bluuebunny/crossref_metadata_2025_split huggingface dataset:
Frequency‐constrained energy and reserve scheduling in wind incorporated low‐inertia power systems considering vanadium flow redox batteries
Authors: Mohiti Maryam , Mazidi Mohammadreza , Kermani Mostafa , Zarchi Davoud Abootorabi 
Published: August 2022

AbstractThis paper proposes a novel energy and reserve scheduling model for power systems with high penetration of wind turbines (WTs). The objective of the proposed model is to minimize the total operation cost of the system while static and dynamic security is guaranteed by preserving the frequency nadir, RoCoF, and quasi‐steady‐state frequency in the predefined range. Likewise, a supervisory, control, and data acquisition (SCADA) system is developed which allows Vanadium Redox Flow Batteries (VRFBs) to continuously communicate and participate in the primary frequency response. To cope with the uncertainties, adaptive information gap decision theory is used that ensures a target operating cost for the risk‐averse operator of the power system. The proposed scheduling model is applied on a modified IEEE 39 bus test system to verify the impacts of the fast reserve provided by the VRFBs in the dynamic frequency security enhancement of the power system with high penetration of WTs.
Optimal design of supply chain inventory information forecasting and control system in cloud environment for biomedical instruments
Authors: Tie Pengfei , Zhao Junqing , Sayyad Shabnam , Saravanan K. , Yadav Ranjeet , Sammy F. 
Published: August 2022

AbstractWith the rapid development of Internet technology, the network information data is exploding, and society has entered the era of cloud data. Cloud data provides a lot of data support for people's life and work, but because of its large number, multifarious types and huge value, there are some problems such as private data leakage and abuse of sensitive information. Stocking of biomedical material at one place only, can cause delay in sending important lifesaving material to needy patients. On the one hand, it is an important content of engineering scheduling theory and method; On the other hand, in medical field, a lot of materials are usually consumed to protect the life of patients. Biomedical informatics and computer vision techniques have been combined in a variety of inter‐multidisciplinary disciplines during the past few decades. We are all aware that inadequate or insufficient cloud access management and controls can expose a corporation to a range of issues. The work that follows offers intelligent supply chain, an upgraded service management control telephone network architecture. If we can acquire according to the patient demands and retain the ideal inventory such that the patient requirement and interest can be safe, the overall cost will be lowered greatly. The experimental results show that R1 orders 31 times, and the total cost is 1,259,520 CNY. R2 ordered 24 times, with a total cost of 982,034 CNY; R3 orders 22 times, and the total cost is 990,146 CNY. Finally, the optimal solution of the total cost after schedule optimization is 3,231,700 CNY. It is proved that the optimal cost finally obtained by forecasting supply chain inventory information based on cloud data environment is also more practical for engineering practice.
Kinematic data rebuild the nuclear star cluster as the most metal-rich region of the Galaxy
Authors: Nogueras-Lara F. 
Published: August 2022

Context.The Galactic centre (GC) is located at only 8 kpc from Earth and constitutes a unique template with which to understand Galactic nuclei. Nevertheless, the high crowding and extinction towards the GC hamper the study of its main stellar components, the nuclear stellar disc (NSD) and the nuclear star cluster (NSC).Aims.Recent work has suggested that the NSD and the NSC can be distinguished along the line of sight towards the NSC via the different extinction of their stars. This motivated us to analyse the proper motion, radial velocity, and the metallicity distributions of the different extinction groups.Methods.We use photometric, kinematic, and metallicity data to distinguish between probable NSD and NSC stars in a region centred on the NSC.Results.We detected two different extinction groups of stars and obtained that they have significantly different proper motion distributions, in agreement with the expected kinematics for the NSD and the NSC. We also derived radial velocity maps that appear to be different for the two components, and found different metallicities for each of them, with the largest one measured for the most extinguished group of stars. We obtained that the metallicity distribution of each extinction group is best fitted by a bimodal distribution, indicating the presence of two metallicity components for each of them (a broad one slightly below solar metallicity, and a more metal-rich, narrower one that is largest for the high-extinction group of stars).Conclusions.We conclude that both extinction groups are distinct GC components with different kinematics and metallicity, and correspond to the NSD and the NSC. Therefore, it is possible to distinguish them via their different extinction. The high mean metallicity, [M/H] ∼ 0.3 dex, obtained for the metal-rich stars of the NSC supports the proposition that this component is arguably the most metal-rich region of the Galaxy.
X-ray view of a merging supermassive black hole binary candidate SDSS J1430+2303: Results from the first ∼200 days of observations
Authors: Dou Liming , Jiang Ning , Wang Tinggui , Shu Xinwen , Yang Huan , Pan Zhen , Zhu Jiazheng , An Tao , Zheng Zhen-Ya , Ai Yanli 
Published: August 2022

Context. Recently we discovered an unprecedented supermassive black hole binary (SMBHB) candidate in the nearby Seyfert galaxy SDSS J1430+2303, which is predicted to merge within three years. X-ray spectroscopy may bring unique kinematic evidence for the last inspiraling stage, when the binary is too close to allow each of them to hold an individual broad line region.
Aims. We try to confirm the unique SMBHB merger event and understand the associated high-energy processes from a comprehensive X-ray view.
Methods. We observed SDSS J1430+2303 with XMM-Newton, NuSTAR, Chandra, and Swift spanning the first ∼200 days since its discovery.
Results. X-ray variability, up to a factor of 7, has been detected on a timescale of a few days. The broadband spectrum from 0.2–70 keV can be well fitted with a model consisting of a power law and a relativistic reflection covered by a warm absorber. The properties of the warm absorber changed dramatically, for example, with a decrease in the line-of-sight velocity from ∼0.2c to ∼0.02c, between the two XMM-Newton observations separated by only 19 days, which can be naturally understood in the context of the SMBHB; although, the clumpy wind scenario cannot be completely excluded. Broad Fe Kα emission has been robustly detected, though its velocity shift or profile change is not yet measurable. Further longer X-ray observations are highly encouraged to detect the expected orbital motion of the binary.
Lensing from small-scale travelling ionospheric disturbances observed using LOFAR
Authors: Boyde Ben , Wood Alan , Dorrian Gareth , Fallows Richard A. , Themens David , Mielich Jens , Elvidge Sean , Mevius Maaijke , Zucca Pietro , Dabrowski Bartosz , Krankowski Andrzej , Vocks Christian , Bisi Mario 
Published: August 2022

Observations made using the LOw-Frequency ARray (LOFAR) between 10:15 and 11:48 UT on the 15th of September 2018 over a bandwidth of approximately 25–65 MHz contain discrete pseudo-periodic features of ionospheric origin. These features occur within a period of approximately 10 min and collectively last roughly an hour. They are strongly frequency dependent, broadening significantly in time towards the lower frequencies, and show an overlaid pattern of diffraction fringes. By modelling the ionosphere as a thin phase screen containing a wave-like disturbance, we are able to replicate the observations, suggesting that they are associated with small-scale travelling ionospheric disturbances (TIDs). This modelling indicates that the features observed here require a compact radio source at a low elevation and that the TID or TIDs in question have a wavelength <~30 km. Several features suggest the presence of deviations from an idealised sinusoidal wave form. These results demonstrate LOFAR’s capability to identify and characterise small-scale ionospheric structures.
Erfassung von Sprache und Kommunikation bei Personen mit MCI
Authors: Vössing Lisa , Hartmann Mareike , Richter Kerstin , Hielscher-Fastabend Martina 
Published: August 2022

Zusammenfassung
Hintergrund Mild Cognitive Impairment (MCI) ist häufig mit Veränderungen sprachlicher und kommunikativer Kompetenzen verbunden. Zur differenzierten Erfassung dieser sprachlichen Veränderungen bei MCI stehen allgemein keine spezifischen Diagnostikinstrumente zur Verfügung. Die vorliegende Studie untersucht, inwiefern die Verfahren BIAS R und ANELT, entwickelt zur Diagnostik neurologisch bedingter Sprachstörungen, Veränderungen im Rahmen eines MCI detektieren können.
Methode Auf Grundlage des kognitiven Status, klassifiziert durch DemTect und MoCA, wurden drei Gruppen verglichen: Personen mit altersgemäßen kognitiven Kompetenzen (Norm), Personen mit leichten kognitiven Beeinträchtigungen (MCI) und Personen mit moderaten kognitiven Defiziten (MCI +).
Ergebnisse BIAS R und ANELT ermitteln Veränderungen sprachlicher und kommunikativer Kompetenzen bei Personen mit moderaten kognitiven Beeinträchtigungen (MCI +), während Personen mit leichten kognitiven Beeinträchtigungen keine signifikanten Unterschiede zur Norm zeigen.
Small for Gestational Age Affects Outcomes on Singletons and Inborn Births in Extremely Preterm Infants: A Japanese Cohort Study
Authors: Suenaga Hideyo , Nakanishi Hidehiko , Uchiyama Atsushi , Kusuda Satoshi ,   on behalf of the Neonatal Research Network of Japan
Published: August 2022

Objective This study aimed to compare the short- and long-term outcomes of extremely preterm small for gestational age (SGA) infants and appropriate for gestational age (AGA) infants in Japan.
Study Design We retrospectively assessed 434 SGA and 1,716 AGA infants born at 22 to 27 weeks of gestational age (GA) and examined their outcomes on singletons and inborn births between 2003 and 2012. Infants were followed-up for 3 years, and the clinical characteristics and outcomes were compared. Fisher's exact and Student's t-tests were used for independent sample comparison. Logistic regression was used to identify associated factors.
Results The prevalence of intraventricular hemorrhage ≥ grade 3 was significantly lower (adjusted odds ratio [aOR]: 0.28; 95% confidence interval [CI]: 0.11 − 0.72), and the prevalence of bronchopulmonary dysplasia at 36 weeks of GA and the need for home oxygen therapy were significantly higher (aOR: 2.20; 95% CI: 1.66 − 2.91 and aOR: 2.46; 95% CI: 1.75–3.47, respectively) in SGA infants than in AGA infants. SGA infants born at 24 to 25 weeks of GA had a significantly higher prevalence of developmental quotient (DQ) < 70 (aOR: 1.73; 95% CI: 1.08 − 2.77). Those born at 26 to 27 weeks of GA showed a significantly higher prevalence of cerebral palsy (CP) and visual impairment (aOR: 2.31; 95% CI: 1.22 − 4.40 and aOR: 2.61; 95% CI: 1.21 − 5.61, respectively).
Conclusion In SGA infants, birth at 24 to 25 weeks of GA is an independent risk factor for DQ < 70, and birth at 26 to 27 weeks of GA is an independent risk factor for CP and visual impairment. However, we did not consider nutritional and developmental factors, and a longer follow-up would help assess neurodevelopmental outcomes.
Key Points
Pd/RHA and Pd/BPA as Eco-Friendly Heterogeneous Catalysts: Microwave-Assisted C–S Cross-Coupling Reaction in DMF
Authors: Katla Ramesh , Katla Rakhi , Goulart Taís Barcelos , Rosa Diego S. , Rosa Gilber R. 
Published: August 2022

AbstractFirst time, Pd-Rice Husk Ash (Pd/RHA) and Pd-Banana Peel Ash (Pd-BPA) were used as eco-friendly catalysts in the C–S cross-coupling reaction of 5-bromo-2,1,3-benzothiadiazole with various benzene thiols in DMF under microwave irradiation at 75 °C, 200 W (100 psi) for 15–25 min. These catalysts were produced from agro-industrial wastes, such as rice husk ash and banana peel ash. These can be recycled and reused up to five catalytic cycles without loss of catalytic efficiency.
Role of Interventional Radiology in the Management of Non-aortic Thoracic Trauma
Authors: Higgins Mikhail C.S.S. , Shi Jessica , Bader Mohammad , Kohanteb Paul A. , Brahmbhatt Tejal S. 
Published: August 2022

AbstractTrauma remains a leading cause of death for all age groups, and nearly two-thirds of these individuals suffer thoracic trauma. Due to the various types of injuries, including vascular and nonvascular, interventional radiology plays a major role in the acute and chronic management of the thoracic trauma patient. Interventional radiologists are critical members in the multidisciplinary team focusing on treatment of the patient with thoracic injury. Through case presentations, this article will review the role of interventional radiology in the management of trauma patients suffering thoracic injuries.
Social media, education, and the rise of populist Euroscepticism
Authors: Fortunato Piergiuseppe , Pecoraro Marco 
Published: August 2022

AbstractThis paper studies how the diffusion of skeptical or negative attitudes towards the European Union (EU) and the process of European integration relates to the new technologies of political communication, education, and their interaction. Using both European-wide and national surveys, we find a strong relationship between exposure to online political activity and Euroscepticism only among individuals with lower formal education. When distinguishing between different forms of online political activity it also finds that it is not the use of the internet per se that matters, but the specific use of social networks, like Twitter or Facebook, for obtaining information about politics. These results turn out to be robust to the use of instrumental variables intended to capture the speed of connection available and the relative easiness of using internet and social media.
Threshold conditions for transversal modes of tunable plasmonic nanolasers shaped as single and twin graphene-covered circular quantum wires
Authors: Herasymova Dariia O , Dukhopelnykov Sergii V , Natarov Denys M , Zinenko Tatiana L , Lucido Mario , Nosich Alexander I 
Published: August 2022

Abstract
We implement the lasing eigenvalue problem (LEP) approach to study the electromagnetic field in the presence of a circular quantum wire (QW) made of a gain material and wrapped in graphene cover and a dimer of two identical graphene-covered QWs, at the threshold of stationary emission. LEP delivers the mode-specific eigenvalue pairs, namely the frequencies and the threshold values of the QW gain index for the plasmon and the wire modes of such nanolasers. In our analysis, we use quantum Kubo formalism for the graphene conductivity and classical Maxwell boundary-value problem for the field functions. The technique involves the resistive boundary conditions, the separation of variables in the local coordinates, and, for the dimer, the addition theorem for the cylindrical functions. For single-wire plasmonic laser, we derive approximate engineering expressions for the lasing frequencies and threshold values of the gain index that complement the full-wave computations. For the dimer, we derive separate determinantal equations for four different classes of symmetry of the lasing supermodes and solve them numerically. Our investigation of the mode frequencies and thresholds versus the graphene and QW parameters shows that plasmon modes or, for the dimer, plasmon supermodes have lower frequencies and thresholds than the wire modes provided that the QW radius is smaller than 10 μm, however in thicker wires they are comparable. Only the plasmon-mode characteristics are well-tunable using the graphene chemical potential. In the dimer, all lasing supermodes form closely located quartets, however, they quickly approach the single-wire case if the inter-wire separation becomes comparable to the radius. These results open a way for building essentially single-mode plasmonic nanolasers and their arrays and suggest certain engineering rules for their design.
Explicit form of Berry phase for time dependent harmonic oscillators in noncommutative space
Authors: Dutta Manjari , Ganguly Shreemoyee , Gangopadhyay Sunandan 
Published: August 2022

Abstract
In this paper we look for the existence of Berry phase in time dependent harmonic oscillators in noncommutative space. Two systems are considered in our study in the noncommutative framework. The first one is a system in which a scale invariant term is present in the Hamiltonian from the beginning, and the second one is a system in which a scale invariant term emerges due to a change of variables from the noncommutative to the commutative ones. We first compute the eigenstates of both the systems using the Lewis invariant approach. We then employ the Lewis invariant technique to obtain the geometric phase under adiabatic approximation. We also calculate the Berry phase explicitly by choosing appropriate forms of the time dependent parameters appearing in the Hamiltonian. Our analysis surprisingly reveals that a scale invariant time reversal symmetry breaking term may not always lead to a non trivial Berry phase.
Neural network reconstruction of the dense matter equation of state from neutron star observables
Authors: Soma Shriya , Wang Lingxiao , Shi Shuzhe , Stöcker Horst , Zhou Kai 
Published: August 2022

Abstract
The Equation of State (EoS) of strongly interacting cold and hot ultra-dense QCD matter remains a major challenge in the field of nuclear astrophysics. With the advancements in measurements of neutron star masses, radii, and tidal deformabilities, from electromagnetic and gravitational wave observations, neutron stars play an important role in constraining the ultra-dense QCD matter EoS. In this work, we present a novel method that exploits deep learning techniques to reconstruct the neutron star EoS from mass-radius (M-R) observations. We employ neural networks (NNs) to represent the EoS in a model-independent way, within the range of ∼1-7 times the nuclear saturation density. The unsupervised Automatic Differentiation (AD) framework is implemented to optimize the EoS, so as to yield through TOV equations, an M-R curve that best fits the observations.
We demonstrate that this method works by rebuilding the EoS on mock data, i.e., mass-radius pairs derived from a randomly generated polytropic EoS. The reconstructed EoS fits the mock data with reasonable accuracy, using just 11 mock M-R pairs observations, close to the current number of actual observations.
Valley dynamics of different excitonic states in monolayer WSe2 grown by molecular beam epitaxy
Authors: Hu Shengmin , Ye Jialiang , Liu Ruiqi , Zhang Xinhui 
Published: August 2022

Abstract
Monolayer transition-metal dichalcogenides possess rich excitonic physics and unique valley-contrasting optical selection rule, and offer a great platform for long spin/valley lifetime engineering and the associated spin/valleytronics exploration. Using two-color time-resolved Kerr rotation and time-resolved reflectivity spectroscopy, we investigate the spin/valley dynamics of different excitonic states in monolayer WSe2 grown by molecular beam epitaxy. With fine tuning of the photon energy of both pump and probe beams, the valley relaxation process for the neutral excitons and trions is found to be remarkably different—their characteristic spin/valley lifetimes vary from picoseconds to nanoseconds, respectively. The observed long trion spin lifetime of > 2.0 ns is discussed to be associated with the dark trion states, which is evidenced by the photon-energy dependent valley polarization relaxation. Our results also reveal that valley depolarization for these different excitonic states is intimately connected with the strong Coulomb interaction when the optical excitation energy is above the exciton resonance.
Experimental investigation of pressure characteristics behind the reflected shock waves in a metrological shock tube
Authors: Yao Zhenjian , Ding Yifan , Li Yongsheng , Yao Lei , Wang Chenchen 
Published: August 2022

Abstract
The pressure behind the reflected shock wave (RSW) in real shock tubes deviates from the ideal behavior. This results in lower measurement accuracy and thus affects experiments and interpretations. The deviations depend on several factors, such as the pressure magnitude, shock tube geometry, and working gas. This study investigated it quantitatively and attempted to accurately describe its characteristics via the introduction of two parameters: pressure gain and pressure rise. To improve the accuracy of the pressure gain measurement, a model of the incident shock wave (ISW) attenuation was proposed and the influence of the shock tube geometry was explored. The experimental results showed that the measurement accuracy was significantly improved: in the cases of 0.07, 0.14, 0.25, and 0.30 mm thick aluminum diaphragms, it was improved by approximately 4, 7, 12, and 22 times, respectively. In addition, a model of the pressure rise dependence on the Mach number of the ISW was constructed through a linear fit of the pressure rise data. Further, the effects of the working gas on the RSW were examined: the results demonstrate that by working with the air the pressure behind the RSW exhibited good stability and amplitude.
An efficient CNN-LSTM network with spectral normalization and label smoothing technologies for SSVEP frequency recognition
Authors: Pan Yudong , Chen Jianbo , Zhang Yangsong , Zhang Yu 
Published: August 2022

Abstract

Objective. Steady-state visual evoked potentials (SSVEPs) based brain–computer interface (BCI) has received great interests owing to the high information transfer rate and available large number of targets. However, the performance of frequency recognition methods heavily depends on the amount of the calibration data for intra-subject classification. Some research adopted the deep learning (DL) algorithm to conduct the inter-subject classification, which could reduce the calculation procedure, but the performance still has large room to improve compared with the intra-subject classification. Approach. To address these issues, we proposed an efficient SSVEP DL NETwork (termed SSVEPNET) based on one-dimensional convolution and long short-term memory (LSTM) module. To enhance the performance of SSVEPNET, we adopted the spectral normalization and label smoothing technologies during implementing the network architecture. We evaluated the SSVEPNET and compared it with other methods for the intra- and inter-subject classification under different conditions, i.e. two datasets, two time-window lengths (1 s and 0.5 s), three sizes of training data. Main results. Under all the experimental settings, the proposed SSVEPNET achieved the highest average accuracy for the intra- and inter-subject classification on the two SSVEP datasets, when compared with other traditional and DL baseline methods. Significance. The extensive experimental results demonstrate that the proposed DL model holds promise to enhance frequency recognition performance in SSVEP-based BCIs. Besides, the mixed network structures with convolutional neural network and LSTM, and the spectral normalization and label smoothing could be useful optimization strategies to design efficient models for electroencephalography data.