bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of alpha-ion stopping on ignition and ignition criteria in inertial confinement fusion experiments
Authors: Reichelt Benjamin L. , Petrasso Richard D. , Li Chikang
Published: January 2024

With the advent of ignited plasmas at the National Ignition Facility (NIF), alpha physics has become a driving factor in theoretical understanding and experimental behavior. In this communication, we explore aspects of direct alpha-ion heating through comparison of the consequences from the one-fluid and two-fluid models in the hydrodynamic approach. We show that the case with all alpha energy deposited in electrons raises the ignition criteria by ∼4 keV or ∼0.2 g/cm2 in the hotspot relative to the case with all alpha energy deposited in ions. In the case of the recently ignited NIF implosion, 30% of the 3.5 MeV α energy is deposited into the DT fuel ions, for which there is negligible difference between the one-fluid and two-fluid ignition criteria. However, changes in the ion stopping fraction through profile effects and alternate stopping power models could lead to ignition curve shifts of ∼1 keV.
Geometrical wetting boundary condition for complex geometries in lattice Boltzmann color-gradient model
Authors: Wang Ningning , Ni Wanglai , Liu Haihu
Published: January 2024

A wetting boundary condition for dealing with moving contact lines on complex surfaces is developed in the lattice Boltzmann color-gradient model. The wetting boundary condition is implemented by combining the geometrical formulation of contact angle and the idea of the prediction–correction wetting scheme, which not only produces the desired contact angles with high accuracy but also avoids the necessity to select an appropriate interface normal vector from multiple solutions that satisfy the contact angle condition. Through the implementation in the framework of color-gradient model, the developed wetting boundary condition is validated against analytical solutions by a series of benchmark cases, including a droplet resting on a cylindrical surface and on a tilt wall, a liquid film migrating between two parallel plates, and the forced imbibition into a pore doublet. The simulation results of static contact angles show that the wetting boundary condition is able to simulate arbitrary values of contact angle and leads to negligible mass leakage across the boundary. For dynamic problems, the wetting boundary condition is found to correctly capture the imbibition dynamics under various flow and viscosity ratio conditions and produce dynamic contact angles that match well with the Cox–Voinov law.
Scattering of gravity-capillary waves on a bottom step
Authors: Meylan M. H. , Stepanyants Y. A.
Published: January 2024

Under the linear approximation, we study the scattering of gravity-capillary waves on a bottom step. The boundary conditions can be satisfied by considering a countable number of evanescent modes that are localized near the bottom step. Such modes have certain specific features compared to similar modes for pure gravity waves. In particular, there exists an extra mode. When a numerical solution is calculated, this extra mode allows us to match in the fluid region and impose the additional condition at the surface, which arises for capillary gravity waves (and not for pure gravity waves). The approximate formulas are suggested for the transformation coefficients. By means of numerical calculations, we find the reflection and transmission coefficients of traveling waves and compare the results with the predictions of the approximate formulas. The approximate formulas are shown to agree well with the numerical data. Both numerical and approximate results agree with the energy flux conservation. We also study the wave transformation on the rectangular underwater bump and trench, which are straightforward extensions of our step calculations. We calculate the transformation coefficients numerically and illustrate the transformation by time-dependent results, which are also shown as animations in the supplementary material.
Validation of minority carrier recombination lifetimes in low-dimensional semiconductors found by analytical photoresponses
Authors: Li Kai , Shen Yinchu , Su Zhijuan , Dan Yaping
Published: January 2024

It is a formidable challenge to find the minority carrier recombination lifetime in low-dimensional devices as low-dimensionality increases the surface recombination rate and often reduces the recombination lifetime to a scale of picoseconds. In this work, we demonstrated a simple but powerful method to quantitatively probe the minority carrier recombination lifetime in silicon nanowires or microwires by fitting the experimental photoresponses with our recently established analytical photoresponse principle of photoconductors. The nanowires were passivated with small molecules and Al2O3 to suppress surface recombination, which will increase the minority recombination lifetimes. As expected, the minority carrier recombination lifetime found by this approach increases by orders of magnitude. These wires were also made into PIN diodes, the leakage of which was reduced at least 1 order of magnitude after surface passivation by Al2O3. The minority recombination lifetime found from the leakage current of these devices is largely consistent with what we found from our analytical photoresponse principle. As a further step, we performed scanning photocurrent microscopy to find the minority diffusion length from which we found that the minority recombination lifetime is close to what we found from the analytical photoresponses. In short, this work validated that our analytical response principle is a reliable method to find the minority recombination lifetime in low-dimensional semiconductors.
Insights on nano-scale flow and interactive transportation of hazardous pollutants under supercritical fluid environment
Authors: Ragui Karim , Chen Lin
Published: January 2024

This perspective paper aims to spark a fundamental debate on the key laws that would combine the nano- to micro-scale flow dynamics of resident contaminants in soil systems under supercritical phase-assisted transportation. The rank of supercritical solvents (SCFs) for hazardous polycyclic aromatic hydrocarbons, benzene, toluene, ethylbenzene, and xylenes is deeply discussed beside its confines to meet the current requests of in situ/ex situ fields. The scaling behaviors during soil–pollutants–SCFs interactions are highlighted to underline the hidden laws behind the basic transportation under flooding remediation. A new strategy based on artificial intelligence learning is emphasized with a demonstrative sample to predict the solubility behavior of this kind of contaminants during a spatiotemporal mechanism. This debate illustrates the conjugate experimental and numerical pathways to deal with the complex nano-remediation dynamics and sheds the light on the current trends and future outlook with techno-economic concerns to promote the faith of a clean and sustainable environment.
Gate recurrent unit network combines with Adaboost algorithm to classify fluid types by well logging parameters
Authors: Sun Youzhuang , Zhang Junhua , Zhang Yongan
Published: January 2024

Given the diverse range of fluid types in reservoirs, their frequent alternation, and complex composition, traditional methods exhibit low accuracy in identifying these types. To address this, we introduce machine learning techniques to predict fluid types by extracting logging data. However, a single Gate Recurrent Unit (GRU) network is insufficient to meet the demands of fluid type prediction. Therefore, we propose a method that combines the GRU network with the Adaboost algorithm, referred to as GRU-Adaboost. The GRU-Adaboost model effectively combines multiple weak classifiers into a more powerful classifier through iterative training and gradual adjustment of sample weights. By using a voting strategy to synthesize the predictions of individual classifiers, the impact of errors from each classifier can be reduced. Compared with traditional GRU networks and Long Short-Term Memory models, the proposed GRU-Adaboost model shows improved accuracy. To validate the feasibility of our method, we apply the proposed algorithm to three wells. Experimental results confirm that the prediction performance of GRU-Adaboost surpasses that of other models.
Influence of dual purging jets on interferometric measurement of optical path difference
Authors: Cao Jian , Wang Peng , Liu Yingzheng
Published: January 2024

Incompressible large eddy simulations of dual purging jets at three Reynolds numbers of ReL = 1500, 1000, and 500 are performed, providing the database for simulated interferometric measurements subjected to the spatiotemporally varying temperature fields. The temperature is modeled as a passive scalar, and the index-of-refraction field is calculated from the air temperature and pressure using the modified Edlén equation. Based on wave optics, wavefront distortions of laser beams traversing the flow field are computed, and the optical path difference measurement is simulated. Statistical results of the velocity and temperature indicate distinctly different flow patterns at three Reynolds numbers. Spectral proper orthogonal decomposition is adopted to analyze the relationship between coherent flow structures and temperature wavepackets. There is a dominant frequency (St = 0.29) at ReL = 1500 and 1000, which is attributed to the Kelvin–Helmholtz instability, whereas the two jets have notable flapping behaviors at ReL = 500. The wavefront distortions are found to be insensitive to the Reynolds number. The effects of the flow region and tracing distance are examined, and the optical performances of different beam pairs for interferometry are evaluated. The optical beams passing through the outer shear layers of the dual jets and wall jets are distorted severely, resulting in large systematic and random errors in the interferometric measurement.
Capillary flow of two immiscible liquids initially separated by a Taylor gas bubble
Authors: Rasuceanu I. , Patrascu C.
Published: January 2024

We investigate the capillary displacement of silicone oil columns by water in tandem with a Taylor gas bubble in horizontally aligned tubes that initially separate the two immiscible liquids. The experiments show that the gas slug's motion forces the drainage of the prefilling liquid through a thin film deposited on the tube's wall. The displaced oil is then recovered at the advancing water meniscus. The dynamics of the capillary displacement and drainage are studied as functions of the silicone oil and gas bubble volumes. We find that the Taylor bubble's length has a small influence on the capillary displacement and drainage of the prefilling liquid. The study presents an adapted model for the capillary drainage and oil recovery using Taylor's law for the deposited film thickness on the tube's wall, which collapses all experimental data onto a single curve.
An entropy generation approach to the molecular recoiling stress relaxation in thin nonequilibrated polymer films
Authors: Madhusudanan Mithun , Chowdhury Mithun
Published: January 2024

In polymers, the equilibrium state is achieved when the chains have access to the maximum number of conformational states, which allows them to explore a larger conformational space, leading to an increase in the entropy of the system. Preparation of thin polymer films using the spin-coating technique results in polymer chains being locked in a nonequilibrium state with lower entropy due to possible stretching of chains during the process. Allowing enough time for recovery results in the relaxation of the spin-coating-induced molecular recoiling stress. Annealing such a film generates entropy due to its inherent irreversibility. We employed the dewetting technique to determine the molecular recoiling stress relaxation time in poly-(tertbutyl styrene) thin films. Furthermore, we qualitatively differentiated the metastable states achieved by the polymer film using entropy generation in a relaxing polymer film as an effect of thermal entropy and associated it with the conformational entropy of polymer chains utilizing the molecular recoiling stress relaxation time. This enabled us to explain molecular recoiling stress relaxation using a rather simplistic approach involving segmental level molecular rearrangements in polymer chains by attaining transient metastable states through an entropically activated process driving toward equilibrium.
On the nature of screening in charge-regulated macroion solutions
Authors: Kumari Sunita , Podgornik Rudolf
Published: January 2024

We present a derivation of the screening length for a solution containing a charge-regulated macroion, e.g. protein, with its counterions. We show that it can be obtained directly from the second derivatives of the total free energy by taking recourse to the “uncertainty relation” of the Legendre transform, which connects the Hessians or the local curvatures of the free energy as a function of density and its Legendre transform, i.e., osmotic pressure, as a function of chemical potentials. Based on the Fowler–Guggenheim–Frumkin model of charge regulation, we then analyze the “screening resonance” and the “overscreening” of the screening properties of the charge-regulated macroion solution.
The impact of inter-dune space and volume ratio on barchan dune collision patterns: A numerical simulation study
Authors: Lin Yuanwei , Guan Kaiyuan , Zhang Yang , Gao Xin , Yang Bin , He Nan
Published: January 2024

Collision among barchan dunes is a main cause for the dune swarm to achieve size and speed selection, and it can be divided into two patterns: coalescence and ejection. Here, a three-dimensional (3D) cellular automaton model is applied to collectively study the effects of inter-dune space and relative dune size on these collision patterns. A parameter space is established that includes a transition surface distinguishing coalescence and ejection. Confirmed by field observations and subaquatic experiments, a comprehensive depiction of transition between coalescence and ejection is provided, which may bring new constraints on the morphodynamics of barchan dune fields.
Investigating the role of blow fly olfaction in flystrike in sheep
Authors: Yan Guanjie , Schlink Anthony C. , Liu Shimin , Greeff Johan C. , Flematti Gavin R. , Martin Graeme B.
Published: January 2024

Breech flystrike is a painful, debilitating and potentially lethal disease caused by the larvae of the blowfly, Lucilia cuprina, and, despite many years of research, it remains a serious financial and animal-welfare issue for the Merino sheep industry in Australia. The common methods of prevention, namely insecticides, crutching and ‘mulesing’, are problematical, so alternative approaches are needed. Breeding for resistance to breech strike is a fundamentally attractive proposition, but the trait itself is difficult and expensive to quantify in large numbers of sheep in extensive production systems. Several indirect traits are correlated with susceptibility to flystrike, but a large proportion of the variation in susceptibility remains unexplained. The common thread through those indirect traits is odour, so we turned to the biology of insect olfaction and its role in fly–sheep interactions. L. cuprina uses odours to detect and locate potential hosts over long distances, to guide orientation and landing behaviour, and to select egg-laying sites. Preliminary studies demonstrated the importance of confining our work to gravid female L. cuprina, and also validated the use of flies reared in the laboratory for experimentation. Using laboratory-reared flies and a combination of gas chromatography–mass spectrometry with electroantennographic detection, we identified odouriferous compounds from sheep that the antenna of L. cuprina can detect. To determine whether the identified compounds were attractive or repulsive, we needed to use a behaviour test. In preliminary studies, we compared four behaviour bioassays (Y-tube, landing time, visiting frequency, and trap) and found the trap to be the most effective. We observed that L. cuprina was attracted by several compounds in Merino wool, including octanal, nonanal and dimethyl trisulfide. We also found that the wool levels of octanal and nonanal are heritable in Merino sheep, suggesting that these compounds might be useful as traits in selection for flystrike resistance. Another possibility is that these olfactory-active compounds might guide efforts to modify the genome of sheep, or perhaps even L. cuprina. Success in these endeavours could save as much as A$200 m per year for the Australian Merino-based industries, while also improving the image of wool in world markets.
Decreasing the intrinsically disordered protein α-synuclein levels by targeting its structured mRNA with a ribonuclease-targeting chimera
Authors: Tong Yuquan , Zhang Peiyuan , Yang Xueyi , Liu Xiaohui , Zhang Jie , Grudniewska Magda , Jung Ikrak , Abegg Daniel , Liu Jun , Childs-Disney Jessica L. , Gibaut Quentin M. R. , Haniff Hafeez S. , Adibekian Alexander , Mouradian M. Maral , Disney Matthew D.
Published: January 2024

α-Synuclein is an important drug target for the treatment of Parkinson’s disease (PD), but it is an intrinsically disordered protein lacking typical small-molecule binding pockets. In contrast, the encoding
SNCA
mRNA has regions of ordered structure in its 5′ untranslated region (UTR). Here, we present an integrated approach to identify small molecules that bind this structured region and inhibit α-synuclein translation. A drug-like, RNA-focused compound collection was studied for binding to the 5′ UTR of
SNCA
mRNA, affording Synucleozid-2.0, a drug-like small molecule that decreases α-synuclein levels by inhibiting ribosomes from assembling onto
SNCA
mRNA. This RNA-binding small molecule was converted into a ribonuclease-targeting chimera (RiboTAC) to degrade cellular
SNCA
mRNA. RNA-seq and proteomics studies demonstrated that the RiboTAC (Syn-RiboTAC) selectively degraded
SNCA
mRNA to reduce its protein levels, affording a fivefold enhancement of cytoprotective effects as compared to Synucleozid-2.0. As observed in many diseases, transcriptome-wide changes in RNA expression are observed in PD. Syn-RiboTAC also rescued the expression of ~50% of genes that were abnormally expressed in dopaminergic neurons differentiated from PD patient–derived iPSCs. These studies demonstrate that the druggability of the proteome can be expanded greatly by targeting the encoding mRNAs with both small molecule binders and RiboTAC degraders.
Multimerization of a disordered kinetochore protein promotes accurate chromosome segregation by localizing a core dynein module
Authors: McGory Jessica M. , Verma Vikash , Barcelos Dylan M. , Maresca Thomas J.
Published: January 2024

Kinetochores connect chromosomes and spindle microtubules to maintain genomic integrity through cell division. Crosstalk between the minus-end directed motor dynein and kinetochore–microtubule attachment factors promotes accurate chromosome segregation by a poorly understood pathway. Here, we identify a linkage between the intrinsically disordered protein Spc105 (KNL1 orthologue) and dynein using an optogenetic oligomerization assay. Core pools of the checkpoint protein BubR1 and the adaptor complex RZZ contribute to the linkage. Furthermore, a minimal segment of Spc105 with a propensity to multimerize and which contains protein binding motifs is sufficient to link Spc105 to RZZ/dynein. Deletion of the minimal region from Spc105 compromises the recruitment of its binding partners to kinetochores and elevates chromosome missegregation due to merotelic attachments. Restoration of normal chromosome segregation and localization of BubR1 and RZZ requires both protein binding motifs and oligomerization of Spc105. Together, our results reveal that higher-order multimerization of Spc105 contributes to localizing a core pool of RZZ that promotes accurate chromosome segregation.
High-Temperature Superconductivity in La3Ni2O7
Authors: Jiang 蒋 Kun 坤 , Wang 汪 Ziqiang 自强 , Zhang 张 Fu-Chun 富春
Published: January 2024

Motivated by the recent discovery of high-temperature superconductivity in bilayer La3Ni2O7 under pressure, we study its electronic properties and superconductivity due to strong electron correlation. Using the inversion symmetry, we decouple the low-energy electronic structure into block-diagonal symmetric and antisymmetric sectors. It is found that the antisymmetric sector can be reduced to a one-band system near half filling, while the symmetric bands occupied by about two electrons are heavily overdoped individually. Using the strong coupling mean field theory, we obtain strong superconducting pairing with B
1g symmetry in the antisymmetric sector. We propose that due to the spin-orbital exchange coupling between the two sectors, B
1g pairing is induced in the symmetric bands, which in turn boosts the pairing gap in the antisymmetric band and enhances the high-temperature superconductivity with a congruent d-wave symmetry in pressurized La3Ni2O7.
Quantization of spinor field in the Schwarzschild spacetime and spin sums for solutions of the Dirac equation
Authors: Egorov Vadim , Smolyakov Mikhail , Volobuev Igor
Published: January 2024

We discuss the problem of canonical quantization of a free massive spinor field in the Schwarzschild spacetime. It is shown that a consistent procedure of canonical quantization of the field can be carried out without taking into account the internal region of the black hole, the canonical commutation relations in the resulting theory hold exactly and the Hamiltonian has the standard form. Spin sums are obtained for solutions of the Dirac equation in the Schwarzschild spacetime.
Conformally Einstein Lorentzian Lie groups: extensions of the Euclidean and Poincaré groups
Authors: Calviño-Louzao Esteban , García-Río Eduardo , Gutiérrez-Rodríguez Ixchel , Vázquez-Lorenzo Ramón
Published: January 2024

We describe all Lorentzian semi-direct extensions of the Euclidean and Poincaré groups which are conformally Einstein.
Non-canonical Higgs inflation
Authors: Pareek Pooja , Nautiyal Akhilesh
Published: January 2024

The large value of non-minimal coupling constantξrequired to satisfy cosmic microwave background observations in Higgs inflation violates unitarity. In this work we study Higgs-inflation with non-canonical kinetic term of DBI form to find whetherξcan be reduced. To study the inflationary dynamics, we transform the action to the Einstein frame, in which the Higgs is minimally coupled to gravity with a non-canonical kinetic term and modified potential. We choose the Higgs self coupling constantλ = 0.14 for our analysis. We find that the value ofξcan be reduced from 103–104toO(10)to satisfy Planck constraints on amplitude of scalar power spectrum. However, this model produces a larger tensor-to-scalar ratior, in comparison to the Higgs inflation with canonical kinetic term. We also find that, to satisfy joint constraints on scalar spectral indexnsand tensor-to-scalar ratiorfrom Planck-2018 and bounds onrfrom Planck and BICEP3, the value ofξshould be of the order of 104. Thus, the issue of unitarity violation remains even after considering Higgs inflation with non-canonical kinetic term.
Absorption cross section in gravity’s rainbow from confluent Heun equation
Authors: Amado Julián Barragán , Kwon Kihong , Gwak Bogeun
Published: January 2024

We investigate the scattering of a massless scalar field by a charged, non-rotating black hole in the presence of gravity’s rainbow. Using the connection coefficients of the confluent Heun equation expressed in terms of the semi-classical confluent conformal blocks and the instanton part of the Nekrasov–Shatashvili free energy, we obtain an asymptotic expansion for the low-energy absorption cross section. Furthermore, we consider the resummation of the instanton contributions to the absorption cross section, which gives the area of the black hole up to a factor of(4/3)2.
Indium defect complexes in (In
x
Ga1−x
)2O3: a combined experimental and hybrid density functional theory study
Authors: Welch Eric , Talukder Md Abdul Ahad , Martins Nathan Rabelo , Borges Pablo Damasceno , Droopad Ravi , Scolfaro Luisa
Published: January 2024

Indium defects in small concentration (In
x
Ga1−x
)2O3 were studied using a combination of spectroscopic and magnetic measurements on thin films varying the indium concentration, coupled with hybrid density functional theory simulations using the supercell method. X-ray diffraction spectra along with Tauc plots and density of states plots reveal a decrease (increase) in the electronic band gap (interlayer lattice spacing) due to the inclusion of indium in monoclinic Ga2O3, while room-temperature Hall measurements show an increase in n-type conductivity. Formation energy calculations reveal that the defect complex of substitutional indium at the octahedrally coordinated cation site (InGa) coupled with an indium interstitial (Ini) in the largest Ga–O cavity in the bulk (ia
), where the two impurities are a maximal distance away in the unit cell, results in the lowest formation energy across much of the electronic band gap; near the conduction band edge the single InGa defect becomes the lowest energy defect, though. These calculations help shed light on the impurity band enhanced, n-type conductivity increase due to small concentration indium doping in Ga2O3 as seen in the spectroscopic/magnetic measurements.
Terajet-assisted time-domain super-resolution imaging
Authors: Paddubskaya A G , Valynets N I , Novitsky A V , Minin O V , Minin I V
Published: January 2024

Large-scale applications of real-time terahertz (THz) imaging are often limited by the spatial resolution of a THz microscope. One of the simplest approaches to circumvent this problem in practice and achieve resolution below the diffraction limit consists in placing a dielectric particle with a size comparable to the radiation wavelength in the vicinity of the focal plane of the THz imaging system. Here, we theoretically consider the transmittance of a THz Gaussian beam through a Teflon sphere to further analyze experimental results on THz superresolution imaging. We address the resolution beyond the diffraction limit (the experimentally determined value is 0.38λ at 0.46 THz) through the superlens effect of the terajet generated by the mesoscale sphere owing to propagating and evanescent partial waves in the terajet. Due to the coupling of the dielectric sphere and time-domain THz spectrometer, we can detect a 10 µm thick PTFE film, which is almost transparent (98% transmittance) in the THz frequency range. The correlation between the transmittance spectrum of the dielectric sphere and the quality of THz images of thin, nonconducting films collected at different frequencies has been demonstrated experimentally and considered analytically. Our study is relevant for hyperspectral imaging applications and further development of the sphere-coupled time-domain THz imaging technique.
Inter-turn short circuit and demagnetization fault diagnosis of ship PMSM based on multiscale residual dilated CNN and BiLSTM
Authors: Yan Guohua , Hu Yihuai
Published: January 2024

Inter-turn short circuit (ITSC) and demagnetization of permanent magnet synchronous motors (PMSMs) can lead to serious ship accidents, timely and accurate fault diagnosis of these faults is very important. A multi-signal fusion fault diagnosis method (MD-CNN-BiLSTM) is proposed based on multi-scale residual dilated convolutional neural network (D-CNN) and bidirectional long and short-term memory (BiLSTM) for PMSM fault diagnosis. This method first takes three-phase current and vibration signals as input; uses a three-column parallel CNN structure with different scales to extract both global signal and local feature. A residual connection in the expanded CNN is then used to eliminate the problems of gradient disappearance or explosion; and finally, BiLSTM is used to further extract features and identify the fault. A 2.2 kW permanent magnet synchronous motor was used to build a fault simulation test rig. The motor stator was rewound to simulate the ITSC fault, and different sizes of permanent magnets were replaced to simulate demagnetization fault. ITSC, demagnetization and their coupled faults were simulated under 10 specific motor speeds and loads respectively. The test proved that the diagnostic accuracy of the proposed method was 4.2% higher than that of ordinary CNN and 29.06% higher than that of BiLSTM. It also had the best diagnostic effect under the noise interference of different intensities. It was verified that the proposed method has good noise interference and strong classification ability.
Comparison of aerosol spectrometers : accounting for evaporation and sampling losses
Authors: Lefebvre Xavier , Succar Antonella , Bédard Emilie , Prévost Michele , Robert Etienne
Published: January 2024

Measuring aerosol size distribution with precision is critical to understand the transmission of pathogens causing respiratory illnesses and to identify risk mitigation strategies. It is however a challenging task as the size of pathogen-carrying particles evolves over time due to evaporation. Although measurement techniques well established in the field of aerosol science are often used to characterize bioaerosols, their performance is seldom assessed with respect to evaporation and deposition in sampling lines. Four instruments providing aerosol size distribution were compared using oil and water-based particles. They each rely on different measurement principles: phase doppler anemometry, light scattering, electrical mobility and aerodynamic impaction. Size distributions of oil-based particles showed consistency across different measurement instruments, but significant discrepancies arose for water-based particles undergoing evaporation. These larger differences result from both evaporation and particle deposition in transit between the sampling point and the measurement inside the instrument. Phase doppler anemometry was best suited for precise size distribution measurement, as it eliminates the need for a sampling line, thereby preventing particle loss or evaporation during transit. With this instrument as a reference, empirical correction factors for evaporation and deposition were derived from dimensionless numbers and experimental data, enabling quantitative assessment of bioaerosol size distribution using different instruments. To obtain the size distribution at the source of the aerosol generation, complete drying of a salt solution was performed. Using the complete drying technique and accounting for losses, sampling instruments can reliably provide this critical information and allow for thorough risk assessment in the context of airborne transmission.
Prediction tool wear using improved deep extreme learning machines based on the sparrow search algorithm
Authors: Zhou Wenjun , Xiao Xiaoping , Li Zisheng , Zhang Kai , He Ruide
Published: January 2024

Accurate tool wear monitoring is crucial for increasing tool life and machining productivity. Although many prediction models can achieve high prediction accuracy, there are problems such as poor stability in the face of different working conditions or tool signals. A tool wear prediction method based on improved deep extreme learning machines (DELMs) was proposed as a solution to this issue; it uses the sparrow search algorithm (SSA) to upgrade the input weight of DELM to improve the model, and then extracts the time-domain, frequency-domain, and time-frequency domain characteristics from multi-sensor signals to construct and test the improved model SSA-DELM. The verification results show that the proposed model accurately reflects the tool wear. Meanwhile, the RMSE of the proposed model decreased by 53.39%, 19.95%, 43.86%, 23.80%, 24.80%, and 3.72%, respectively, and the MAE decreased by 67.81%, 17.87%, 32.70%, 29.90%, 30.30%, and 6.78%, respectively, compared to the with unimproved DELM, particle swarm optimization-least squares support vector machine, long short-term memory, stacked sparse autoencoder, recurrent neural network, and dung beetle optimizer-DELM.
Enhanced curve-based segmentation method for point clouds of curved and irregular structures
Authors: Song Limei , Zhang Zongyang , Xu Chongdi , Yang Yangang , Zhu Xinjun
Published: January 2024

This paper proposes an improved method for model-based segmentation (MS) of curved and irregular mounded structures in 3D measurements. The proposed method divides the point cloud data into several levels according to the reasonable width calculated from the density of points. Then, it fits a curve model with 2D points for each level separately. The classification results of specific types are merged to obtain specific structural measurement data in 3D space. We use MS method, difference of normals based segmentation, region growing algorithm, constrained planar cuts, and locally convex connected patches as a control group. The results show that the proposed method achieves higher accuracy with a mean intersection merge ratio of more than 0.8238, at least 37.92% higher than other methods. The method proposed in this paper requires less time to process than other methods. Therefore, the proposed method effectively and efficiently segments the measurement data of curved and irregular mounded structures in 3D measurements. The method proposed in this paper has also been applied in the practical robotic grinding task. The root mean square error of the grinding amount is less than 2 mm, and good grinding results are achieved.
Incipient fault detection based on ensemble learning and distribution dissimilarity analysis in multi-feature processes
Authors: Liu Meizhi , Kong Xiangyu , Luo Jiayu , Yang Lei
Published: January 2024

Timely and accurate detection of incipient faults has attracted considerable attention and research interest in recent years, due to its potential for the prevention of serious safety incidents and for supporting preventive maintenance. However, most existing methods use single detection model, neglecting the coexistence of multiple features and the local data distribution information found in industrial scenes. To overcome this problem, an incipient fault detection method named multiple model ensemble and distribution dissimilarity analysis (MME-DISSIM) is proposed. First, various multivariate statistical analysis methods are employed as basic detectors to comprehensively capture the feature information hidden in the process data. Second, DISSIM analysis is performed to evaluate the dissimilarity between the current sliding window and each training subset. This evaluation allows for the calculation of weighting factors for each basic detector, which helps to preserve the local distribution information of the current sliding window. Third, ensemble learning is utilized to integrate the statistics from all basic detectors into two detection indices to determine the operation status of the system. In addition, two measurement metrics are defined to quantitatively analyze the fault level of incipient faults. Finally, several experiments on a numerical case, Tennessee Eastman process, and actual PROcess NeTwork Optimization are presented to verify the efficacy and superiority of the proposed method.
Adaptive graph-guided joint soft clustering and distribution alignment for cross-load and cross-device rotating machinery fault transfer diagnosis
Authors: Xu Huoyao , Peng Xiangyu , Wang Junlang , Liu Jie , He Chaoming
Published: January 2024

Domain adaptation (DA) is an effective solution for addressing the domain shift problem. However, existing DA techniques usually directly match the distributions of the data in the original feature space, where some of the features may be distorted by a large domain shift. Besides, geometric and clustering structures of the data, which play a significant role in revealing hidden failure patterns, are not considered in traditional DA methods. To tackle the above issues, a new joint soft clustering and distribution alignment with graph embedding (JSCDA-GE) method is proposed. Specifically, weighted subspace alignment is proposed to align bases of source and target subspaces by combining instance reweighting and subspace alignment strategies. Then, JSCDA-GE formulates an objective function by incorporating dynamic distribution alignment, soft large margin clustering, and GE in a unified structural risk minimization framework. Ultimately, JSCDA-GE aims to learn a generalization classifier for fault diagnosis. Its effectiveness and superiority have been confirmed through 36 tasks on 2 bearing databases.
Nitriding layer depth detection based on mixing frequency nonlinear ultrasonic parameters
Authors: Li Xinxin , Bi Yiwen , Tang Weili , Mao Hanling , Huang Zhenfeng
Published: January 2024

Nitriding treatment can improve the surface properties of workpieces, thus increasing the service life of the workpiece. The depth of nitriding layer is not only one of the important indexes for evaluating the nitriding effect, but also an important factor affecting the end-use performance of the workpiece. While the existing hardness and metallographic methods cannot meet the needs for non-destructive testing of nitriding layer depth in shaft parts. Therefore, a method using non-linear ultrasonic testing technology is proposed for non-destructive evaluation of nitriding layer depth. In this study, 1045 steel shaft specimens with different nitriding layer depths were prepared by a liquid salt bath nitriding method. The total depth of the nitriding layer was measured using a microhardness tester, and metallographic microscopy was applied to observe microstructure changes before and after nitriding treatment. With the proposed non-destructive method, the longitudinal critically refracted (LCR) wave mixing detection model was established and the ultrasonic nonlinear coefficients were used for characterizing the nitrided layer depths. Experimental results show that the LCR wave sum frequency (LCRWSF) detection model better characterizes the nitriding layer depth of 1045 steel and has higher sensitivity. As a result, the LCRWSF model is more suitable to efficiently estimate the nitrided layer depth.
Design and dynamic analysis of a highly sensitive MEMS gyroscope based on mode localization
Authors: Hou W , Zhang Q C , Hao S Y , Zhang K P
Published: January 2024

Micro-electromechanical systems (MEMS) gyroscopes have important applications in various fields, including aviation, spaceflight, weaponry and automatic driving. To improve the robustness and sensitivity, we design a novel dual-mass MEMS gyroscope based on mode localization in this paper. The gyroscope structure comprises a pair of perturbation systems connected with weakly coupled resonator systems, which eliminates the mode matching and achieves mode localization effects. The dynamic behavior of the MEMS gyroscope is developed using the complex exponential method. The detection characteristics of the amplitude ratio (AR) and amplitude difference (AD) are compared. By combining numerical simulation, we analyzed the influence of critical parameters. It is indicated that the sensitivity can reach up to 40 036.9 ppm/°/s through the AR output, which is two magnitudes higher than the traditional MEMS gyroscope. For the detection of the micro-angular rate, the AD output has advantages in sensitivity, and the AR output has a smaller nonlinearity error. In addition, structural parameters, especially the voltage of the perturbation parallel plates, have a significant impact on the system’s sensitivity. If the breakdown voltage requirement is satisfied, the sensitivity can be enhanced more than ten times by amplifying the voltage, which further broadens the application field of the MEMS gyroscope.
High-performance plasmonic mid-infrared bandpass filters by inverse design
Authors: Zhang Jiarui , Chen Zeji , Su Zhijuan , Dan Yaping
Published: January 2024

Plasmonic spectral filters composed of periodic nanostructured metal films offer novel opportunities for the development of multispectral imaging technologies in the mid-infrared region. However, traditional plasmonic filters, which typically feature simplistic structures such as nanoholes or nanorings, are constrained by a narrow bandpass and significant crosstalk, leading to limited practical performance. Filters designed using inverse techniques allow a substantial degree of freedom in creating intricate structures that align with desired spectral characteristics, including a quasi-square spectral profile, high transmission, wide full width at half maximum, and reduced crosstalk. In this study, we have utilized an inverse design algorithm to engineer high-performance bandpass filters for the mid-infrared range, achieving an average transmittance exceeding 80% within the bandpass window and below 10% in the stop band, which is comparable to that of commercial multilayer Bragg filters. Nanofabrication processes were employed to transfer the designed pattern into the gold film on ZnS substrate that is transparent in the mid-infrared range. The resulting filters exhibit spectral performance analogous to that of the inversely designed models, making them suitable for direct integration with mid-infrared photodetector arrays in multispectral imaging systems.
Determination of output factor for CyberKnife using scintillation dosimetry and deep learning
Authors: Ocampo Jeremy , Heyes Geoff , Dehghani Hamid , Scanlon Tim , Jolly Simon , Gibson Adam
Published: January 2024

Objective. Small-field dosimetry is an ongoing challenge in radiotherapy quality assurance (QA) especially for radiosurgery systems such as CyberKnifeTM. The objective of this work is to demonstrate the use of a plastic scintillator imaged with a commercial camera to measure the output factor of a CyberKnife system. The output factor describes the dose on the central axis as a function of collimator size, and is a fundamental part of CyberKnife QA and integral to the data used in the treatment planning system. Approach. A self-contained device consisting of a solid plastic scintillator and a camera was build in a portable Pelicase. Photographs were analysed using classical methods and with convolutional neural networks (CNN) to predict beam parameters which were then compared to measurements. Main results. Initial results using classical image processing to determine standard QA parameters such as percentage depth dose (PDD) were unsuccessful, with 34% of points failing to meet the Gamma criterion (which measures the distance between corresponding points and the relative difference in dose) of 2 mm/2%. However, when images were processed using a CNN trained on simulated data and a green scintillator sheet, 92% of PDD curves agreed with measurements with a microdiamond detector to within 2 mm/2% and 78% to 1%/1 mm. The mean difference between the output factors measured using this system and a microdiamond detector was 1.1%. Confidence in the results was enhanced by using the algorithm to predict the known collimator sizes from the photographs which it was able to do with an accuracy of less than 1 mm. Significance. With refinement, a full output factor curve could be measured in less than an hour, offering a new approach for rapid, convenient small-field dosimetry.
A multi-resolution TOF-DOI detector for human brain dedicated PET scanner
Authors: He Wen , Zhao Yangyang , Huang Wenjie , Zhao Xin , Niu Ming , Yang Hang , Zhang Lei , Ren Qiushi , Gu Zheng
Published: January 2024

Objective. We propose a single-ended readout, multi-resolution detector design that can achieve high spatial, depth-of-interaction (DOI), and time-of-flight (TOF) resolutions, as well as high sensitivity for human brain-dedicated positron emission tomography (PET) scanners. Approach. The detector comprised two layers of LYSO crystal arrays and a lightguide in between. The top (gamma ray entrance) layer consisted of a 16 × 16 array of 1.53 × 1.53 × 6 mm3 LYSO crystals for providing high spatial resolution. The bottom layer consisted of an 8 × 8 array of 3.0 × 3.0 × 15 mm3 LYSO crystals that were one-to-one coupled to an 8 × 8 multipixel photon counter (MPPC) array for providing high TOF resolution. The 2 mm thick lightguide introduces inter-crystal light sharing that causes variations of the light distribution patterns for high DOI resolution. The detector was read out by a PETsys TOFPET2 application-specific integrated circuit. Main result. The top and bottom layers were distinguished by a convolutional neural network with 97% accuracy. All crystals in the top and bottom layers were resolved. The inter-crystal scatter (ICS) events in the bottom layer were identified, and the measured average DOI resolution of the bottom layer was 4.1 mm. The coincidence time resolution (CTR) for the top–top, top-bottom, and bottom–bottom coincidences was 476 ps, 405 ps, and 298 ps, respectively. When ICS events were excluded from the bottom layer, the CTR of the bottom–bottom coincidence was 277 ps. Significance. The top layer of the proposed two-layer detector achieved a high spatial resolution and the bottom layer achieved a high TOF resolution. Together with its high DOI resolution and detection efficiency, the proposed detector is well suited for next-generation high-performance brain-dedicated PET scanners.
Investigation of core transport changes in DIII-D discharges with off-axis T

e
profile peaks
Authors: Xie R , Austin M E , Gentle K , Petty C C
Published: January 2024

DIII-D discharges that transition to H-mode solely with off-axis electron cyclotron heating (ECH) often exhibit strong off-axis peaking of electron temperature profiles at the heating location. Electron heat transport properties near these off-axis temperature peaks have been studied using modulated ECH. The Fourier analyzed electron temperature data have been used to infer electron thermal diffusivity. Comparisons with numerical solutions of the time-dependent electron thermal equation find that the data are consistent with a narrow region with electron diffusivity χ

e
an order of magnitude lower than the average value across the plasma, suggesting an electron internal transport barrier (ITB) near the ECH heating location. Detailed profile analysis and equilibrium reconstructions suggest that the formation of these ITBs are correlated with off-axis values of the safety factor q being near 1. Furthermore, the ECH driven H-mode discharges demonstrate more rapid electron heating rate near the ECH deposition location than L-mode discharges with higher auxiliary ECH heating power. Additional modeling attributes this difference to the modification of electron heat transport in the core at the L-H transition, which also sustains the off-axis electron temperature peaks.
Numerical model of restrikes in gliding arc discharges
Authors: Bourlet Aymeric , Tholin Fabien , Labaune Julien , Pechereau François , Vincent-Randonnier Axel , Laux Christophe O
Published: January 2024

Direct current (DC) electric arcs are of particular interest because they can produce large volumes of thermal plasmas with controlled energy deposition. When such discharges are applied in a gas flow, convection displaces the top of the arc downstream while the arc roots remain attached to the electrodes, thus increasing the length of the arc over time. However, this growth is limited by a restrike phenomenon, which starts from streamers appearing in high electric field regions and shortcutting the long, stretched electric arc. From a numerical point of view, DC arcs can be efficiently simulated with a resistive magneto-hydrodynamics (MHD) model, with numerical requirements in terms of spatial and temporal discretization that are compatible with classic fluid dynamics and combustion simulations. However, arc restrikes rely on the propagation of streamer discharges that are highly non-neutral phenomena, whereas classical MHD assumes neutrality. To tackle this problem, we propose in this paper a model of restrike that can be used in an MHD approach. After describing the ideas of the model, we perform a parametric study of the input parameters to examine its influence on the discharge dynamics.