bluuebunny/crossref_metadata_2025_split huggingface dataset:
An improved underwater TDOA/AOA joint localisation algorithm
Authors: Jiang Feng , Zhang Zhenkai 
Published: February 2021

AbstractTo solve the problem of sound source localisation in underwater sensor networks, this paper constructs a pseudo‐linear equation system of time difference of arrival and angle of arrival (TDOA/AOA) and then uses the weighted least squares algorithm to estimate the target position. This paper proposes a two‐stage weighted least squares algorithm that uses target position error. First, the adapted TDOA equation and the existing AOA equation are combined into the first‐stage weighted least squares algorithm, which improves the estimation accuracy of the first stage compared with the traditional algorithm. Second, this paper uses the target position error in the second stage to derive a new TDOA/AOA equation. Finally, the target position calculated in the previous stage is adjusted by the solved target position error. The performance of the proposed algorithm is verified by comparison with the Cramer–Rao lower bound. Simulation results show that the proposed algorithm still has good localisation performance even under high‐angle noise.
Non‐unit protection method for long transmission lines in MTDC grids
Authors: Mirhosseini Seyed Sattar , Jamali Sadegh , Popov Marjan 
Published: February 2021

AbstractThis paper presents a non‐unit protection method for long transmission lines of multi‐terminal HVDC (MTDC) grids based on the magnitude and direction of modal voltage and current travelling waves. The method overcomes the difficulty resulting from high attenuation and distortion as reported in previous methods using fault‐generated transients for protection of long HVDC lines. The proposed method determines the faulted pole using multi‐resolution morphological gradient of the pole voltage. Then, the multiplication of multi‐resolution morphological gradient of the modal travelling waves is utilised as a criterion to discriminate between internal and external faults and non‐fault events. The criterion is a negative high value for internal faults, a negative low value for forward external faults and events, and a positive value for backward external faults and events. A four‐terminal HVDC grid with modular multilevel converters including long HVDC lines is modelled using the PSCAD/EMTDC software. The simulation study validates effectiveness of the method for detection and discrimination of high resistance faults on long lines, as well as stability against external DC and AC faults, and DC circuit breaker opening and reclosing transients. The proposed method uses a relatively low sampling frequency and local data, i.e. no requirement for a communication link.
Unveiling the traits of massive young stellar objects through a multi-scale survey
Authors: Frost A. J. , Oudmaijer R. D. , de Wit W. J. , Lumsden S. L. 
Published: February 2021

Context.The rarity and deeply embedded nature of young massive stars has limited the understanding of the formation of stars with masses larger than 8M⊙. Previous work has shown that complementing spectral energy distributions with interferometric and imaging data can probe the circumstellar environments of massive young stellar objects (MYSOs) well. However, complex studies of single objects often use different approaches in their analysis. Therefore the results of these studies cannot be directly compared.Aims.This work aims to obtain the physical characteristics of a sample of MYSOs at ~0.01″ scales, at ~0.1″ scales, and as a whole, which enables us to compare the characteristics of the sources.Methods.We apply the same multi-scale method and analysis to a sample of MYSOs. High-resolution interferometric data (MIDI/VLTI), near-diffraction-limited imaging data (VISIR/VLT, COMICS/Subaru), and a multi-wavelength spectral energy distribution are combined. By fitting simulated observables derived from 2.5D radiative transfer models of disk-outflow-envelope systems to our observations, the properties of the MYSOs are constrained.Results.We find that the observables of all the MYSOs can be reproduced by models with disk-outflow-envelope geometries, analogous to the Class I geometry associated with low-mass protostars. The characteristics of the envelopes and the cavities within them are very similar across our sample. On the other hand, the disks seem to differ between the objects, in particular with regards to what we interpret as evidence of complex structures and inner holes.Conclusions.The MYSOs of this sample have similar large-scale geometries, but variance is observed among their disk properties. This is comparable to the morphologies observed for low-mass young stellar objects. A strong correlation is found between the luminosity of the central MYSO and the size of the transition disk-like inner hole for the MYSOs, implying that photoevaporation or the presence of binary companions may be the cause.
Multichannel autocalibration for the Atmospheric Imaging Assembly using machine learning
Authors: Dos Santos Luiz F. G. , Bose Souvik , Salvatelli Valentina , Neuberg Brad , Cheung Mark C. M. , Janvier Miho , Jin Meng , Gal Yarin , Boerner Paul , Baydin Atılım Güneş 
Published: February 2021

Context. Solar activity plays a quintessential role in affecting the interplanetary medium and space weather around Earth. Remote-sensing instruments on board heliophysics space missions provide a pool of information about solar activity by measuring the solar magnetic field and the emission of light from the multilayered, multithermal, and dynamic solar atmosphere. Extreme-UV (EUV) wavelength observations from space help in understanding the subtleties of the outer layers of the Sun, that is, the chromosphere and the corona. Unfortunately, instruments such as the Atmospheric Imaging Assembly (AIA) on board the NASA Solar Dynamics Observatory (SDO), suffer from time-dependent degradation that reduces their sensitivity. The current best calibration techniques rely on flights of sounding rockets to maintain absolute calibration. These flights are infrequent, complex, and limited to a single vantage point, however.
Aims. We aim to develop a novel method based on machine learning (ML) that exploits spatial patterns on the solar surface across multiwavelength observations to autocalibrate the instrument degradation.
Methods. We established two convolutional neural network (CNN) architectures that take either single-channel or multichannel input and trained the models using the SDOML dataset. The dataset was further augmented by randomly degrading images at each epoch, with the training dataset spanning nonoverlapping months with the test dataset. We also developed a non-ML baseline model to assess the gain of the CNN models. With the best trained models, we reconstructed the AIA multichannel degradation curves of 2010–2020 and compared them with the degradation curves based on sounding-rocket data.
Results. Our results indicate that the CNN-based models significantly outperform the non-ML baseline model in calibrating instrument degradation. Moreover, multichannel CNN outperforms the single-channel CNN, which suggests that cross-channel relations between different EUV channels are important to recover the degradation profiles. The CNN-based models reproduce the degradation corrections derived from the sounding-rocket cross-calibration measurements within the experimental measurement uncertainty, indicating that it performs equally well as current techniques.
Conclusions. Our approach establishes the framework for a novel technique based on CNNs to calibrate EUV instruments. We envision that this technique can be adapted to other imaging or spectral instruments operating at other wavelengths.
Research on the application of target detection based on deep learning technology in power grid operation inspection
Authors: Weifu Peng , Shu Du , Shaolei Chen , Qing Zhou , Na Tang 
Published: February 2021

-External damage to power facilities caused by crane, excavator and other construction operations increases year by year, which will seriously threaten the safe operation of power system. It is an important measure to ensure the safe and reliable operation of power system to implement intelligent monitoring and early warning of power external breakdown through video and other non-contact observation means. The video data of power mainly comes from the fixed monitoring of helicopters, uavs and transformation poles and towers, which is characterized by large amount of data, complex scenes and serious environmental interference. The traditional target detection method usually selects the candidate area first, and then makes judgment based on the characteristics of human construction. The detection speed is slow and the accuracy is low, which makes it impossible to monitor the video data in real time, so as to make timely and accurate early warning and intervention fbr external damage. The target detection method based on deep learning optimizes or even eliminates the selection of candidate regions, which greatly speeds up the detection speed. By learning a lot of target samples through the deep neural network, the characteristics of high robustness are gradually fitted to make the target judgment more accurate.
There are three key problems in introducing the target detection method based on deep learning into the power video detection: Firstly, the target detection method based on deep learning has a large amount of calculation and many parameters. In order to realize in-place operation on terminals with limited computing and storage capacity, it is necessary to find a practical method to simplify the network and reduce the amount of operational data in the detection process, which is the key to realize in-place operation and terminal operation of deep neural network. Secondly, for specific application scenarios, the effect of different target detection algorithms varies greatly, and there is a strong particularity of power video. Finding an effective target detection method is the key to improve the detection speed and accuracy. Finally, with the continuous development of deep learning, the structure of deep neural network changes with each passing day, and each has its own characteristics, which network structure is used as the feature extraction layer of target detection algorithm is the focus of research.
Dermatochirurgie: Lagerungstrick bei axillären Eingriffen und Hypermobilität der Brust
Authors: Weimann K. , Löser C. R. 
Published: February 2021

ZusammenfassungFür den operativen Alltag ist es eine große Erleichterung, wenn man mit geeigneten Lagerungshilfen ein übersichtliches Operationsgebiet schaffen kann. Wir demonstrieren eine einfache Technik, die sich insbesondere bei Eingriffen nahe der Brust bewährt. Auch bei einer hypermobilen Brust („mobile Mamma“) genügt man so den Anforderungen an eine fachgerechte Lagerung.
Quo Vadis Urogynecology 2020 – Innovative Treatment Concepts for Urinary Incontinence and Pelvic Organ Prolapse
Authors: Naumann Gert 
Published: February 2021

AbstractThe current treatment for urinary incontinence and pelvic organ prolapse includes a wide range of innovative options for conservative and surgical therapies. Initial treatment for pelvic floor dysfunction consists of individualized topical estrogen therapy and professional training in passive and active pelvic floor exercises with biofeedback, vibration plates, and a number of vaginal devices. The method of choice for the surgical repair of stress urinary incontinence consists of placement of a suburethral sling. A number of different methods are available for the surgical treatment of pelvic organ prolapse using either a vaginal or an abdominal/endoscopic approach and autologous tissue or alloplastic materials for reconstruction. This makes it possible to achieve optimal reconstruction both in younger women, many of them affected by postpartum trauma, and in older women later in their lives. Treatment includes assessing the patientʼs state of health and anesthetic risk
profile. It is important to determine a realistically achievable patient preference after explaining the individualized concept and presenting the alternative surgical options.
Study on E-Cigarettes and Pregnancy (STEP) – Results of a Mixed Methods Study on Risk Perception of E-Cigarette Use During Pregnancy
Authors: Schilling Laura , Spallek Jacob , Maul Holger , Schneider Sven 
Published: February 2021

Abstract
Introduction E-cigarette use during pregnancy is a risk factor for maternal and fetal health. Early studies on animals showed that in utero exposure to e-cigarettes can have negative health outcomes for the fetus. There has been only limited research into the risk perceptions of e-cigarette use during pregnancy. This study was conducted to comprehensively characterize the constructs of risk perceptions with regard to e-cigarette use during pregnancy using an Integrated Health Belief Model (IHBM).
Methods Our STudy on E-cigarettes and Pregnancy (STEP) used a mixed methods approach, with the study divided into an initial qualitative part and a quantitative part. A netnographic approach was used for the first part, which consisted of the analysis of 1552 posts from 25 German-language online discussion threads on e-cigarette use during pregnancy. Using these qualitative results, a quantitative questionnaire was developed to explore risk perception constructs about e-cigarette use during pregnancy. This questionnaire was subsequently administered to pregnant women (n = 575) in one hospital in Hamburg, Germany. Descriptive and bivariate analysis was used to examine differences in risk perception according to participantsʼ tobacco and e-cigarette user status before and during pregnancy. While the study design, methods and sample have been extensively described in our recently published study protocol in the January 2020 issue of
Geburtshilfe und Frauenheilkunde, this paper is devoted to a presentation of the results of our mixed methods study.
Results Themes related to perceived threats identified in the qualitative study part were nicotine-related health risks and potential health risks of additional ingredients. Perceived benefits were possibility and facilitation of smoking cessation and a presumed potential to reduce harm. The subsequent quantitative part showed that nearly all participants (99.3%) perceived e-cigarettes which contained nicotine as constituting a threat to the health of the unborn child. The most commonly perceived barrier was health-related (96.6%), while the most commonly perceived benefit was a reduction in the amount of tobacco cigarettes consumed (31.8%). We found that particularly perceived benefits varied depending on the participantʼs tobacco and e-cigarette user status.
Conclusion When considering future prevention strategies, the potential health risks and disputed effectiveness of e-cigarettes as a tool for smoking cessation need to be taken into account and critically discussed.
Citizens’ attitudes towards local autonomy and inter-local cooperation: evidence from Western Europe
Authors: Strebel Michael A. , Kübler Daniel 
Published: February 2021

AbstractRecent decades have seen a strengthening of local autonomy in many European states. At the same time, local governance capacities were strengthened through intermunicipal structures and territorial consolidation to prepare local authorities for additional tasks. In this paper, we assess what citizens think about strengthening local autonomy and strengthening inter-local cooperation. We argue that citizens’ attitudes towards local autonomy and inter-local cooperation are a function of their behavioural, emotional and ideological connection to the local. Using data from a population-based survey in eight West European metropolitan areas in France, Germany, Switzerland and the UK, we show that local autonomy and inter-local cooperation supporters have divergent ideological positions concerning the allocation of political authority across state scales. Inter-local cooperation is supported by voters of new progressive left parties but opposed by right-wing nationalist partisans—who in contrast favour local autonomy. This suggests that the demarcation–integration divide which structures citizens’ attitudes towards international integration also matters for subnational and local governance reforms.
Compact sources and cosmological horizons in lower dimensional bootstrapped Newtonian gravity
Authors: Casadio Roberto , Micu Octavian , Mureika Jonas 
Published: February 2021

Abstract
We study the bootstrapped Newtonian potential generated by a localised source in one and two spatial dimensions, and show that both cases naturally lead to finite spatial extensions of the outer vacuum. We speculate that this implies the necessary existence of a cosmological (particle) horizon associated with compact sources. In view of the possible dimensional reduction occurring in ultra-high energy processes—like scatterings at Planckian energies, the gravitational collapse of compact objects or the end-point of black hole evaporation—one can consider such lower-dimensional ‘bubbles’ immersed in our Universe as describing (typically Planckian size) baby Universes relevant to those dynamics.
Prediction of combustion states from flame image in a domestic coal burner
Authors: Onat Cem , Daşkin Mahmut , Toraman Suat , Golgiyaz Sedat , Talu Muhammed Fatih 
Published: February 2021

Abstract
Coal is still a strategic fuel for many developing countries. The environmental impact of emissions resulting from the widespread use of coal worldwide is a matter of serious debate. In this perspective, clean coal burning technologies are in demand. In this study, a measurement system that estimates emission from flame images in a domestic coal burner is proposed. The system consists of a charge-coupled device camera, image processing software (real time image acquisition, noise reduction and extracting features) and artificial intelligence elements (classification of features by neural networks). In feature extraction stage, only five flame region features (Gx, Gy
, trace, L
2 and L
∞ norm) is extracted. Gcx
and Gcy
are the instantaneous change of the horizontal and vertical components of center mass of the flame image. These features are new concepts for emission estimation from the flame image. The proposed system makes a difference with its simpler structure and higher accuracy compared to its counterparts previously presented in the literature.
Thermochromic VO2–SiO2 composite coating from ammonium citrato-oxovanadate(IV)
Authors: Zhang Jing , Wang Tengfei , Xu Weiwei , Yang Xiaohui , Zuo Xiaoling , Cheng Weiwei , Zhou Chaobiao 
Published: February 2021

Abstract
Vanadium dioxide (VO2) coating plays an important role in energy saving and environmental protection due to its unique reversible phase transition. To solve the daylighting issue of VO2 coating, a VO2 (M)–silicon dioxide (SiO2) composite coating is fabricated from ammonium citrato-oxovanadate(IV) by a SiO2-assisted coating method. The VO2 (M)–SiO2 composite coating possesses excellent thermochromic properties that have produced varying results, i.e. 49.2% of visible transmittance, 52.3% of transmittance reduction at 2000 nm wavelength, 12% of solar energy modulation (ΔT

sol
) and a phase transition temperature of 56.0 °C. Our findings may pave the way to extending the large-scale application of smart windows based on thermochromic VO2.
Real-time registration of 3D echo to x-ray fluoroscopy based on cascading classifiers and image registration
Authors: Ma YingLiang , James Housden R , Fazili Ansab , Arujuna Aruna V , Rhode Kawal S 
Published: February 2021

Abstract
Three-dimensional (3D) transesophageal echocardiography (TEE) is one of the most significant advances in cardiac imaging. Although TEE provides real-time 3D visualization of heart tissues and blood vessels and has no ionizing radiation, x-ray fluoroscopy still dominates in guidance of cardiac interventions due to TEE having a limited field of view and poor visualization of surgical instruments. Therefore, fusing 3D echo with live x-ray images can provide a better guidance solution. This paper proposes a novel framework for image fusion by detecting the pose of the TEE probe in x-ray images in real-time. The framework does not require any manual initialization. Instead it uses a cascade classifier to compute the position and in-plane rotation angle of the TEE probe. The remaining degrees of freedom are determined by fast marching against a template library. The proposed framework is validated on phantoms and patient data. The target registration error for the phantom was 2.1 mm. In addition, 10 patient datasets, seven of which were acquired from cardiac electrophysiology procedures and three from trans-catheter aortic valve implantation procedures, were used to test the clinical feasibility as well as accuracy. A mean registration error of 2.6 mm was achieved, which is well within typical clinical requirements.
Single-hole physics in GaAs/AlGaAs double quantum dot system with strong spin–orbit interaction
Authors: Studenikin Sergei , Korkusinski Marek , Bogan Alex , Gaudreau Louis , Austing D Guy , Sachrajda Andrew S , Tracy Lisa , Reno John , Hargett Terry 
Published: February 2021

AbstractThere is rapidly expanding interest in exploiting the spin of valence-band holes rather than conduction-band electrons for spin qubit semiconductor circuits composed of coupled quantum dots. The hole platform offers stronger spin–orbit interaction (SOI), large difference between in-dot-plane and out-of-dot-planeg-factors, i.e.g-factor anisotropy, and a significantly reduced hyperfine coupling to nuclei in the host material. These attributes collectively can deliver fast all-electric coherent spin manipulation, efficient spin-flip inter-dot tunneling channels, a voltage tunable effectiveg-factor, ag-factor adjustable to nearly zero in an appropriately oriented external magnetic field, and long spin relaxation and coherence times. Here, we review our recent work on the physics of heavy holes confined in a planar GaAs/AlGaAs double quantum dot system with strong SOI. For asingle-hole, we have performed resonant tunneling magneto-spectroscopy to extract spin-flip and spin-conserving tunneling strengths, implemented spin-flip Landau–Zener–Stückelberg–Majorana (LZSM) interferometry, determined the spin relaxation timeT1as a function of magnetic field using a fast single-shot latched charge technique, electrically tuned the effectiveg-factor revealed by electric dipole spin resonance, and found signatures of the hyperfine interaction and dynamic nuclear polarization with holes. Fortwo-holes, we have measured the energy spectrum in the presence of strong SOI (and so not limited by Pauli spin blockade), quantified the heavy-hole (HH)g-factor anisotropy on tilting the magnetic field, described a scheme to employ HHs whoseg-factor is tunable to nearly zero for an in-plane magnetic field for a coherent photon-to-spin interface, and observed a well-defined LZSM interference pattern at small magnetic fields on pulsing through the singlet-triplet anti-crossing.
Linear voltage regulation in DC-to-DC converters
Authors: Veselovskiy A P , Kosareva L I , Zverev S G 
Published: February 2021

Abstract
The article deals with the most dynamically developing branch of power electronics related to solving tasks of voltage regulation in DC-to-DC converters. Linear regulation of the output voltage is carried out using pulse-width modulation. A linear regulatory characteristic is obtained over the entire control range from zero to maximum values. The formula of the output voltage regulation characteristic is obtained through a mathematical model of a pulse-width control method with a variable pulse width.