bluuebunny/crossref_metadata_2025_split huggingface dataset:
Active unfolding of the glucocorticoid receptor by the Hsp70/Hsp40 chaperone system in single-molecule mechanical experiments
Authors: Moessmer Patrick , Suren Thomas , Majdic Ulrike , Dahiya Vinay , Rutz Daniel , Buchner Johannes , Rief Matthias 
Published: April 2022

Significance
One of the key unresolved questions in the field of molecular chaperones is how they can actively unfold proteins. In this study, we discovered that the Hsp70/Hsp40 chaperone system completely unfolds a native soluble substrate protein, the ligand-binding domain of the glucocorticoid receptor, in a concerted action. Our high-resolution optical tweezers data show in real time how the substrate is attacked by the chaperone machinery. As soon as the hormone has left the binding pocket, up to five Hsp70/Hsp40 complexes bind and unfold the protein in a stepwise manner. This finding constitutes direct evidence that the chaperone machinery can bind to the folded core of the receptor, thus providing a mechanism for Hsp70-induced protein unfolding.
Generic character of charge and spin density waves in superconducting cuprates
Authors: Lee Sangjun , Huang Edwin W. , Johnson Thomas A. , Guo Xuefei , Husain Ali A. , Mitrano Matteo , Lu Kannan , Zakrzewski Alexander V. , de la Peña Gilberto A. , Peng Yingying , Huang Hai , Lee Sang-Jun , Jang Hoyoung , Lee Jun-Sik , Joe Young Il , Doriese William B. , Szypryt Paul , Swetz Daniel S. , Chi Songxue , Aczel Adam A. , MacDougall Gregory J. , Kivelson Steven A. , Fradkin Eduardo , Abbamonte Peter 
Published: April 2022

Significance
The essential physics of the cuprate high-temperature superconductors have been a central focus of condensed-matter physics for more than three decades. Although initially controversial, it is now clear that a ubiquitous tendency toward charge-density-wave (CDW) order is intertwined with the superconductivity. However, this manifests differently in distinct cuprates. On the basis of extensive X-ray and neutron scattering studies of the temperature and doping dependence of the CDW and spin-density-wave (SDW) correlations in one representative cuprate and a comparison with existing studies on other cuprates, we show that there plausibly is a single, preferred CDW order at the microscale, whose manifestation at low temperatures is modified in predictable ways by material-specific details, including its interaction with SDW order.
Interacting pest control and pollination services in coffee systems
Authors: Martínez-Salinas Alejandra , Chain-Guadarrama Adina , Aristizábal Natalia , Vilchez-Mendoza Sergio , Cerda Rolando , Ricketts Taylor H. 
Published: April 2022

Significance
Food production depends on biodiversity and ecosystem services (ES) such as pest control and pollination. Our knowledge about biodiversity benefits to crop production has increased in recent decades, but most studies treat ES separately and then add up their values. Ignoring that these services, being part of the same system, likely interact is blinding us to potential synergies and trade-offs. Our field experiment shows, at realistic field scales, that pest control and pollination can interact positively. This synergy translates directly to improved yields and income for coffee farmers, who produce a global commodity worth $24 billion per year. Our findings highlight the need to study interactions to understand the linkages between biodiversity, ES, and farmers’ livelihoods.
Transmogrification of ocean into continent: implications for continental evolution
Authors: Morgan Jason P. , Vannucchi Paola 
Published: April 2022

SignificanceThis study proposes a geological mechanism for creating continental crust and lithosphere. When continents collide, the typical embayments and protrusions along their rifted margins make it likely that fragments of seafloor will be trapped within the growing mountain belt. These become preferential centers of sedimentation that eventually convert former seafloor into a unique form of continental crust and lithosphere, leading to characteristic temporal changes in the relative strength and uplift/subsidence of these regions. The Alpine–Himalayan mountain chain in Eurasia shows several stages of this process, which we further explore with a one-dimensional thermal-rheological model. In Asia, this process appears to have created a characteristic paired-mountain belt geomorphology (Himalaya/Tibet + Tian Shan) that has greatly strengthened the East Asian Monsoon.
Investigation of three topological edge states in honeycomb lattices based on graphene plasmonic crystal
Authors: Li Zhi , He Zhen , Zhuo Liqiang , Su Shaojian , Lin Zhili , Qiu Weibin , Huang Beiju , Kan Qiang 
Published: April 2022

Abstract
In this article, three categories of the edge states in the honeycomb lattice are investigated theoretically by using the effective tight-binding Hamiltonian. The edge-bulk corresponding dispersions of zigzag, bearded, and armchair edge states analytically. The actual edge-bulk corresponding and the light field distribution of the graphene plasmonic crystals are obtained by solving Maxwell equations with boundary conditions, which are in good agreement with the analytical results. The proposed plasmonic structures provide guidance for designing the frequency range dependent property of topological structures, and show the potential applications in topological robust devices.
Study the mixed valence problem in asymmetric Anderson model: Fano–Kondo resonance around Fermi level
Authors: Li ZhenHua , Cheng YongXi , Zheng Xiao , Wei JianHua , Yan YiJing , Luo Hong-Gang 
Published: April 2022

Abstract
We numerically calculate the local density of states (LDOS) in asymmetric Anderson model in mixed valence regime using hierarchical equations of motion approach. Based on the idea that the asymmetric line shape of LDOS around Fermi level stems from the interference between the single particle resonance and the Kondo resonance, we perform a fitting. From the fitting results, we obtain the Kondo temperatures and the Fano factors with changing the single particle energy. The tendency of Kondo temperature agrees with the previous analytic expressions and the Fano factors are in an expected variation of Fano resonance. Our study shows that the Fano–Kondo resonance can reasonably explain the asymmetric line shape of the LDOS around the Fermi level.
On the fly swapping algorithm for ordering of degrees of freedom in density matrix renormalization group
Authors: Li Weitang , Ren Jiajun , Yang Hengrui , Shuai Zhigang 
Published: April 2022

Abstract
Density matrix renormalization group (DMRG) and its time-dependent variants have found widespread applications in quantum chemistry, including ab initio electronic structure of complex bio-molecules, spectroscopy for molecular aggregates, and charge transport in bulk organic semiconductors. The underlying wavefunction ansatz for DMRG, matrix product state (MPS), requires mapping degrees of freedom (DOF) into a one-dimensional topology. DOF ordering becomes a crucial factor for DMRG accuracy. In this work, we propose swapping neighboring DOFs during the DMRG sweeps for DOF ordering, which we term ‘on the fly swapping’ (OFS) algorithm. We show that OFS is universal for both static and time-dependent DMRG with minimum computational overhead. Examples are given for one dimensional antiferromagnetic Heisenberg model, ab initio electronic structure of N2 molecule, and the S1/S2 internal conversion dynamics of pyrazine molecule. It is found that OFS can indeed improve accuracy by finding better DOF ordering in all cases.
EPSPatNet86: eight-pointed star pattern learning network for detection ADHD disorder using EEG signals
Authors: Tanko Dahiru , Barua Prabal Datta , Dogan Sengul , Tuncer Turker , Palmer Elizabeth , Ciaccio Edward J , Acharya U Rajendra 
Published: April 2022

Abstract

Objective. The main objective of this work is to present a hand-modelled one-dimensional signal classification system to detect Attention-Deficit Hyperactivity Disorder (ADHD) disorder using electroencephalography (EEG) signals. Approach. A novel handcrafted feature extraction method is presented in this research. Our proposed method uses a directed graph and an eight-pointed star pattern (EPSPat). Also, tunable q wavelet transforms (TQWT), wavelet packet decomposition (WPD), statistical extractor, iterative Chi2 (IChi2) selector, and the k-nearest neighbors (kNN) classifier have been utilized to develop the EPSPat based learning model. This network uses two wavelet decomposition methods (TQWT and WPD), and 85 wavelet coefficient bands are extracted. The proposed EPSPat and statistical feature creator generate features from the 85 wavelet coefficient bands and the original EEG signal. The learning network is termed EPSPatNet86. The main purpose of the presented EPSPatNet86 is to detect abnormalities of the EEG signals. Therefore, 85 wavelet subbands have been generated to extract features. The created 86 feature vectors have been evaluated using the Chi2 selector and the kNN classifier in the loss value calculation phase. The final features vector is created by employing a minimum loss-valued eight feature vectors. The IChi2 selector selects the best feature vector, which is fed to the kNN classifier. An EEG signal dataset has been used to demonstrate the presented model’s EEG signal classification ability. We have used an ADHD EEG dataset since ADHD is a commonly seen brain-related ailment. Main results. Our developed EPSPatNet86 model can detect the ADHD EEG signals with 97.19% and 87.60% accuracy using 10-fold cross and subject-wise validations, respectively. Significance. The calculated results demonstrate that the presented EPSPatNet86 attained satisfactory EEG classification ability. Results show that we can apply our developed EPSPatNet86 model to other EEG signal datasets to detect abnormalities.
Neural network flows of low q-state Potts and clock models
Authors: Giataganas Dimitrios , Huang Ching-Yu , Lin Feng-Li 
Published: April 2022

Abstract
It is known that a trained restricted Boltzmann machine (RBM) on the binary Monte Carlo Ising spin configurations, generates a series of iterative reconstructed spin configurations which spontaneously flow and stabilize to the critical point of physical system. Here we construct a variety of neural network (NN) flows using the RBM and (variational) autoencoders, to study the q-state Potts and clock models on the square lattice for q = 2, 3, 4. The NN are trained on Monte Carlo spin configurations at various temperatures. We find that the trained NN flow does develop a stable point that coincides with critical point of the q-state spin models. The behavior of the NN flow is nontrivial and generative, since the training is unsupervised and without any prior knowledge about the critical point and the Hamiltonian of the underlying spin model. Moreover, we find that the convergence of the flow is independent of the types of NNs and spin models, hinting a universal behavior. Our results strengthen the potential applicability of the notion of the NN flow in studying various states of matter and offer additional evidence on the connection with the renormalization group flow.
Astrometric Precision Tests on TESS Data
Authors: Gai M. , Vecchiato A. , Riva A. , Busonero D. , Lattanzi M. , Bucciarelli B. , Crosta M. , Qi Z. 
Published: April 2022

Abstract
Astrometry at or below the microarcsec level with an imaging telescope assumes that the uncertainty on the location of an unresolved source can be an arbitrarily small fraction of the detector pixel, given a sufficient photon budget. This paper investigates the geometric limiting precision, in terms of CCD pixel fraction, achieved by a large set of star field images, selected among the publicly available science data of the Transiting Exoplanet Survey Satellite (TESS) mission. The statistics of the distance between selected bright stars (G ≃ 5 mag), in pixel units, is evaluated, using the position estimate provided in the TESS light curve files. The dispersion of coordinate differences appears to be affected by long term variation and noisy periods, at the level of 0.01 pixel. The residuals with respect to low-pass filtered data (tracing the secular evolution), which are interpreted as the experimental astrometric noise, reach the level of a few milli-pixel or below, down to 1/5900 pixel. Saturated images are present, evidencing that the astrometric precision is mostly preserved across the CCD columns, whereas it features a graceful degradation in the along column direction. The cumulative performance of the image set is a few micropixel across columns, or a few 10 μpx along columns. The idea of astrometric precision down to a small fraction of a CCD pixel, given sufficient signal to noise ratio, is confirmed by real data from an in-flight science instrument to the 10−6 pixel level. Implications for future high precision astrometry missions are briefly discussed.
The Renovated Thacher Observatory and First Science Results
Authors: Swift Jonathan J. , Andersen Karina , Arculli Toby , Browning Oakley , Ding Jeffrey , Edwards Nick , Fanning Tomás , Geyer John , Huber Grace , Jin-Ngo Dylan , Kelliher Ben , Kirkpatrick Colin , Kirkpatrick Liam , Klink Douglas , Lavine Connor , Lawrence George , Lawrence Yousef , Cyrus Leung Feng Lin , Luebbers Julien , Myles Justin , O’Neill Theo J. , Osuna Jaime , Phipps Peter , Rahman Gazi , Rosenbaum Teddy , Stacey Holland , Stacey Piper , Tang Hadrien , Wood Asher , Wilcox Alejandro , Vyhnal Christopher R. , Yang Grace , Yim Jennifer , Yin Yao , Zhang Jack , Foley Ryan J. , Gardner Paul , Stafford Greg , Rowe David , Ivarsen Kevin , Hedrick Richard 
Published: April 2022

Abstract
Located on the campus of the Thacher School in Southern California, the Thacher Observatory has a legacy of astronomy research and education that dates back to the late 1950s. In 2016, the observatory was fully renovated with upgrades including a new 0.7 m telescope, a research grade camera, and a slit dome with full automation capabilities. The low-elevation site is bordered by the Los Padres National Forest and therefore affords dark to very dark skies allowing for accurate and precise photometric observations. We present a characterization of the site including sky brightness, weather, and seeing, and we demonstrate the on-sky performance of the facility. Our primary research programs are based around our multi-band photometric capabilities and include photometric monitoring of variable sources, a nearby supernova search and followup program, a quick response transient followup effort, and exoplanet and eclipsing binary light curves. Select results from these programs are included in this work which highlight the broad range of science available to an automated observatory with a moderately sized telescope.
Embedding decomposition for artifacts removal in EEG signals
Authors: Yu Junjie , Li Chenyi , Lou Kexin , Wei Chen , Liu Quanying 
Published: April 2022

Abstract

Objective. Electroencephalogram (EEG) recordings are often contaminated with artifacts. Various methods have been developed to eliminate or weaken the influence of artifacts. However, most of them rely on prior experience for analysis. Approach. Here, we propose an deep learning framework to separate neural signal and artifacts in the embedding space and reconstruct the denoised signal, which is called DeepSeparator. DeepSeparator employs an encoder to extract and amplify the features in the raw EEG, a module called decomposer to extract the trend, detect and suppress artifact and a decoder to reconstruct the denoised signal. Besides, DeepSeparator can extract the artifact, which largely increases the model interpretability. Main results. The proposed method is tested with a semi-synthetic EEG dataset and a real task-related EEG dataset, suggesting that DeepSeparator outperforms the conventional models in both EOG and EMG artifact removal. Significance. DeepSeparator can be extended to multi-channel EEG and data with any arbitrary length. It may motivate future developments and application of deep learning-based EEG denoising. The code for DeepSeparator is available at https://github.com/ncclabsustech/DeepSeparator.
Dye degradation efficiency of green synthesized NiO@GO nanocomposite with biological application
Authors: Subashini K. , Prakash S. , Anusuya Devi V.S. , Sujatha V. 
Published: April 2022

Abstract
The photocatalytic activity of green synthesized nickel oxide nanoparticles derived using Sterculia foetida leaf extract was examined by introducing into graphene oxide (GO). Graphene oxide has porous nature which might enlarge the photocatalytic execution of NiO nanoparticles. NiO nanoparticles (NiO NPs) were prepared by solution combustion method and introduced into graphene oxide (GO) synthesized by Hummers method to form NiO@GO nanocomposite. Various techniques were used for the material characterization of the above synthesized compounds such as UV, FTIR, Powder X-ray diffraction (PXRD), Transmission electron microscopy (TEM). The photocatalytic execution of NiO@GO nanocomposite on deterioration of Methylene blue (MB) and Malachite Green (MG) have been examined and the results indicate that the GO plays a critical part in the improvement of photocatalytic execution. Antibacterial activity has been carried out against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). The synthesized NiO@GO nanocomposite accomplishes a most extreme decay efficiency of 98% for Methylene blue than Malachite green under UV-light.
Surface treatment of magnetron-sputtered tantalum pentoxide coatings and its effect on the phenotype and function of immune cells in vitro
Authors: Donkov N , Zykova A , Safonov V , Dudin S , Yakovin S , Goltsev A , Dubrava T 
Published: April 2022

Abstract
The effect was analyzed of surface treatment by argon ions and electron beam on the properties of tantalum pentoxide coatings deposited by reactive magnetron sputtering and the treatment’s correlation with immune cells response. The characteristics of the coatings were determined by means of energy dispersive X-ray (EDX) scanning electron microscopy (SEM), X-ray photoemission spectroscopy (XPS), and atomic force microscopy (AFM). The results demonstrate that the electron-irradiation post-treatment process stimulates the adhesive potential and phagocytic activity of antigen-presenting cells.
Double-discharge plasma system for deposition of carbon nanostructures
Authors: Marinov S , Vachkov V , Ivanov I , Kiss’ovski Zh 
Published: April 2022

Abstract
Deposition of carbon nanostructures from ethanol precursor at atmospheric pressure can be enhanced via the use of a double-discharge system - a microwave and a DC discharge. We used a surface-wave discharge at a frequency of 2.45 GHz in a gas mixture of Ar, H2 and C2H5OH to create a plasma column in a small-diameter ceramic tube and a plasma plume above it. The plume spectra in the UV/Vis range were measured by an optical system with an iHR550 spectrometer; the gas temperature and the electron temperature and density were calculated from the emission lines. The high gas temperature T
g ∼3000 K and electron density (∼6×1020 m3) in the microwave plasma plume cause an effective dissociation of the ethanol even at low levels of absorbed power (10 W) and a strong carbon Swan band is registered in the spectrum. Transporting the created neutral and charged particles to the substrate at atmospheric pressure is difficult due to their short mean-free-path; we, therefore, applied an additional DC discharge. This two-discharge system allows more reactive species and ions from the ethanol decomposition to reach the substrate, thus speeding up the deposition of carbon nanostructures. Such structures were deposited on Ni foil and Ni foam substrates under fixed plasma parameters and controlled substrate temperature. The morphology of the produced graphene structures was studied using SEM and Raman spectroscopy.
Cirrus-cloud conditioned ratio of multiple-to-single backscatter atmospheric phase functions
Authors: Evgenieva Ts , Anguelov V , Gurdev L 
Published: April 2022

Abstract
The present work is related to LIDAR remote sensing of the atmosphere in the presence of cirrus clouds (CC) along the LIDAR line of sight (LOS), when the multiple-backscatter component of the LIDAR return may be essential. E. Eloranta has found analytical expressions of the multiple-backscatter components of different orders as containing the corresponding ratios of the multiple-to-single backscatter phase functions of the backward scattering medium. As a main purpose of this work, we estimated the above-mentioned ratios in cases of backscattering from air and CC, using accurate approximations of the single-scattering phase functions obtained by U. Wandinger. The results obtained show that the multiple-to-single backscatter phase function ratios for air are equal to unity, while for CCs they are quite near unity.
Development of lidar for remote methane sensing using an optimal configuration of high-power laser diodes
Authors: Pencheva V , Penchev S , Dreischuh T 
Published: April 2022

Abstract
A broadband differential absorption lidar (DIAL) is developed making us of the properties of high-power pulsed laser diodes for the purpose of monitoring methane, a major atmospheric greenhouse biogas. The detection range is optimized for the CH4 Q-branch 2v3 overtone spectrum centered at 1.667 μm and mixed with water-vapor absorption bands of. The resonance absorption evaluated of the DIAL signal is an integral sum of the multiple CH4 resonance absorption lines modulating the characteristic broad laser line and simultaneously compensating the interfering water-vapor absorption. A compact DIAL scheme is developed using an optimal configuration of high-power laser diodes matching the selected spectral parameters.
Effect of growth temperature on nitrogen incorporation into GaAsN during liquid-phase epitaxy
Authors: Milanova M , Donchev V , Georgiev S , Kirilov K , Terziyska P 
Published: April 2022

Abstract
We studied the growth temperature effect on nitrogen incorporation into GaAsN layers grown by liquid-phase epitaxy (LPE). The growth of dilute nitrides at nearly equilibrium conditions during LPE presents several major challenges: low solubility of nitrogen in Ga-melt, small incorporation efficiency in the solid and high volatility of nitrogen. GaAsN layers are grown from three different initial epitaxy temperatures: 580 °C, 680 °C and 780° C using GaN powder in the melt as a source of nitrogen. The N content in GaAsN is estimated from X-ray diffraction curves applying Vegard’s law. The local microstructure and surface morphology of the grown layers are studied by Fourier-transform infrared spectroscopy and atomic force microscopy measurements, respectively. The absorption edge and the composition dependence of the effective band gap are determined by employing optical transmission and surface photovoltage spectroscopies.
Progress report on the online processing upgrade at the NA62 experiment
Authors: Ammendola R. , Biagioni A. , Ciardiello A. , Cretaro P. , Frezza O. , Lamanna G. , Lo Cicero F. , Lonardo A. , Martinelli M. , Piandani R. , Pontisso L. , Raggi M. , Simula F. , Soldi D. , Turisini M. , Vicini P. 
Published: April 2022

Abstract
A new FPGA-based low-level trigger processor has been installed at the NA62 experiment. It is intended to extend the features of its predecessor due to a faster interconnection technology and additional logic resources available on the new platform. With the aim of improving trigger selectivity and exploring new architectures for complex trigger computation, a GPU system has been developed and a neural network on FPGA is in progress. They both process data streams from the ring imaging Cherenkov detector of the experiment to extract in real time high level features for the trigger logic. Description of the systems, latest developments and design flows are reported in this paper.