bluuebunny/crossref_metadata_2025 huggingface dataset:
A near X-point charge exchange neutral spectroscopy (CENS) system for DIII-D
Authors: Haskey S. R. , Chrystal C. , Angulo A. , Bortolon A. , Wolfe E. , Linsenmayer E. , Marini C. , Scotti F. , Agustin K.
Published: September 2024

A 16 channel spectroscopy system has been installed on DIII-D to provide information about the energy distribution of the atomic neutrals using the Doppler shift and broadening of passive Balmer-α emission. The lines of sight are dominantly in the toroidal direction, with tangencies near the lowest point on closed magnetic flux surfaces moving from the lower divertor upward into the confined plasma. This allows the system to provide details of the neutrals as they undergo various atomic physics processes while traveling upward from the lower divertor. The spectrally resolved measurements provide several advantages that complement typical optical filter based measurements of hydrogenic spectral lines. These include more direct measurements of the neutrals that fuel deeper in the plasma and capturing neutral velocity distribution information via the Doppler broadened and shifted line. In addition, the spectral separation of higher energy “thermal” neutrals and bright cold emission from the scrape-off layer allows for a more straightforward calculation of the underlying neutral densities based on the emission because of the dependence of the thermal emission on confined plasma properties that are approximately flux functions and well measured.
Beyond the mean-field approximation for pair correlations in classical density functional theory: Reference inhomogeneous non-associating monomeric fluids for use with SAFT-VR Mie DFT
Authors: Bernet Thomas , Ravipati Srikanth , Cárdenas Harry , Müller Erich A. , Jackson George
Published: September 2024

A free-energy functional is presented to explicitly take into account pair correlations between molecules in inhomogeneous fluids. The framework of classical density functional theory (DFT) is used to describe the variation in the density of molecules interacting through a Mie (generalized Lennard-Jones) potential. Grand Canonical Monte Carlo simulations are performed for the systems to validate the new functional. The statistical associating fluid theory developed for Mie fluids (SAFT-VR Mie) is selected as a reference for the homogeneous bulk limit of the DFT and is applied here to systems of spherical non-associating particles. The importance of a correct description of the pair correlations for a reliable representation of the free energy in the development of the equation of state is duly noted. Following the Barker–Henderson high-temperature expansion, an analogous formulation is proposed from the general DFT formalism to develop an inhomogeneous equivalent of the SAFT-VR Mie free energy as a functional of the one-body density. In order to make use of this new functional in adsorption studies, a non-local version of the DFT is considered, with specific weighted densities describing the effects of neighboring molecules. The computation of these quantities is possible in three-dimensional space for any pore geometry with repulsive or attractive walls. We showcase examples to validate the new functional, revealing a very good agreement with molecular simulation. The new SAFT-DFT approach is well-adapted to describe realistic complex fluids.
Toward the improvement of vibronic spectra and non-radiative rate constants using the vertical Hessian method
Authors: Böhmer Tobias , Kleinschmidt Martin , Marian Christel M.
Published: September 2024

For the computation of vibrationally resolved electronic spectra, various approaches can be employed. Adiabatic approaches simulate vibronic transitions using harmonic potentials of the initial and final states, while vertical approaches extrapolate the final state potential from the gradients and Hessian at the Franck–Condon point, avoiding a full exploration of the potential energy surface of the final state. Our implementation of the vertical Hessian (VH) method has been validated with a benchmark set of four small molecules, each presenting unique challenges, such as complex topologies, problematic low-frequency vibrations, or significant geometrical changes upon electronic excitation. We assess the quality of both adiabatic and vertical approaches for simulating vibronic transitions. For two types of donor–acceptor compounds with promising thermally activated delayed fluorescence properties, our computations confirm that the vertical approaches outperform the adiabatic ones. The VH method significantly reduces computational costs and yields meaningful emission spectra, where adiabatic models fail. More importantly, we pioneer the use of the VH method for the computation of rate constants for non-radiative processes, such as intersystem crossing and reverse intersystem crossing along a relaxed interpolated pathway of a donor–acceptor compound. This study highlights the potential of the VH method to advance computational vibronic spectroscopy by providing meaningful simulations of intricate decay pathway mechanisms in complex molecular systems.
Open-path detection of organic vapors via quantum infrared spectroscopy
Authors: Neves Simon , Kartiyasa Adimulya , Ghosh Shayantani , Gaulier Geoffrey , La Volpe Luca , Wolf Jean-Pierre
Published: September 2024

In recent years, quantum Fourier transform infrared (QFTIR) spectroscopy has emerged as an alternative to conventional absorption spectroscopy in the mid-infrared region of the spectrum. By harnessing induced coherence and spectral correlations of photon pairs in a nonlinear Michelson interferometer, this technique offers promising potential for the practical detection of organic gases. However, little research was conducted to bring QFTIR spectrometers closer to domestic or in-field usage. In this work, we present the first use of a QFTIR spectrometer for open-path detection of multiple interfering organic gases in ambient air. We built a nonlinear Michelson interferometer with 1.7 m-long arms to increase the absorption length, coupled with analysis techniques from classical differential absorption spectroscopy used for gas-traces detection. We thus characterize our spectrometer’s sensitivity to acetone, methanol, and ethanol vapors and demonstrate the accurate identification of mixtures of these gases released in ambient air. We show this characteristic is preserved over time by performing a measurement overnight and tracking the evolution of different gases’ average concentrations. These results constitute the first use-case of a QFTIR spectrometer as a detector of organic gases and, thus, represent an important milestone toward the development of such detectors in practical situations.
Numerical simulation of compositional flow in shale gas-condensate reservoirs using generic projection-based embedded discrete fracture model
Authors: Luo Chenjie , Rao Xiang , He Xupeng
Published: September 2024

Current commercial and in-house numerical simulators often employ discrete fracture models (DFM) and embedded discrete fracture models (EDFM) for flow simulation in fractured reservoirs. However, a generic projection-based embedded discrete fracture model (pEDFM), which outperforms both DFM and EDFM in any flow scenario, has not yet been integrated into these simulators. In this paper, we introduce a pioneering development of a novel numerical simulation approach specifically tailored for generic pEDFM, designed to enhance gas injection energy in shale gas-condensate reservoirs. This method is the first of its kind to seamlessly integrate pEDFM with a widely used commercial simulator, Computer Modeling Group. By doing so, we ensure not only the practical applicability of the generic pEDFM simulation in the field but also address the challenges associated with developing additional high-performance nonlinear solvers. Three numerical examples demonstrate the advantages of this novel method: compared to DFM, it does not require the generation of grids that match the morphology of the fracture network, thereby reducing computational costs and convergence difficulties; compared to EDFM, it can simulate with much higher accuracy the impact of high- and low-conductivity fractures on compositional flow; and compared to local grid refinement, it can handle more complex fracture patterns. Theoretically, this method is the optimal numerical simulation tool in terms of comprehensive computational performance for research on gas injection energy supplementation in fractured gas-condensate reservoirs.
Lunar heat flow from the observation of Chinese Chang’E 2 and LRO diviner radiometers
Authors: Zhang Dan , Li Cui
Published: September 2024

Lunar heat flow within 75°N to 65°S and 60°W to 100°E regions is retrieved from microwave brightness temperature observed by Chang’E-2 (CE-2) Lunar Microwave Radiometers and infrared brightness temperature observed by Lunar Reconnaissance Orbiter (LRO) Diviner Radiometers. The product of the regolith’s thermal conductivity and vertical temperature gradient yields the lunar heat flow. The vertical temperature gradient is calculated by a new temperature profile, the unknown parameters of which are determined from CE-2 microwave brightness temperature using a multi-layered lunar surface microwave brightness temperature model. The boundary condition of the temperature profile is determined by the LRO infrared brightness temperature. The measured heat flow at the Apollo 15 landing site is chosen as a calibration reference point in the retrieval process. The retrieved lunar heat flow within 75°N to 65°S and 60°W to 100°E regions ranged from 0.8 to 69.2 mW/m2. According to the retrieved results, lunar heat flow in the highlands is higher than the maria. The highest heat flux within 75°N to 65°S and 60°W to 100°E regions on the Moon are located toward the eastern highlands with an averaged heat flow value of 35.8 mW/m2, and the lowest heat flux is basically located in the typical maria such as Oceans Procellarum, Mare Imbrium, and Mare Serenitatis with an averaged heat flow value of 18.5 mW/m2.
Nanoscale subsurface imaging by non-steady-state electron beam-driven scanning thermoelectric capacitance microscopy
Authors: Xu Kunqi , Zeng Huarong , Zhao Kunyu , Yang Weiwei , Shi Xun , Chen Lidong
Published: September 2024

Nanoscale subsurface characterization technologies based on the scanning electron microscope platform offer incomparable advantages of nondestructiveness and penetration depths up to the micrometer scale. However, the electron beam can serve not just as a mechanical/electrical excitation source but also as an excellent nanoscale thermal excitation source, which can facilitate the development of nanoscale subsurface imaging methods based on the Seebeck effect in semiconducting materials. In this work, a subsurface nondestructive imaging technology, scanning thermoelectric capacitance microscopy (STeCM), was developed based on the interaction between a non-steady-state electron beam and semiconducting materials, exploiting the Seebeck effect. In STeCM, a square wave-modulated hot electron beam with huge kinetic energy excites a “thermal wave” in the subsurface local region of the semiconducting sample. The heated local region, acting as a thermoelectric capacitor, undergoes cyclic charging and discharging, leading to the generation of periodic current due to non-equilibrium carrier migration. The second-order harmonic component of this current is demodulated to visualize embedded local thermal/thermoelectric inhomogeneities. Amazingly, for STeCM sample, only a smooth or polished surface is required, eliminating the need for any microfabrication, which will effectively decrease the configuration difficulty in the experiment. STeCM offers an alternative subsurface nondestructive imaging technology for more efficient, simple, and robust characterization.
Imaging nanoscale molecular binding in functionalized graphene via tip-enhanced Raman spectroscopy
Authors: You Xiao , Huang Chiung-Wei , Vinodgopal Kizhanipuram , Atkin Joanna M.
Published: September 2024

Surface functionalization of low-dimensional nanomaterials offers a means to tailor their optoelectronic and chemical characteristics. However, functionalization reactions are sensitive to the inherent surface features of nanomaterials, such as defects, grain boundaries, and edges. Conventional optical characterization methods, such as Raman spectroscopy, have limited sensitivity and spatial resolution and, therefore, struggle to visualize reaction sites and chemical species. Here, we demonstrate the capability of spatially and chemically sensitive tip-enhanced Raman spectroscopy imaging to map the distribution of molecules in covalently functionalized graphene. Hyperspectral vertex component analysis and density functional theory are necessary to interpret the nature of binding sites and extract information from the spatially and spectrally heterogeneous datasets. Our results clarify the origin of heterogeneous surface functionalization, resolving preferential binding at edges and defects. This work demonstrates the potential of nanospectroscopic tools combined with unsupervised learning to characterize complex, partially ordered optoelectronic nanomaterials.
Semiclassical dynamics in Wigner phase space I: Adiabatic hybrid Wigner dynamics
Authors: Malpathak Shreyas , Ananth Nandini
Published: September 2024

The Wigner phase space formulation of quantum mechanics is a complete framework for quantum dynamic calculations that elegantly highlights connections with classical dynamics. In this series of two articles, building upon previous efforts, we derive the full hierarchy of approximate semiclassical (SC) dynamic methods for adiabatic and non-adiabatic problems in Wigner phase space. In Paper I, focusing on adiabatic single surface processes, we derive the well-known double Herman–Kluk (DHK) approximation for real-time correlation functions in Wigner phase space and connect it to the linearized SC (LSC) approximation through a stationary phase approximation. We exploit this relationship to introduce a new hybrid SC method, termed Adiabatic Hybrid Wigner Dynamics (AHWD) that allows for a few important “system” degrees of freedom (dofs) to be treated at the DHK level, while treating the rest of the dofs (the “bath”) at the LSC level. AHWD is shown to accurately capture quantum interference effects in models of coupled oscillators and the decoherence of vibrational probability density of a model I2 Morse oscillator coupled to an Ohmic thermal bath. We show that AHWD significantly mitigates the sign problem and employs reduced dimensional prefactors bringing calculations of complex system–bath problems within the reach of SC methods. Paper II focuses on extending this hybrid SC dynamics to nonadiabatic processes.
Mechanistic analysis of droplets blocked at junctions of serial wedge pattern
Authors: Zhao Denghui , Guo Yali , Guo Zhenglong , Bao Minle , Gong Luyuan , Shen Shengqiang
Published: September 2024

Serial wedge pattern has garnered significant interest for its potential applications in rapid and long-distance liquid transport. However, the occurrence of droplets being blocked at junctions of the serial wedge pattern poses a critical challenge to droplet transport. In this paper, the blocking of droplets is introduced in detail, and the condition of the blocking is systematically investigated. The threshold of blocking is quantitatively represented by the width difference between the wide and narrow ends of wedge (ld). Pinning resistance encountered by droplets when detaching from junctions is a primary cause of blocking. The pinning resistance leads to the droplet tails being torn off. It has been observed that ld plays a crucial role in ensuring smooth droplet transport on the serial wedge pattern and preventing blocking. Larger volume of droplets negatively influences passage by reducing the transport velocity. Conversely, increasing the volume of droplets helps restrain the torn-off tail. Optimizing the curvature at junctions mitigates blocking by not only increasing transport velocity but also decreasing the volume of the torn-off tail. A systematic understanding of the mechanism of blocking can significantly advance the practicality of pumpless droplet transport on the serial wedge pattern.
Density-gradient-driven drift waves in the solar corona
Authors: Brchnelova M. , Pueschel M. J. , Poedts S.
Published: September 2024

It has been suggested that under solar coronal conditions, drift waves may contribute to coronal heating. Specific properties of the drift waves to be expected in the solar corona have, however, not yet been determined using more advanced numerical models. We investigate the linear properties of density-gradient-driven drift waves in the solar coronal plasma using gyrokinetic ion–electron simulations with the gyrokinetic code Gene, solving the Vlasov–Maxwell equations in five dimensions assuming a simple slab geometry. We determine the frequencies and growth rates of the coronal density gradient-driven drift waves with changing plasma parameters, such as the electron β, the density gradient, the magnetic shear, and additional temperature gradients. To investigate the influence of the finite Larmor radius effect on the growth and structure of the modes, we also compare the gyrokinetic simulation results to those obtained from drift-kinetics. In most of the investigated conditions, the drift wave has positive growth rates that increase with increasing density gradient and decreasing β. In the case of increasing magnetic shear, we find that from a certain point, the growth rate reaches a plateau. Depending on the considered reference environment, the frequencies and growth rates of these waves lie on the order of 0.1 mHz–1 Hz. These values correspond to the observed solar wind density fluctuations near the Sun detected by WISPR, currently of unexplained origin. As a next step, nonlinear simulations are required to determine the expected fluctuation amplitudes and the plasma heating resulting from this mechanism.
Oligoyne bridges enable strong through-bond coupling and efficient triplet transfer from CdSe QD trap excitons for photon upconversion
Authors: Miyashita Tsumugi , He Sheng , Jaimes Paulina , Kaledin Alexey L. , Fumanal Maria , Lian Tianquan , Lee Tang Ming
Published: September 2024

Polyyne bridges have attracted extensive interest as molecular wires due to their shallow distance dependence during charge transfer. Here, we investigate whether triplet energy transfer from cadmium selenide (CdSe) quantum dots (QDs) to anthracene acceptors benefits from the high conductance associated with polyyne bridges, especially from the potential cumulene character in their excited states. Introducing π-electron rich oligoyne bridges between the surface-bound anthracene-based transmitter ligands, we explore the triplet energy transfer rate between the CdSe QDs and anthracene core. Our femtosecond transient absorption results reveal that a rate constant damping coefficient of β is 0.118 ± 0.011 Å−1, attributed to a through-bond coupling mechanism facilitated by conjugation among the anthracene core, the oligoyne bridges, and the COO⊖ anchoring group. In addition, oligoyne bridges lower the T1 energy level of the anthracene-based transmitters, enabling efficient triplet energy transfer from trapped excitons in CdSe QDs. Density-functional theory calculations suggest a slight cumulene character in these oligoyne bridges during triplet energy transfer, with diminished bond length alternation. This work demonstrates the potential of oligoyne bridges in mediating long-distance energy transfer.
Numerical simulation of spray cooling heat transfer evolution based on experimental data
Authors: Yang Xin , Shen Feng , Wang Jia , Wu Di , Duan Longsheng , Duan Li , Kang Qi
Published: September 2024

Spray cooling is an effective solution for high heat flux dissipation challenges. Accurate prediction of heat transfer efficiency by numerical simulation can reduce the cost of spray cooling in engineering applications. To improve the accuracy of numerical simulation, this study develops a mathematical model for droplet collision and heat transfer response based on experimental data. In spray cooling experiments, droplets are sprayed onto a 200 °C aluminum alloy thermal wall using an atomizing nozzle, temperature is monitored, and the curve of heat flux variation during cooling is estimated from temperature data. Analysis of high-speed photography results provides the droplet diameter, velocity, and spatial distribution. We discover that the average Weber number of droplets, We, has a power-law relationship with the volumetric flow rate, Q, as We ∼ Q1.55. The velocity and position of spray droplets approximately follow a normal distribution, while the diameter follows a Log-normal distribution. By analyzing the relation between heat flux and spray distribution, an experimental-data-based model, named Droplet Collision-Associated Heat Transfer Model, is designed. Integrating this experimental-data-based model with the discrete phase model (DPM), the heat transfer evolution process in spray cooling is simulated with high reliability. Particles sources are generated based on the experimentally obtained droplet parameter probability distributions, DPM is used to capture the trajectories of droplets, and the droplet impact heat transfer correlation model calculates the thermal response of the wall. Compared with experimental results, the simulation error is only 7.49%. Simulation results indicate that spray cooling at high flow rates has better temperature uniformity.
Numerical simulation of unsteady single-stage transonic axial compressor flow
Authors: Song Tingjian , Xiao Zuoli
Published: September 2024

The steady and unsteady flow properties of the National Aeronautics and Space Administration (NASA) single-stage transonic compressor stage 35 are numerically investigated through the Reynolds-averaged Navier–Stokes (RANS) simulation method. The main purpose of the present paper is twofold. One is to validate the capability of the Spalart–Allmaras (S–A)-Helicity-γ model in unsteady RANS (URANS) simulation for rotor–stator interaction of a whole-stage compressor, and another is to figure out the roles played by helicity modification and transition augmentation in improving the performance of traditional S–A model. The results of steady RANS simulation indicate that the S–A model with helicity regulation is more sensitive to vortex structures in the end wall and blade-tip regions, while the inclusion of transitional intermittency factor can help predict the important transition phenomenon in the midspan region. As the back pressure increases, the inaccuracy of flow fields exchange caused by the mixing plane method becomes nonnegligible for the prediction of aerodynamic performance and thermodynamic quantities. Thus, URANS simulation seems to be necessary for more accurate prediction of the flow details of the stator subjected to periodic sweep of the rotor wake. On the suction surface of the stator, a turbulent separation bubble near the leading edge is transported downstream and merges into another separation bubble with much lower turbulence intensity at the trailing edge periodically. The combination of helicity and transition modifications provides advantages over traditional S–A model in describing this process, quite similar to its performance in steady simulations.
A study on liquid film and evaporation characteristics of fuel jet impingement on the scorching wall of evaporation tube for gas turbine
Authors: Peng Jinlou , Fan Weijun , Zhang Rongchun
Published: September 2024

The phenomenon of liquid jet impingement forming a liquid film on a wall has extensive applications in aerospace engineering. A numerical approach to simulate the impingement of fuel jets on the scorching wall inside the evaporation tube of a gas turbine is employed in this work. The effects of the inlet air Reynolds number, the fuel mass flow rate, and the fuel injection angle on the characteristics of evaporation, flow field structure, and film development within the tube are discussed. The results indicate that an optimal inlet air Reynolds number of 49 000 and an optimal injection angle of 30° maximize the evaporation rate to 90.83% and 83.01%, respectively, and that the evaporation rate decreases as the fuel mass flow rate increases. A semiempirical evaporation model of the evaporation tube Evap=e0.2853×Reair,in0.2935× AFR0.6079×α−0.1662 is proposed. Moreover, a valley-shaped low-speed zone, referred to as the retarding effect, is observed inside the tube; its range and intensity are quantitatively described and related to the phenomenon of film separation. As the inlet air Reynolds number increases, the likelihood of film separation and the film surface velocity both increase, delaying the separation point. The fuel mass flow rate has little effect on the film surface velocity, but a decrease in the fuel mass flow rate results in a thinner film, making it more prone to separation. For fuel side injection, as the fuel injection angle increases, the film thickness becomes more uneven, and the influence of the retarding effect behind the jet increases, promoting film separation.
Three-dimensional high-sampling super-resolution reconstruction of swirling flame based on physically consistent diffusion models
Authors: Huang Longzhang , Zheng Chenxu , Chen Yanyu , Xu Wenjiang , Yang Fan
Published: September 2024

Three-dimensional swirling flame flow fields are often limited by factors such as system complexity and operational difficulty, resulting in relatively low achievable spatial resolution in experimental measurements. Providing high-quality visual data is crucial for optimizing the design of combustion chambers. This paper proposes a three-dimensional high-sampling super-resolution reconstruction method based on a physically consistent diffusion model to enhance combustion diagnosis capabilities. When basic diffusion models are used for super-resolution reconstruction, they may introduce artifacts or blurring. This can disrupt the inherent physical connections among flames, adversely affecting the reconstruction of flame details. Therefore, we have introduced a physically consistent encoder designed to process flame swirling data. This encoder allows the model to delve deeper into the intrinsic flow structure of the flame data, capturing flame resolution features across various scales and levels. It improves the accuracy of texture detail reconstruction in areas of intense combustion. During the training process, we have incorporated structural similarity loss into the loss function to assist the model in generating detailed and consistent edge combustion feature within the flame flow structure. These methods ensuring high fidelity and visual quality in the reconstructed flame. With the total voxel number 8× and 64× super-resolution tasks of the three-dimensional temperature fields of the swirling flames, the experimental results have shown that the method not only yields higher peak signal-to-noise ratio (PSNR) values and lower mean absolute error (MAE) compared to the baseline methods but also results in a more realistic visual representation of flame details.
Quantum sparse coding and decoding based on quantum network
Authors: Ji Xun , Liu Qin , Huang Shan , Chen Andi , Wu Shengjun
Published: September 2024

Sparse coding provides a versatile framework for efficiently capturing and representing crucial data (information) concisely, which plays an essential role in various computer science fields, including data compression, feature extraction, and general signal processing. Here, we propose symmetric quantum neural networks for realizing sparse coding and decoding algorithms. Our networks consist of multi-layer, two-level unitary transformations that are naturally suited for optical circuits. Specifically, the two networks we propose can be efficiently trained together or separately via a quantum natural gradient descent algorithm. Utilizing the trained model, we achieve coding and decoding of sparse data including sparse classical data of binary and grayscale images, as well as sparse quantum data that are quantum states in a certain smaller subspace. The results demonstrate an accuracy of 98.77% for image reconstruction and a fidelity of 97.68% for quantum state revivification. Our quantum sparse coding and decoding model offers improved generalization and robustness compared to the classical model, giving insights to further research on quantum advantages in artificial neural networks.
Blocking layer of dark current for Si-based short-wave infrared photodetection
Authors: Yu Liang , Wu Li , Dai Xiyuan , Yang Yanru , Yan Zhongyao , Liu Kaixin , Ma Fengyang , Lu Ming , Sun Jian
Published: September 2024

Effective suppression of dark current is essential for improving the performance of bulk defect-mediated absorption (BDA) photodetectors. Blocked impurity band (BIB) infrared detectors have been developed and utilized from mid-infrared to far-infrared wavelength regions for low noise. In this work, a blocking layer of dark current was applied to a BDA short-wave infrared (SWIR) photodetector, emulating the concept of BIB detectors. ZnO was chosen as the blocking layer to impede the transport of electrons from the bulk defect levels due to its wide bandgap and to allow the photocurrent to remain nearly unaffected by proper positioning of the conduction band minimum. After introducing the ZnO blocking layer, the dark current density of the photodetector was reduced by two orders of magnitude, and the specific detectivity was enhanced by one order of magnitude. The effects of TiO2 and WO3 as blocking layers were also investigated and compared with ZnO. This work offers an effective method for enhancing detectivity in SWIR BDA photodetection by suppressing the dark current efficiently.
A new method for short-term photovoltaic power generation forecast based on ensemble model
Authors: Zhang Yunxiu , Li Bingxian , Han Zhiyin
Published: September 2024

Photovoltaic (PV) power generation is influenced by various factors, including weather conditions, the quality of PV inverters, and the cleanliness of PV modules, with weather conditions having a particularly significant impact on power output. This paper proposes a novel method for PV power generation prediction based on an ensemble forecasting model, aimed at constructing an efficient and stable PV prediction model. Initially, Z-score is employed to filter outliers in the PV data, and Robust STL–bilinear temporal–spectral fusion is introduced for time series feature extraction. Subsequently, an ensemble forecasting model based on bidirectional long short-term memory and extreme gradient boosting is proposed to address the limitations of existing predictive models, which suffer from low robustness and an inability to provide stable forecasts. Furthermore, to mitigate the performance degradation of the prediction model due to manual tuning, a tactics enhanced white shark optimizer is proposed for parameter optimization of the ensemble model. The optimization performance is validated using the IEEE CEC2021 test functions. Finally, the proposed method is tested on PV power generation data from a site in Shandong, China. The results demonstrate that the proposed ensemble forecasting method achieves high accuracy and exhibits strong model stability.
A high-efficiency tunable relativistic magnetron with diffraction output
Authors: Chen Kunpeng , Xu Haodong , Liu Zeyang , Fan Yuwei
Published: September 2024

In this paper, a high-efficiency tunable relativistic magnetron with diffraction output (HTRMDO) is presented and studied numerically. To increase the tuning bandwidth and power efficiency, the outer radius of the resonant cavity and the magnetic field are simultaneously varied. The simulation results show that the HTRMDO has a tuning range between 1.280 and 2.430 GHz, corresponding to a tuning bandwidth of 62.0% with a center frequency of 1.855 GHz. In the tuning range, the maximum power efficiency is 71.9% and the minimum power efficiency is 36.0%, which complies with the 3 dB principle. Moreover, its output mode remains constant as TE31. This is a record tuning bandwidth and power efficiency for the continuously tunable relativistic magnetron.
Single-molecule force spectroscopy reveals intra- and intermolecular interactions of
Caenorhabditis elegans
HMP-1 during mechanotransduction
Authors: Le Shimin , Yu Miao , Fu Chaoyu , Heier Jonathon A. , Martin Sterling , Hardin Jeff , Yan Jie
Published: September 2024

The
Caenorhabditis elegans
HMP-2/HMP-1 complex, akin to the mammalian

β

-catenin-

α

-catenin complex, serves as a critical mechanosensor at cell–cell adherens junctions, transducing tension between HMR-1 (also known as cadherin in mammals) and the actin cytoskeleton. Essential for embryonic development and tissue integrity in
C. elegans
, this complex experiences tension from both internal actomyosin contractility and external mechanical microenvironmental perturbations. While offering a valuable evolutionary comparison to its mammalian counterpart, the impact of tension on the mechanical stability of HMP-1 and HMP-2/HMP-1 interactions remains unexplored. In this study, we directly quantified the mechanical stability of full-length HMP-1 and its force-bearing modulation domains (M1-M3), as well as the HMP-2/HMP-1 interface. Notably, the M1 domain in HMP-1 exhibits significantly higher mechanical stability than its mammalian analog, attributable to interdomain interactions with M2-M3. Introducing salt bridge mutations in the M3 domain weakens the mechanical stability of the M1 domain. Moreover, the intermolecular HMP-2/HMP-1 interface surpasses its mammalian counterpart in mechanical stability, enabling it to support the mechanical activation of the autoinhibited M1 domain for mechanotransduction. Additionally, the phosphomimetic mutation Y69E in HMP-2 weakens the mechanical stability of the HMP-2/HMP-1 interface, compromising the force-transmission molecular linkage and its associated mechanosensing functions. Collectively, these findings provide mechanobiological insights into the
C. elegans
HMP-2/HMP-1 complex, highlighting the impact of salt bridges on mechanical stability in

α

-catenin and demonstrating the evolutionary conservation of the mechanical switch mechanism activating the HMP-1 modulation domain for protein binding at the single-molecule level.
SETD1B mutations confer apoptosis resistance and BCL2 independence in B cell lymphoma
Authors: Portelinha Ana , Wang Shenqiu , Parsa Sara , Jiang Man , Gorelick Alexander N. , Mohanty Sagarajit , Sharma Soumya , de Stanchina Elisa , Berishaj Marjan , Zhao Chunying , Heward James , Aryal Neeraj K. , Tavana Omid , Wen Jiayu , Fitzgibbon Jude , Dogan Ahmet , Younes Anas , Melnick Ari M. , Wendel Hans-Guido
Published: September 2024

The translocation t(14;18) activates BCL2 and is considered the initiating genetic lesion in most follicular lymphomas (FL). Surprisingly, FL patients fail to respond to the BCL2 inhibitor, Venetoclax. We show that mutations and deletions affecting the histone lysine methyltransferase SETD1B (KMT2G) occur in 7% of FLs and 16% of diffuse large B cell lymphomas (DLBCL). Deficiency in SETD1B confers striking resistance to Venetoclax and an experimental MCL-1 inhibitor. SETD1B also acts as a tumor suppressor and cooperates with the loss of KMT2D in lymphoma development in vivo. Consistently, loss of SETD1B in human lymphomas typically coincides with loss of KMT2D. Mechanistically, SETD1B is required for the expression of several proapoptotic BCL2 family proteins. Conversely, inhibitors of the KDM5 histone H3K4 demethylases restore BIM and BIK expression and synergize with Venetoclax in SETD1B-deficient lymphomas. These results establish SETD1B as an epigenetic regulator of cell death and reveal a pharmacological strategy to augment Venetoclax sensitivity in lymphoma.
Research on posture optimization and accuracy compensation technology in robotic side milling
Authors: Song Ci , Liu Zhibing , Wang Xibin , Qiu Tianyang , Liang Zhiqiang , Shen Wenhua , Gao Yuhang , Ma Senjie
Published: September 2024

Weak stiffness and poor posture accuracy are two key problems that need to be sorted out in robotic side milling. Firstly, an index for evaluating the cutting plane stiffness was proposed based on the closeness of uniformly distributed chords between the evaluated ellipse and the ideal circle. A novel comprehensive posture optimization model was constructed by considering the kinematic characteristics and milling stability. To improve the posture accuracy, a full closed-loop compensation system with laser tracker was built. Combined with the analysis of error similarity and reducer backlash, mapping posture error to joint space was regarded as the problem of selecting joint angles under certain constraints, and it was solved by introducing an improved grey wolf optimization algorithm. Experimental results show that the posture error can be less than 0.05° through two compensations. The stiffness index is effective and the machining error can be reduced by around 15% after posture optimization.
Spectral triples and Dixmier trace representations of Gibbs measures: theory and examples
Authors: Cioletti L , Hataishi L Y , Lopes A O , Stadlbauer M
Published: September 2024

In this paper we study spectral triples and non-commutative expectations associated to expanding and weakly expanding maps. In order to do so, we generalise the Perron–Frobenius–Ruelle theorem and obtain a polynomial decay of the operator, which allows to prove differentiability of a dynamically defined ζ-function at its critical parameter. We then generalise Sharp’s construction of spectral triples to this setting and provide criteria when the associated spectral metric is non-degenerate and when the non-commutative expectation of the spectral triple is colinear to the integration with respect to the associated equilibrium state from thermodynamic formalism. Due to our general setting, we are able to simultaneously analyse expanding maps on manifolds or connected fractals, subshifts of finite type as well as the Dyson model from statistical physics, which underlines the unifying character of noncommutative geometry. Furthermore, we derive an explicit representation of the ζ-function associated to a particular class of pathological continuous potentials, giving rise to examples where the representation as a non-commutative expectation via the associated zeta function holds, and others where it does not hold.
Thickness-dependent evolution of magnetization reversal in coupled permalloy nanocaps
Authors: Mary Anija , Thomas Senoy
Published: September 2024

The magnetization reversal mechanisms in permalloy (Py) nanocaps, coupled through an indirect exchange interaction, were investigated using micromagnetic simulations. This indirect exchange interaction can oscillate between ferromagnetic and antiferromagnetic types, depending on the thickness of the metallic interlayer. In ferromagnetically coupled Py nanocaps, coordinated nucleation and annihilation of magnetic vortices were observed. On the other hand, antiferromagnetically coupled caps exhibited a coherent rotation of spins, stabilizing a double onion state at remanence. The study also investigated the impact of nanocap thickness on the magnetization reversal process. As the thickness of the Py cap increased, the magnetization reversal displayed characteristics typical of a weakly coupled system. This shift in magnetization reversal behavior is attributed to the relative decrease in exchange coupling strength between the nanocaps as their thickness increases.
Korn and Poincaré-Korn inequalities: A different perspective
Authors: Di Fratta Giovanni , Solombrino Francesco
Published: September 2024

We present a concise point of view on the first and the second Korn’s inequality for general exponent

p
p

and for a class of domains that includes Lipschitz domains. Our argument is conceptually very simple and, for

p
=
2

p = 2

, uses only the classical Riesz representation theorem in Hilbert spaces. Moreover, the argument for the general exponent

1
>
p
>
∞

1>p>\infty

remains the same, the only change being invoking now the

q
q

-Riesz representation theorem (with

q
q

the harmonic conjugate of

p
p

). We also complement the analysis with elementary derivations of Poincaré-Korn inequalities in bounded and unbounded domains, which are essential tools in showing the coercivity of variational problems of elasticity but also propedeutic to the proof of the first Korn inequality.
Questions about Boij–Söderberg theory
Authors: Erman Daniel , Sam Steven
Published: September 2024

Boij-Söderberg theory focuses on the properties and duality relationship between two types of numerical invariants. One side involves the Betti table of a graded free resolution over the polynomial ring. The other side involves the cohomology table of a coherent sheaf on projective space. We discuss open questions and problems in Boij-Söderberg theory.
Occupational mechanical exposures as risk factor for shoulder osteoarthritis: a systematic review
Authors: Thorsen Ea Helene Korsgaard , Dalbøge Annett , Hovgaard Nicholas , Andersen Johan Hviid , Jahn Alexander
Published: September 2024

Objectives

The aim of this systematic review was to study the association between occupational mechanical exposures and shoulder osteoarthritis (OA).

Methods

A protocol was registered in PROSPERO. Four databases were systematically searched based on PECOS criteria. Outcome was defined as shoulder OA (acromioclavicular (AC) and/or glenohumeral OA) and exposure as occupational mechanical exposures (vibration, upper arm elevation, force, lifting, repetition, and combined mechanical exposures). We included epidemiological studies estimating the prevalence of shoulder OA or the association between occupational mechanical exposures and shoulder OA. Two researchers independently screened articles, performed data extraction, and assessed the risk of bias and level of evidence using GRADE.

Results

A total of 1642 articles were screened, of which 7 met the inclusion criteria. Four studies were assessed as having a high risk of bias, 1 with a moderate risk, and 2 with a low risk. Based on job titles, higher prevalence estimates (2.9% to 61.8%) were found in exposed job groups. For all occupational mechanical exposures, exposure–response relations were found in relation to AC OA. For vibration, the odds ratio (OR) ranged between 1.7 and 3.1 in the highest exposure groups, while the ORs for upper arm-elevation, force, lifting, repetition, and combined mechanical exposures ranged between 0.5 to 2.2, 1.3 to 1.8, 7.3 to 10.3, 2.4, and 2.2 to 2.9. Low or very low level of evidence was found for all exposures.

Conclusions

This systematic review found an indication of an association between occupational mechanical exposures and shoulder OA, especially AC OA. However, the level of evidence varied between low and very low. High-quality studies assessing the association and differentiating between the specific shoulder joints are highly warranted.
Molecular modification of chlorogenic acid via radiolysis with inhibitory effects on NO production
Authors: Jeong Gyeong Han , Lee Hanui , Lee Kyung-Bon , Chung Byung Yeoup , Bai Hyoung-Woo
Published: September 2024

The molecular modification of chlorogenic acid (1) through γ-irradiation resulted in the formation of five new products: chlorogenosins A (2), B (3), C (4), D (5), and E (6) along with known compounds rosmarinosin B (7), protocatechuic acid (8), and protocatechuic aldehyde (9). The structures of the new compounds were elucidated using spectroscopic methods, including one-dimensional and two-dimensional nuclear magnetic resonance, high-resolution electrospray ionization mass spectroscopy, and circular dichroism spectroscopy. The potential anti-inflammatory activities of all the isolated compounds were determined by evaluating their inhibitory effects on the nitric oxide (NO) production in lipopolysaccharide-induced RAW 264.7 macrophages. Notably, compounds 2 and 3, which contained two hydroxymethyl functionalities instead of the trans-olefinic moiety present in the original chlorogenic acid, exhibited stronger inhibitory effects on NO production than that of the original compound. These findings suggest that the predominant chemical changes induced in chlorogenic acid by γ-irradiation may enhance its anti-inflammatory properties.
Investigation of physiological roles of UDP-glycosyltransferase UGT76F2 in auxin homeostasis through the TAA-YUCCA auxin biosynthesis pathway
Authors: Harada Mio , Kubotsu Tomoaki , Agui Takemoto , Dai Xinhua , Zhao Yunde , Kasahara Hiroyuki , Hayashi Ken-ichiro
Published: September 2024

Cellular auxin (indole-3-acetic acid, IAA) levels are coordinately regulated by IAA biosynthesis and inactivation. IAA is synthesized through sequential reactions by two enzymes, TAA1 and YUCCA, in a linear indole-3-pyruvic acid (IPA) pathway. TAA1 converts tryptophan to IPA, and YUCCA catalyzes the oxidative decarboxylation of IPA into IAA. Arabidopsis UDP-glycosyltransferase UGT76F2 (At3g55710) was previously reported to catalyze the glycosylation of IPA and consequently modulate IAA levels. We carefully analyzed the physiological roles of UGT76F2 and its close homolog UGT76F1 (At3g55700) in IAA homeostasis. We generated two independent ugt76f1 ugt76f2 double null Arabidopsis mutants (ugt76f1f2) with a 2.7 kb deletion, along with two independent ugt76f2 single null mutants by CRISPR/Cas9 gene editing technology. Surprisingly, these null mutants exhibited indistinguishable phenotypes from the wild-type seedlings under our laboratory conditions. Our results indicate that UGT76F1 and UGT76F2 do not play important roles in regulating IAA biosynthesis via IPA glycosylation.
MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning
Authors: Huang Zhijian , Fan Ziyu , Shen Siyuan , Wu Min , Deng Lei
Published: September 2024

Motivation

Effective molecular representation is critical in drug development. The complex nature of molecules demands comprehensive multi-view representations, considering 1D, 2D, and 3D aspects, to capture diverse perspectives. Obtaining representations that encompass these varied structures is crucial for a holistic understanding of molecules in drug-related contexts.

Results

In this study, we introduce an innovative multi-view contrastive learning framework for molecular representation, denoted as MolMVC. Initially, we use a Transformer encoder to capture 1D sequence information and a Graph Transformer to encode the intricate 2D and 3D structural details of molecules. Our approach incorporates a novel attention-guided augmentation scheme, leveraging prior knowledge to create positive samples tailored to different molecular data views. To align multi-view molecular positive samples effectively in latent space, we introduce an adaptive multi-view contrastive loss (AMCLoss). In particular, we calculate AMCLoss at various levels within the model to effectively capture the hierarchical nature of the molecular information. Eventually, we pre-train the encoders via minimizing AMCLoss to obtain the molecular representation, which can be used for various down-stream tasks. In our experiments, we evaluate the performance of our MolMVC on multiple tasks, including molecular property prediction (MPP), drug-target binding affinity (DTA) prediction and cancer drug response (CDR) prediction. The results demonstrate that the molecular representation learned by our MolMVC can enhance the predictive accuracy on these tasks and also reduce the computational costs. Furthermore, we showcase MolMVC’s efficacy in drug repositioning across a spectrum of drug-related applications.

Availability and implementation

The code and pre-trained model are publicly available at https://github.com/Hhhzj-7/MolMVC.