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At least 865 records · Page 48

Application of combined optical signal processing methods to compensate for nonlinear effects in fibre-optic communication links

We report on the use of complex quadrature amplitude signal processing methods based on a combination of static neural networks and special modulation techniques. The conditions are found that allow one to construct the most effective combination of signal processing methods for transmitting signals with considerable power (in the nonlinear regime). Using analytical methods, it is shown how the statistical properties of a signal affect the efficiency of combined processing methods. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

GUN1 interacts with MORF2 to regulate plastid RNA editing during retrograde signaling

During development or under stress, chloroplasts generate signals that regulate the expression of a large number of nuclear genes, a process called retrograde signaling. GENOMES UNCOUPLED 1 (GUN1) is an important regulator of this pathway. In this study, we have discovered an unexpected role for GUN1 in plastid RNA editing, as gun1 mutations affect RNA-editing efficiency at multiple sites in plastids during retrograde signaling. GUN1 plays a direct role in RNA editing by physically interacting with MULTIPLE ORGANELLAR RNA EDITING FACTOR 2 (MORF2). MORF2 overexpression causes widespread RNA-editing changes and a strong genomes uncoupled ( gun ) molecular phenotype similar to gun1 . MORF2 further interacts with RNA-editing site-specificity factors: ORGANELLE TRANSCRIPT PROCESSING 81 (OTP81), ORGANELLE TRANSCRIPT PROCESSING 84 (OTP84), and YELLOW SEEDLINGS 1 (YS1). We further show that otp81 , otp84 , and ys1 single mutants each exhibit a very weak gun phenotype, but combining the three mutations enhances the phenotype. Our study uncovers a role for GUN1 in the regulation of RNA-editing efficiency in damaged chloroplasts and suggests that MORF2 is involved in retrograde signaling.

59 BASIC BIOLOGICAL SCIENCES↗

Fatty acid-mediated signaling as a target for developing type 1 diabetes therapies

Type 1 diabetes (T1D) is an autoimmune disease in which pro-inflammatory and cytotoxic signaling drive the death of the insulin-producing ß cells. This complex signaling is regulated in part by fatty acids and their bioproducts, making them excellent therapeutic targets. We provide an overview of the fatty acid actions on ß cells by discussing how they can cause lipotoxicity or regulate inflammatory response during insulitis. Additionally, we also discuss how diet can affect the availability of fatty acids and disease development. Finally, we discuss development avenues that need further exploration. Fatty acids, such as hydroxyl fatty acids, ω-3 fatty acids and their downstream products, are druggable candidates that promote protective signaling. Inhibitors and antagonists of enzymes and receptors of arachidonic acid and free fatty acid metabolites, which cause pro-inflammatory and cytotoxic responses, have the potential to be developed as therapeutic targets also. Further, because diet is the main source of fatty acid intake in humans, balancing protective and pro-inflammatory/cytotoxic fatty acid levels through dietary therapy may have beneficial effects, delaying T1D progression. Therefore, therapeutic interventions targeting fatty acid signaling hold potential as avenues to treat T1D.

60 APPLIED LIFE SCIENCES↗

Adaptive Online Multivariate Signal Extraction With Locally Weighted Robust Polynomial Regression

High-frequency, multivariate data collected in real-time and used to control or make decisions regarding a process’ operation often contain some noise and outliers. Thus, a method to extract the signal is needed in order to reduce the number and magnitude of control-based adjustments that are implemented. Such a method must be (i) online, depending only on past and current observations; (ii) fast, producing a smooth value more quickly than the measurement frequency; (iii) robust, ignoring brief bursts of erroneously measured values; (iv) multivariate, ignoring observations that are jointly unusual; (v) adaptive, adjusting to periods of rapid fluctuation in the signal versus periods of stability; and (vi) purely data-driven, not incorporating any information about the process from which the data are collected. Most existing methods are only able to address a subset of these six features. Furthermore, we also require the method to be nonlinear, providing a local nonlinear estimate of the signal. In this work, we propose a novel, real-time signal extraction method based on a local, robust polynomial fit. We demonstrate the performance of our method compared to a state-of-the-art competitor through simulation. For illustration, the methodology is applied to data collected from a reverse osmosis water treatment process.

97 MATHEMATICS AND COMPUTING↗

INTERPRETING THE GLOBAL 21-cm SIGNAL FROM HIGH REDSHIFTS. II. PARAMETER ESTIMATION FOR MODELS OF GALAXY FORMATION

Following our previous work, which related generic features in the sky-averaged (global) 21-cm signal to properties of the intergalactic medium, we now investigate the prospects for constraining a simple galaxy formation model with current and near-future experiments. Markov-Chain Monte Carlo fits to our synthetic data set, which includes a realistic galactic foreground, a plausible model for the signal, and noise consistent with 100 hr of integration by an ideal instrument, suggest that a simple four-parameter model that links the production rate of Lyα, Lyman-continuum, and X-ray photons to the growth rate of dark matter halos can be well-constrained (to ∼0.1 dex in each dimension) so long as all three spectral features expected to occur between 40 ≲ ν/MHz ≲ 120 are detected. Several important conclusions follow naturally from this basic numerical result, namely that measurements of the global 21-cm signal can in principle (i) identify the characteristic halo mass threshold for star formation at all redshifts z ≳ 15, (ii) extend z ≲ 4 upper limits on the normalization of the X-ray luminosity star formation rate (L{sub X}–SFR) relation out to z ∼ 20, and (iii) provide joint constraints on stellar spectra and the escape fraction of ionizing radiation at z ∼ 12. Though our approach is general, the importance of a broadband measurement renders our findings most relevant to the proposed Dark Ages Radio Explorer, which will have a clean view of the global 21-cm signal from ∼40 to 120 MHz from its vantage point above the radio-quiet, ionosphere-free lunar far-side.

79 ASTRONOMY AND ASTROPHYSICS↗

ON THE DETECTION OF GLOBAL 21-cm SIGNAL FROM REIONIZATION USING INTERFEROMETERS

Detection of the global redshifted 21-cm signal is an excellent means of deciphering the physical processes during the Dark Ages and subsequent Epoch of Reionization (EoR). However, detection of this faint monopole is challenging due to the high precision required in instrumental calibration and modeling of substantially brighter foregrounds and instrumental systematics. In particular, modeling of receiver noise with mK accuracy and its separation remains a formidable task in experiments aiming to detect the global signal using single-element spectral radiometers. Interferometers do not respond to receiver noise; therefore, here we explore the theory of the response of interferometers to global signals. In other words, we discuss the spatial coherence in the electric field arising from the monopole component of the 21-cm signal and methods for its detection using sensor arrays. We proceed by first deriving the response to uniform sky of two-element interferometers made of unit dipole and resonant loop antennas, then extend the analysis to interferometers made of one-dimensional arrays and also consider two-dimensional aperture antennas. Finally, we describe methods by which the coherence might be enhanced so that the interferometer measurements yield improved sensitivity to the monopole component. We conclude (a) that it is indeed possible to measure the global 21-cm from EoR using interferometers, (b) that a practically useful configuration is with omnidirectional antennas as interferometer elements, and (c) that the spatial coherence may be enhanced using, for example, a space beam splitter between the interferometer elements.

79 ASTRONOMY AND ASTROPHYSICS↗

Augmented signal processing in Liquid Argon Time Projection Chambers with a deep neural network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Signal processing to reduce dark noise impact in precision timing

We introduce a technique to mitigate the effects of low frequency noise on precision timing. The example of Dark Count Noise Rate (DCR) in Silicon Photomultipliers (SiPMs) is emphasized. This technique exploits the correlation between time shifts on the leading edge of a signal and the residual slope of the baseline (due to noise) which remains after baseline subtraction. In fast timing applications (such as for Time-of-flight particle ID) the signal arrival time is typically captured on the signal leading edge. The signal risetime is often fixed by the physics of the sensor and input circuit. Then accurate pulse timing can be achieved by correcting a leading edge threshold time (depending on a slope proportional to both the Amplitude and the risetime) to a “constant fraction” time. This compensation for time walk due to amplitude fluctuations breaks down once we introduce interference from low frequency noise on the leading edge. In this paper we demonstrate that an additional measurement of the slope at threshold can be used to correct for this noise jitter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Can I solve my structure by SAD phasing? Anomalous signal in SAD phasing

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. We present a simple theoretical framework for describing measurements of anomalous differences and the resulting useful anomalous correlation and anomalous signal in a SAD experiment. Here, the useful anomalous correlation is defined as the correlation of anomalous differences with ideal anomalous differences from the anomalous substructure. The useful anomalous correlation reflects the accuracy of the data and the absence of minor sites. The useful anomalous correlation also reflects the information available for estimating crystallographic phases once the substructure has been determined. In contrast, the anomalous signal (the peak height in a model-phased anomalous difference Fourier at the coordinates of atoms in the anomalous substructure) reflects the information available about each site in the substructure and is related to the ability to find the substructure. A theoretical analysis shows that the expected value of the anomalous signal is the product of the useful anomalous correlation, the square root of the ratio of the number of unique reflections in the data set to the number of sites in the substructure, and a function that decreases with increasing values of the atomic displacement factor for the atoms in the substructure. In conclusion, this means that the ability to find the substructure in a SAD experiment is increased by high data quality and by a high ratio of reflections to sites in the substructure, and is decreased by high atomic displacement factors for the substructure.

59 BASIC BIOLOGICAL SCIENCES↗

A Cyber-Physical System for Freeway Ramp Meter Signal Control Using Deep Reinforcement Learning in a Connected Environment

Freeway bottlenecks such as on-ramp merging areas account for about 40% of recurring freeway congestion. It is generally agreed that building more roads and adding more lanes to existing infrastructure does not solve the congestion problem, and so dynamic traffic control measures offer a more cost-effective alternative. Ramp meters, traffic signal devices that regulate traffic flow entering freeways, are among the most effective measures to mitigate congestion at on-ramp merging areas on freeways. The confluence of deep reinforcement learning (RL) and connectivity provides a possible solution to advance ramp meter signal control. Deep RL is a group of machine-learning methods that enables an agent learning from the environment to improve its performance. In this study, three deep RL methods-proximal policy optimization (PPO), Ape-X deep Q-network (DQN), and asynchronous advantage actor-critic agents (A3C)-are explored for ramp meter signal control to maximize vehicle speed and traffic throughput, as well as to minimize energy consumption and emissions at freeway on-ramp merging areas in a connected environment. The low computational requirement and scalability of deep RL for deployment make it a powerful optimization tool for time-sensitive applications such as ramp meter signal control. The results of this study show that deep RL methods yield superior performance to both a fixed-time controller and ALINE A, a state-of-the-art feedback controller.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Small-Signal Analysis of Current-Limiting Grid-Forming Inverters

Grid-forming (GFM) inverters are equipped with a current limiter to protect the device during grid disturbances. Because the intervention of the current limiter can compromise the transient stability of the GFM inverter, various types of current limiter designs and additional frequency-stabilization control methods have been proposed in recent literature to aid in transient GFM inverter stability; however, the small-signal stability implications of adding these additional control blocks during, in particular, off-nominal conditions are not fully understood. To address this challenge, this paper presents a generic small-signal model of a GFM inverter that incorporates various types of current limiters and frequency stability-enhancing controls. With the proposed model, we analyze the root causes of inverter instability, which reveals two critical design trade-offs. First, due to current-limiter engagement caused by a disturbance, the GFM inverter dynamics are altered, which can lead to voltage oscillations. Second, additional frequency-stabilization controls can improve the small-signal stability of the GFM inverter, but at the cost of reduced power and voltage support to the grid. Comprehensive hardware experiments validate the theoretical concept and analysis. The findings in this work underscore the importance of incorporating both transient-response and small-signal dynamics requirements into the design procedure of GFM current limiters and frequency-stabilization controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Commodity Traffic Signal Control and Routing With Connected Vehicles

We report a real-time traffic management policy that integrates traffic signal control and multi-commodity routing of connected vehicles in networks with multiple destinations is developed. The proposed policy is based on a multi-commodity formulation of the store-and-forward model and assumes all vehicles are able to exchange information with the infrastructure. Vehicles share information about their current location and final destination. Based on this information, the strategy determines both optimized signal timings at every intersection and vehicle-specific routing information at every link of the network. The control actions, i.e., signal times and routing information, are updated at every cycle and delivered by a finite horizon optimal control problem cast into a rolling horizon framework. The underlying optimization problem is convex, and thus the method is suitable for real-time operation in large networks. The method is validated via a micro-simulation study in networks with up to twenty intersections and, in all simulations, outperforms a real-time traffic-responsive signal control strategy that is based on a single-commodity store-and-forward model. The scalable computation effort for increasing network sizes and prediction horizon confirms the computational efficiency of the method.

42 ENGINEERING↗

Unified Model of Current-Limiting Grid-Forming Inverters for Large-Signal Analysis

Grid-forming (GFM) inverters can hardly withstand any overloading. As such, GFM inverters need a current limiter in their control system to avoid hardware damage during overloading or grid disturbances. When the current limiter is engaged for inverter protection, however, it dynamically changes the inverter output impedance, which can significantly affect the system behavior against large disturbances. For example, when the current limiter curtails the output power, the primary controller of the GFM inverter-which generates the voltage and angle reference-is prone to losing synchronization with the grid. This can cause large-signal instability in the network. This paper presents a unified GFM current-limiter model to gain a deeper understanding of the impact of the GFM inverter current limiting on large-signal instability and other system behaviors. The unified model captures several well-known current limiters for GFM inverters, and it reveals their large-signal equivalence characterized by the limiter angle. We use the unified model to present in-depth insights into the driving forces that cause large-signal instability in GFM inverter-driven grids. Further, this paper illustrates that the unified model can be used as a tool for assessing the system-level impacts of various GFM current-limiter designs during grid disturbances. Using numerical, analytical, electromagnetic transient models, and a hardware setup, the validity of the unified model is evaluated.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR values were found to increase with decreasing RMSE values of projection angular gaps with strong correlations (r ≈ −0.7) regardless of the reconstruction algorithm used. Conclusions: Based on the authors’ results, displacement-based binning methods, better reconstruction algorithms, and the acquisition of even projection angular views are the most important factors to consider for improving thoracic 4D-CBCT image quality. In view of the practical issues with displacement-based binning and the fact that projection angular spacing is not currently directly controllable, development of better reconstruction algorithms represents the most effective strategy for improving image quality in thoracic 4D-CBCT for IGRT applications at the current stage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Origin of a signal detected with the LSD detector after the accident at the chernobyl nuclear power plant

A rare signal was detected at 23:53 Moscow time on April 27, 1986 with the LSD low-background scintillation detector located under Mont Blanc at a distance of 1820 km from Chernobyl. To reveal the origin of this signal, we discuss the results obtained with other instruments operating within a similar program, as well as analyze the characteristics of the pulses of the signal and facts referring to the explosion of the Chernobyl reactor. A hypothesis based on detection with the LSD of gamma-quanta from {beta} decays of {sup 135}I nuclei ejected into atmosphere by the reactor explosion and carried in the underground detector camera with air of positive ventilation is considered. The explosion origin of the LSD signal indicates a new technogenic source of the background in the search for neutrino bursts from cores of collapsing stars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

New estimates of extensive-air-shower energies on the basis of signals in scintillation detectors

New formulas for estimating the energy of inclined extensive air showers (EASs) on the basis of signals in detectors by means of an original method and detailed tables of signals induced in scintillation detectors by photons, electrons, positrons, and muons and calculated with the aid of the GEANT4 code package were proposed in terms of the QGSJETII-04, EPOS LHC, and GHEISHA models. The parameters appearing in the proposed formulas were calculated by employing the CORSIKA code package. It is shown that, for showers of zenith angles in the range of 20◦–45◦, the standard constant-intensity-cut method, which is used to interpret data from the Yakutsk EAS array, overestimates the shower energy by a factor of 1.2 to 1.5. It is proposed to employ the calculated VEM (Vertical Equivalent Muon) signal units of 10.8 and 11.4 MeV for, respectively, ground-based and underground scintillation detectors and to take into account the dependence of signals on the azimuthal angle of the detector position and fluctuations in the development of showers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A real signal and its states

The paper describes the general physical theory of signals, carriers of information, which supplements Shannon’s abstract classical theory and is applicable in much broader fields, including nuclear physics. It is shown that in the absence of classical noise its place should be taken by the physical threshold of signal perception for objects of both macrocosm and microcosm. The signal perception threshold allows the presence of subthreshold (virtual) signal states. For these states, Boolean algebra of logic (A = 0/1) is transformed into the “algebraic logic” of probabilities (0 ≤ a ≤ 1). The similarity and difference of virtual states of macroand microsignals are elucidated. “Real” and “quantum” information for computers is considered briefly. The maximum information transmission rate is estimated based on physical constants.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Atomic-Force Microscopy of Resistive Nonstationary Signal Switching in ZrO{sub 2}(Y) Films

Local resistive switching by complex nonstationary signals in zirconium-dioxide-stabilized films on conducting substrates has been studied by atomic-force microscopy with a conducting probe. Film resistance was switched by triangular voltage pulses on which a high-frequency sinusoidal signal was superimposed. It is found that the ratio of currents through the junction between the probe and film surface in high-resistance and low-resistance states increases after the superposition of a sinusoidal signal (as compared to switching by simple triangular pulses). An increase in the temporal stability of the current strength in these states was also found when switching with a sinusoidal signal. This effect is associated with resonant activation of oxygen ion migration over vacancies in an external ac electric field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗