Molecules as Sources for Indistinguishable Single Photons

We report on the triggered generation of indistinguishable photons by solid-state single-photon sources in two separate cryogenic laser scanning microscopes. Organic fluorescent molecules were used as emitters and investigated by means of high resolution laser spectroscopy. Continuous-wave photon correlation measurements on individual molecules proved the isolation of single quantum systems. By using frequency selective pulsed excitation of the molecule and efficient spectral filtering of its emission, we produced triggered Fourier-limited single photons. In a further step, local electric fields were applied to match the emission wavelengths of two different molecules via Stark effect. Identical single photons are indispensible for the realization of various quantum information processing schemes proposed. The solid-state approach presented here prepares the way towards the integration of multiple bright sources of single photons on a single chip.Comment: Accepted for publication in J. Mod. Opt. This is the original submitted versio

Optical Coherence Tomography for Examination of Parchment Degradation

A novel application of Optical Coherence Tomography utilizing infrared light of 830 nm central wavelength for non invasive examination of the structure of parchment, some covered with iron gall ink, is presented. It is shown that both the parchment and the ink applied are sufficiently transparent to light of this wavelength. In the study, Spectral OCT (SOCT) as well as Polarisation Sensitive OCT (PS-OCT) techniques were used to obtain cross-sectional images of samples of parchment based on scattering properties. The second technique was additionally employed to recover the birefringence properties and the optical axis orientations of the sample. It was shown that freshly produced parchment exhibits a degree of birefringence. However, this property declines with ageing, and samples of old parchment completely depolarise the incident light

Quantum Interference of Tunably Indistinguishable Photons from Remote Organic Molecules

We demonstrate two-photon interference using two remote single molecules as bright solid-state sources of indistinguishable photons. By varying the transition frequency and spectral width of one molecule, we tune and explore the effect of photon distinguishability. We discuss future improvements on the brightness of single-photon beams, their integration by large numbers on chips, and the extension of our experimental scheme to coupling and entanglement of distant molecules

Konzeption und Entwicklung eines Condition Monitoring Systems mit Low Cost Sensoren zur Überwachung von Roboterschwingungen

Im Rahmen dieser Veröffentlichung wird ein Konzept zur Erfassung des Schwingungsverhaltens von Industrierobotern mit Hilfe von Low Cost Sensoren vorgestellt. Durch dieses sollen die dynamischen Eigenschaften des Industrieroboters im gesamten Arbeitsraum untersucht werden. Die Roboterstruktur wird dazu durch eine speziell konstruierte Unwuchtscheibe angeregt. Das Messsystem besteht aus einem Beschleunigungssensor, einem Arduino-Mikrocontroller und einem eigens entwickelten Mess- und Auswerteprogramm in der Softwareumgebung MATLAB®. Die Validierung des Konzeptes erfolgt jeweils mit Messreihen an einem Kragbalken sowie an einem Industrieroboter durch den Vergleich mit einem Referenzmesssystem der Firma Brüel & Kjaer. Durch das entwickelte Low Cost Condition Monitoring System lassen sich die Anregungsfrequenzen und –amplituden mit hinreichender Genauigkeit erfassen und Rückschlüsse auf das Schwingungsverhalten des Industrieroboters ziehen

Imaging shear stress distribution and evaluating the stress concentration factor of the human eye.

Healthy eyes are vital for a better quality of human life. Historically, for man-made materials, scientists and engineers use stress concentration factors to characterise the effects of structural non-homogeneities on their mechanical strength. However, such information is scarce for the human eye. Here we present the shear stress distribution profiles of a healthy human cornea surface in vivo using photo-stress analysis tomography, which is a non-intrusive and non-X-ray based method. The corneal birefringent retardation measured here is comparable to that of previous studies. Using this, we derive eye stress concentration factors and the directional alignment of major principal stress on the surface of the cornea. Similar to thermometers being used for monitoring the general health in humans, this report provides a foundation to characterise the shear stress carrying capacity of the cornea, and a potential bench mark for validating theoretical modelling of stresses in the human eye in future

Comparison of three creatinine-based equations to predict adverse outcome in a cardiovascular high-risk cohort:an investigation using the SPRINT research materials

Background:Novel creatinine-based equations have recently been proposed but their predictive performance for cardiovascular outcomes in participants at high cardiovascular risk in comparison to the established CKD-EPI 2009 equation is unknown. Method:In 9361 participants from the United States included in the randomized controlled SPRINT trial, we calculated baseline estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009, CKD-EPI 2021, and EKFC equations and compared their predictive value of cardiovascular events. The statistical metric used is the net reclassification improvement (NRI) presented separately for those with and those without events. Results:During a mean follow-up of 3.1 ± 0.9 years, the primary endpoint occurred in 559 participants (6.0%). When using the CKD-EPI 2009, the CKD-EPI 2021, and the EKFC equations, the prevalence of CKD (eGFR &lt;60 ml/min/1.73 m2 or &gt;60 ml/min/1.73 m2 with an ACR ≥30 mg/g) was 37% vs. 35.3% (P = 0.02) vs. 46.4% (P &lt; 0.001), respectively. The corresponding mean eGFR was 72.5 ± 20.1 ml/min/1.73 m2 vs. 73.2 ± 19.4 ml/min/1.73 m2 (P &lt; 0.001) vs. 64.6 ± 17.4 ml/min/1.73 m2 (P &lt; 0.001). Neither reclassification according to the CKD-EPI 2021 equation [CKD-EPI 2021 vs. CKD-EPI 2009: NRIevents: −9.5% (95% confidence interval (CI) −13.0% to −5.9%); NRInonevents: 4.8% (95% CI 3.9% to 5.7%)], nor reclassification according to the EKFC equation allowed better prediction of cardiovascular events compared to the CKD-EPI 2009 equation (EKFC vs. CKD-EPI 2009: NRIevents: 31.2% (95% CI 27.5% to 35.0%); NRInonevents: −31.1% (95% CI −32.1% to −30.1%)). Conclusion. Substituting the CKD-EPI 2009 with the CKD-EPI 2021 or the EKFC equation for calculation of eGFR in participants with high cardiovascular risk without diabetes changed the prevalence of CKD but was not associated with improved risk prediction of cardiovascular events for both those with and without the event.</p

Comparison of three creatinine-based equations to predict adverse outcome in a cardiovascular high-risk cohort:an investigation using the SPRINT research materials

Background:Novel creatinine-based equations have recently been proposed but their predictive performance for cardiovascular outcomes in participants at high cardiovascular risk in comparison to the established CKD-EPI 2009 equation is unknown. Method:In 9361 participants from the United States included in the randomized controlled SPRINT trial, we calculated baseline estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009, CKD-EPI 2021, and EKFC equations and compared their predictive value of cardiovascular events. The statistical metric used is the net reclassification improvement (NRI) presented separately for those with and those without events. Results:During a mean follow-up of 3.1 ± 0.9 years, the primary endpoint occurred in 559 participants (6.0%). When using the CKD-EPI 2009, the CKD-EPI 2021, and the EKFC equations, the prevalence of CKD (eGFR &lt;60 ml/min/1.73 m2 or &gt;60 ml/min/1.73 m2 with an ACR ≥30 mg/g) was 37% vs. 35.3% (P = 0.02) vs. 46.4% (P &lt; 0.001), respectively. The corresponding mean eGFR was 72.5 ± 20.1 ml/min/1.73 m2 vs. 73.2 ± 19.4 ml/min/1.73 m2 (P &lt; 0.001) vs. 64.6 ± 17.4 ml/min/1.73 m2 (P &lt; 0.001). Neither reclassification according to the CKD-EPI 2021 equation [CKD-EPI 2021 vs. CKD-EPI 2009: NRIevents: −9.5% (95% confidence interval (CI) −13.0% to −5.9%); NRInonevents: 4.8% (95% CI 3.9% to 5.7%)], nor reclassification according to the EKFC equation allowed better prediction of cardiovascular events compared to the CKD-EPI 2009 equation (EKFC vs. CKD-EPI 2009: NRIevents: 31.2% (95% CI 27.5% to 35.0%); NRInonevents: −31.1% (95% CI −32.1% to −30.1%)). Conclusion. Substituting the CKD-EPI 2009 with the CKD-EPI 2021 or the EKFC equation for calculation of eGFR in participants with high cardiovascular risk without diabetes changed the prevalence of CKD but was not associated with improved risk prediction of cardiovascular events for both those with and without the event.</p

Comparison of three creatinine-based equations to predict adverse outcome in a cardiovascular high-risk cohort: an investigation using the SPRINT research materials

Background. Novel creatinine-based equations have recently been proposed but their predictive performance for cardiovascular outcomes in participants at high cardiovascular risk in comparison to the established CKD-EPI 2009 equation is unknown. Method. In 9361 participants from the United States included in the randomized controlled SPRINT trial, we calculated baseline estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009, CKD-EPI 2021, and EKFC equations and compared their predictive value of cardiovascular events. The statistical metric used is the net reclassification improvement (NRI) presented separately for those with and those without events. Results. During a mean follow-up of 3.1 ± 0.9 years, the primary endpoint occurred in 559 participants (6.0%). When using the CKD-EPI 2009, the CKD-EPI 2021, and the EKFC equations, the prevalence of CKD (eGFR <60 ml/min/1.73 m2 or >60 ml/min/1.73 m2 with an ACR ≥30 mg/g) was 37% vs. 35.3% (P = 0.02) vs. 46.4% (P < 0.001), respectively. The corresponding mean eGFR was 72.5 ± 20.1 ml/min/1.73 m2 vs. 73.2 ± 19.4 ml/min/1.73 m2 (P < 0.001) vs. 64.6 ± 17.4 ml/min/1.73 m2 (P < 0.001). Neither reclassification according to the CKD-EPI 2021 equation [CKD-EPI 2021 vs. CKD-EPI 2009: NRIevents: −9.5% (95% confidence interval (CI) −13.0% to −5.9%); NRInonevents: 4.8% (95% CI 3.9% to 5.7%)], nor reclassification according to the EKFC equation allowed better prediction of cardiovascular events compared to the CKD-EPI 2009 equation (EKFC vs. CKD-EPI 2009: NRIevents: 31.2% (95% CI 27.5% to 35.0%); NRInonevents: −31.1% (95% CI −32.1% to −30.1%)). Conclusion. Substituting the CKD-EPI 2009 with the CKD-EPI 2021 or the EKFC equation for calculation of eGFR in participants with high cardiovascular risk without diabetes changed the prevalence of CKD but was not associated with improved risk prediction of cardiovascular events for both those with and without the event

RoSA: A Framework for Modeling Self-Awareness in Cyber-Physical Systems

The role of smart and autonomous systems is becoming vital in many areas of industry and society. Expectations from such systems continuously rise and become more ambitious: long lifetime, high reliability, high performance, energy efficiency, and adaptability, particularly in the presence of changing environments. Computational self-awareness promises a comprehensive assessment of the system state for sensible and well-informed actions and resource management. Computational self-awareness concepts can be used in many applications such as automated manufacturing plants, telecommunication systems, autonomous driving, traffic control, smart grids, and wearable health monitoring systems. Developing self-aware systems from scratch for each application is the most common practice currently, but this is highly redundant, inefficient, and uneconomic. Hence, we propose a framework that supports modeling and evaluation of various self-aware concepts in hierarchical agent systems, where agents are made up of self-aware functionalities. This paper presents the Research on Self-Awareness (RoSA) framework and its design principles. In addition, self-aware functionalities abstraction, data reliability, and confidence, which are currently provided by RoSA, are described. Potential use cases of RoSA are discussed. Capabilities of the proposed framework are showcased by case studies from the fields of healthcare and industrial monitoring. We believe that RoSA is capable of serving as a common framework for self-aware modeling and applications and thus helps researchers and engineers in exploring the vast design space of hierarchical agent-based systems with computational self-awareness