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The quest to develop materials that enable the manufacture of dimensionally ultra-stable structures for critical-dimension components in spacecraft has led to much research over many decades and the evolution of carbon fibre reinforced polymer materials. This has resulted in structural designs that feature a near-zero coefficient of thermal expansion. However, the dimensional instabilities that result from moisture ingression and release remain the fundamental vulnerability of the matrix, which restricts many applications. Here, we address this challenge by developing a space-qualifiable physical surface barrier that blends within the mechanical properties of the composite, thus becoming part of the composite itself. The resulting enhanced composite features mechanical integrity and a strength that is superior to the underlying composite, while remaining impervious to moisture and outgassing. We demonstrate production capability for a model-sized component for the Sentinel-5 mission and demonstrate such capability for future European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) programmes such as Copernicus Extension, Earth Explorer and Science Cosmic Visions. Multiple layers of diamond-like carbon films are shown to act as moisture barriers when conformally deposited on carbon fibre reinforced polymers used in space applications.

Among hematological cancers, Acute Lymphoblastic Leukemia (ALL) and Chronic Lymphocytic Leukemia (CLL) are the most common leukemia in children and elderly people respectively. Some patients do not respond to chemotherapy treatments and it is necessary to complement it with immunotherapy-based treatments such as chimeric antigen receptor (CAR) therapy, which is one of the newest and more effective treatments against these cancers and B-cell lymphoma. Although complete remission results are promising, CAR T cell therapy presents still some risks for the patients, including cytokine release syndrome (CRS) and neurotoxicity. We proposed a different immune cell source for CAR therapy that might prevent these side effects while efficiently targeting malignant cells. NK cells from different sources are a promising vehicle for CAR therapy, as they do not cause graft versus host disease (GvHD) in allogenic therapies and they are prompt to attack cancer cells without prior sensitization. We studied the efficacy of NK cells from adult peripheral blood (AB) and umbilical cord blood (CB) against different target cells in order to determine the best source for CAR therapy. AB CAR-NK cells are slightly better at killing CD19 presenting target cells and CB NK cells are easier to stimulate and they have more stable number from donor to donor. We conclude that CAR-NK cells from both sources have their advantages to be an alternative and safer candidate for CAR therapy.

Paratuberculosis (PTB) is a chronic granulomatous enteritis caused by Mycobacterium avium subsp. paratuberculosis (Map). Vaccination is one of the most cost-effective tools for PTB control, although alternative treatments like the probiotic Dietzia have been explored with promising results. Using a rabbit model, we investigated the association of immunological and microbiota profiles in Gut Associated Lymphoid Tissue (GALT) with the effects in protection induced by the administration of Dietzia spp., the commercial vaccine (Silirum ® ) and the combination of both. The treatment with the probiotic diminished inflammation, but failed to control Map burden, suggesting a detrimental effect. Rabbits treated with the probiotic presented the highest rates of tissue lesion extension, although the immunological profile was not suggestive of an inflammatory state. Map load in both vaccinated groups was similar indicating that both treatments are equally effective in eliminating the infection, suggesting the role of vaccination in eliminating the infection prevails over the immunomodulatory effects of the probiotic. There were slight variations in the presence of some taxonomic groups depending on the treatment, highlighting the complexity of microbial interactions and the need to optimise treatment combinations in the context of each disease and animal species.

We fabricated a device that controls the motion of flux quanta in a niobium superconducting film grown on an array of nanoscale triangular pinning potentials. The controllable rectification of the vortex motion is due to the asymmetry of the fabricated magnetic pinning centers. The reversal in the direction of the vortex flow is explained by the interaction between the vortices trapped on the magnetic nanostructures and the interstitial vortices. The applied magnetic field and input current strength can tune both the polarity and magnitude of the rectified vortex flow. Our ratchet system is explained and modeled theoretically, taking the interactions between particles into consideration.

The objective of this research is to predict the delays in the departure of scheduled commercial flights through a methodology that uses predictive tools based on machine learning/deep learning (ML/DL), with supervised training in regression, based on the available flight datasets. Since the novel contribution of this work is, first, to make the comparison of the predictions in terms of means and statistical variance of the different ML/DL models implemented and, second, to determine the coefficients of the importance of the features or flight attributes, using ML methods known as permutation importance, it is possible to rank the importance of flight attributes by their influence in determining the delay time and reduce the problem of selecting the most important flight attributes. From the results obtained, it is worth mentioning that the model that presents the best performance is the ensemble or combinatorial method of random forest regressor models, with an acceptable prediction range (measured with the root-mean-square-error).

Carbon fibre reinforced polymers (CFRP) were introduced to the aerospace, automobile and civil engineering industries for their high strength and low weight. A key feature of CFRP is the polymer sizing - a coating applied to the surface of the carbon fibres to assist handling, improve the interfacial adhesion between fibre and polymer matrix and allow this matrix to wet-out the carbon fibres. In this paper, we introduce an alternative material to the polymer sizing, namely carbon nanotubes (CNTs) on the carbon fibres, which in addition imparts electrical and thermal functionality. High quality CNTs are grown at a high density as a result of a 35 nm aluminium interlayer which has previously been shown to minimise diffusion of the catalyst in the carbon fibre substrate. A CNT modified-CFRP show 300%, 450% and 230% improvements in the electrical conductivity on the ‘surface’, ‘through-thickness’ and ‘volume’ directions, respectively. Furthermore, through-thickness thermal conductivity calculations reveal a 107% increase. These improvements suggest the potential of a direct replacement for lightning strike solutions and to enhance the efficiency of current de-icing solutions employed in the aerospace industry.

Background:Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multiple treatment options recommended by clinical guidelines. Understanding treatment patterns among SLE patients is important for assessing treatment burden, the impact of clinical guidelines, and guiding medicinal product development. However, only limited data on treatment patterns exist in SLE, especially in paediatric-onset SLE.Objectives:To characterise adult and paediatric patients diagnosed with SLE at the time of diagnosis, and describe the patterns of medications used to treat their condition.Methods:We conducted a cohort study using five databases of routinely collected healthcare data from four European countries. Data sources include three primary or outpatient care databases [Clinical Practice Research Datalink (CPRD) GOLD (UK), IQVIA Disease Analyzer (DA) Germany (DE), Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP) (ES)], and two hospital databases [Institut Municipal Assistència Sanitària Hospital del Mar Information System (IMASIS) (ES) and Clinical Data Warehouse of Bordeaux University Hospital (CDWBordeaux) (FR)].We described the characteristics of adult and paediatric (<18 years) patients at time of SLE diagnosis, including age, sex, comorbidities, and concurrent medication use. We analysed the different medicines used, calculated the percentage of SLE patients commencing pre-specified SLE treatments in the first month and year after diagnosis, reported number of prescriptions, starting dose, cumulative dose, and duration of treatment for each of the treatments, and characterised which drugs were used as first-line or second-line treatments.Results:We included 11,255 patients with a first diagnosis of SLE for patient characterisation and 5,718 for our medicine utilisation analyses. Across all databases, the majority of adult SLE patients were female (80-88%), with median age of 49 to 54 years at diagnosis. In the paediatric cohort, 66-83% of SLE patients were female, with median age of 12 to 16 years at diagnosis. Hydroxychloroquine and glucocorticoids were most used as first line treatments in both adults and paediatric patients, with second line treatments including mycophenolate mofetil and methotrexate. Relatively few cases of monoclonal antibody use were seen in both groups. Initial glucocorticoid dosing in paediatric patients was often higher than in adults. In the paediatric cohort, for hydroxychloroquine, median duration was between 50 to 501 days across primary care databases and 8 days for CDWBordeaux hospital, median initial daily dose ranged from 199 to 300 mg, median cumulative dose ranged from 20,000 to 116,600 mg, number of prescriptions in the first drug era was 1 to 10 across all databases. For prednisone/prednisolone, median duration was between 74 to 246 days for primary care databases and 13 days for CDWBordeaux hospital, median initial daily dose ranged from 10 to 60 mg, median cumulative dose ranged from 775 to 2,150 mg, number of prescriptions in the first drug era was 1 to 5 across all databases. In the adult new user cohort, for hydroxychloroquine, median duration was 39 to 485 days for primary care databases and 4 to 30 days for hospital databases, median initial daily dose ranged from 13 to 400 mg, median cumulative dose ranged from 600 to 130,051 mg, number of prescriptions in the first drug era was 1 to 6 across all databases. For prednisone/prednisolone, median duration was 7 to 111 days for primary care databases and 4 to 30 days for hospital databases, median initial daily dose ranged from 2 to 40 mg, median cumulative dose ranged from 20 to 1,038 mg, number of prescriptions in the first drug era was 1 to 4 across all databases.Conclusion:Our results show that treatment choices for SLE in adults across four European countries are overall in line with most recent therapeutic consensus guidelines. A higher prescription of glucocorticoids seen in paediatric patients suggests the need for effective steroid-sparing treatment alternatives as indicated by paediatric specific guidelines.REFERENCES:NIL.Acknowledgements:This study is based in part on data from the Clinical Practice Research Datalink obtained under license from the UK Medicines and Healthcare products Regulatory Agency. The data is provided by patients and collected by NHS as part of their care and support programme. The views expressed in this article are the personal views of the author(s) and should not be understood or quoted as being made on behalf of or reflecting the position of the regulatory agency/agencies or organisations with which the author(s) is/are employed/affiliated.Disclosure of Interests:Francesco Dernie: None declared, Mike Du: None declared, Marti Catala Sabate: None declared, Antonella Delmestri: None declared, Wai Yi Man: None declared, James Brash Employee of IQVIA, Hanne van Ballegooijen Employee of IQVIA, Núria Mercadé-Besora: None declared, Talita Duarte-Salles: None declared, Miguel-Angel Mayer: None declared, Angela Leis: None declared, Juan Manuel Ramirez-Anguita: None declared, Romain Griffier: None declared, Guillaume Verdy: None declared, Albert Prats-Uribe: None declared, Alexandra Pacurariu: None declared, Daniel Morales: None declared, Roberto De Lisa: None declared, Sara Galluzzo: None declared, Gunter Egger: None declared, Daniel Prieto-Alhambra DPA’s research group has received consultancy fees from Astra Zeneca and UCB Biopharma., DPA’s department has received grant/s from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, and UCB Biopharma. Amgen, Astellas, Janssen, Synapse Management Partners and UCB Biopharma have funded or supported training programmes organised by DPA’s department., Eng Hooi Tan: None declared.

This paper presents a novel version control system for point clouds, which allows the complete editing history of a dataset to be stored. For each intermediate version, this system stores only the information that changes with respect to the previous one, which is compressed using a new strategy based on several algorithms. It allows undo/redo functionality in memory, which serves to optimize the operation of the version control system. It can also manage changes produced from third-party applications, which makes it ideal to be integrated into typical Computer-Aided Design workflows. In addition to automated management of incremental versions of point cloud datasets, the proposed system has a much lower storage footprint than the manual backup approach for most common point cloud workflows, which is essential when working with LiDAR (Light Detection and Ranging) data in the context of spatial big data.

The widespread use of LiDAR technologies has led to an ever-increasing volume of captured data that pose a continuous challenge for its storage and organization, so that it can be efficiently processed and analyzed. Although the use of system files in formats such as LAS/LAZ is the most common solution for LiDAR data storage, databases are gaining in popularity due to their evident advantages: centralized and uniform access to a collection of datasets; better support for concurrent retrieval; distributed storage in database engines that allows sharding; and support for metadata or spatial queries by adequately indexing or organizing the data. The present work evaluates the performance of four popular NoSQL and relational database management systems with large LiDAR datasets: Cassandra, MongoDB, MySQL and PostgreSQL. To perform a realistic assessment, we integrate these database engines in a repository implementation with an elaborate data model that enables metadata and spatial queries and progressive/partial data retrieval. Our experimentation concludes that, as expected, NoSQL databases show a modest but significant performance difference in favor of NoSQL databases, and that Cassandra provides the best overall database solution for LiDAR data.

The management of large point clouds obtained by LiDAR sensors is an important topic in recent years due to the widespread use of this technology in a wide variety of applications and the increasing volume of data captured. One of the main applications of LIDAR systems is the study of the temporal evolution of the real environment. In open environments, it is important to know the evolution of erosive processes or landscape transformation. In the context of civil engineering and urban environments, it is useful for monitoring urban dynamics and growth, and changes during the construction of buildings or infrastructure facilities. The main problem with change detection (CD) methods is erroneous detection due to precision errors or the use of different capture devices at different times. This work presents a method to compare large point clouds, based on the study of the local fractal dimension of point clouds at multiple scales. Our method is robust in the presence of environmental and sensor factors that produce abnormal results with other methods. Furthermore, it is more stable than others in cases where there is no significant displacement of points but there is a local alteration of the structure of the point cloud. Furthermore, the precision can be adapted to the complexity and density of the point cloud. Finally, our solution is faster than other CD methods such as distance-based methods and can run at O(1) under some conditions, which is important when working with large datasets. All these improvements make the proposed method more suitable than the others to solve complex problems with LiDAR data, such as storage, time series data management, visualization, etc.