Speech and language abilities of children with the familial form of 22q11.2 deletion syndrome

The 22q11.2 Deletion Syndrome (22q11.2DS), which encompasses Shprintzen syndrome, DiGeorge and velocardiofacial syndrome, is the most common microdeletion syndrome in humans with an estimated incidence of approximately 1/4000 per live births. After Down syndrome, it is the second most common genetic syndrome associated with congenital heart malformations. The mode of inheritance of the 22q11.2DS is autosomal dominant. In approximately 72-94% of the cases the deletion has occurred de novo, while in 6 to 28% of patients deletion was inherited from a parent. As a part of a multidisciplinary study we examined the speech and language abilities of members of two families with inherited form of 22q11.2DS. The presence of 22q11.2 microdeletion was revealed by fluorescence in situ hybridization (FISH) and/or multiplex ligation-dependent probe amplification (MLPA). In one family we detected 1.5 Mb 22q11.2 microdeletion, while in the other family we found 3Mb microdeletion. Patients from both families showed delays in cognitive, socio-emotional, speech and language development. Furthermore, we found considerable variability in the phenotypic characteristics of 22q11.2DS and the degree of speech-language pathology not only between different families with 22q11.2 deletion, but also among members of the same family. In addition, we detected no correlation between the phenotype and the size of 22q11.2 microdeletion

Improved computation in terms of accuracy and speed of LTI system response with arbitrary input

Spectral analysis and system identification techniques require suitably long data sets. Linear time-invariant (LTI) systems under random input can be demanding in terms of accurate simulation of all dynamics because of calculation time. This paper details an extension of the state-space formulation of LTI systems for higher order holds, for periodic and for exponential inputs. Exact solutions of the differential state equation are implemented into loops computing only matrix-vector multiplications. The algorithmic complexity is compared to other ordinary differential equations solvers. The presented methods can be applied to arbitrary inputs. In particular, it is shown that long system responses under random input can be computed efficiently and accurately in the time and frequency domains

Automatische Schwingungsüberwachung von aeroelastischen Systemen

Die Schwingungen linear elastischer Strukturen lassen sich durch wenige modale Parameter bestehend aus Eigenfrequenzen, Eigenschwingungsformen, Dämpfungsmaße und modalen Massen beschreiben. Diese modalen Parameter werden unmittelbar vor dem Erstflug eines Prototyps für ein neu entwickeltes Flugzeug in einem Ground Vibration Test (GVT) identifiziert. Im Flug verändern sich die modalen Parameter aufgrund der einwirkenden instationären aerodynamischen Kräfte in Abhängigkeit der Flughöhe und -geschwindigkeit. Unter besonderen Bedingungen kann das aeroelastische System instabil werden, indem die schwingende Struktur Energie aus dem Strömungsfeld bezieht und die Schwingungsamplituden anwachsen. Dieses Phänomen nennt sich Flattern. Eine echtzeitfähige modale Identifikation kann kontinuierlich den Schwingungszustand des aeroelastischen Systems in Abhängigkeit geeigneter Parameter beobachten. Weisen die Änderungen der bereits ermittelten modalen Parameter (insbesondere der Dämpfung) darauf hin, dass ein zulässiger Grenzwert überschritten werden kann, können geeignete Maßnahmen eingeleitet werden. Im vorliegenden Beitrag wird eine Echtzeit-Analyse von gemessenen Beschleunigungen schwingender Strukturen zur Überwachung der Eigenfrequenzen, Dämpfungsmaße und Schwingungsformen vorgestellt. Eine auf kurze Rechenzeit optimierte MATLAB Implementierung in Verbindung mit DEWEtron oder National Instruments Messanlagen wird präsentiert. Die Methoden der experimentellen und operationellen Modalanalyse werden hinsichtlich effizienter und schneller Algorithmen erklärt, welche Ergebnisse in nur wenigen Sekunden bereitstellen. Die identifizierten modalen Parameter werden in Abhängigkeit des Flugzustands über Machzahl und Flughöhe dargestellt, um den Trend der Flatterstabilität vorhersagen zu können

Good vibrations - Surfin the wake in style: An approach to real-time-in-flight modal and loads analysis

This paper presents the concluded iLOADS project from the flight testing perspective. The project as a whole is being briefly described. A series of flight tests marked the end of the project, providing data to verify postulated theories and a proof-of-concept for the tools designed and developed during the project. The end result delivered input to DLR’s loads process and verified a new on-board real time flutter / modal analysis software tool. Flight Testing was performed with DLR’s Gulfstream G550 HALO

Online monitoring of flutter stability during wind tunnel testing of an elastic wing with pylon and engine nacelle within the HMAE1 project

Flutter testing in high speed wind tunnels is very challenging and costly. In order to enhance safety levels and to increase the amount of scientific output, real time identification methods are indispensable. This paper addresses a technique for fast and reliable identification of eigenfrequencies and damping ratios using operational modal analysis methods. The procedure has been developed by the Institute of Aeroelasticity of the German Aerospace Center (DLR) in Goettingen, Germany. It uses acceleration signals from turbulence excitation during wind tunnel testing for output-only modal identification. The evolution of eigenfrequencies and damping ratios in the range of interest is tracked over time and wind tunnel parameters. In more detail, the paper focuses on a wind tunnel test campaign conducted by the aircraft manufacturer Embraer, the German Aerospace Center, the Netherlands Aerospace Centre (NLR) and German–Dutch Wind Tunnels (DNW) on a highly elastic fiberglass wing body pylon nacelle configuration

HALO flight test with instrumented under-wing stores for aeroelastic and load measurements in the DLR project iLOADS

HALO (High Altitude and Long Range Research Aircraft), the atmospheric research aircraft of the German Aerospace Center (DLR), can be equipped with under-wing stores at different wing positions to transport scientific instruments for atmospheric research. The particle measurement system (PMS) carrier is such an external store which can carry three instruments at the same time per wing. Any modifications on an aircraft must be tested numerically and experimentally to ensure the structural integrity of the aircraft for all flight conditions. Load and flutter analyses can be validated with flight test data. For flight test, the aircraft and the under-wing stores of HALO must be equipped with acceleration and strain sensors. To reduce flight test time it is necessary to make quick decisions during the flight test. Therefore the DLR Institute of Aeroelasticity in Göttingen has developed a real-time analysis procedure for online identification of modal parameters like eigenfrequencies, damping ratios and mode shapes. These parameters vary with flight conditions and are necessary to analyse the aeroelastic stability of the system. The department of loads analysis and aeroelastic design and the department of structural dynamics and system identification have tested the newly developed procedure in 14 flight hours on the HALO. A network of three distributed data acquisition modules enabled the recording of the flight test instrumentation with 51 accelerometers and 16 strain gauge bridges. The measured data were distributed online on several computers where the newly developed software was implemented, allowing an instantaneous analysis of the structural dynamics behaviour and loads in flight. This paper provides an overview of the conducted flight vibration tests with HALO. It also shows the capability of the newly developed online monitoring system for aeroelastic identification