scholarly journals Rotational Coherence Spectroscopy of Molecules in Helium Nanodroplets: Reconciling the Time and the Frequency Domains

2020 ◽  
Vol 125 (1) ◽  
Author(s):  
Adam S. Chatterley ◽  
Lars Christiansen ◽  
Constant A. Schouder ◽  
Anders V. Jørgensen ◽  
Benjamin Shepperson ◽  
...  
2014 ◽  
Vol 45 (01) ◽  
Author(s):  
G Mingoia ◽  
K Langbein ◽  
M Dietzek ◽  
G Wagner ◽  
S Smesny ◽  
...  

2015 ◽  
Vol 135 (12) ◽  
pp. 1565-1573
Author(s):  
Yoshitaka Ohshio ◽  
Daisuke Ikefuji ◽  
Yuko Suhara ◽  
Masato Nakayama ◽  
Takanobu Nishiura

Author(s):  
Włodzimierz Pogribny ◽  
Marcin Drzycimski ◽  
Zdzisław Drzycimski

2021 ◽  
pp. 0958305X2110220
Author(s):  
Ngo Thai Hung

Previous studies ignored the distinction between short, medium, and long term by decomposing macroeconomic variables and human development index at different time scales. We re-visit the causal association between biomass energy (BIO), economic growth (GDP), trade openness (TRO), industrialization (IND), foreign direct investment (FDI), and human development (HDI) in China on a quarterly scale by scale basis for the period 1990 to 2019 using the tools of wavelet, i.e., wavelet correlation, wavelet coherence and scale by scale Granger causality test. The main findings uncover that IND, TRO, GDP, and BIO positively drive the HDI at low and medium frequencies, while FDI negatively impacts HDI during the sample period. Additionally, there is a bidirectional relationship between GDP and HDI at different time and frequency domains. Specifically, we discover that the positive co-movement is more robust in the aftermath of the global financial crisis, particularly for HDI, BIO, GDP, and TRO at medium frequencies throughout the period under research. Our empirical insights have significant implications for achieving human development sustainability in China.


Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3484
Author(s):  
Felix Duensing ◽  
Elisabeth Gruber ◽  
Paul Martini ◽  
Marcelo Goulart ◽  
Michael Gatchell ◽  
...  

Complexes of atomic gold with a variety of ligands have been formed by passing helium nanodroplets (HNDs) through two pickup cells containing gold vapor and the vapor of another dopant, namely a rare gas, a diatomic molecule (H2, N2, O2, I2, P2), or various polyatomic molecules (H2O, CO2, SF6, C6H6, adamantane, imidazole, dicyclopentadiene, and fullerene). The doped HNDs were irradiated by electrons; ensuing cations were identified in a high-resolution mass spectrometer. Anions were detected for benzene, dicyclopentadiene, and fullerene. For most ligands L, the abundance distribution of AuLn+ versus size n displays a remarkable enhancement at n = 2. The propensity towards bis-ligand formation is attributed to the formation of covalent bonds in Au+L2 which adopt a dumbbell structure, L-Au+-L, as previously found for L = Xe and C60. Another interesting observation is the effect of gold on the degree of ionization-induced intramolecular fragmentation. For most systems gold enhances the fragmentation, i.e., intramolecular fragmentation in AuLn+ is larger than in pure Ln+. Hydrogen, on the other hand, behaves differently, as intramolecular fragmentation in Au(H2)n+ is weaker than in pure (H2)n+ by an order of magnitude.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4347
Author(s):  
Boyun Lyu ◽  
Yu Hua ◽  
Jiangbin Yuan ◽  
Shifeng Li

The Enhanced Loran (eLoran) system is valued for its important role in the positioning, navigation, and timing fields; however, with its current modulation methods, low data rate restricts its development. Ultra narrow band (UNB) modulation is a modulation method with extremely high spectrum utilization. If UNB modulation can be applied to the eLoran system, it will be very helpful. The extended binary phase shift keying modulation in UNB modulation is selected for a detailed study, parameters and application model are designed according to its unique characteristics of signal time and frequency domains, and it is verified through simulation that the application of this modulation not only meets the design constraints of the eLoran system but also does not affect the reception of the respective signals of both parties. Several feasible schemes are compared, analyzed, and selected. Studies have revealed that application of UNB modulation in the eLoran system is feasible, and it will increase the data rate of the system by dozens of times.


2021 ◽  
pp. 1-12
Author(s):  
Omid Izadi Ghafarokhi ◽  
Mazda Moattari ◽  
Ahmad Forouzantabar

With the development of the wide-area monitoring system (WAMS), power system operators are capable of providing an accurate and fast estimation of time-varying load parameters. This study proposes a spatial-temporal deep network-based new attention concept to capture the dynamic and static patterns of electrical load consumption through modeling complicated and non-stationary interdependencies between time sequences. The designed deep attention-based network benefits from long short-term memory (LSTM) based component to learning temporal features in time and frequency-domains as encoder-decoder based recurrent neural network. Furthermore, to inherently learn spatial features, a convolutional neural network (CNN) based attention mechanism is developed. Besides, this paper develops a loss function based on a pseudo-Huber concept to enhance the robustness of the proposed network in noisy conditions as well as improve the training performance. The simulation results on IEEE 68-bus demonstrates the effectiveness and superiority of the proposed network through comparison with several previously presented and state-of-the-art methods.


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