It is challenging to implement genuine free running single-photon detectors for the 1550 nm wavelength range with simultaneously high detection efficiency (DE), low dark noise, and good time resolution. We report a novel read out system for the signals from a negative feedback avalanche diode (NFAD) [M. A. Itzler, X. Jiang, B. Nyman, and K. Slomkowski, "Quantum sensing and nanophotonic devices VI," Proc. SPIE 7222, 72221K (2009); X. Jiang, M. A. Itzler, K. ODonnell, M. Entwistle, and K. Slomkowski, "Advanced photon counting techniques V," Proc. SPIE 8033, 80330K (2011); M. A. Itzler, X. Jiang, B. M. Onat, and K. Slomkowski, "Quantum sensing and nanophotonic devices VII," Proc. SPIE 7608, 760829 (2010)], which allows useful operation of these devices at a temperature of 193 K and results in very low darkcounts (∼100 counts per second (CPS)), good time jitter (∼30 ps), and good DE (∼10%). We characterized two NFADs with a time-correlation method using photons generated from weak coherent pulses and photon pairs produced by spontaneous parametric down conversion. The inferred detector efficiencies for both types of photon sources agree with each other. The best noise equivalent power of the device is estimated to be 8.1 × 10(-18) W Hz(-1/2), more than 10 times better than typical InP/InGaAs single photon avalanche diodes (SPADs) show in free running mode. The afterpulsing probability was found to be less than 0.1% per ns at the optimized operating point. In addition, we studied the performance of an entanglement-based quantum key distribution (QKD) using these detectors and develop a model for the quantum bit error rate that incorporates the afterpulsing coefficients. We verified experimentally that using these NFADs it is feasible to implement QKD over 400 km of telecom fiber. Our NFAD photon detector system is very simple, and is well suited for single-photon applications where ultra-low noise and free-running operation is required, and some afterpulsing can be tolerated.
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Sci Rep
January 2025
Division of Experimental Psychology and Neuropsychology, Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee 45, 14195, Berlin, Germany.
Neuropsychological assessment has to consider the subjective and objective functional deficits of help-seeking individuals in several cognitive domains. Due to time constraints in clinical practice, several web-based approaches have been developed. The current study examined whether functional deficits in the mnestic and attentive domain can be predicted based on an unsupervised self-administered online assessment neuropsychological online screening (NOS): This screening includes self-reports and psychometric memory tests (face-name association, visual short-term memory).
View Article and Find Full Text PDFMagn Reson Med
January 2025
Department of Radiology & Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Purpose: To correct maternal breathing and fetal bulk motion during fetal 4D flow MRI.
Methods: A Doppler-ultrasound fetal cardiac-gated free-running 4D flow acquisition was corrected post hoc for maternal respiratory and fetal bulk motion in separate automated steps, with optional manual intervention to assess and limit fetal motion artifacts. Compressed-sensing reconstruction with a data outlier rejection algorithm was adapted from previous work.
Comput Methods Programs Biomed
January 2025
Laberit, Avda. de Catalunya, 9, València, 46020, Spain.
Background And Objective: Despite significant investments in the normalization and the standardization of Electronic Health Records (EHRs), free text is still the rule rather than the exception in clinical notes. The use of free text has implications in data reuse methods used for supporting clinical research since the query mechanisms used in cohort definition and patient matching are mainly based on structured data and clinical terminologies. This study aims to develop a method for the secondary use of clinical text by: (a) using Natural Language Processing (NLP) for tagging clinical notes with biomedical terminology; and (b) designing an ontology that maps and classifies all the identified tags to various terminologies and allows for running phenotyping queries.
View Article and Find Full Text PDFDrug Saf
January 2025
Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Background: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence of their real-world effectiveness remains unclear.
Objective: To summarise the evidence on the effectiveness of NLP/ML in detecting ADEs from unstructured EHR data and ultimately improve pharmacovigilance in comparison to other data sources.
J Biol Rhythms
January 2025
Department of Biochemistry and Structural Biology, University of Texas Health San Antonio, San Antonio, Texas.
Circadian disruption is pervasive in modern society and associated with increased risk of disease. Chronic jet lag paradigms are popular experimental tools aiming to emulate human circadian disruption experienced during rotating and night shift work. Chronic jet lag induces metabolic phenotypes tied to liver and systemic functions, yet lack of a clear definition for how rhythmic physiology is impaired under these conditions hinders the ability to identify the underlying molecular mechanisms.
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