bluuebunny/crossref_metadata_2025 huggingface dataset:
Mathematical modeling of tissue porosity effect and non-Newtonian behavior of blood on anomalous effect on blood flow in micro-blood vessels
Authors: Bali Rekha , Tripathi Ragini , Mishra Swati
Published: November 2024

The effect of tissue porosity on anomalous blood flow behavior in micro-blood vessels is investigated in this study. This model includes the effects of tissue porosity on the two-phase flow of blood in narrow tubes. It consists of a core region of erythrocyte suspension with non-Newtonian fluid and a peripheral layer of plasma surrounding the core. The governing partial differential equations are solved using the mathematical and analytical approach. Analytical results for apparent viscosity, bluntness of the velocity profile, and the ratio of capillary hematocrit to discharge hematocrit are presented and discussed through graphs, illustrating the impact of various parameters and their axial variations with diameter of small vessels. The presence of porosity in the surrounding tissue alters flow characteristics, influencing factors such as local hemodynamics and nutrient exchange. This comprehensive approach enhances our understanding of blood flow behavior in microcirculation and informs applications in microvascular tissue engineering, drug delivery, and the treatment of vascular-related disorders.
Experimental investigation of electron-impact reactions in the plasma discharge of a water-vapor Hall thruster
Authors: Shirasu K. , Koizumi H. , Sekine H. , Komurasaki K.
Published: November 2024

The axial distribution of the electron density and temperature in the discharge plasma of a water-vapor Hall thruster is measured by a cylindrical Langmuir probe using a fast-moving system. They are evaluated in two ways; by integrating full trace of the measured electron energy distribution function (EEDF) and by fitting a Maxwellian EEDF to the low-energy part of the measured EEDF. The ion current density for each species produced by electron-impact ionization is estimated using the obtained electron density and temperature. It is revealed that OH+ and H+ can be contained other than H2O+ with non-negligible fractions, causing an additional 20%–25% loss of the anode efficiency estimated by the plume diagnostics. It is also suggested that elastic momentum transfer, electronic excitation, and dissociation to the neutral fragments are more dominant processes than ionization, whereas the electron attachment, rotational excitation and vibrational excitation are minor events among the electron-impact reactions. The subsequent ionization processes from the neutral fragments are also expected to play an important role in determining the effective design and operating parameters for further improvement of the mass utilization efficiency.
Mitigation of hot-electron preheat from the two-plasmon-decay instability using silicon-doped plastic shells in direct-drive implosions on OMEGA
Authors: Churnetski K. , Patel D. , Theobald W. , Betti R. , Cao D. , Ceurvorst L. , Rosenberg M. J. , Solodov A. A. , Stoeckl C. , Regan S. P.
Published: November 2024

Hot electrons generated by the two-plasmon-decay (TPD) instability in laser-direct-drive implosions preheat the fuel and degrade performance. The mitigation of preheat using silicon-doped ablators (i.e., preheat is reduced by a factor of 1.40 ± 0.04) while decreasing the ratio of the laser spot diameter to the target diameter (Rb/Rt) to mitigate cross-beam energy transfer has been demonstrated on the OMEGA laser for quarter-critical laser intensities of 4.1×1014 W/cm2, equivalent to an incident laser intensity of 8.3×1014 W/cm2. The silicon dopant increases the electron temperature of the ablation plasma, which raises the intensity threshold for the onset of the TPD instability. These results show that implosion designs utilizing higher drive intensities can be used to achieve higher shell velocities, which are currently inaccessible with plastic ablators due to excessive preheat.
Multifrequency electrical impedance tomography system based on undersampling combined with a fast digital demodulation algorithm
Authors: Liu Jinzhen , Zhou Yapeng , Xiong Hui , Li Xiaobin , Shi Fangming
Published: November 2024

Multifrequency electrical impedance tomography (MFEIT) has shown great application prospects in the field of biomedical imaging. To realize high-precision multifrequency electrical impedance information acquisition, a high-precision MFEIT system with undersampling combined with a fast digital demodulation algorithm is proposed. The system is integrated with 16 electrodes, and semi-parallel acquisition is used. In addition, a novel multifrequency digital demodulation algorithm is applied to enhance the accuracy of multifrequency excitation signal demodulation and achieve rapid demodulation. This improvement is achieved by analyzing the process of the multifrequency digital demodulation algorithm and combining undersampling with a fast digital demodulation technique. To evaluate the proposed method, a systematic comparative experiment is conducted. The experimental results demonstrate that the demodulation error using the undersampling method is less than 0.7% within the frequency range of 5–500 kHz. In addition, the system achieves a maximum signal-to-noise ratio of 62.92 dB, an average blur radius of 0.953, and an average position error percentage of 9.3%. The results indicate that the MFEIT system constructed based on the above research has good performance and a high signal-to-noise ratio.
Electron cyclotron emission quasi-optical transmission system on the HL-3 tokamak
Authors: Yu X. , Shi Z. B. , Yang Z. C. , Jiang M. , Chen W. , Yu G. Y. , Zhu Y. L. , Deng W. C. , Zhou Y. , Shen Y. Q. , Wen J. , Shi P. W. , Han K. X.
Published: November 2024

A new quasi-optical (QO) Electron Cyclotron Emission (ECE) transmission system has been established on the HL-3 tokamak, which includes a focusing QO mirror combination and a long-distance transmission line. This system was developed to meet the requirements for poloidal spatial resolution and the high signal-to-noise ratio needed for magnetohydrodynamic (MHD) instability studies using ECE on the HL-3. The QO mirror combination was installed inside the vacuum chamber for focusing. Laboratory test results, theoretical calculations, and synthetic ECE simulation results indicate that the Gaussian beam can meet the spatial resolution requirements for the accurate measurement of the MHD instability on the q = 1/2/3 surfaces, corresponding to the poloidal mode numbers m = 3/6/9. This includes good diagnostic poloidal spatial resolution for the important 2/1 and 3/2 modes. At the front end of the transmission line, a high-efficiency mode converter was designed to transition the TE10 mode to the HE11 mode for input into the transmission line, with an insertion loss of less than 1.5 dB. A 30 m long-distance corrugated oversized waveguide was constructed, with transmission losses ranging from 6 to 10 dB in the 60–120 GHz range. Polarization adjustment results show that the polarization offset and geometric spatial polarization angle change consistently, which can provide a reference for polarization adjustment in other complex structured transmission lines. The newly established ECE QO transmission system will provide strong support for future physics research involving ECE on the HL-3.
Contribution of the interfacial oxygen vacancies on the asymmetric switching behaviors of the Al:Hf0.5Zr0.5O2 ferroelectric films
Authors: Liu Xin , Zhao Weidong , Wang Jiawei , Yao Lulu , Ding Man , Cheng Yonghong
Published: November 2024

In this work, we investigated the effects of interfacial oxygen vacancies on the ferroelectric behaviors and switching properties of Al:Hf0.5Zr0.5O2 (Al:HZO) films. Our study employed a Pt/Al:Hf0.5Zr0.5O2/Si structure to form two interfaces with different interfacial oxygen defects. Oxygen vacancies were mainly accumulated at the HZO/Si interface, confirmed by the XPS results. By carefully examining the P–V loops, C–V loops, and the corresponding switching current loops, we found that the domains were clearly divided into two parts, which resulted in the slit-up of the switching current peaks and distorted P–V loops. Further cycling results showed that the wake-up performances had arisen from the biased domains. We further simulated the switching dynamics by using the nucleation limited switching model. Distorted switching kinetics and unsatisfied switching polarization were observed for the initial samples, while the switching dynamics showed the same tendency after waking up. The results elucidate that the influence of interfacial oxygen vacancies is mainly to induce the built-in field at the interface, which may be helpful for the understanding of the switching behaviors of HfO2-based ferroelectric films.
Predictions of the interfacial free energy along the coexistence line from single-state calculations
Authors: Sanchez-Burgos Ignacio , Montero de Hijes Pablo , Sanz Eduardo , Vega Carlos , Espinosa Jorge R.
Published: November 2024

The calculation of the interfacial free energy between two thermodynamic phases is crucial across various fields, including materials science, chemistry, and condensed matter physics. In this study, we apply an existing thermodynamic approach, the Gibbs–Cahn integration method, to determine the interfacial free energy under different coexistence conditions, relying on data from a single-state calculation at specified pressure and temperature. This approach developed by Laird et al. [J. Chem. Phys. 131, 114110 (2009)] reduces the computational demand and enhances efficiency compared to methods that require separate measurements at each thermodynamic state. The integration scheme computes the excess interfacial free energy using unbiased constant volume, temperature, and number of particle simulations (NVT), where the two phases coexist, to provide input for the calculations. We apply this method to the Lennard-Jones and mW water models for liquid–solid interfaces, as well as the Lennard-Jones and TIP4P/2005 models for liquid–vapor interfaces. Our results demonstrate the accuracy and effectiveness of this integration route for estimating the interfacial free energy along a coexistence line.
Interband and intraband transitions, as well as charge mobility in driven two-band model with electron–phonon coupling
Authors: Wang Yu , Dou Wenjie
Published: November 2024

Interband and intraband transitions are fundamental concepts in the study of electronic properties of materials, particularly semiconductors and nanomaterials. These transitions involve the movement of electrons between distinct energy states or bands within a material. In addition, charge mobility is also a critical parameter in materials science and electronics. A thorough understanding of these transitions and mobility is critical for the development and optimization of advanced electronic and optoelectronic devices. In this study, we investigate the influence of external periodic drivings on interband and intraband transitions, as well as charge mobility, within a driven two-band model that includes electron–phonon coupling. These external periodic drivings can include a periodic laser field, a time-varying magnetic or electric field, or an alternating current voltage source. We have developed the Floquet surface hopping and Floquet mean field methods to simulate electronic dynamics under various drivings in both real and reciprocal spaces. Our findings demonstrate that periodic drivings can enhance interband transitions while suppressing intraband transitions. In addition, charge mobility is restrained by these external periodic drivings in the driven two-band model.
Molecular structures of residual solvent in polyacrylonitrile based electrolytes: Implications for conductivity and stability
Authors: Lin Lu , Liu Changhao , Sacci Robert L. , Chen X. Chelsea , Doughty Benjamin
Published: November 2024

Lithium-ion batteries increasingly play significant roles in modern technologies; however, increased energy density also raises concerns about electrolyte safety. Traditional electrolytes that use volatile organic solvents face risks of thermal runaways and fires from electrode shorting. In response, polymer-based solid electrolytes have been developed for replacement. Polyacrylonitrile (PAN) is a promising fire-resistant component for electrolyte fabrication, but its limited solubility necessitates using low-volatility solvents, which are notoriously difficult to remove in subsequent drying processes. Here, we use femtosecond two-dimensional infrared spectroscopy to provide an in-depth understanding of how residual solvent from processing affects the molecular structures and dynamics within a polymer electrolyte. To this end, linear and nonlinear infrared spectroscopies are employed to interrogate the molecular interactions in PAN-based electrolytes containing various contents of N,N-dimethylformamide (DMF). We show that the amount of DMF within the PAN electrolyte affects the Li+ structure. The coordination can proceed through the carbonyl group and/or the amide nitrogen to form antiparallel structures with the nitrile groups of PAN through dipole–dipole interactions. The free motion of DMF is drastically inhibited upon interaction with Li+ and PAN, which decreases the ionic conductivity and potentially affects the stability (resistance toward removal and chemical decomposition). These findings have implications for the design and processing of solid polymer electrolytes.
Oxygen incorporation effects on the structural and thermoelectric properties of copper(I) iodide
Authors: Markwitz Martin , Malone Niall , Back Song Yi , Gobbi Alexander , Hardy Jake , Murmu Peter P. , Mori Takao , Ruck Ben J. , Kennedy John V.
Published: November 2024

Oxygen is a ubiquitous contaminant in thin films grown in high vacuum systems, and it was hypothesized to play an important role in the properties of the p-type conductivity of transparent copper(I) iodide, CuI. We study the ambient properties of CuI deposited at various partial pressures of oxygen gas. Through a variety of experimental techniques, we find that achieving a critical oxygen partial pressure of below p(O2) = 3×10−5 mbar is essential for depositing stoichiometric and conductive CuI thin films. Notably, we relate the commonly reported copper excess to the presence of oxygen within the CuI films. Notably, we relate the commonly reported excess of copper in CuI thin films to to the presence of oxygen. Finally, we infer from transport and optical measurements that the hole transporting properties of sputtered CuI films are dominated by an abundance of VCu defects with an acceptor transition energy of 84±3 meV rather than OI defects with an acceptor transition energy of 175±14 meV.
Understanding long-range opposite charge repulsion in multivalent salt solutions
Authors: Agrawal Nikhil R. , Carraro Carlo , Wang Rui
Published: November 2024

The electrostatic correlations between ions profoundly influence the structure and forces within electrical double layers. Here, we apply the modified Gaussian renormalized fluctuation theory to investigate the counter-intuitive phenomenon of repulsion between two oppositely charged surfaces and discuss its relationship with overcharging. By accurately accounting for the effect of spatially varying ion–ion correlations, we capture these repulsive forces for divalent, trivalent, as well as tetravalent ions, in quantitative agreement with reported simulation results. We show that the opposite-charge repulsion is long-ranged with an effective length scale of a few nanometers. The strength of opposite-charge repulsion increases monotonically with the multivalent salt concentration, in stark contrast with the non-monotonic salt concentration dependence of other ion correlation-driven phenomena, such as overcharging and like-charge attraction. We also elucidate that the origin of the opposite-charge repulsion is the large number of ions attracted to the double layer as a result of ion–ion correlations, leading to higher osmotic pressure and stronger screening of the electrostatic attraction, which results in an overall repulsive force between two oppositely charged surfaces. Furthermore, we demonstrate that there is no causal relationship between opposite-charge repulsion and the overcharging of the surface. Opposite-charge repulsion is accompanied by overcharging at large separation distances but can also occur in normal double layers without overcharging at intermediate separation distances.
Near-nozzle flash-boiling flow of iso-octane, methanol, and ammonia in the engine combustion network spray G injector
Authors: Rachakonda Sampath K. , Goette Daniel , Schmidt David P.
Published: November 2024

Non-carbon and e-fuels such as ammonia and methanol are attractive options for the transportation community's decarbonization efforts. To utilize these highly volatile fuels, their in-nozzle flow and near-nozzle spray behavior must be better understood. The current work uses computational fluid dynamics (CFD) simulations to make a comparison of the internal flow and near-nozzle behavior of methanol, ammonia, and iso-octane injection. The behavior of the near-nozzle spray of these fuels was studied by subjecting them to flash-boiling and subcooled conditions through the Engine Combustion Network's (ECN) eight-hole Spray G injector. Three-dimensional transient CFD simulations were performed using an in-house CFD solver that accounts for thermodynamic non-equilibrium aspects of phase change and needle motion. The conditions for comparing the behavior of methanol and ammonia were inspired by the standard subcooled (Spray G) and flash-boiling (Spray G2) conditions stipulated by ECN using iso-octane as the working fluid. The run conditions for ammonia and methanol injection were chosen to reveal the influence of fuel properties and the challenges posed for high pressure direct injection. Iso-octane was also simulated at an elevated injection temperature, in addition to the ECN's G and G2 conditions, to assess the influence of increased saturation pressure on the ensuing spray. The findings indicate that saturation pressure and the enthalpy of vaporization (hfg) are critical to our understanding of the in-nozzle flow and near-nozzle spray behavior of volatile fuels. The non-dimensional quantity representing the ratio of the saturation pressure to the chamber pressure, Rp, is necessary for describing the spectrum of flash-boiling but not sufficient. A second-order effect is induced due to the influence of the enthalpy of vaporization when sprays are subjected to the same Rp values. This effect of the hfg is required for understanding the extent of vaporization. Additionally, it was also observed that sprays with extremely high values of Rp exhibit a strong underexpanded near-nozzle jet behavior in addition to a bell-shaped morphology coupled with a complete spray collapse.
Three-dimensional effects of a tandem flapping–fixed wing configuration at low Reynolds number
Authors: Li Gang , Wu Jianghao , Zhang Yanlai , Chen Long
Published: November 2024

The flow interaction between the front and rear wings in tandem configuration can lead to superior aerodynamic performance in insects and micro air vehicles. Previous studies have shown that the interaction of a two-dimensional tandem flapping–fixed airfoil configuration can enhance the lift performance of the fixed airfoil at a low Reynolds number. However, it is unclear whether the lift enhancement is maintained in three dimension and the role of the wingtip vortex is not fully understood. In this paper, we numerically studied the three-dimensional flapping–fixed wing configuration. The effect of the aspect ratio is investigated. Results show that the three-dimensional flow interaction enhances the lift generation of the fixed wing through a quasi-two-dimensional strong upwash flow generated by the flapping wing, which increases the effective incoming velocity and the effective angle of attack and strengthens the leading edge vortex of the fixed wing. The upwash flow drops near the wingtip due to the wingtip vortex. Moreover, extra lift enhancement of a low-aspect-ratio fixed wing is induced by a high-aspect-ratio flapping wing, which generates strong upwash flow fully covering the fixed wing in the spanwise direction. The exposure to the strong upwash flow near the wingtip of the fixed wing prevents the sharp reduction in the effective incoming velocity, the effective angle of attack, and the local circulation of the leading edge vortex. Our findings encourage the combination of a high-aspect-ratio flapping wing and a low-aspect-ratio fixed wing in this configuration for the design of micro air vehicles.
Vortex induced vibration prediction through machine learning techniques
Authors: Ijaz A. , Manzoor S.
Published: November 2024

The recent rise of machine learning (ML) has revolutionized many fields since its advent, leading to remarkable advances in data science, medical research, and many engineering fields. The vortex induced vibration problem being a complex amalgamation of fluid dynamics, fluid-structure interaction, and structural vibration fields of engineering, has always been a costly nut to crack experimentally while being a highly time-consuming problem to solve through numerical simulations. The current study is aimed at bridging the gap by the use of recent advances in AI and ML through the application of various recent techniques applied to the same problem for a better prediction of the results. The dataset used for training and testing models was self-generated, validated, published, and hence considered suitable for further research into identification of suitable techniques for the effective and efficient prediction of the vortex-induced vibrations phenomenon. The current study delves into the application of a host of supervised learning techniques, including artificial neural networks (ANNs), support vector machine (SVM), decision trees, ensemble methods, and Gaussian Process Regression (GPR), on the same dataset. The ANN was analyzed using multiple training–testing ratios. Three different variations of decision trees were analyzed i.e., course, medium, and fine. Six different algorithms for SVM were tested including: linear, quadratic, cubic, coarse Gaussian, medium Gaussian, and fine Gaussian. Both bagging and boosting type ensemble methods were also tested while four different algorithms of GPR were examined, namely, exponential, squared exponential, rational quadratic, and Matern 5/2. The results are analyzed on a parametric basis using mean squared error (MSE), root mean squared error (RMSE), R-squared (R2), and mean absolute error primarily. The results show that even a training–testing ratio of 30:70 may provide sufficiently credible predictions although for a ratio of 50:50, the accuracy of predictions shows diminishing returns and hence is a sufficiently high training–testing ratio. Fine decision trees, fine Gaussian SVM, boosting ensemble method, and Matern 5/2 GPR algorithms showed the best results within their own techniques while the GPR techniques provided the best predictions of all the different techniques tested.
On the NH stretch ν1 band of methyleneimine CH2NH
Authors: Nejad A.
Published: November 2024

Over four decades, the 3262.622(2) cm−1 band [Halonen and Duxbury, Chem. Phys. Lett. 118, 246–251 (1985)] of H2C=NH (methyleneimine or methanimine) has been cited as the ν1 NH stretch fundamental. In this article, the assignment is comprehensively reviewed for the first time, concluding that the band should instead be assigned to the CN stretching overtone 2ν4. The analysis of vibrational wavenumbers and transition dipole moments is guided by large basis set coupled-cluster anharmonic frequency calculations. A comparison with the vibrations of its perfluorinated analog (difluoromethanimine, F2C=NH) exemplifies that fc-CCSD(T)/ANO2 VPT2, as expected, is able to provide very accurate vibrational band centers for these semi-rigid molecules. As a by-product of the analysis, a significant reorientation of the ν1 transition dipole moment of methyleneimine by more than 100° away from the NH bond toward the nitrogen lone pair is found. MP2 fails to capture this effect, possibly due to a mild multireference character as suggested by a comparison with CCD, CCSD, and CCSD(T).
Numerical simulation study on fracture propagation of radial borehole fracturing based on discrete lattice method
Authors: Qin Yong , Cui Hongjia , Guo Tiankui , Wang Haiyang , Chen Ming
Published: November 2024

Radial borehole fracturing is a kind of reservoir transformation technology combining radial borehole and hydraulic fracturing. The research on the influencing mechanism and main control factors of fracture propagation in radial borehole fracturing is still incomplete. This paper establishes a three-dimensional fracture propagation model of radial borehole fracturing based on the discrete lattice method, and carries out numerical simulation. The guidance strength (I) was introduced, the larger the value of I, the stronger the ability of radial borehole to guide the targeted propagation of hydraulic fractures. As azimuth of radial borehole increases, the distance of fracture starting deflection becomes smaller and the I decrease. Azimuth ≤45° is conducive to better guide hydraulic fractures in radial borehole; The radius and length of radial borehole are proportional to the I; Smaller radial borehole spacing (<1.5 m) is more conducive to radial borehole guided hydraulic fracture targeted propagation; When horizontal in situ stress difference is large, the stress difference will seriously affect the radial borehole guiding hydraulic fractures; With the increase in elastic modulus, permeability and Poisson's ratio, the I decreases. But the influence of Poisson's ratio is small; Larger displacement is conducive to the propagation of hydraulic fractures along radial borehole direction; The viscosity is about 50 mPa·s, and the radial borehole has the best guidance for hydraulic fractures; the gray correlation analysis results show that the three radial borehole parameters, radius, length, and azimuth, have the strongest correlation with the I.
A comprehensive mesh stiffness model for spur gear considering coupling effective of thermo-elastohydrodynamic lubrication
Authors: Zhou Shihua , Zhang Dongsheng , Zhou Chenhui , Yu Xinhai , Zhou Zichun , Ren Zhaohui
Published: November 2024

Thermal elastohydrodynamic lubrication (TEHL) plays a crucial role in meshing stiffness, friction, wear, vibration, and transmission stability during the gear meshing. Based on the TEHL and Blok theories, a comprehensive meshing stiffness model of spur gear is proposed by combining thermal stiffness, oil film stiffness, and time-varying meshing stiffness, which is closer to the actual working conditions compared with conventional method. The influences of torque, rotational speed, and module on the lubrication performance and meshing characteristics are investigated, and the distributions of oil film pressure, film thickness, tooth surface temperature rise, friction coefficient, and stiffness are obtained. The results reveal that a light torque, large rotational speed, and module can improve loading capacity and lubrication performance, but excessive parameters will increase tooth surface temperature rise and thermal deformation, and reinforce meshing impact, which further increase the tooth surface wear or bonding. Therefore, it can be concluded that the reasonable parameter match is valid in improving gear lubrication characteristics, mitigating meshing impact and improving gear meshing characteristics, and further enhance system stability.
Medium-density amorphous ice unveils shear rate as a new dimension in water’s phase diagram
Authors: de Almeida Ribeiro Ingrid , Dhabal Debdas , Kumar Rajat , Banik Suvo , Sankaranarayanan Subramanian K. R. S. , Molinero Valeria
Published: November 2024

Recent experiments revealed a new amorphous ice phase, medium-density amorphous ice (MDA), formed by ball-milling ice

I
h

at 77 K [Rosu-Finsen
et al.
, Science
379
, 474–478 (2023)]. MDA has density between that of low-density amorphous (LDA) and high-density amorphous (HDA) ices, adding to the complexity of water’s phase diagram, known for its glass polyamorphism and two-state thermodynamics. The nature of MDA and its relation to other amorphous ices and liquid water remain unsolved. Here, we use molecular simulations under controlled pressure and shear rate at 77 K to produce and investigate MDA. We find that MDA formed at constant shear rate is a steady-state nonequilibrium shear-driven amorphous ice (SDA), that can be produced by shearing ice

I
h

, LDA, or HDA. Our results suggest that MDA could be obtained by ball-milling water glasses without crystallization interference. Increasing the shear rate at ambient pressure produces SDAs with densities ranging from LDA to HDA, revealing shear rate as a new thermodynamic variable in the nonequilibrium phase diagram of water. Indeed, shearing provides access to amorphous states inaccessible by controlling pressure and temperature alone. SDAs produced with shearing rates as high as 10
6
s
−1
sample the same region of the potential energy landscape than hyperquenched glasses with identical density, pressure, and temperature. Intriguingly, SDAs obtained by shearing at ~10
8
s
−1
have density, enthalpy, and structure indistinguishable from those of water “instantaneously” quenched from room temperature to 77 K over 10 ps, making them good approximants for the “true glass” of ambient liquid water.
Production of prominence by Mandarin‑speaking EFL
learners
Authors: Hua Congchao
Published: November 2024

This study investigated Mandarin-speaking
English-as-a-foreign-language (EFL) learners’ prominence production in relation
to prominence position, focus type, and proficiency. Eighty Mandarin-speaking
EFL learners and 20 native English speakers read 12 question-answer pairs in
English, with the questions eliciting different prominence patterns (end vs.
non-end) for different focus types (broad vs. narrow). The results revealed that
the phonological aspect (prominence assignment) was influenced by prominence
position, focus type, and proficiency, but the phonetic aspect (phonetic
realization of prominence) was affected only by prominence position.
Phonologically, the learners achieved more native-like performance on end than
non-end prominence, on broad than narrow focus, and their performance improved
with proficiency. Phonetically, they achieved more native-like performance on
end than non-end prominence and produced native-like F0 and intensity, but not
duration. Drawing on these patterns, in teaching priorities should be given to
prominence assignment over phonetic realization, non-end over end prominence,
and narrow over broad focus.
Regulation of NMDAR activation efficiency by environmental factors and subunit composition
Authors: He Miaomiao , Wollmuth Lonnie P.
Published: November 2024

NMDA receptors (NMDAR) convert the major excitatory neurotransmitter glutamate into a synaptic signal. A key question is how efficiently the ion channel opens in response to the rapid exposure to presynaptic glutamate release. Here, we applied glutamate to single channel outside-out patches and measured the successes of channel openings and the latency to first opening to assay the activation efficiency of NMDARs under different physiological conditions and with different human subunit compositions. For GluN1/GluN2A receptors, we find that various factors, including intracellular ATP and GTP, can enhance the efficiency of activation presumably via the intracellular C-terminal domain. Notably, an energy-based internal solution or increasing the time between applications to increase recovery time improved efficiency. However, even under these optimized conditions and with a 1-s glutamate application, there remained around 10–15% inefficiency. Channel activation became more inefficient with brief synaptic-like pulses of glutamate at 2 ms. Of the different NMDAR subunit compositions, GluN2B-containing NMDARs showed the lowest success rate and longest latency to first openings, highlighting that they display the most distinct activation mechanism. In contrast, putative triheteromeric GluN1/GluN2A/GluN2B receptors showed high activation efficiency. Despite the low open probability, NMDARs containing either GluN2C or GluN2D subunits displayed high activation efficiency, nearly comparable with that for GluN2A-containing receptors. These results highlight that activation efficiency in NMDARs can be regulated by environmental surroundings and varies across different subunits.
Lateral size dependence of photoconductivity in TMD networks
Authors: Olaya-Cortes D , Ramos L , Rubio T , Pabon J P , Hernandez Y
Published: November 2024

Photoconductivity is an important feature of semiconductors that finds major attention in the fields of solar cells, hydrogen and oxygen evolution reactions, and photodetectors. This feature involves a change of density of charge carriers induced by light, which is dependent on the generation of light-induced carriers and the recombination of excitons. This phenomenon has been observed in transition metal dichalcogenides (TMDs) since 2010; however, when printing such materials on flexible substrates, they form networks that would exhibit distinct transport characteristics compared to isolated TMDs crystals. In this work, TMD nanosheets are printed by vacuum filtering and their photoconductivity was measured by using a xenon lamp inside an obscure chamber. Molybdenum disulfide-based devices show higher responsivity as compared with tungsten disulfide devices, which is attributed to an increased light absorption and hydroxyl groups attached to the surface of the MoS2 networks that enhance the photoconductivity by increasing the carrier lifetimes. Furthermore, the responsivity of the devices behaves similarly to the conductivity, which is modeled as networks of pairs of nanosheets and junctions through percolative paths. Finally, this is the first report that shows that the response time of the devices increases with lateral size.
MSDFNet: multi-scale detail feature fusion encoder–decoder network for self-supervised monocular thermal image depth estimation
Authors: Kong Lingjun , Zheng Qianhui , Wang Wenju
Published: November 2024

Currently available thermal image depth estimation methods are difficult to efficiently extract fine multi-scale feature information from thermal images and suffer from the problem of blurring details at the edges of the estimated depth map. To address these challenges, this paper proposes MSDFNet, a multi-scale detail feature fusion encoder–decoder network, for self-supervised monocular thermal image depth estimation. The model is based on a channel expansion hourglass residual lightweight feature encoder, which can capture rich and fine-grained multi-scale feature information with low computational effort. MSDFNet utilizes a detail feature weight evaluation decoder to fuse cross-scale features and reevaluate the importance of each feature, thereby emphasizing critical edge information at multiple scales. Additionally, MSDFNet incorporates a depth consistency loss function, which provides self-supervised signals for the detailed features of thermal images and improves the optimization of network performance. The method is applied to the ViViD++ and MS2 datasets and achieves state-of-the-art depth estimation performance compared to existing state-of-the-art algorithms. In the Indoor Dark scenario of the ViViD++ dataset, the Abs Rel, Sq Rel, RMSE, and RMSE log error metric values of MSDFNet are reduced by 6.71%, 11.92%, 9.09%, and 5.73%, respectively, while the accuracy metric values

δ
<

1.25
i

,
i
=
1
,
2
,
3

were improved by 4.18%, 1.13%, and 0.2%, respectively. In addition, MSDFNet proves its excellent generalization ability on the MS2 dataset. The Abs Rel and RMSE error values in the night scene are reduced by 45.6% and 30.09%, respectively, and the accuracy

δ
<

1.25
i

,
i
=
1
,
3

is improved by 20.95% and 1.33%, respectively. The Abs Rel and RMSE values in the rainy day scenario are reduced by 1.33% and 1.21%, respectively, and the accuracy

δ
<

1.25
i

,
i
=
1
,
3

is improved by 0.24% and 0.83%, respectively.
Research on belt deviation diagnosis of belt conveyors based on deep learning
Authors: Wu Lei , Wang Yahu , Zhang Wei , Huang Shuai , Li Junxia
Published: November 2024

Due to the slow detection speed, low accuracy, and small detection range of existing methods for detecting belt deviation in belt conveyors, this paper introduces an enhanced ultra-fast lane detection (UFLD) algorithm that leverages deep learning for the detection of belt deviation. Based on the UFLD algorithm, a variable step-size row anchor division method is proposed, and the simple parameter-free attention module is added to the network to enhance the network model’s focus on edge information of conveyor belts. Furthermore, improvements are made to the convolution operations in the ResNet-18 Stem and the downsampling operations in the residual modules, thereby enhancing the network’s ability to recognize the edges of conveyor belts. Based on the established experimental platform, a high-definition camera equipped with a track-type inspection robot was used to inspect the entire belt conveyor, covering the whole of the transmission line. The conveyor belt operation datasets collected under various working conditions were used to train and comparatively study the Hough Transform, DHT, YOLOv5, YOLOv8, LaneNet, SAD, and UFLD algorithms. The experimental outcomes demonstrate that the algorithm introduced in this article outperforms the other algorithms, achieving an F1-measure of 90.31%, an accuracy rate of 94.19 %, and a detection speed of 71 frames per second, meeting the real-time diagnostic needs for belt misalignment in the coal mining industry.
Gas volume fraction measurement based on ultrasonic array sensors in gas–liquid two-phase flow
Authors: Guo Jiachen , Yang Xuning , Liu Miaomiao , Xie Fei , Zhao Ning
Published: November 2024

The volume gas fraction is an important parameter in gas–liquid two-phase flow, which plays a significant role in the study of mass and heat transfer, pressure drop, and other aspects of gas–liquid two-phase flow. Accurate identification and characterization of gas volume fraction is an important prerequisite for scientific study and industrial process. In this paper, phased array ultrasonic technology was used to conduct flow parameter measurement experiments of three flow patterns (slug flow, plug flow, and stratified flow) in horizontal pipes at the high-precision gas–liquid two-phase flow testing device. Through an analysis of measurement results by the sector scan method, coupled with principal component analysis to mitigate noise and extract eigenvalues from the acquired 128 * 448 matrix data, a predictive model for gas volume fraction satisfying the three flow patterns is established by the random forest algorithm. The Laboratory results show that the average mean absolute percentage error is 10.98%. The model is adaptive to the three flow patterns, which provides a technical solution to the gas volume fraction detection of gas–liquid two-phase flow in industrial process.
Novel calibration method for fine soil electrical resistivity based on van der Pauw configuration
Authors: Ma Deliang , Zhang Chunqi , Li Teng , Feng Huaiping
Published: November 2024

Soil electrical resistivity (ER) serves as an important parameter for indirectly monitoring various physical properties. The Miller box, based on Ohm’s Law, is commonly employed to measure resistivity. However, its probes tend to insert destructively into the soil sample. Van der Pauw (vdP) method is a classical, non-destructive technique used for measuring the ER of thin samples. Applying the vdP method to soil, which is a non-flat sample, presents certain challenges. In this paper, a novel soil resistivity calibration method (vdP box) is developed based on the vdP method, with consideration given to thickness extension. The relative resistivity error between the VDP box and Miller box for fine soil is less than 1% with various diameters and moisture content, which verified the accuracy and stability of the new device. This device achieves simple, fast, and non-destructive testing of soil resistivity and provides a novel method to study other properties of soil indirectly through resistivity.
Fault diagnosis of rolling bearing based on parameter-adaptive re-constraint VMD optimized by SABO
Authors: Guo Jinxi , Zhang Tianyao , Xue Kunlin , Liu Jiehui , Wu Jie , Zhao Yadong
Published: November 2024

Variational mode decomposition (VMD) is widely used in fault-bearing vibration-signal processing. Nonetheless, VMD remains a challenging task because of the difficulty in finding the optimal combination of parameters and excessive fault information in the residual term. The optimal parameter combination plays a balancing role in the optimization process, controlling the error between the reconstructed signal and the original signal while suppressing interference between modes. To address these defects, a parameter-adaptive re-constrained VMD method based on a subtraction average-based optimizer (SABO) is proposed. In this method, exponential functions are first used to build filters to implement a re-constrained VMD. Focusing on the fault information and minimizing it in the residuals. Then, SABO was employed to find the best parameter combination for subsequent signal processing. Finally, the signal is decomposed, and envelope spectral analysis is performed on each component to extract the fault frequencies, thereby identifying the specific fault type. Numerical simulations and real experimental data were used to demonstrate the effectiveness of the proposed method. In addition, the generalization ability of the proposed method was tested using 40 sets of sample data, and the average accuracy of this method reached 97.5%. Compared with other commonly used signal decomposition methods, the superiority of this method in rolling bearing fault feature extraction is proved.
Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT)
Authors: Yang Dongrong , Wu Xin , Li Xinyi , Mansfield Ryan , Xie Yibo , Wu Qiuwen , Jackie Wu Q , Sheng Yang
Published: November 2024

Purpose. To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-risk (OAR) sparing performance. Methods. With IRB approval, one hundred and twenty HN patients receiving IMRT were included. The DRL agent was trained with 20 patients. During each inverse optimization process, the intermediate dosimetric endpoints’ values, dose volume constraints’ values and structure objective function losses were collected as the DRL states. By adjusting the objective constraints as actions, the agent learned to seek optimal rewards by balancing OAR sparing and planning target volume (PTV) coverage. Reward computed from current dosimetric endpoints and clinical objectives were sent back to the agent to update action policy during model training. The trained agent was evaluated with the rest 100 patients. Results. The DRL agent was able to generate a clinically acceptable IMRT plan within

12.4
±
3.1

min without human intervention. DRL plans showed lower PTV maximum dose (109.2%) compared to clinical plans (112.4%) (p < .05). Average median dose of left parotid, right parotid, oral cavity, larynx, pharynx of DRL plans were 15.6 Gy, 12.2 Gy, 25.7 Gy, 27.3 Gy and 32.1 Gy respectively, comparable to 17.1 Gy, 15.7 Gy, 24.4 Gy, 23.7 Gy and 35.5 Gy of corresponding clinical plans. The maximum dose of cord + 5 mm, brainstem and mandible were also comparable between the two groups. In addition, DRL plans demonstrated reduced variability, as evidenced by smaller 95% confidence intervals. The total MU of the DRL plans was 1611 vs 1870 (p < .05) of clinical plans. The results signaled the DRL’s consistent planning strategy compared to the planners’ occasional back-and-forth decision-making during planning. Conclusion. The proposed DRL agent is capable of efficiently generating HN IMRT plans with consistent quality.
Convolution spatial-temporal attention network for EEG emotion recognition
Authors: Cao Lei , Yu Binlong , Dong Yilin , Liu Tianyu , Li Jie
Published: November 2024

In recent years, emotion recognition using electroencephalogram (EEG) signals has garnered significant interest due to its non-invasive nature and high temporal resolution. We introduced a groundbreaking method that bypasses traditional manual feature engineering, emphasizing data preprocessing and leveraging the topological relationships between channels to transform EEG signals from two-dimensional time sequences into three-dimensional spatio-temporal representations. Maximizing the potential of deep learning, our approach provides a data-driven and robust method for identifying emotional states. Leveraging the synergy between convolutional neural network and attention mechanisms facilitated automatic feature extraction and dynamic learning of inter-channel dependencies. Our method showcased remarkable performance in emotion recognition tasks, confirming the effectiveness of our approach, achieving average accuracy of 98.62% for arousal and 98.47% for valence, surpassing previous state-of-the-art results of 95.76% and 95.15%. Furthermore, we conducted a series of pivotal experiments that broadened the scope of emotion recognition research, exploring further possibilities in the field of emotion recognition.
A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals
Authors: Basso Giulio , Haakma Reinder , Vullings Rik
Published: November 2024

Objective. Pulse decomposition analysis (PDA) has been proposed to extract reliable information from photoplethysmography (PPG) morphology by decomposing the signal in its physiological sub-waves. The Gaussian model has been widely used in the literature, even though it often underperforms because it is limited to symmetric morphologies. More advanced asymmetric models, such as the Gamma model, have been proposed to achieve improved accuracy. However, the physiological interpretation of the Gamma model is less effective than the Gaussian model, challenging the assessment of the clinical relevance of the outcomes. This paper aims to design an asymmetric PDA model with improved accuracy and effective physiological interpretability. Approach. We implemented a novel PDA model called the skewed-Gaussian model and tested it on 8000 PPG pulses from the MIMIC-III Waveform Database. The performances were compared with the reference Gamma-Gaussian model. Models’ accuracies were assessed using the residual sum of squares, while Bland–Altman plots were used to evaluate biases. Lastly, the sensitivity and robustness of the models to the initial values’ choice were evaluated using random initial values. Main results. Our model achieved significantly higher accuracy than the reference model. The analysis with random initial values suggested that the model was less sensitive and consistently more robust. Finally, we highlighted the physiological interpretation of the model. Significance. The proposed model may help to establish a link between alterations in cardiovascular functions and variations detectable in the PPG signal, as well as opening up new avenues for PPG-based remote patient monitoring.