, preventing a clear assessment of prediction models and potentially leading to dangerous on-road situations. We argue that following evaluation practices in safety assessment for AVs, assessment of prediction models should be performed in a scenario-based fashion. To encourage scenario-based assessment of prediction models and illustrate the dangers of improper assessment, we categorize trajectories of the Waymo Open Motion dataset according to the type of movement they capture. Next, three different models are thoroughly evaluated for different trajectory types and prediction horizons. Results show that common evaluation methods are insufficient and the assessment should be performed depending on the application in which the model will operate.

Background: Patients undergoing allogeneic hematopoietic cell transplant (HCT) or solid organ transplant (SOT) are at risk of developing Epstein–Barr virus driven post-transplant lymphoproliferative disorder (EBV+ PTLD), a rare hematologic malignancy, which is often aggressive and life-threatening. Patients with relapsed or refractory (r/r) EBV+ PTLD have few treatment options with poor outcomes, demonstrating a clear unmet medical need. Tabelecleucel is an investigational, off-the-shelf, allogeneic EBV-specific T-cell immunotherapy being studied in patients with serious EBV+ diseases (NCT04554914 & NCT03394365) that has demonstrated clinical benefit and favorable safety profile in the treatment of EBV+ PTLD after failure of rituximab (R) ± chemotherapy (Prockop, EBMT 2021, ATC 2021, ASH 2021). Aims: First analyses of demographics, efficacy and safety results of r/r EBV+ PTLD patients following SOT or HCT who presented between Jul 2020 and Nov 2021 and consented to research. Methods: Atara Biotherapeutics supports an ongoing expanded access program (EAP) in Europe for patients with EBV+ diseases who have no other treatment options. Demographics, efficacy and safety data of r/r EBV+ PTLD patients following SOT or HCT who presented to the EAP between Jul 2020 and Nov 2021 and consented to research were analyzed. Results: A total of 48 EAP requests from 9 countries for patients with EBV+ diseases were received. Twenty-two patients from 7 countries consented to this research: 16 EBV+ PTLD and 6 EBV+ non-PTLD. Of the 16 PTLD patients 15 received at least one dose of tabelecleucel. Overall, 9 out of 15 (60%) patients achieved a response as assessed by the treating physician, with 6 complete responses and 3 partial responses. Eight out of nine responses were seen after the first cycle. No adverse events were reported as related to tabelecleucel by the treating physician. Image:Summary/Conclusion: The successful execution of this European EAP demonstrates the feasibility to deliver an off-the-shelf allogeneic EBV+ T-cell therapy in time-sensitive clinical situations when no other treatment options exist. These data show clinically meaningful outcomes for patients with r/r EBV+PTLD post-SOT or post-HCT treated with tabelecleucel consistent with previously reported favorable safety and efficacy profile (Prockop, ASH 2021).

The development of new assessment methods for the performance of automated vehicles is essential to enable the deployment of automated driving technologies, due to the complex operational domain of automated vehicles. One contributing method is scenario-based assessment in which test cases are derived from real-world road traffic scenarios obtained from driving data. Given the complexity of the reality that is being modeled in these scenarios, it is a challenge to define a structure for capturing these scenarios. An intensional definition that provides a set of characteristics that are deemed to be both necessary and sufficient to qualify as a scenario assures that the scenarios constructed are both complete and intercomparable. In this article, we develop a comprehensive and operable definition of the notion of scenario while considering existing definitions in the literature. This is achieved by proposing an object-oriented framework in which scenarios and their building blocks are defined as classes of objects having attributes, methods, and relationships with other objects. The object-oriented approach promotes clarity, modularity, reusability, and encapsulation of the objects. We provide definitions and justifications of each of the terms. Furthermore, the framework is used to translate the terms in a coding language that is publicly available.

Perceptions of parents of young children receiving early intervention are important to understand. Parents have valuable opinions on the delivery of early interventions services and can provide critical feedback that can help professionals revise their existing early intervention delivery modalities. In the current study, we examined the perceptions of parents of young children with Down syndrome on early intervention services in Turkey. Specifically, we aimed to understand the parents' views on medical and educational evaluation and diagnosis processes. The study was conducted using a cross-sectional research design, which is one of the survey design methods. Data were collected from a total of 893 parents via an online survey. The results demonstrated that children with Down syndrome were diagnosed within an average of 2.3 months from birth, but the average age for starting education was 10.5 months. The majority of the parents evaluated the process until their children were diagnosed and accessed education services as a rather slow process that proceeded with their own means and efforts. Furthermore, the parents reported that during the diagnosis processes the type of materials, equipment, toys, and settings used were not relevant and time provided was insufficient. Moreover, the majority of the parents reported that the education services presented to them and their children were not sufficient and early intervention services were not provided within a system. As a result, although the legal regulations in Turkey are parallel to those in developed countries and studies in the field have been increasingly gaining momentum, issues such as the absence of an early intervention system model, insufficient cooperation between experts and institutions, and the shortage of expert staff in the field are still present and awaiting a solution.