bluuebunny/crossref_metadata_2025 huggingface dataset:
Structure of the human ATAD2 AAA+ histone chaperone reveals mechanism of regulation and inter-subunit communication
Authors: Cho Carol , Ganser Christian , Uchihashi Takayuki , Kato Koichi , Song Ji-Joon
Published: September 2023

ATAD2 is a non-canonical ATP-dependent histone chaperone and a major cancer target. Despite widespread efforts to design drugs targeting the ATAD2 bromodomain, little is known about the overall structural organization and regulation of ATAD2. Here, we present the 3.1 Å cryo-EM structure of human ATAD2 in the ATP state, showing a shallow hexameric spiral that binds a peptide substrate at the central pore. The spiral conformation is locked by an N-terminal linker domain (LD) that wedges between the seam subunits, thus limiting ATP-dependent symmetry breaking of the AAA+ ring. In contrast, structures of the ATAD2-histone H3/H4 complex show the LD undocked from the seam, suggesting that H3/H4 binding unlocks the AAA+ spiral by allosterically releasing the LD. These findings, together with the discovery of an inter-subunit signaling mechanism, reveal a unique regulatory mechanism for ATAD2 and lay the foundation for developing new ATAD2 inhibitors.
High-dimensional time-frequency entanglement in a singly-filtered biphoton frequency comb
Authors: Cheng Xiang , Chang Kai-Chi , Sarihan Murat Can , Mueller Andrew , Spiropulu Maria , Shaw Matthew D. , Korzh Boris , Faraon Andrei , Wong Franco N. C. , Shapiro Jeffrey H. , Wong Chee Wei
Published: September 2023

High-dimensional quantum entanglement is a cornerstone for advanced technology enabling large-scale noise-tolerant quantum systems, fault-tolerant quantum computing, and distributed quantum networks. The recently developed biphoton frequency comb (BFC) provides a powerful platform for high-dimensional quantum information processing in its spectral and temporal quantum modes. Here we propose and generate a singly-filtered high-dimensional BFC via spontaneous parametric down-conversion by spectrally shaping only the signal photons with a Fabry-Pérot cavity. High-dimensional energy-time entanglement is verified through Franson-interference recurrences and temporal correlation with low-jitter detectors. Frequency- and temporal- entanglement of our singly-filtered BFC is then quantified by Schmidt mode decomposition. Subsequently, we distribute the high-dimensional singly-filtered BFC state over a 10 km fiber link with a post-distribution time-bin dimension lower bounded to be at least 168. Our demonstrations of high-dimensional entanglement and entanglement distribution show the singly-filtered quantum frequency comb’s capability for high-efficiency quantum information processing and high-capacity quantum networks.
The Stochastic Climate Model helps reveal the role of memory in internal variability in the Bohai and Yellow Sea
Authors: Lin Lin , von Storch Hans , Chen Xueen
Published: October 2023

Hasselmann’s theory elucidates how short-term random noise leads to longer-term unprovoked variations, i.e., red spectra. Here, we study ensembles of numerical model simulations of the hydrodynamics of the Bohai and Yellow Sea concerning internal variability formation. Short(/long) term variations are associated with small(/large) spatial scales, and the internal variability of long-term temporal and large-scale variations is markedly enhanced, even without external forcing on these scales, when the tides are turned off. This pattern is well explained by Hasselmann’s theory. A critical element in this theory is the concept of memory, which in our ensembles exhibits a scale dependence that aligns with the scale-dependent nature of redness. Additionally, this framework clarifies why there is a significant reduction of long-term fluctuations during winter and when tides are active: the system’s memory is notably diminished under these conditions.
In planta expression of human polyQ-expanded huntingtin fragment reveals mechanisms to prevent disease-related protein aggregation
Authors: Llamas Ernesto , Koyuncu Seda , Lee Hyun Ju , Wehrmann Markus , Gutierrez-Garcia Ricardo , Dunken Nick , Charura Nyasha , Torres-Montilla Salvador , Schlimgen Elena , Mandel Amrei M. , Theile Erik Boelen , Grossbach Jan , Wagle Prerana , Lackmann Jan-Wilm , Schermer Bernhard , Benzing Thomas , Beyer Andreas , Pulido Pablo , Rodriguez-Concepcion Manuel , Zuccaro Alga , Vilchez David
Published: October 2023

In humans, aggregation of polyglutamine repeat (polyQ) proteins causes disorders such as Huntington’s disease. Although plants express hundreds of polyQ-containing proteins, no pathologies arising from polyQ aggregation have been reported. To investigate this phenomenon, we expressed an aggregation-prone fragment of human huntingtin (HTT) with an expanded polyQ stretch (Q69) in Arabidopsis thaliana plants. In contrast to animal models, we find that Arabidopsis sp. suppresses Q69 aggregation through chloroplast proteostasis. Inhibition of chloroplast proteostasis diminishes the capacity of plants to prevent cytosolic Q69 aggregation. Moreover, endogenous polyQ-containing proteins also aggregate on chloroplast dysfunction. We find that Q69 interacts with the chloroplast stromal processing peptidase (SPP). Synthetic Arabidopsis SPP prevents polyQ-expanded HTT aggregation in human cells. Likewise, ectopic SPP expression in Caenorhabditis elegans reduces neuronal Q67 aggregation and subsequent neurotoxicity. Our findings suggest that synthetic plant proteins, such as SPP, hold therapeutic potential for polyQ disorders and other age-related diseases involving protein aggregation.
Discrimination exposure impacts unhealthy processing of food cues: crosstalk between the brain and gut
Authors: Zhang Xiaobei , Wang Hao , Kilpatrick Lisa A. , Dong Tien S. , Gee Gilbert C. , Labus Jennifer S. , Osadchiy Vadim , Beltran-Sanchez Hiram , Wang May C. , Vaughan Allison , Gupta Arpana
Published: October 2023

Experiences of discrimination are associated with adverse health outcomes, including obesity. However, the mechanisms by which discrimination leads to obesity remain unclear. Utilizing multi-omics analyses of neuroimaging and fecal metabolites, we investigated the impact of discrimination exposure on brain reactivity to food images and associated dysregulations in the brain–gut–microbiome system. We show that discrimination is associated with increased food-cue reactivity in frontal-striatal regions involved in reward, motivation and executive control; altered glutamate-pathway metabolites involved in oxidative stress and inflammation as well as preference for unhealthy foods. Associations between discrimination-related brain and gut signatures were skewed towards unhealthy sweet foods after adjusting for age, diet, body mass index, race and socioeconomic status. Discrimination, as a stressor, may contribute to enhanced food-cue reactivity and brain–gut–microbiome disruptions that can promote unhealthy eating behaviors, leading to increased risk for obesity. Treatments that normalize these alterations may benefit individuals who experience discrimination-related stress.
CuO metallic aerogels with a tailored nodular morphology
Authors: dos Santos-Gómez Lucía , Rey-Raap Natalia , García-Granda S. , Arenillas Ana
Published: September 2023

This work reports, for the first time, an efficient and fast microwave-based method for the preparation of CuO aerogels.
Sequential annulation and isomerisation reaction of 3-acylmethylidene oxindoles with Huisgen zwitterions and synthesis of 5-(3-oxindolyl)oxazoles
Authors: Xue Feixue , Yang Chang-Jiang , Tang Tong , He Zhengjie
Published: September 2023

A one-pot synthesis of 5-(3-oxindolyl)oxazoles has been developed by a sequential annulation/isomerization strategy.
Palladium-catalyzed [4 + 2] cycloaddition of 2-methylidenetrimethylene carbonate or methylene cyclic carbamate with sulfamate-derived cyclic imines
Authors: Sun Li , Li Jiyu , Wu Yafei , Li Ying , Chen Junqi , Xia Xiaoye , Yuan Chunhao , Guo Hongchao , Mao Biming
Published: September 2023

A Pd-catalyzed [4+2] cycloaddition of 2-methylidenetrimethylene carbonate or methylene cyclic carbamate with sulfamate-derived cyclic imines has been successfully developed to afford oxazine or hydropyrimidine derivatives.
Unravelling the link between neurodevelopmental disorders and short tandem CGG-repeat expansions
Authors: Annear Dale J. , Kooy R. Frank
Published: September 2023

Neurodevelopmental disorders (NDDs) encompass a diverse group of disorders characterised by impaired cognitive abilities and developmental challenges. Short tandem repeats (STRs), repetitive DNA sequences found throughout the human genome, have emerged as potential contributors to NDDs. Specifically, the CGG trinucleotide repeat has been implicated in a wide range of NDDs, including Fragile X Syndrome (FXS), the most common inherited form of intellectual disability and autism. This review focuses on CGG STR expansions associated with NDDs and their impact on gene expression through repeat expansion-mediated epigenetic silencing. We explore the molecular mechanisms underlying CGG-repeat expansion and the resulting epigenetic modifications, such as DNA hypermethylation and gene silencing. Additionally, we discuss the involvement of other CGG STRs in neurodevelopmental diseases. Several examples, including FMR1, AFF2, AFF3, XYLT1, FRA10AC1, CBL, and DIP2B, highlight the complex relationship between CGG STR expansions and NDDs. Furthermore, recent advancements in this field are highlighted, shedding light on potential future research directions. Understanding the role of STRs, particularly CGG-repeats, in NDDs has the potential to uncover novel diagnostic and therapeutic strategies for these challenging disorders.
Expanding on the fundamental metallicity relation in dwarf galaxies with MUSE
Authors: Bulichi Teodora-Elena , Fahrion Katja , Mernier François , Hilker Michael , Leaman Ryan , Lyubenova Mariya , Müller Oliver , Neumayer Nadine , Martin-Navarro Ignacio , Pinna Francesca , Rejkuba Marina , Scholz-Diaz Laura , van de Ven Glenn
Published: September 2023

The mass–metallicity relation (MZR) represents one of the most important scaling relations in the context of galaxy evolution, comprising a positive correlation between stellar mass and metallicity (Z). The fundamental metallicity relation (FMR) introduces a new parameter into the dependence, namely, the star formation rate (SFR). While several studies have found that Z is anti-correlated with the SFR at a fixed mass, the validity of this statement has been questioned extensively and no widely accepted consensus has been reached thus far. With this work, we investigate the FMR in nine nearby, spatially resolved, dwarf galaxies, using gas diagnostics on integral-field spectroscopic data of the Multi Unit Spectroscopic Explorer (MUSE), pushing such investigations to lower galaxy masses and higher resolutions. We find that both the MZR and FMR exhibit different behaviours within different star-forming regions of the galaxies. We find that the SFR surface-density-and-metallicity anti-correlation is tighter in the low-mass galaxies of our sample. For all the galaxies considered, we find a SFR surface-density-and-stellar-mass surface-density correlation. We propose that the main reason behind these findings is connected to the accretion mechanisms of the gas fuelling star formation, namely: low-mass, metal-poor galaxies accrete pristine gas from the intergalactic medium, while in more massive and metal-enriched systems, the gas responsible for star formation is recycled from previous star-forming episodes.
Resistive relativistic MHD simulations of astrophysical jets
Authors: Mattia G. , Del Zanna L. , Bugli M. , Pavan A. , Ciolfi R. , Bodo G. , Mignone A.
Published: September 2023

Aims. The main goal of the present paper is to provide the first systematic numerical study of the propagation of astrophysical relativistic jets, in the context of high-resolution, shock-capturing Resistive Relativistic MagnetoHydroDynamic (RRMHD) simulations. We aim to investigate different values and models for the plasma resistivity coefficient, and to assess their impact on the level of turbulence, the formation of current sheets and reconnection plasmoids, the electromagnetic energy content, and the dissipated power.

Methods. We used the PLUTO code for simulations and we assumed an axisymmetric setup for the jets, endowed with both poloidal and toroidal magnetic fields, and propagating in a uniform magnetized medium. The gas was assumed to be characterized by a realistic, Synge-like equation of state (the Taub equation), appropriate for such astrophysical jets. The Taub equation was combined here for the first time with the implicit-explicit Runge-Kutta time-stepping procedure, as required in RRMHD simulations.

Results. The main result is that turbulence is clearly suppressed for the highest values of resistivity (low Lundquist numbers), current sheets are broader, and plasmoids are barely present, while for low values of resistivity the results are very similar to ideal runs, in which dissipation is purely numerical. We find that recipes employing a variable resistivity based on the advection of a jet tracer or on the assumption of a uniform Lundquist number improve on the use of a constant coefficient and are probably more realistic possible sites for the acceleration of the nonthermal particles that produce the observed high-energy emission, preserving as they do the development of turbulence and of sharp current sheets.
Adhesion of 111Indium-Labeled Platelets to the Defoamers of Two Types of Bentley BOS-10 Oxygenators
Authors: Hope A. F. , Heyns A. du P. , Lötter M.G. , Meyer J. M.
Published: October 2023

111Indium-labelled autologus blood platelets administered to patients preoperatively can be traced in the components of the extracorporeal circuit by gamma camera scintillation imaging. Quantitative assessments can be made of platelet/biomaterial adhesion.

It was thus possible to compare the ratio of adherent platelets on the defoaming systems of two types of Bentley BOS-10 oxygenators. The results indicated that more platelets adhered to the areas of the defoamer where gas bubbles burst than to areas such as the gaseous micro-emboli inhibitor sponge through which all the bubbles had to pass in the later types of BOS-10 oxygenator. In both types the pattern of platelet adhesion to the defoamer layers was comparable and was not influenced by bypass time. Gamma camera images of the oxygenators showed that most platelet adhesion took place in areas of blood/gas to biomaterial interfaces. Tubing circuits and cannulae displayed negligible 111 Indium activity on their surfaces, while the oxygenators held a mean of 8.5% of the activity administered to the patients. This technique could be applied to study platelet interaction with various extracorporeal circuits and oxygenators and may help to clarify the role of cardiopulmonary bypass (CPB) in thrombocytopoenia during heart surgery cases.
Classification of the HCN isomerization reaction dynamics in Ar buffer gas via machine learning
Authors: Yamashita Takefumi , Miyamura Naoaki , Kawai Shinnosuke
Published: September 2023

The effect of the presence of Ar on the isomerization reaction HCN ⇄ CNH is investigated via machine learning. After the potential energy surface function is developed based on the CCSD(T)/aug-cc-pVQZ level ab initio calculations, classical trajectory simulations are performed. Subsequently, with the aim of extracting insights into the reaction dynamics, the obtained reactivity, that is, whether the reaction occurs or not under a given initial condition, is learned as a function of the initial positions and momenta of all the atoms in the system. The prediction accuracy of the trained model is greater than 95%, indicating that machine learning captures the features of the phase space that affect reactivity. Machine learning models are shown to successfully reproduce reactivity boundaries without any prior knowledge of classical reaction dynamics theory. Subsequent analyses reveal that the Ar atom affects the reaction by displacing the effective saddle point. When the Ar atom is positioned close to the N atom (resp. the C atom), the saddle point shifts to the CNH (HCN) region, which disfavors the forward (backward) reaction. The results imply that analyses aided by machine learning are promising tools for enhancing the understanding of reaction dynamics.
Optimal performances of a-Si:H/c-Si heterojunction silicon solar cells based on a statistical approach
Authors: Trinh Thanh Thuy , Nguyen Cam Phu Thi , Nguyen Chi-Hieu , Giang Ngo Thi Thanh , Nguyen Phuong T. K. , Yi Junsin , Dao Vinh-Ai
Published: September 2023

Finding the optimal condition from a wide range of cell fabrication conditions and design parameters is typically a time-consuming and cumbersome task. In this study, the combination of the Taguchi approach and Grey relational analysis was employed for optimization of the conversion efficiency of hydrogenated amorphous silicon/crystalline silicon heterojunction (a-Si:H/c-Si HJ) solar cells. With the help of the Taguchi method via an orthogonal array, the reconstruction of the impact of input parameters on single performance characteristics is still ensured while reducing the number of simulations by 99.8%. The simulated results suggested that the density of interfacial defects (Dit) plays a key role in obtaining a high open-circuit voltage (Voc) and fill factor (FF), respectively. Meanwhile, the emitter thickness is the dominant factor in achieving a high short-circuit current density (Jsc). As a result, these two factors dominate the conversion efficiency. Furthermore, the overall optimal condition is also obtained by the Grey relational analysis. The simplified HJ cell configuration using this optimal condition displayed the highest conversion efficiency of 25.86%, yielding a 2.25% absolute increase in efficiency compared to the initial condition. The results highlight the effectiveness of our proposed approach in reducing the number of experiments needed for cell optimization.
Orbital-free QM/MM simulation combined with a theory of solutions
Authors: Takahashi Hideaki
Published: September 2023

In a recent study, we developed a kinetic-energy density functional that can be utilized in orbital-free quantum mechanical/molecular mechanical (OF-QM/MM) simulations. The functional includes the nonlocal term constructed from the response function of the reference system of the QM solute. The present work provides a method to combine the OF-QM/MM with a theory of solutions based on the energy representation to compute the solvation free energy of the QM solute in solution. The method is applied to the calculation of the solvation free energy Δμ of a QM water solute in an MM water solvent. It is demonstrated that Δμ is computed as −7.7 kcal/mol, in good agreement with an experimental value of −6.3 kcal/mol. We also develop a theory to map the free energy δμ due to electron density polarization onto the coordinate space of electrons. The free energy density obtained by the free-energy mapping for the QM water clarifies that each hydrogen atom makes a positive contribution (+34.7 kcal/mol) to δμ, and the oxygen atom gives the negative free energy (−71.7 kcal/mol). It is shown that the small polarization free energy −2.4 kcal/mol is generated as a result of the cancellation of these counteracting energies. These analyses are made possible by the OF-QM/MM approach combined with a statistical theory of solutions.
Understanding and modeling unstarting phenomena in a supersonic inlet cascade
Authors: Mushtaq Noraiz , Gaetani Paolo
Published: October 2023

The renewed interest in supersonic turbomachinery research was driven by its potential applications in emerging fields. However, the design of supersonic inlet cascades faces significant challenges due to the inherent limitations of supersonic flows. While several studies have been published on the unstarting of supersonic intakes, there exists a major knowledge gap in the unstarting of supersonic blade rows. This paper presents the research on a novel unstarting mechanism for supersonic inlet cascades induced by the formation of a collective shock. Tailored simulations were carried out to study the coalescence of the leading-edge bow shock waves and to investigate the stability and the hysteresis of this phenomenon. Then, a reduced order model was developed and verified to estimate the limit induced by this additional unstarting mechanism. Since the accuracy of the unstarting condition relies heavily on the predicted bow shock shape, novel strategies were proposed to improve the estimate of the asymptotic slope of the bow shock and to account for large incidence angles. Furthermore, the well-known Kantrowitz criterion for the self-starting of a supersonic channel was reviewed and adapted to supersonic blade rows by considering both weak and strong oblique shock waves in the calculation of the maximum contract ratio. Then, it was demonstrated the importance of accounting for shock-induced boundary layer separation in the starting process of a supersonic machine. Finally, computational fluid dynamics simulations reveal the high sensitivity of the self-starting limit to the cascade solidity and profile shape.
Local turbulence generation using conditional generative adversarial networks toward Reynolds-averaged Navier–Stokes modeling
Authors: Yan Chongyang , Zhang Yufei
Published: October 2023

Data-driven turbulence modeling has been extensively studied in recent years. To date, only high-fidelity data from the mean flow field have been used for Reynolds-averaged Navier–Stokes (RANS) modeling, while the instantaneous turbulence fields from direct numerical simulation and large eddy simulation simulations have not been utilized. In this paper, a new framework is proposed to augment machine learning RANS modeling with features extracted from instantaneous turbulence flow data. A conditional generative model is trained to model the probability distribution of the local instantaneous turbulence field given local mean flow features. Then, the generative model is transferred to machine learning RANS modeling. The present work is mainly focused on generating a local instantaneous turbulence field using conditional generative adversarial networks (CGANs). Several GANs are trained first on the turbulence data from channel flow and periodic hill flow to generate complete one-dimensional and two-dimensional turbulence fields. Then, a CGAN is trained on the periodic hill flow data to generate local turbulence fields. Statistical analysis is performed on the generated samples from the GAN models. The first and second moments, the two-point correlation, and the energy spectra conform well to those of real turbulence. Finally, the information learned by the CGAN is used for machine learning RANS modeling by multitask learning, and the feasibility of the framework proposed in this paper is initially verified.
Wake physics of two-dimensional flapping-hydrofoil turbines
Authors: Yao Huilan , Wang Liangjiao , Zhang Huaixin , Liu Yong
Published: October 2023

We present a numerical study on the wake of two-dimensional flapping-hydrofoil turbines using Reynolds averaged Navier–Stokes method with shear stress transport k–ω model. The adaptive mesh refinement was applied for vortex simulations. The pitching amplitude ranges from 50° to 90°, and the reduced frequency ranges from 0.10 to 0.20. By varying the reduced frequency and pitching amplitude, we visualized three different types of wakes, and they are the von Karman wake, the mixed wake, and the chaotic wake. We found that there is a critical value of the reduced frequency to determine whether the wake will eventually develop into a standard von Karman wake. When the vortices leave the hydrofoil, they first form a classical staggered arrangement and then develop into a stable double-row configuration. The regular motions of vortices along specific trajectories are explained by analyzing the resultant velocity using velocity polygon, taking into account the effects of vortex interactions and environmental factors. The main component of vortex induced velocities at specific locations is always opposite to the freestream velocity, which is the cause of velocity attenuation in the wake. With the increase in the reduced frequency and pitching amplitude, the velocity attenuation is getting worse. The maximum velocity attenuation usually occurs farther downstream from the hydrofoil for large reduced frequencies and large pitching amplitudes. The wake of a flapping-hydrofoil turbine is divided into four feature zones by studying the time-varying characteristics of velocities, which deepens the understanding of the wake and can provide important references in selecting the optimal location for downstream turbines.
Instabilities in a turbulent swirling source flow between parallel rings
Authors: Fan M. , Dazin A. , Bois G. , Romanò F.
Published: October 2023

Instabilities in a source flow between parallel rings with spatially modulated inflow conditions rotating at angular rate Ω are investigated in this Letter. Numerical simulations are conducted for five flow rates. Two inlet conditions are considered: an idealized one, in which the inlet flow is sealed, and a more realistic one, in which a leakage flow is entrained to enter the diffuser. The resulting fast Fourier transforms, wavelet analyses, and phase averages unravel the primary rotating instability that propagates in the parallel rings and leads to severe blockage for the mean flow. Moreover, secondary instabilities are triggered. Their identification is eased by the idealized inflow. We further discuss the imprinting of such instabilities in determining the route to chaos observed in the diffuser with more realistic inlet conditions. Special attention is here paid to identifying how the secondary instability mechanism is affected by the inflow.
Interpolation and sampling effects on recurrence quantification measures
Authors: Antary Nils , Trauth Martin H. , Marwan Norbert
Published: October 2023

The recurrence plot and the recurrence quantification analysis (RQA) are well-established methods for the analysis of data from complex systems. They provide important insights into the nature of the dynamics, periodicity, regime changes, and many more. These methods are used in different fields of research, such as finance, engineering, life, and earth science. To use them, the data have usually to be uniformly sampled, posing difficulties in investigations that provide non-uniformly sampled data, as typical in medical data (e.g., heart-beat based measurements), paleoclimate archives (such as sediment cores or stalagmites), or astrophysics (supernova or pulsar observations). One frequently used solution is interpolation to generate uniform time series. However, this preprocessing step can introduce bias to the RQA measures, particularly those that rely on the diagonal or vertical line structure in the recurrence plot. Using prototypical model systems, we systematically analyze differences in the RQA measure average diagonal line length for data with different sampling and interpolation. For real data, we show that the course of this measure strongly depends on the choice of the sampling rate for interpolation. Furthermore, we suggest a correction scheme, which is capable of correcting the bias introduced by the prepossessing step if the interpolation ratio is an integer.
Physical insight of thin AlGaN back barrier for millimeter-wave high voltage AlN/GaN on SiC HEMTs
Authors: Shanbhag Ajay , Grandpierron Francois , Harrouche Kathia , Medjdoub Farid
Published: October 2023

In this work, physical mechanisms underlying carbon-doped buffer combined with an AlGaN back-barrier layer are investigated in state-of-the-art millimeter-wave AlN/GaN transistors. We have fabricated devices with and without the insertion of a thin AlGaN back-barrier layer with reduced carbon concentration to analyze the improvement resulting from this buffer architecture. More specifically, the impact of the Al mole fraction into the back-barrier, carbon doping in the buffer, and channel thickness on 100 nm gate length device performance has been studied. It appears that a 150 nm undoped GaN channel followed by a highly carbon-doped GaN buffer results in good electron confinement at the expense of a high current collapse. On the other hand, an Al mole fraction of 25% in the AlGaN back barrier layer coupled with a 150 nm undoped GaN channel provides excellent electron confinement, resulting not only in a low DIBL under high electric field but also low current collapse. Calibrated on experimental devices, TCAD simulations reveal that the electric field penetration inside the GaN buffer is prevented owing to a strong polarization from the back barrier when the Al-content is high enough. That is why, the electron confinement is superior for the 25% Al mole fraction in the back barrier along with reduced current collapse. As a result, careful engineering of the carbon concentration together with the undoped GaN channel thickness is crucial to achieve robust devices, which can, thus, deliver high device performance with superior voltage operation while using short gate lengths.
Impingement of ferrofluid droplets on superamphiphobic surfaces under magnetic fields
Authors: Zhang Jun , Wei Hao , Jin Yakang , Li Bin , Niu Wenbin , Zang Jiadong , Lu Wenlong , Chen Longquan
Published: October 2023

Ferrofluids are novel functional materials that have extensively been exploited in fluid-based management and control systems, and thus underlying the dynamic interactions between ferrofluid and solid under various conditions is rather essential. Herein, we report an experimental investigation on the impingement of millimeter-sized ferrofluid droplets on superamphiphobic surfaces. Comparing to droplet impact under no magnetic field, the employment of a non-uniform vertical magnetic field does not change the types of impact phenomena but alters their transitional boundaries and affects droplet dynamic behaviors. At low We, the magnetic force couples with hydrodynamic forces to slightly enlarge the upper threshold for complete rebound, while the enhanced droplet–surface adhesion prolongs the contact time and decreases the restitution coefficient of bouncing droplets; at intermediate We, the promoting effect of the magnetic field on partial rebound was also identified due to the strong droplet–surface adhesion and the additional magnetic force; at high We, a decrease in the damping coefficient and spring constant of the post-impact droplet oscillations emerges if a magnetic field is applied, which is attributed to the volume and shape effects and well explained by simple scaling analyses. We also demonstrate that upward jets are still stimulated in ferrofluid droplet impacts, but they follow scaling laws distinct from simple liquids. Regardless of whether a magnetic field is applied, ferrofluid droplet spreading is mainly dominated by capillary and inertial forces, and such a conclusion can only be drawn when the characteristic length scale for droplet inertia is correctly chosen for data analyses.
Temperature-dependent fluorescence quenching and Forster resonance energy transfer (FRET) in phenanthroline derivative and ZrO2 nanoparticles using spectroscopic method
Authors: H. K. Deepa , Reddy Jagannatha , Sharma Kalpana , Melavanki Raveendra , Koppal V. V.
Published: October 2023

1,10-Phenanthroline monohydrate (1,10-phen) is a fluorescent compound and a chemically versatile ligand that forms complexes with transition metals. The fluorescence quenching study has been done for 1,10-phen in the present study. We have synthesized Zirconium oxide (ZrO2) nanoparticles (NPs) by the modified precipitation method followed by post-hydrothermal synthesis. The synthesized NPs were subjected to x-ray diffraction, Scanning Electron Microscopy, Energy Dispersive x-ray, Ultraviolet-visible, and Fluorimetry characterization techniques. The effect of ZrO2 NPs on absorption and emission spectra of 1,10-phen has been investigated through spectroscopic technique. The excitation and emission wavelengths of 1,10-phen are observed to be 280 and 363 nm, respectively. Temperature studies to differentiate between static and dynamic quenching have been done through the Stern–Volmer plot. The type of fluorescence quenching mechanism is found to be collisional quenching. A study of the Forster resonance energy transfer theory on 1,10-phen was carried out with metal oxide ions. There is a considerable energy transfer between 1,10-phen and metal oxide ions. The present investigation can be aided in various applications, such as fluorescent biosensors and medical diagnosis.
Generation of Ultrafast Attosecond Magnetic Field from Ne Dimer in Circularly Polarized Laser Pulses
Authors: Yan 闫 Shujuan 淑娟 , Xu 徐 Qingyun 清芸 , Hao 郝 Xinyu 欣宇 , Guo 郭 Ying 颖 , Guo 郭 Jing 静
Published: September 2023

By numerically solving time-dependent Schrödinger equations, we investigate the generation of electron currents, ultrafast magnetic fields and photoelectron momentum distributions (PMD) when circularly polarized laser pulses interact with a Ne dimer in the charge migration (CM) process. By adjusting the laser wavelength, we consider two cases: (i) coherent resonance excitation (λ = 76 nm) and (ii) direct ionization (λ = 38 nm). The results show that the current and magnetic field generated by the Ne dimer under resonance excitation are stronger than under direct ionization. This phenomenon is due to the quantum interference between the initial state 2pσ
g and the excited state 3sσ
g under resonance excitation, so the CM efficiency of the dimer can be improved and the strength of the PMD under different ionization conditions is opposite to the strength of the electron current and induced magnetic field. In addition, we also find that both 2pπ
g and 2pπ
u have coherent resonance excitation with 3sσ
g state and generate periodic oscillating currents for the Ne dimer. The study of the dynamics of the Ne dimer under different ionization conditions lays a foundation for research of ultrafast magnetism in complex molecular systems.
Giant Nonlinear Optical Response in Topological Semimetal Molybdenum Phosphide
Authors: Hu 胡 Kai 凯 , Qin 秦 Yujie 羽婕 , Cheng 程 Liang 亮 , Shi 石 Youguo 友国 , Qi 齐 Jingbo 静波
Published: September 2023

Nonlinear optical properties are investigated using the static and time-resolved second harmonic generation in the topological material molybdenum phosphide (MoP) with three-component fermions. Giant second harmonic generation signals are detected and the derived χ
(2) value is larger than that of the typical electro–optic material. Upon optical excitation, no photoinduced change of the symmetry is detected in MoP, which is quite different from previous observations in several other topological materials.
Reduced-order autodifferentiable ensemble Kalman filters
Authors: Chen Yuming , Sanz-Alonso Daniel , Willett Rebecca
Published: October 2023

This paper introduces a computational framework to reconstruct and forecast a partially observed state that evolves according to an unknown or expensive-to-simulate dynamical system. Our reduced-order autodifferentiable ensemble Kalman filters (ROAD-EnKFs) learn a latent low-dimensional surrogate model for the dynamics and a decoder that maps from the latent space to the state space. The learned dynamics and decoder are then used within an EnKF to reconstruct and forecast the state. Numerical experiments show that if the state dynamics exhibit a hidden low-dimensional structure, ROAD-EnKFs achieve higher accuracy at lower computational cost compared to existing methods. If such structure is not expressed in the latent state dynamics, ROAD-EnKFs achieve similar accuracy at lower cost, making them a promising approach for surrogate state reconstruction and forecasting.
Hadron transverse momentum distributions in the Tsallis statistics with escort probabilities
Authors: Parvan A S
Published: September 2023

The exact and approximate hadron transverse momentum distributions for the Fermi–Dirac, Bose–Einstein and Maxwell-Boltzmann statistics of particles in the framework of the Tsallis statistics with escort probabilities (the Tsallis-3 statistics) have been derived. The classical and quantum transverse momentum distributions in the zeroth term approximation and the quantum transverse momentum distributions in the factorization approximation introduced in the zeroth term approximation were found. The transverse momentum distributions in the zeroth term approximation and in the factorization approximation of the zeroth term approximation are the same in the Tsallis-3, Tsallis-2 and q-dual statistics. The well-known classical phenomenological Tsallis distribution exactly coincides with the classical transverse momentum distribution of the Tsallis-3 statistics in the zeroth term approximation for which the entropy of the system is zero in the whole range of state variables. However, the quantum phenomenological Tsallis distribution does not coincide with either the exact or approximate transverse momentum distributions of the Tsallis-3 statistics. The exact Tsallis-3 classical distribution and the classical phenomenological Tsallis distribution were applied to describe the experimental spectra of the charged pions produced in the proton-proton collisions at high energies. The values of the parameters (T, q) for both these model distributions differ in the whole energy range. Thus, the classical phenomenological Tsallis distribution is an unsatisfactory approximation for the exact classical transverse momentum distribution of the Tsallis-3 statistics.
Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions
Authors: Birky Donovan , Garbrecht Karl , Emery John , Alleman Coleman , Bomarito Geoffrey , Hochhalter Jacob
Published: September 2023

To generate material models with fewer limiting assumptions while maintaining closed-form, interpretable solutions, we propose using genetic programming based symbolic regression (GPSR), a machine learning (ML) approach that describes data using free-form symbolic expressions. To maximize interpretability, we start from an analytical, derived material model, the Gurson model for porous ductile metals, and systematically relax inherent assumptions made in its derivation to understand each assumption’s contribution to the GPSR model forms. We incorporate transfer learning methods into the GPSR training process to increase GPSR efficiency and generate models that abide by known mechanics of the system. The results show that regularizing the GPSR fitness function is critical for generating physically valid models and illustrate how GPSR allows a high level of interpretability compared with other ML approaches. The method of systematic assumption relaxation allows the generation of models that address limiting assumptions found in the Gurson model, and the symbolic forms allow conjecture of decreased material strength due to void interaction and non-symmetric void shapes.
Measurement of the full wave field on a shell using a single-point laser Doppler vibrometer
Authors: Li Chunlin , Xu Shaohang , Liu Yongquan
Published: October 2023

To experimentally measure the complicated vibration and wave characteristics of a shell, a 3D scanning laser Doppler vibrometer is a competent but costly instrument due to the requirement of exactly aligning each point when scanning the shell. Here we propose a simplified measuring method just by utilizing a single-point laser vibrometer fixed on a motorized positioning system. The clamp can be rotated to adjust the incident angles and translated to capture the whole tested region. During each test in a specific incident angle, the signals are interpolated to generate a continuous wave field in both the time domain and the frequency domain, eliminating the need for alignment. The in-plane and out-of-plane wave fields are obtained from the measured 3D signal using the projection relationship, and then verified both experimentally and numerically. Furthermore, we show that the present method can be used to test complex wave fields, such as the scattering field by obstacles on a cylindrical shell. The present work may stimulate systematically experimental studies on the wave propagation and vibration on shells.
Image encryption scheme based on optical chaos and DNA Rubik’s cube algorithm
Authors: Chen Wei-Hao , Zhou Xue-Fang , Zheng Ning , Li Min-Jun , Hu Miao
Published: September 2023

In order to improve the complexity of optical chaotic sequence output and the encryption efficiency of bit plane encryption, an image encryption algorithm based on optical chaos and DNA Rubik’s cube scrambling is proposed. An external disturbance structure of light injection is proposed to improve the complexity of the chaotic sequence of light output from the slave laser by the external disturbance generated by the mutual injection between the driving laser and the main laser. Meanwhile, in the image algorithm, in addition to Rubik’s cube scrambling at the pixel level, this paper proposes a bit plane encryption method based on DNA plane Rubik’s cube scrambling, which reduces the amount of encrypted data and further improves the security of image encryption by using encryption selection of different DNA encoding modes. The scrambled images are diffused by DNA calculation and optical chaos sequence at the bit-level and pixel level respectively. Through the quantitative analysis of the security simulation of the proposed algorithm, the results show that the algorithm guarantees a certain encryption efficiency under the condition of good security, the key space is 1064, the information entropy of each test ciphertext image is close to the theoretical maximum, and the test indexes of plaintext sensitivity and key sensitivity are close to ideal values. For differential attacks, chosen plaintext attacks, known plaintext attacks, exhaustive attacks, cropping attacks, and noise attacks have good robustness.
Space-resolved line shape model for sputtered atoms of finite-size targets
Authors: Sackers M , Marchuk O , Ertmer S , Brezinsek S , Kreter A
Published: September 2023

High-resolution emission spectroscopy provides valuable information on the physical sputtering process during plasma-wall interaction. Up to now, analyzing the observed spectral lines during sputtering did not account for the finite size of the targets. It becomes crucial if the size of the target becomes comparable with the distance the sputtered atoms travel before emitting the photons. So, for example, the generally used standard emission model based on an infinite target or the point source approximation breaks for observations using two lines of sight: parallel and perpendicular to the normal of the target. It is impossible to achieve consistent results for energy and angular distribution of sputtered atoms. The new space-resolved emission model for finite-size targets developed in this work removes this gap. It incorporates the space-velocity transformation for the distribution function and includes the finite lifetime of excited states. The model was validated using emission spectra of sputtered atoms from a polycrystalline tungsten sample bombarded by monoenergetic Ar+ with kinetic energies of 100 eV to 140 eV at normal incidence in the linear plasma device PSI-2. Using the new model enables the simultaneous fitting of the line shapes of sputtered tungsten for both observation angles. The optimization process is performed using the standard Thompson distribution by separating the energy-dependent parameter and the angular distribution.
Polarization factors and their effects on the rotational gyromagnetic ratio
Authors: Tabar E , Kuliev A A , Yakut H , Hoşgör G , Kemah E
Published: September 2023

The effect of the polarizations on the collective gyromagnetic ratio (g

R
) has been investigated in detail using the Rotational Invariant Quasiparticle Phonon Nuclear Model (RI-QPNM). The model includes an axially symmetric mean-field potential, monopole pairing, spin-dependent residual interactions, and the restoration forces determined according to Pyatov’s prescription for rotational invariance. The restoration of the rotational symmetry gives a solution at the zero energy associated with the rotational branch of nucleonic motion, allowing us to obtain the g

R
-factors of the core. The remaining solutions lead to the appearance of configuration mixing in the excitation spectrum of the odd-mass deformed nucleus. The configuration mixing quenches both spin and angular momentum matrix elements and affects the contribution of the odd particle to the g

R
. It has been demonstrated that the polarization factors associated with the ΔK = 1 matrix elements are essential to achieve quantitative agreement with the experimental data. It has also been shown that the general assumption for core polarization, i.e.,

g

s

e
f
f

≈
0.6

g

s

f
r
e
e

,

is insufficient to explain the experimental data.
Multilayer neural networks for studying three-dimensional flow of non-Newtonian fluid flow with the impact of magnetic dipole and gyrotactic microorganisms
Authors: Madhu J , Baili Jamel , Kumar R Naveen , Prasannakumara B C , Gowda R J Punith
Published: September 2023

The current paper explores the three-dimensional flow of an Oldroyd-B liquid with the impact of a magnetic dipole that occurred by stretching a flat surface placed in the plane with a linear velocity variation in two directions containing motile gyrotactic microorganisms. Using proper similarity transformations, the governing equations are reduced into nonlinear coupled ordinary differential equations (ODEs). The ODEs are then solved using Runge–Kutta-Fehlberg (RKF) method. The training, testing, and validation processes are carried out in parallel to adapt neural networks and calculate an approximate solution for the considered model. This helps to reduce the mean square error (MSE) function by Levenberg–Marquardt backpropagation. The efficiency of the suggested backpropagated neural networks methodology has been demonstrated by utilizing outcomes such as MSE, error histograms, correlation and regression. Results reveal that the heat transport augments for increased Biot number values. The mass transport declines for improved chemical reaction rate parameter values. A higher Peclet number will result in a lower motile diffusivity and result in a decline in the micro-organism’s density profile. For the least value of Mu and gradient, better convergence of the findings can be achieved with better network testing and training.
On novel topological characteristics of graphene
Authors: Ediz Süleyman
Published: September 2023

Molecular topological indices are quantitative measurements that only take into account the topology of a compound’s molecular graph, disregarding any knowledge of the atom locations or chemical connections. An allotrope of carbon called graphene is composed of a single layer of atoms set up in a hexagonal lattice nanostructure. A single layer of carbon atoms organized in a honeycomb pattern make up the two-dimensional substance known as graphene. Graphene possesses significant inherent qualities like strong strength and great thermal and electrical conductivity. It is a sustainable substance with practically countless eco-friendly applications. In this study, we calculate the R molecular topological indices, S molecular topological indices, and Van molecular topological indices of graphene structure, taking into account all conceivable combinations of the number of rows and hexagons. There are high correlations between R, S Van index values and neighbourhood-based entropy values of graphene. This shows that these new indices can be used in QSPR/QSAR studies in chemistry and physics.