This article deals with X-band radar trial campaigns in 2006 and 2007 at Orly Airport, and in June 2008 at Paris-CDG Airport. An X-band Doppler radar has been deployed to assess short range (inferior ...to 2000 m) wake vortex monitoring capabilities in all weather conditions (dry and wet conditions). Recorded data have been correlated with electromagnetic and fluid mechanical models of wake turbulences for better and more accurate understanding of roll-up radar cross section (RCS) and Doppler signature.
Cet article traite des campagnes de mesures radar bande X de 2006 et 2007 sur l'Aéroport Orly et juin 2008 sur l'Aéroport de Paris-CDG. Un radar Doppler bande X a été déployé pour évaluer les capacités d'imagerie à courte portée (inférieure à 2000 m) des tourbillons de sillage suivant différentes conditions météorologiques (air clair et pluie). Les données enregistrées ont été corrélées avec les modèles électromagnétiques et les modèles de mécaniques des fluides des turbulences de sillage pour une meilleure compréhension de la surface équivalente radar (SER) des rouleaux et de leur signature Doppler.
Background:
While substantial progress has been made in the development of disease-modifying medications for multiple sclerosis (MS), a high percentage of treated patients still show progression and ...persistent inflammatory activity. Autologous haematopoietic stem cell transplantation (AHSCT) aims at eliminating a pathogenic immune repertoire through intense short-term immunosuppression that enables subsequent regeneration of a new and healthy immune system to re-establish immune tolerance for a long period of time. A number of mostly open-label, uncontrolled studies conducted over the past 20 years collected about 4000 cases. They uniformly reported high efficacy of AHSCT in controlling MS inflammatory disease activity, more markedly beneficial in relapsing-remitting MS. Immunological studies provided evidence for qualitative immune resetting following AHSCT. These data and improved safety profiles of transplantation procedures spurred interest in using AHSCT as a treatment option for MS.
Objective:
To develop expert consensus recommendations on AHSCT in Germany and outline a registry study project.
Methods:
An open call among MS neurologists as well as among experts in stem cell transplantation in Germany started in December 2021 to join a series of virtual meetings.
Results:
We provide a consensus-based opinion paper authored by 25 experts on the up-to-date optimal use of AHSCT in managing MS based on the Swiss criteria. Current data indicate that patients who are most likely to benefit from AHSCT have relapsing-remitting MS and are young, ambulatory and have high disease activity. Treatment data with AHSCT will be collected within the German REgistry Cohort of autologous haematopoietic stem CeLl trAnsplantation In MS (RECLAIM).
Conclusion:
Further clinical trials, including registry-based analyses, are urgently needed to better define the patient characteristics, efficacy and safety profile of AHSCT compared with other high-efficacy therapies and to optimally position it as a treatment option in different MS disease stages.
Plain language summary
Autologous haematopoietic stem cell transplantation for multiple sclerosis
Substantial progress has been made in the development of disease-modifying medications for multiple sclerosis (MS) during the last 20 years. However, in a relevant percentage of patients, the disease cannot completely be contained. Autologous haematopoietic stem cell transplantation (AHSCT) enables rebuilding of a new and healthy immune system and to potentially stop the autoimmune disease process for a long time. A number of studies documenting 4000 cases cumulatively over the past 20 years reported high efficacy of AHSCT in controlling MS inflammatory disease activity. These data and improved safety profiles of the treatment procedures spurred interest in using AHSCT as a treatment option for MS.
An open call among MS neurologists as well as among experts in stem cell transplantation in Germany started in December 2021 to join a series of video calls to develop recommendations and outline a registry study project.
We provide a consensus-based opinion paper authored by 25 experts on the up-to-date optimal use of AHSCT in managing MS. Current data indicate that patients are most likely to benefit from AHSCT if they are young, ambulatory, with high disease activity, that is, relapses or new magnetic resonance imaging (MRI) lesions. Treatment data with AHSCT will be collected within the German REgistry Cohort of autoLogous haematopoietic stem cell transplantation MS (RECLAIM).
Further clinical trials including registry-based analyses and systematic follow-up are urgently needed to better define the optimal patient characteristics as well as the efficacy and safety profile of AHSCT compared with other high-efficacy therapies. These will help to position AHSCT as a treatment option in different MS disease stages.
The factories of the future will be highly digitalized in order to enable flexible and interconnected manufacturing processes. Especially wireless technologies will be beneficial for industrial ...automation. However, the high density of metallic objects is challenging for wireless systems due to multipath fading. In order to understand the signal propagation in industrial environments, this paper provides results from a number of channel measurement campaigns funded by the German research initiative “Reliable wireless communication in the industry”. We give an overview of different measurement scenarios covering visible light communication and radio communication below 6 GHz. We analyze large and small scale parameters as well as delay statistics of the wireless channels. Finally, we discuss the importance of the results for the definition of industrial channel models.
The steadily growing use of license-free frequency bands requires reliable coexistence management for deterministic medium utilization. For interference avoidance, proper wireless interference ...identification (WII) is essential. In this work we propose the first WII approach based upon deep convolutional neural networks (CNNs). The CNN naively learns its features through self-optimization during an extensive data-driven GPU-based training process. We propose a CNN example which is based upon sensing snapshots with a limited duration of 12.8 μs and an acquisition bandwidth of 10 MHz. The CNN distinguishes between 15 classes. They represent packet transmissions of IEEE 802.11 b/g, IEEE 802.15.4 and IEEE 802.15.1 with overlapping frequency channels within the 2.4 GHz ISM band. We show that the CNN outperforms state-of-the-art WII approaches and has a classification accuracy greater than 95 % for signal-to-noise ratio of at least -5 dB.
The extent to which wireless technologies in license-free bands are used comes along with a decrease in performance due to mutual interference. This problem can be solved by implementation of an ...automated coexistence management that distributes the resources space, time and frequency. This can be done by means of an optimization algorithm that is able to find a global optimum in a large finite solution set. We implemented such an algorithm based upon evolutionary algorithms (EA). Utilizing this algorithm, we can repeatedly optimize the resource distribution. The wireless infrastructure is represented through a graph, where edges constitute the interferences.
The steadily growing use of license-free frequency bands require reliable coexistence management and therefore proper wireless interference classification (WIC). In this work, we propose a WIC ...approach based upon a deep convolutional neural network (CNN) which classifies multiple IEEE 802.15.1, IEEE 802.11 b/g and IEEE 802.15.4 interfering signals in the presence of a utilized signal. The generated multi-label dataset contains frequency- and time-limited sensing snapshots with the bandwidth of 10MHz and duration of 12.8 μs, respectively. Each snapshot combines one utilized signal with up to multiple interfering signals. The approach shows promising results for same-technology interference with a classification accuracy of approximately 100% for narrow-band IEEE 802.15.1 and IEEE 802.15.4 signals. For cross-technology interference, wide-band IEEE 802.11 b/g signals achieve an accuracy above 90 %.
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