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An Inexpensive Uv-Led Photoacoustic Based Real-Time Sensor-System Detecting Exhaled Trace-Acetone
(2024)
In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) – providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 6.4 ppbV and an NNEA of 1.1E-9 Wcm-1Hz-0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.
Real-time computational speed and a high degree of precision are requirements for computer-assisted interventions. Applying a segmentation network to a medical video processing task can introduce significant inter-frame prediction noise. Existing approaches can reduce inconsistencies by including temporal information but often impose requirements on the architecture or dataset. This paper proposes a method to include temporal information in any segmentation model and, thus, a technique to improve video segmentation performance without alterations during training or additional labeling. With Motion-Corrected Moving Average, we refine the exponential moving average between the current and previous predictions. Using optical flow to estimate the movement between consecutive frames, we can shift the prior term in the moving-average calculation to align with the geometry of the current frame. The optical flow calculation does not require the output of the model and can therefore be performed in parallel, leading to no significant runtime penalty for our approach. We evaluate our approach on two publicly available segmentation datasets and two proprietary endoscopic datasets and show improvements over a baseline approach.
Finding the optimal join order (JO) is one of the most important problems in query optimisation, and has been extensively considered in research and practise. As it involves huge search spaces, approximation approaches and heuristics are commonly used, which explore a reduced solution space at the cost of solution quality. To explore even large JO search spaces, we may consider special-purpose software, such as mixed-integer linear programming (MILP) solvers, which have successfully solved JO problems. However, even mature solvers cannot overcome the limitations of conventional hardware prompted by the end of Moore’s law. We consider quantum-inspired digital annealing hardware, which takes inspiration from quantum processing units (QPUs). Unlike QPUs, which likely remain limited in size and reliability in the near and mid-term future, the digital annealer (DA) can solve large instances of mathematically encoded optimisation problems today. We derive a novel, native encoding for the JO problem tailored to this class of machines that substantially improves over known MILP and quantum-based encodings, and reduces encoding size over the state-of-the-art. By augmenting the computation with a novel readout method, we derive valid join orders for each solution obtained by the (probabilistically operating) DA. Most importantly and despite an extremely large solution space, our approach scales to practically relevant dimensions of around 50 relations and improves result quality over conventionally employed approaches, adding a novel alternative to solving the long-standing JO problem.
In this study, a pilot-scale trickle-bed reactor for biological methanation and various scale-up scenarios for 2023 and 2050 were investigated using LCA. A best- and worst-case scenario for technology development until 2050 was evolved using cross consistency analysis and morphological field, based on which the data for the ecological models were determined.The results show that the plant scale-up has a very positive effect on the ecological consequences of methanation. In the best-case scenario, the values are a factor of 23-780 lower than those of the actual plant today. A hot-spot analysis showed that especially electrolysis operation has a large impact on total emissions. The final Monte-Carlo simulation shows that the technology is likely to achieve a low GWP with a median of 104.0 kg CO2-eq / MWh CH4.
Inverse problems are inherently ill-posed and therefore require regularization techniques to achieve a stable solution. While traditional variational methods have wellestablished theoretical foundations, recent advances in machine learning based approaches have shown remarkable practical performance. However, the theoretical foundations of learning-based methods in the context of regularization are still underexplored. In this paper, we propose a general framework that addresses the current gap between learning-based methods and regularization strategies. In particular, our approach emphasizes the crucial role of data consistency in the solution of inverse problems and introduces the concept of data-proximal null-space networks as a key component for their solution. We provide a complete convergence analysis by extending the concept of regularizing null-space networks with data proximity in the visual part. We present numerical results for limited-view computed tomography to illustrate the validity of our framework.
Hintergrund /Zielsetzung
Der Beitrag befasst sich mit Wissenstand und Einstellung der Bevölkerung. Betrachtet werden die Übermittlung und Verfügbarkeit von Gesundheitsdaten, Gesundheitsregister, die elektronische Patientenakte, Einwilligungsverfahren für die Übermittlung von Daten und der Zugriff auf Gesundheitsdaten zu Forschungszwecken.
Methoden
Die Studie basiert auf einer computergestützten Telefonbefragung (Dual-Frame) bei einer Zufallsstichprobe der Bevölkerung in Deutschland im Zeitraum 01.-27.06.2022 (n=1.308).
Ergebnisse
Der Wissensstand zur Übermittlung von Gesundheitsdaten an Krankenkassen ist hoch, wohingegen das Vorhandensein zentraler Sterbe-, Impf-, und Gesundheitsregister und der Zugriff auf Gesundheitsdaten durch behandelnde Ärztinnen und Ärzte überschätzt werden. Die Akzeptanz medizinischer Register ist sehr hoch. Die elektronische Patientenakte ist bei der Hälfte der Bevölkerung unbekannt, die Nutzungsbereitschaft ist eher gering ausgeprägt, bei der Übertragung von Daten wird eine Zustimmungsoption bevorzugt und über achtzig Prozent würden die Daten der elektronischen Patientenakte zur Forschung freigeben. Drei Viertel würden ihre Gesundheitsdaten allgemein zur Forschung freigeben, insbesondere an Universitäten in Deutschland, wobei meist Anonymität Bedingung ist. Die Bereitschaft zur Datenfreigabe steigt mit Höhe des Vertrauens in Presse sowie in Universitäten und Hochschulen und sinkt, wenn ein Datenleck als schwerwiegend betrachtet wird.
Diskussion und Schlussfolgerung
In Deutschland besteht, wie in anderen europäischen Ländern, eine große Bereitschaft zur Freigabe von Gesundheitsdaten zu Forschungszwecken. Dagegen ist der Wunsch zur Nutzung der elektronischen Patientenakte eher gering. Ebenso niedrig ist die Akzeptanz einer Widerspruchsoption, die jedoch als Voraussetzung für eine erfolgreiche Einführung einer elektronischen Patientenakte gilt. Vertrauen in die Forschung und staatliche Stellen, die Gesundheitsdaten verarbeiten, sind zentrale Faktoren.
Trace gas analysis in breath is challenging due to the vast number of different components. We present a highly sensitive quantum cascade laser based photoacoustic setup for breath analysis. Scanning the range between 8260 and 8270 nm with a spectral resolution of 48 pm, we are able to quantify acetone and ethanol within a typical breath matrix containing water and CO2. We photoacoustically acquired spectra within this region of mid-infra-red light and prove that those spectra do not suffer from non-spectral interferences. The purely additive behavior of a breath sample spectrum was verified by comparing it with the independently acquired single component spectra using Pearson and Spearman correlation coefficients. A previously presented simulation approach is improved and an error attribution study is presented. With a 3σ detection limit of 6.5 ppbV in terms of ethanol and 250 pptV regarding acetone, our system is among the best performing presented so far.
Fires in tunnels are known to lead to explosive spalling of the tunnel linings, mainly due to rapid expansion of water as a result of vaporization in the concrete. In order to determine water content and assess fire safety within tunnel linings a novel measurement system has been developed. The development process includes the calibration of the sensor system via both direct and indirect approaches. This work compares both calibration methods and shows the differences that can occur due to measurement uncertainty. This work presents the measured water content within the Inntal tunnel, Austria as a representative tunnel from a total of four investigated tunnels. The obtained water content is compared to that found in the literature, and recommendations for practical work in terms of fire safety is given.
With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10−9) methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective, is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a five day period at Hohenpeißenberg, Germany. As a reference device a calibrated cavity ringdown spectrometer Picarro G2301 from the meteorological observatory was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to environmental influences. The obtained results show that relaxation effects due to fluctuating environmental conditions, e.g. ambient humidity, are a non-negligible factor in PA sensor systems. Applying algorithm compensation techniques, which are capable of calculating the influence of relaxational effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 % from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.
Friction has long been an important issue in multibody dynamics. Static friction models apply appropriate regularization techniques to convert the stick inequality and the non-smooth stick-slip transition of Coulomb’s approach into a continuous and smooth function of the sliding velocity. However, a regularized friction force is not able to maintain long-term stick. That is why, dynamic friction models were developed in the last decades. The friction force depends herein not
only on the sliding velocity but also on internal states. The probably best known representative, the LuGre friction model, is based on a fictitious bristle but realizes a too simple approximation. The recently published second order dynamic friction model describes the dynamics of a fictitious bristle more accurately. Its performance is compared here to stick-slip friction models, developed and launched not long ago by commercial multibody software packages.