In der Astronomie zeigen viele Quellen ein veränderliches Verhalten, das in manchen Fällen sehr kurz sein und im Bereich von Sekunden bis Minuten liegen kann. Beispiele dafür sind Gammablitze (GB) und aktive Galaxienkerne (AGK). Um die zugrundeliegenden physikalischen Prozesse besser zu verstehen, ist eine Messung der Photonenflussänderung notwendig. Allerdings kann die Entdeckung sehr kurzzeitiger Ausbrüche im sehr hochenergetischen Bereich des Spektrums, für welche Cherenkov Teleskope, wie VERITAS, zum Einsatz kommen, schwierig sein. Die Ursache dafür ist der hohe Untergrund und die relativ niedrige Signalrate. Diese Arbeit behandelt die Implementierung fortschrittlicher und für die Entdeckung signifikanter Ratenänderung optimierter, statistischer Methoden (exp-test and Bayesian-Blocks) innerhalb der VERITAS-Analyse. Das Verhalten dieser Methoden wird anhand von Daten minutenlanger Ausbrüche, die mittels Monte-Carlo-Technik für zwei unterschiedliche VERITAS Stadien simuliert wurden (vor und nach der Hardware-Aufrüstung), bewertet und miteinander verglichen. Die fortschrittlichen Methoden verbessern die Empfindlichkeit bei der Entdeckung von kurzzeitigen Ausbrüchen, wenn deren Fluss den des Krebsnebels übersteigt (Krebsnebel-Einheit = K.E.). Es sind nun Ausbrüche von 2 K.E. selbst dann nachweisbar, wenn deren Dauer nur 100 Sek. beträgt. Dies ist mit der Standardmethode nicht möglich. Im darauffolgenden Schritt dieser Arbeit werden das Nachglühen von 6 GB sowie die 450, ebenfalls mit VERITAS erzeugten, Aufnahmen von AGK-Quellen mittels der fortschrittlichen Methoden analysiert. In keiner der AGK-Aufnahmen wird eine signifikante Entdeckung kurzzeitiger Variabilität gemacht, was mit den anerkannten AGK-Modellen übereinstimmt. Auch die Untersuchung des Nachglühens der 6 GB offenbart keine kurzen Ausbrüche im GeV-TeV Bereich. Jedoch ist es für 2 von ihnen möglich, ein oberes Flusslimit von 1.25 K.E. (3,7 · 10^(−10) erg/(cm^2*s) [0,1;10 TeV]) abzuschätzen. / In astronomy, many of the observed sources show a transient behavior. Examples are gamma-ray bursts (GRBs) and active galactic nuclei (AGN). For those source types the variability can be very short, in the order of seconds to minutes. Measuring the flux variations is necessary to understand the underlying physical processes responsible for the emission. However, the detection of very short flares can be difficult in the very high-energy range, in which imaging atmospheric Cherenkov telescopes like VERITAS are operating. This is due to the large background and the comparable low signal rates. This thesis discusses the implementation of advanced statistical methods (exp-test and Bayesian-Blocks) into the VERITAS analysis framework, that are optimized for the detection of significant variations in the event rate. The performance of these methods is evaluated and compared by using Monte Carlo simulations of minute scale flares for two different VERITAS states, pre- and post-hardware-upgrade. It is shown that the advanced methods can improve the detection sensitivity for short flares with high fluxes of more than the Crab flux (Crab unit = C.U.). For example, flares at 2 C.U. with short durations down to 100 sec are now detectable, which is not possible with the standard method. In the next step of this thesis, 6 GRB afterglows and 450 runs of AGN data, observed by VERITAS, are analyzed with the advanced methods. In none of the AGN runs a significant detection of short time variability is made, which is in consistence with the canonical AGN models. The investigation of the 6 GRB afterglows also did not reveal any short flares in the GeV-TeV range. However, for two of them it was possible to estimate an upper flux limit of 1.25 C.U. (3,7 * 10^(−10) erg/(s*cm^2) [0,1;10 TeV]).

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Background The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures. Methods T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12–29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression. Results Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN. Conclusions In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.