bluuebunny/crossref_metadata_2025_split huggingface dataset:
An adaptive non‐searching method for long‐time coherent integration of manoeuvring target with multiple motion models
Authors: Zhao Jia , Chen Yan , Cheng Jiayu 
Published: February 2022

AbstractLong‐time coherent integration (LTCI) is one of the effective methods to enhance the radar detection capability of manoeuvring targets. In most existing studies, the target is assumed to move at a consistent model during the total integration time. In modern times, this point is not always true. The modern targets often possess strong manoeuvring penetration capability, which enables the presence of multiple motion models (i.e. the target's motion model is changing during the total integration time) with a high possibility, especially when the coherent integration time is long. This factor would reduce the performance of the existing LTCI methods. In this study, an adaptive non‐searching method, based on the adjacent cross correlation function (ACCF)/modified ACCF (MACCF), Keystone transform (KT)/second‐order KT, Hough transform and fractional Fourier transform, is proposed for LTCI of a manoeuvring target with multiple motion models. First, the motion model change points are identified. Subsequently, the adaptive case prejudgement and parameters estimation for different motion stages are completed. Finally, the LTCI of the manoeuvring target with multiple motion models is realised after motion compensation. Simulation results demonstrate the effectiveness of the proposed method.
Early Biochemical Markers in Predicting the Clinical Outcome of COVID-19 Patients Admitted in Tertiary Care Hospital
Authors: Prasad Shrishtidhar , Patel Suprava , Behera Ajoy Kumar , Gitismita Naik , Shah Seema , Nanda Rachita , Mohapatra Eli 
Published: February 2022

Abstract
Introduction An array of routinely accessible serum biomarkers was assessed to explore their overall impact on severity and mortality in coronavirus disease 2019.
Materials and Methods A retrospective analysis of 1,233 adults was conducted. The study groups comprised 127 nonsurvivors and 1,106 survivors. Data for demographic details, clinical presentations, and laboratory reports were recorded from the medical record section. The predictors were analyzed for their influence on mortality.
Results The mean (+ standard deviation) age of the patients in the nonsurvivor group was 58.8 (13.8) years. The mean age (56.4 years) was highest in severe grade patients. The odds ratio for death was 2.72 times for patients above the age of 40 years. About 46% of nonsurvivors died within 5 days of admission. Males were found to be more prone to death than females by a factor of 1.36. Serum urea depicted highest sensitivity (85%) for nonsurvival at 52.5 mg/dL. Serum albumin (3.23 g/dL), albumin-to-globulin ratio (0.97), and C-reactive protein-to albumin ratio (CAR) (2.08) showed a sensitivity of more than 70% for mortality outcomes. The high hazard ratio (HR) for deceased patients with hyperkalemia was 2.419 (95% confidence interval [CI] = 1.96–2.99; p < 0.001). The risk for nonsurvival was increased with elevated serum creatinine by 15.6% and uric acid by 21.7% (p < 0.001). The HR for hypoalbuminemia was 0.254 (95% CI: 0.196–0.33; p < 0.001) and CAR was 1.319 (95% CI: 1.246–1.397; p < 0.001). Saturation of oxygen (p < 0.001), lactate dehydrogenase (p = 0.006), ferritin (p = 0.004), hyperuricemia (p = 0.027), hyperkalemia (p < 0.001), hypoalbuminemia (p = 0.002), and high CAR values (0.031) served as potential predictors for mortality.
Conclusion Adjusting for all the predictor variables, serum uric acid, potassium, albumin, and CAR values at the time of admission were affirmed as the potential biomarkers for mortality.
High-resolution vibronic spectroscopy of a single molecule embedded in a crystal
Authors: Zirkelbach Johannes , Mirzaei Masoud , Deperasińska Irena , Kozankiewicz Boleslaw , Gurlek Burak , Shkarin Alexey , Utikal Tobias , Götzinger Stephan , Sandoghdar Vahid 
Published: February 2022

Vibrational levels of the electronic ground states in dye molecules have not been previously explored at a high resolution in solid matrices. We present new spectroscopic measurements on single polycyclic aromatic molecules of dibenzoterrylene embedded in an organic crystal made of para-dichlorobenzene. To do this, we use narrow-band continuous-wave lasers and combine spectroscopy methods based on fluorescence excitation and stimulated emission depletion to assess individual vibrational linewidths in the electronic ground state at a resolution of ∼30 MHz dictated by the linewidth of the electronic excited state. In this fashion, we identify several exceptionally narrow vibronic levels with linewidths down to values around 2 GHz. Additionally, we sample the distribution of vibronic wavenumbers, relaxation rates, and Franck–Condon factors, in both the electronic ground and excited states for a handful of individual molecules. We discuss various noteworthy experimental findings and compare them with the outcome of density functional theory calculations. The highly detailed vibronic spectra obtained in our work pave the way for studying the nanoscopic local environment of single molecules. The approach also provides an improved understanding of the vibrational relaxation mechanisms in the electronic ground state, which may help create long-lived vibrational states for applications in quantum technology.
Genetic analysis of cancer drivers reveals cohesin and CTCF as suppressors of PD-L1
Authors: Oreskovic Ena , Wheeler Emily C. , Mengwasser Kristen E. , Fujimura Eric , Martin Timothy D. , Tothova Zuzana , Elledge Stephen J. 
Published: February 2022

Significance
The PD-1/PD-L1 immunoinhibitory axis plays a key role in immune evasion of cancer cells, and therapies targeting PD-1/PD-L1 show high efficacy in certain cancer types. Understanding how cancer drivers regulate immune surveillance will enable development of novel therapeutic strategies targeting cancer-mediated immune evasion, and identification of new biomarkers of response. Here, we utilized genetic screening with a curated library of 500 tumor suppressor genes to identify cohesin subunits and CTCF among the most significant suppressors of PD-L1. We report upregulation of additional key immune-regulatory molecules PD-L2 and MHC-I, and describe transcriptional consequences of loss of the STAG2 cohesin subunit, including an induction of IFN and NF-κB responses, which have implications for biology and treatment of cohesin-deficient tumors.
Low energy inelastic electron scattering from carbon monoxide: II. Excitation of the b3Σ+, j3Σ+, B1Σ+, C1Σ+ and E1Π Rydberg electronic states
Authors: Zawadzki Mateusz , Khakoo Murtadha A , Sakaamini Ahmad , Voorneman Logan , Ratkovich Luka , Mašín Zdeněk , Dora Amar , Laher Russ , Tennyson Jonathan 
Published: February 2022

Abstract
In this second part of a two part paper (first part: Zawadzki et al (2020 J. Phys. B: At. Mol. Opt. Phys.
53 165201)) we present differential scattering cross sections for excitation of several Rydberg electronic states of carbon monoxide by electron impact. The first part concerned the low-lying valence states of CO. In the present study cross sections are obtained experimentally using low-energy electron energy-loss spectroscopy and theoretically using the R-matrix method. Incident electron energies range from near-threshold of 12.5 eV to 20 eV while the scattering angles range from 20° to 120°. The R-matrix calculations use three distinct close-coupling models and their results are compared to available experimental and theoretical cross sections. The overall comparison leads to significantly improved description of the excitation cross sections for this target.
Energetic Au ion beam implantation of ZnO nanopillars for optical response modulation
Authors: Macková Anna , Malinský Petr , Jagerová Adéla , Mikšová Romana , Lalik Ondrej , Nekvindová Pavla , Mistrík Jan , Marvan Petr , Sofer Zdenek , Holý Václav , Schutter Jan David , Kentsch Ulrich , Azarov Alexander , Galeckas Augustinas 
Published: February 2022

Abstract
Nanopillars of ZnO were implanted with Au-400 keV ions at various ion fluences from 1 × 1015 cm−2 to 1 × 1016 cm−2 and subsequently annealed at 750 °C for 15 min in order to reduce the implantation damage and to support Au nanoparticle (NP) aggregation. It was found that implantation-induced effects and thermal effects influence the Au NP coalescence as well as the quality of the ZnO nanopillars. Rutherford Back-Scattering spectrometry (RBS) showed the broader Au-depth profiles than it was theoretically predicted, but the Au-concentration maximum agrees well with prediction taking into account the effective ZnO layer density. The implantation at the higher fluences induced the morphology modification of the nanopillar layer evidenced by RBS and scanning electron microscopy (SEM). An indirect evidence of this effect was given by optical ellipsometry due to gradual refractive index changes in the ZnO nanopillars with the increased Au-ion fluence. Optical characterization of the Au-implanted and annealed nanopillars performed by means of photoluminescence (PL) and diffuse-reflectance spectroscopy (DRS) evidenced the surface plasmon resonance (SPR) activity of the embedded Au NPs. The SPR-enhanced scattering and PL emission observed in the spectral range 500–650 nm are ascribed to Au NPs or more complex Au-clusters. In addition, the ellipsometry measurements of extinction coefficient are found to corroborate well results from DRS, both indicating increase of SPR effect with the increase of Au-ion fluence and after the post-annealing.
A novel INS/ADS integrated navigation method based on INS error model-aided unbiased converted measurement
Authors: Li Zhenwei , Cheng Yongmei , Zhang Xiaodong , Zhang Yachong , Yang Shaohua 
Published: February 2022

Abstract
In the inertial navigation system (INS)/ air data system (ADS) integrated navigation system, the measurements of INS and ADS need to be converted to a unified coordinate for fusion. However, the sensor noises cause serious conversion bias in the direct measurement conversion method. In this paper, a novel INS/ADS integrated navigation method based on INS error model-aided unbiased converted measurement (IEM-UCM) is proposed. First, the IEM-UCM model of ADS data from spherical frame to navigation frame is developed, which exploits the INS error model to calculate the compensation factors. Subsequently, the noise covariance of the converted measurement is derived. Finally, a standard Kalman filter (KF) is implemented for INS/ADS integrated navigation. The simulation results validate the effectiveness of the proposed method in terms of the unbiasedness and consistency of the converted measurement. The root mean square error values indicate that the proposed method outperforms the existing methods in navigation accuracy.
A review on III–V compound semiconductor short wave infrared avalanche photodiodes
Authors: Liang Yan , Perumal Veeramalai Chandrasekar , Lin Guochen , Su Xiangbin , Zhang Xiaoming , Feng Shuai , Xu Yingqiang , Li Chuanbo 
Published: February 2022

Abstract
The on-chip avalanche photodiodes (APDs) are crucial component of a fully integrated photonics system. Specifically, III–V compound APD has become one of the main applications of optical fiber communication reception due to adaptable bandgap and low noise characteristics. The advancement of structural design and material choice has emerged as a means to improve the performance of APDs. Therefore, it is inevitable to review the evolution and recent developments on III–V compound APDs to understand the current progress in this field. To begin with, the basic working principle of APDs are presented. Next, the structure development of APDs is briefly reviewed, and the subsequent progression of III–V compound APDs (InGaAs APDs, Al
x
In1−x
As
y
Sb1−y
APDs) is introduced. Finally, we also discuss the key issues and prospects of Al
x
In1−x
As
y
Sb1−y
digital alloy avalanche APDs that need to be addressed for the future development of ≥2 μm optical communication field.
Size dependent effects of two phase viscoelastic medium on damping vibrations of smart nanobeams: an efficient implementation of GDQM
Authors: Naderi Ali , Behdad Shahin , Fakher Mahmood 
Published: February 2022

Abstract
This paper studies the dynamics of nonlocal piezo-magnetic nanobeams (PMNBs) embedded in the local/nonlocal viscoelastic medium through the consistent and paradox-free model of the nonlocal theory. Besides, to perform the dynamic analysis, an exact solution and an efficient approach of generalized differential quadrature method (GDQM) are introduced. Since the size-dependency of the uniform loads is wrongly neglected by the nonlocal elasticity in differential form, the size-dependency of piezo-magnetic load is applied through the two-phase theory. Also, size dependency of the viscoelastic medium is accurately applied and examined through the solutions presented employing the differential two-phase theory and satisfying the constitutive boundary conditions. In this regard, the two-phase resultant equations of motions together with boundary conditions including the constitutive ones related to two-phase PMNB and the two-phase medium are attained. To confirm the credibility and efficiency of the extracted equations as well as presented solution procedures, several analogical studies are accomplished, and it is shown that the results obtained from the differential relations are reliable and consistence with those extracted from the integral nonlocal relations. It is shown that the present approach of the GDQM simplifies the solution procedures of the nonlocal problems and improves the precisions in the cases close to the pure nonlocal state. The presented results emphasize that the size-dependency of viscoelastic medium, external electric, and magnetic loads play significant roles on the vibration characteristics, and therefore it must be considered based on two-phase theory. The available results can be helpful to achieve an excellent design of smart nanobeams embedded in viscoelastic medium.
Phase diagram of quantum generalized Potts-Hopfield neural networks
Authors: Fiorelli Eliana , Lesanovsky Igor , Müller Markus 
Published: February 2022

Abstract
We introduce and analyze an open quantum generalization of the q-state Potts-Hopfield neural network (NN), which is an associative memory model based on multi-level classical spins. The dynamics of this many-body system is formulated in terms of a Markovian master equation of Lindblad type, which allows to incorporate both probabilistic classical and coherent quantum processes on an equal footing. By employing a mean field description we investigate how classical fluctuations due to temperature and quantum fluctuations effectuated by coherent spin rotations affect the ability of the network to retrieve stored memory patterns. We construct the corresponding phase diagram, which in the low temperature regime displays pattern retrieval in analogy to the classical Potts-Hopfield NN. When increasing quantum fluctuations, however, a limit cycle phase emerges, which has no classical counterpart. This shows that quantum effects can qualitatively alter the structure of the stationary state manifold with respect to the classical model, and potentially allow one to encode and retrieve novel types of patterns.
Physical aspects of cnoidal waves in non-thermal electron-beam plasma systems
Authors: Mehdipoor Mostafa , Asri Mehdi 
Published: February 2022

Abstract
The effects of electron beam and non-thermal electrons on ion-acoustic cnoidal waves (IACWs) structure in a two-fluid plasma system are investigated. A Kappa-Cairns type distribution is assumed for the background electrons. The Korteweg–de Vries (K-dV) equation is obtained by employing reductive perturbation technique and the analytical solution of K-dV equation is derived by employing the Sagdeev pseudo-potential approach. It is seen that in the presence of the electron beam, four modes can exist in this plasma model. In this study, it is observed that only two modes are real in all cases. Furthermore, it is found that the characteristics of the ion-acoustic cnoidal wave depend strongly on the electron beam parameters (via

ν

and

U

0

) as well as the non-thermal indexes for the plasma electrons (via

κ

and

α

).
Traceable spectral interferometry for length measurement
Authors: Lancaster A J , O’Connor D 
Published: February 2022

Abstract
Spectral interferometry is becoming a popular method of performing dimensional measurements, e.g. of surfaces, but such devices require pre-calibration of their spectrometers to achieve traceability. The use of a spectral lamp and imaging spectrometer to perform inherently traceable distance measurements using spectral interferometry, without the need for external calibration, is proposed and its experimental feasibility demonstrated. Initial experiments show measurements over a working range of 200 µm. The estimated standard uncertainty of the distance measurements is 0.6 nm, corresponding to an expanded uncertainty of 1.2 nm at k = 2.
Exploring dynamic functional connectivity alterations in the preclinical stage of Alzheimer’s disease: an exploratory study from SILCODE
Authors: Yang Fan , Jiang Xueyan , Yue Feng , Wang Luyao , Boecker Henning , Han Ying , Jiang Jiehui 
Published: February 2022

Abstract

Objective. Exploring functional connectivity (FC) alterations is important for the understanding of underlying neuronal network alterations in subjective cognitive decline (SCD). The objective of this study was to prove that dynamic FC can better reflect the changes of brain function in individuals with SCD compared to static FC, and further to explore the association between FC alterations and amyloid pathology in the preclinical stage of Alzheimer’s disease. Approach. A total of 101 normal control (NC) subjects, 97 SCDs, and 55 cognitive impairment (CI) subjects constituted the whole-cohort. Of these, 29 NCs and 52 SCDs with amyloid images were selected as the sub-cohort. First, independent components (ICs) were identified by IC analysis and static and dynamic FC were calculated by pairwise correlation coefficient between ICs. Second, FC alterations were identified through group comparison, and seed-based dynamic FC analysis was done. Analysis of variance was used to compare the seed-based dynamic FC maps and measure the group or amyloid effects. Finally, correlation analysis was conducted between the altered dynamic FC and amyloid burden. Main results. The results showed that 42 ICs were revealed. Significantly altered dynamic FC included those between the salience/ventral attention network, the default mode network, and the visual network. Specifically, the thalamus/caudate (IC 25) drove the hub role in the group differences. In the seed-based dynamic FC analysis, the dynamic FC between the thalamus/caudate and the middle temporal/frontal gyrus was observed to be higher in the SCD and CI groups. Moreover, a higher dynamic FC between the thalamus/caudate and visual cortex was observed in the amyloid positive group. Finally, the altered dynamic FC was associated with the amyloid global standardized uptake value ratio (SUVr). Significance. Our findings suggest SCD-related alterations could be more reflected by dynamic FC than static FC, and the alterations are associated with global SUVr.
SQNN: a spike-wave index quantification neural network with a pre-labeling algorithm for epileptiform activity identification and quantification in children
Authors: Yu Yifei , Chen Yehong , Li Yuanxiang , Gao Zaifen , Gai Zhongtao , Zhou Yunqing 
Published: February 2022

Abstract

Objective. Electrical status epilepticus during slow sleep (ESES) is a phenomenon identified by strong activation of epileptiform activity in the electroencephalogram (EEG) during sleep. For children disturbed by ESES, spike-wave index (SWI) is defined to quantify the epileptiform activity in the EEG during sleep. Accurate SWI quantification is important for clinical diagnosis and prognosis. To quantify SWI automatically, a deep learning method is proposed in this paper. Approach. Firstly, a pre-labeling algorithm (PreLA) composed of the adaptive wavelet enhanced decomposition and a slow-wave discrimination rule is designed to efficiently label the EEG signal. It enables the collection of large-scale EEG dataset with fine-grained labels. Then, an SWI quantification neural network (SQNN) is constructed to accurately classify each sample point as normal or abnormal and to identify the abnormal events. SWI can be calculated automatically based on the total duration of abnormalities and the length of the signal. Main results. Experiments on two datasets demonstrate that the PreLA is effective and robust for labeling the EEG data and the SQNN accurately and reliably quantifies SWI without using any thresholds. The average estimation error of SWI is 3.12%, indicating that our method is more accurate and robust than experts and previous related works. The processing speed of SQNN is 100 times faster than that of experts. Significance. Deep learning provides a novel approach to automatic SWI quantification and PreLA provides an easy way to label the EEG data with ESES syndromes. The results of the experiments indicate that the proposed method has a high potential for clinical diagnosis and prognosis of epilepsy in children.
NSTX-U theory, modeling and analysis results
Authors: Guttenfelder W. , Battaglia D.J. , Belova E. , Bertelli N. , Boyer M.D. , Chang C.S. , Diallo A. , Duarte V.N. , Ebrahimi F. , Emdee E.D. , Ferraro N. , Fredrickson E. , Gorelenkov N.N. , Heidbrink W. , Ilhan Z. , Kaye S.M. , Kim E.-H. , Kleiner A. , Laggner F. , Lampert M. , Lestz J.B. , Liu C. , Liu D. , Looby T. , Mandell N. , Maingi R. , Myra J.R. , Munaretto S. , Podestà M. , Rafiq T. , Raman R. , Reinke M. , Ren Y. , Ruiz J. Ruiz , Scotti F. , Shiraiwa S. , Soukhanovskii V. , Vail P. , Wang Z.R. , Wehner W. , White A.E. , White R.B. , Woods B.J.Q. , Yang J. , Zweben S.J. , Banerjee S. , Barchfeld R. , Bell R.E. , Berkery J.W. , Bhattacharjee A. , Bierwage A. , Canal G.P. , Chen X. , Clauser C. , Crocker N. , Domier C. , Evans T. , Francisquez M. , Gan K. , Gerhardt S. , Goldston R.J. , Gray T. , Hakim A. , Hammett G. , Jardin S. , Kaita R. , Koel B. , Kolemen E. , Ku S.-H. , Kubota S. , LeBlanc B.P. , Levinton F. , Lore J.D. , Luhmann N. , Lunsford R. , Maqueda R. , Menard J.E. , Nichols J.H. , Ono M. , Park J.-K. , Poli F. , Rhodes T. , Riquezes J. , Russell D. , Sabbagh S.A. , Schuster E. , Smith D.R. , Stotler D. , Stratton B. , Tritz K. , Wang W. , Wirth B. 
Published: February 2022

Abstract
The mission of the low aspect ratio spherical tokamak NSTX-U is to advance the physics basis and technical solutions required for optimizing the configuration of next-step steady-state tokamak fusion devices. NSTX-U will ultimately operate at up to 2 MA of plasma current and 1 T toroidal field on axis for 5 s, and has available up to 15 MW of neutral beam injection power at different tangency radii and 6 MW of high harmonic fast wave heating. With these capabilities NSTX-U will develop the physics understanding and control tools to ramp-up and sustain high performance fully non-inductive plasmas with large bootstrap fraction and enhanced confinement enabled via the low aspect ratio, high beta configuration. With its unique capabilities, NSTX-U research also supports ITER and other critical fusion development needs. Super-Alfvénic ions in beam-heated NSTX-U plasmas access energetic particle (EP) parameter space that is relevant for both α-heated conventional and low aspect ratio burning plasmas. NSTX-U can also generate very large target heat fluxes to test conventional and innovative plasma exhaust and plasma facing component solutions. This paper summarizes recent analysis, theory and modelling progress to advance the tokamak physics basis in the areas of macrostability and 3D fields, EP stability and fast ion transport, thermal transport and pedestal structure, boundary and plasma material interaction, RF heating, scenario optimization and real-time control.