Geometrical jitter and bolometric regime in photon detection by straight superconducting nanowire

We present a direct observation of the geometrical jitter in single photon detection by a straight superconducting nanowire. Differential measurement technique was applied to the 180-{\mu}m long nanowire similar to those commonly used in the technology of superconducting nanowire single photon detectors (SNSPD). A non-gaussian geometrical jitter appears as a wide almost uniform probability distribution (histogram) of the delay time (latency) of the nanowire response to detected photon. White electrical noise of the readout electronics causes broadened, Gaussian shaped edges of the histogram. Subtracting noise contribution, we found for the geometrical jitter a standard deviation of 8.5 ps and the full width at half maximum (FWHM) of the distribution of 29 ps. FWHM corresponds to the propagation speed of the electrical signal along the nanowire of $6.2\times10^{6}$ m/s or 0.02 of the speed of light. Alternatively the propagation speed was estimated from the central frequency of the measured first order self-resonance of the nanowire. Both values agree well with each other and with previously reported values. As the intensity of the incident photon flux increases, the wide probability distribution collapses into a much narrower Gaussian distribution with a standard deviation dominated by the noise of electronics. We associate the collapse of the histogram with the transition from the discrete, single photon detection to the uniform bolometric regim

K(2P)18.1 translates T cell receptor signals into thymic regulatory T cell development

It remains largely unclear how thymocytes translate relative differences in T cell receptor (TCR) signal strength into distinct developmental programs that drive the cell fate decisions towards conventional (Tconv) or regulatory T cells (Treg). Following TCR activation, intracellular calcium (Ca2+) is the most important second messenger, for which the potassium channel K(2P)18.1 is a relevant regulator. Here, we identify K(2P)18.1 as a central translator of the TCR signal into the thymus-derived Treg (tTreg) selection process. TCR signal was coupled to NF-kappa B-mediated K(2P)18.1 upregulation in tTreg progenitors. K(2P)18.1 provided the driving force for sustained Ca2+ influx that facilitated NF-kappa B- and NFAT-dependent expression of FoxP3, the master transcription factor for Treg development and function. Loss of K(2P)18.1 ion-current function induced a mild lymphoproliferative phenotype in mice, with reduced Treg numbers that led to aggravated experimental autoimmune encephalomyelitis, while a gain-of-function mutation in K(2P)18.1 resulted in increased Treg numbers in mice. Our findings in human thymus, recent thymic emigrants and multiple sclerosis patients with a dominant-negative missense K(2P)18.1 variant that is associated with poor clinical outcomes indicate that K(2P)18.1 also plays a role in human Treg development. Pharmacological modulation of K(2P)18.1 specifically modulated Treg numbers in vitro and in vivo. Finally, we identified nitroxoline as a K(2P)18.1 activator that led to rapid and reversible Treg increase in patients with urinary tract infections. Conclusively, our findings reveal how K(2P)18.1 translates TCR signals into thymic T cell fate decisions and Treg development, and provide a basis for the therapeutic utilization of Treg in several human disorders.Peer reviewe

Amorphous Silicon / Crystalline Silicon Heterojunction Solar Cells

Amorphous Silicon/Crystalline Silicon Solar Cells deals with some typical properties of heterojunction solar cells, such as their history, the properties and the challenges of the cells, some important measurement tools, some simulation programs and a brief survey of the state of the art, aiming to provide an initial framework in this field and serve as a ready reference for all those interested in the subject. This book helps to “fill in the blanks” on heterojunction solar cells. Readers will receive a comprehensive overview of the principles, structures, processing techniques and the current developmental states of the devices

Automated Video-Based Analysis Framework for Behavior Monitoring of Individual Animals in Zoos Using Deep Learning - A Study on Polar Bears

The monitoring of animals under human care is a crucial tool for biologists and zookeepers to keep track of the animals’ physical and psychological health. Additionally, it enables the analysis of observed behavioral changes and helps to unravel underlying reasons. Enhancing our understanding of animals ensures and improves ex situ animal welfare as well as in situ conservation. However, traditional observation methods are time- and labor-intensive, as they require experts to observe the animals on-site during long and repeated sessions and manually score their behavior. Therefore, the development of automated observation systems would greatly benefit researchers and practitioners in this domain. We propose an automated framework for basic behavior monitoring of individual animals under human care. Raw video data are processed to continuously determine the position of the individuals within the enclosure. The trajectories describing their travel patterns are presented, along with fundamental analysis, through a graphical user interface (GUI). We evaluate the performance of the framework on captive polar bears (Ursus maritimus). We show that the framework can localize and identify individual polar bears with an F1 score of 86.4%. The localization accuracy of the framework is 19.9±7.6 cm, outperforming current manual observation methods. Furthermore, we provide a bounding-box-labeled dataset of the two polar bears housed in Nuremberg Zoo