bluuebunny/crossref_metadata_2025 huggingface dataset:
Low-frequency dynamics of 0.45PMN-0.55PSN solid solution
Authors: Molokov A. Yu. , Koroleva E. Yu. , Bronwald Yu. A. , Vakulenko A. F. , Vakhrushev S. B.
Published: September 2024

Lead magnoniobate-scandoniobate (PMN-PSN) solid solutions are important functional materials for transducer/actuator devices due to their extraordinary dielectric and electromechanical properties. These unique properties are related to the unusual low-frequency relaxation dynamics, which has not been sufficiently understood until now. In our paper the low-frequency relaxation dynamics of 0.45Pb(Mg1/3Nb2/3)O3–0.55Pb(Sc1/2Nb1/2)O3 single crystal is studied in frequency range 10 mHz–1 MHz at temperatures near the dielectric permittivity maximum. Four relaxation processes are identified. Low-frequency mode demonstrating the critical divergence around 306 K is revealed. However, the phase transition into ferroelectric phase at this temperature does not occur. Near 306 K, the appearance of M-type superstructure is found related to the combination of oxygen octahedral rotation and anti-parallel shifts of lead ions. The appearance of the additional order parameter suppresses the slowing down of the ferroelectric mode and the phase transition into the ferroelectric phase occurs only below 295 K. In addition, two relaxation processes, similar to reorientation and “breathing” polar nanoregion (PNR) modes reported for PMN, are found. The sharp softening of “reorientation mode” is observed on cooling from 315 to 295 K with Tf ∼288 K. The fourth relaxation process is the Debye process, and we assume that it is associated with defects relaxation. Below 295 K, all four relaxation processes still exist, but their parameters are practically temperature independent. The low-temperature phase is not exactly a “normal” ferroelectric phase, the PNRs persist in the FE phase.
Numerical modeling and suppression of combustion instabilities in a partially premixed combustor
Authors: Li Shengnan , Liu Xiao , Zhang Zhihao , Lv Guangpu , Zheng Hongtao , Meng Qingyang , Wang Zijun
Published: September 2024

To suppress the combustion instabilities faced in the lean premixed combustion, the impacts of swirler hub configurations on combustion instabilities under elevated pressure are investigated using large eddy simulation combined with a flamelet generation manifold model. Good agreement between the numerical predictions and experimental data is achieved. The flow fields of the combustors with three distinct swirler configurations are simulated: prototype, swirler with lobes on the hub of pilot stage, and with lobes on the hub of the first main stage. Furthermore, dynamic mode decomposition (DMD) is used to extract the dynamic characteristics, and a flame transfer function (FTF) is employed to characterize the fluctuation characteristics. The results show that the prototype combustor demonstrates a coupled fluctuation between flow and heat release. Influenced by the precessing vortex core (PVC), the flame angle varies between 70° and 90° and the first DMD modes of axial velocity, temperature, and heat release rate are all at a frequency of 470 Hz. The lobes on the hub of the pilot stage suppress the formation of PVC, making the combustion very stable. The flame angle remains constant at 80°, and the gain of FTF is lower than 1. However, adding lobes to the first main stage makes the combustion extremely unstable. The flow field structure undergoes drastic changes, mimicking a “breathe” process. The flame surface is highly distorted, and flashback phenomena occur.
Numerical investigation and passive control of dust pollution on a minivan
Authors: Yang Zhendong , Jin Yifeng , Gu Zhengqi
Published: September 2024

A dynamic model using a discrete phase approach was developed to study dust pollution on a minivan's side and rear surfaces. Numerical simulations, validated by road tests, analyzed dust concentration and distribution. A significant factor in sidewall dust pollution is the pressure difference inside and outside the wheel cavity, particularly behind the wheel cavity, which affects about 40% of the sidewall. Large trailing vortices at the rear create a low-pressure zone, leading to rear dust pollution characterized by low concentration, large area, and dispersed regions. Aerodynamic devices were proposed to mitigate pollution. Simulations showed that side attachments, such as wheel deflectors, wheel cavity baffle, and mudguards, reduce aerodynamic drag and sidewall dust pollution, with wheel cavity baffles reducing the affected area by about 48.98%. Rear attachments, like diffusers and roof deflector, minimize rear dust pollution, with roof deflector reducing the area by approximately 87.24%. These findings highlight the effectiveness of aerodynamic modifications in controlling dust pollution on a minivan.
Aerodynamic optimization of double S-duct caret intake by self-adapting non-dominated sorting genetic algorithm
Authors: Wang Bin , Wang Qiang
Published: September 2024

The caret intake could not only provide compressed airflow to the aircraft engine stably but also should have applicable radar stealth performance. Radar stealth means that the echo intensity of the intake should be low when detected by radar, which could be measured by radar cross section (RCS). The airflow distribution of the double S-duct caret intake was numerically optimized to improve aerodynamic performance, with radar stealth performance as constraints. Self-adaptive genetic algorithm and Kriging model were used to improve the optimization efficiency. There could be multiple boundary-layer separations in the S-duct caret intake, resulting in obvious total pressure distortion at the outlet and secondary flow. To suppress these adverse airflow phenomena, the optimization of the double S-duct intake was defined as a problem with two targets and multiple constraints. By defining the probabilities of selection and variation as functions of the iteration number and the fitness, the self-adapting non-dominated sorting genetic algorithm can be applicable for such a problem. Using the Kriging model, which was proven to have satisfactory accuracy in predicting performance parameters, an optimized intake with both excellent aerodynamic and stealth performance was obtained, with a 30% reduction in DC60 value and a 47% reduction in SC60 value compared to the intake before optimization.
Three-dimensional vorticity–velocity formulation in a lattice Boltzmann method
Authors: Kefayati Gholamreza
Published: September 2024

In recent decades, a paradigm shift in macroscopic methods has favored the use of non-primitive variables, such as velocity and vorticity (V–V), over traditional primitive variables. This shift eliminates the need for solving a Poisson equation for pressure, aligning numerical treatments more closely with physical reality. However, the lattice Boltzmann method (LBM), renowned for its efficacy in studying fluid flow phenomena, continues to rely on the conventional pressure–velocity (P–V) approach. This conventional approach necessitates a pressure–density relation, posing challenges in maintaining the incompressible condition. This study pioneers a novel application of the LBM to three-dimensional velocity–vorticity equations, expanding upon our suggested recent method for two-dimensional cases [Kefayati, Phys. Fluids. 36, 013128 (2024)]. To address the complexities introduced by the vortex stretching term in three dimensions, a new equilibrium distribution function is formulated and introduced to the three-dimensional nature of the vorticity vector. The paper details the derivation of the three-dimensional LBM and substantiates its effectiveness through numerical examples, showcasing its applicability in fluid dynamics. By bridging the gap between traditional P–V formulations and the benefits of non-primitive V–V variables, this work contributes to the ongoing exploration of LBM applications in fluid dynamics. The focus on three-dimensional scenarios involving velocity–vorticity equations marks a significant advancement, offering insights into the nuanced dynamics of fluid flow and paving the way for more accurate and realistic simulations in complex environments.
Maximal transport of non-Newtonian fluid in an anisotropic rotating porous channel with an inclined magnetic field
Authors: Gupta Nitish , Vajravelu Kuppalapalle
Published: September 2024

This study explores the flow characteristics of a viscous, incompressible, conducting Jeffrey fluid in a rotating channel filled with anisotropic porous medium with an inclined magnetic field. The study has relevance to fluid motion in striated rock formations and seepage flow in rotating systems across insulation or geological layers. The channel's rotation axis and a principal axis of the permeability tensor are perpendicular to the walls. The flow is described by the Darcy–Brinkman model under no-slip boundary conditions, applicable in regenerative heat exchangers. Key parameters include the rotation rate and the lateral permeabilities. They have significant impacts on flow behavior. Fluid velocity consists of a primary component aligned with the pressure gradient and a secondary component influenced by the Coriolis force. The variation in lateral permeabilities affects the convexity of the velocity profile, while the magnetic field allows for control of both velocity and volumetric flow rates. The Jeffrey parameter and the inclination angle further enhance the flow behavior. This study provides comprehensive analysis through tables and figures for various values of the anisotropic Darcy number and the rotation parameter, detailing the model's physical properties. The effects of the product of skin friction and the Reynolds number are also discussed, with results aligning with the existing literature for limiting cases. These findings offer valuable insights into fluid behavior in complex environments where rotation, porous structures, and magnetic fields interact with implications for process optimization, resource recovery, and sustainable engineering practices.
Self-assembled monolayers: a journey from fundamental tools for understanding interfaces to commercial sensing technologies
Authors: Dief Essam M. , Tilley Richard D. , Gooding J. Justin
Published: September 2024

Self-assembled monolayers were first described in the 1980s and have now become ubiquitous in many interfacial technologies. In this account, we discuss different self-assembled monolayer systems, outlining their positives and negatives. We then overview other researchers’ work and our own group’s journey in using self-assembled monolayers to develop new concepts in sensing and addressing general challenges faced by many types of sensors. Finally, we reflect on some of the challenges monolayer chemistry needs to address to facilitate further use of this powerful surface chemistry in commercial devices.
Septo-dentate gyrus cholinergic circuits modulate function and morphogenesis of adult neural stem cells through granule cell intermediaries
Authors: Chen Ze-Ka , Quintanilla Luis , Su Yijing , Sheehy Ryan N. , Simon Jeremy M. , Luo Yan-Jia , Li Ya-Dong , Chen Zhe , Asrican Brent , Tart Dalton S. , Farmer W. Todd , Ming Guo-Li , Song Hongjun , Song Juan
Published: September 2024

Cholinergic neurons in the basal forebrain play a crucial role in regulating adult hippocampal neurogenesis (AHN). However, the circuit and molecular mechanisms underlying cholinergic modulation of AHN, especially the initial stages of this process related to the generation of newborn progeny from quiescent radial neural stem cells (rNSCs), remain unclear. Here, we report that stimulation of the cholinergic circuits projected from the diagonal band of Broca (DB) to the dentate gyrus (DG) neurogenic niche promotes proliferation and morphological development of rNSCs, resulting in increased neural stem/progenitor pool and rNSCs with longer radial processes and larger busy heads. Interestingly, DG granule cells (GCs) are required for DB-DG cholinergic circuit–dependent modulation of proliferation and morphogenesis of rNSCs. Furthermore, single-nucleus RNA sequencing of DG reveals cell type–specific transcriptional changes in response to cholinergic circuit stimulation, with GCs (among all the DG niche cells) exhibiting the most extensive transcriptional changes. Our findings shed light on how the DB-DG cholinergic circuits orchestrate the key niche components to support neurogenic function and morphogenesis of rNSCs at the circuit and molecular levels.
Soul
is a master control gene governing the development of the
Drosophila
prothoracic gland
Authors: Liu Wen , Yan Minyi , King-Jones Kirst
Published: September 2024

The prothoracic gland (PG) is a major insect endocrine organ. It is the principal source of insect steroid hormones, and critical for key developmental events such as the molts, the establishment of critical weight (CW), pupation, and sexual maturation. However, little is known about the developmental processes that regulate PG morphology. In this study, we identified
soul
, which encodes a PG-specific basic helix–loop–helix (bHLH) transcription factor. We demonstrate that Tap, also a bHLH protein, dimerizes with Soul. Both are expressed in the developing PG. Interfering with either
soul
or
tap
function caused strikingly similar phenotypes, resulting in small and fragmented PGs, the abolishment of steroid hormone-producing gene expression, larval arrest, and a failure to undergo metamorphosis. Furthermore, both
soul
and
tap
showed expression peaks just prior to the CW checkpoint. Disrupting
soul-
or
tap-
function before, but not after, the CW checkpoint caused larval arrest, and perturbed highly similar gene cohorts, which were enriched for regulators and components of the steroid hormone biosynthesis pathway. Intriguingly, a chitin-based cuticle gene,
Cpr49Ah
, and a POU domain transcription factor gene,
pdm3
, are direct target genes of the Soul/Tap complex, and disruption of either phenocopied key aspects of
soul/tap
loss-of-function phenotypes. Taken together, our findings demonstrate that the Soul/Tap heterodimer resides at the top of a complex gene hierarchy that drives PG development, CW establishment, and steroid hormone production.
Global fishing patterns amplify human exposures to methylmercury
Authors: Li Mi-Ling , Thackray Colin P. , Lam Vicky W. Y. , Cheung William W. L. , Sunderland Elsie M.
Published: September 2024

Global pollution has exacerbated accumulation of toxicants like methylmercury (MeHg) in seafood. Human exposure to MeHg has been associated with long-term neurodevelopmental delays and impaired cardiovascular health, while many micronutrients in seafood are beneficial to health. The largest MeHg exposure source for many general populations originates from marine fish that are harvested from the global ocean and sold in the commercial seafood market. Here, we use high-resolution catch data for global fisheries and an empirically constrained spatial model for seafood MeHg to examine the spatial origins and magnitudes of MeHg extracted from the ocean. Results suggest that tropical and subtropical fisheries account for >70% of the MeHg extracted from the ocean because they are the major fishing grounds for large pelagic fishes and the natural biogeochemistry in this region facilitates seawater MeHg production. Compounding this issue, micronutrients (selenium and omega-3 fatty acids) are lowest in seafood harvested from warm, low-latitude regions and may be further depleted by future ocean warming. Our results imply that extensive harvests of large pelagic species by industrial fisheries, particularly in the tropics, drive global public health concerns related to MeHg exposure. We estimate that 84 to 99% of subsistence fishing entities globally likely exceed MeHg exposure thresholds based on typical rates of subsistence fish consumption. Results highlight the need for both stringent controls on global pollution and better accounting for human nutrition in fishing choices.
Pressure-Induced Structural Transition and Enhanced Photoelectric Properties of Tm2S3
Authors: Shen 申 Zhi-Wei 志伟 , Wu 邬 Zhong-Yan 中炎 , Wang 王 Shao-Jie 绍杰 , Wang 王 He-Chong 贺冲 , Li 李 Hong-Kai 宏凯 , Song 宋 Jing 静 , Gao 高 Guo-Ying 国英 , Wang 王 Lin 霖 , Tian 田 Yong-Jun 永君
Published: September 2024

Rare earth sesquisulfides have drawn growing attention in photoelectric applications because of their excellent electronic and photoelectric properties upon compression. We investigate the structural, electrical, and photoelectric properties of Tm2S3 under high pressure through electrical impedance, UV-vis absorption, Raman spectroscopy, x-ray diffraction, and photoelectric measurements. It is found that δ-Tm2S3 transforms into high-pressure α-phase around 5 GPa, accompanied by a substantial reduction in atomic distance, bandgap, and resistivity. Consequently, the photocurrent density and responsivity of Tm2S3 exhibit dramatic increase behavior, achieving five orders of magnitude enhancement in α-phase compared with the initial δ-Tm2S3. Moreover, α-phase maintains a high photocurrent responsivity of three orders of magnitude after unloading. This work demonstrates significant enhancement of the photoelectric properties of Tm2S3 by applying pressure, which paves the way for improving the performance of future photoelectric devices.
A framework for curriculum transformation in quantum information science and technology education
Authors: Goorney Simon , Bley Jonas , Heusler Stefan , Sherson Jacob
Published: September 2024

The field of Quantum Information Science and Technology (QIST) is booming. Due to this, many new educational courses and university programs are needed in order to prepare a workforce for the developing industry. Owing to its specialist nature, teaching approaches in this field can easily become disconnected from the substantial degree of science education research which aims to support the best approaches to teaching in Science, Technology, Engineering and Mathematics fields. In order to connect these two communities with a pragmatic and repeatable methodology, we have synthesised this educational research into a decision-tree based theoretical model for the transformation of QIST curricula, intended to provide a didactical perspective for practitioners. The Quantum Curriculum Transformation Framework consists of four steps: (1) choose a topic, (2) choose one or more targeted skills, (3) choose a learning goal and (4) choose a teaching approach that achieves this goal. We show how this can be done using an example curriculum and more specifically quantum teleportation as a basic concept of quantum communication within this curriculum. By approaching curriculum creation and transformation in this way, educational goals and outcomes are more clearly defined which is in the interest of the individual and the industry alike. The framework is intended to structure the narrative of QIST teaching, and with future testing and refinement it will form a basis for further research in the didactics of QIST.
Nodes and energy flow in the transverse oscillations of resonantly end-driven stretched strings with viscous damping
Authors: Repetto C E , Roatta A , Welti R
Published: September 2024

Most of the works that analyze the forced oscillations of strings assume that, although they can support a tension T, they are perfectly elastic/flexible entities that do not have losses. In this work we will show that the incorporation of losses, even maintaining the analysis in a linear regime, allows us to clarify some details of the behavior that is observed in the forced oscillations of a real string. By introducing a dissipative force into the analysis, it is possible to predict not only the resonance frequencies but also how the oscillation amplitudes depend on the strength of the driving force. We can also analyze the variation of the amplitude of the antinodes when the excitation frequency approaches the resonance frequency. This amplitude variation has a behavior very similar to that of the resonance amplitude of a spring-mass oscillator. It is generally recognized that the nodes of a string, in forced oscillation, are not points of absolute rest because the energy of vibration must be transmitted through these points. However, it is difficult to find works that analyze the peculiar properties of this small movement. In this work we calculate the amplitudes of the nodes and deduce the peculiar properties of their movement. We also calculate the time averaged energy that flows along the string, from its excitation point to its fixed end.
Time-resolved Auger–Meitner spectroscopy of the photodissociation dynamics of CS2
Authors: Thompson Henry J , Plekan Oksana , Bonanomi Matteo , Pal Nitish , Allum Felix , Brynes Alexander D , Coreno Marcello , Coriani Sonia , Danailov Miltcho B , Decleva Piero , Demidovich Alexander , Devetta Michele , Faccialà Davide , Feifel Raimund , Forbes Ruaridh , Grazioli Cesare , Holland David M P , Piseri Paolo , Prince Kevin C , Rolles Daniel , Schuurman Michael S , Simoncig Alberto , Squibb Richard J , Tenorio Bruno N C , Vozzi Caterina , Zangrando Marco , Callegari Carlo , Minns Russell S , Di Fraia Michele
Published: September 2024

The photodissociation dynamics of UV excited CS2 are investigated using time-resolved Auger–Meitner (AM) spectroscopy. AM decay is initiated by inner-shell ionisation with a femtosecond duration x-ray (179.9 eV) probe generated by the FERMI free electron laser. The time-delayed x-ray probe removes an electron from the S(2p) orbital leading to secondary emission of a high energy electron through AM decay. We monitor the electron kinetic energy of the AM emission as a function of pump-probe delay and observe time-dependent changes in the spectrum that correlate with the formation of bound, excited-state CS2 molecules at early times, and CS + S fragments on the picosecond timescale. The results are analysed based on a simplified kinetic scheme that provides a time constant for dissociation of approximately 1.2 ps, in agreement with previous time-resolved x-ray photoelectron spectroscopy measurements (Gabalski, et al 2023 J. Phys. Chem. Lett. 14 7126–7133).
The influence of resonant light pulses on high harmonic generation in solids
Authors: Shao Tian-Jiao , Hu Fang , Zhang Qiu-Lan , Zou Huan-Qing , Yang Ai-Guo
Published: September 2024

We have theoretically studied high harmonic generation (HHG) in solids driven simultaneously by a mid-infrared (MIR) laser and a high-order harmonic pulse with energy around the band gap between the valence band and conduction band. By adding this resonant harmonic light pulse with the relative intensity ratio of 4%, the high-order harmonic emission from the crystal is enhanced by 1–2 orders of magnitude. The yield of HHG in solid increases monotonically with the relative strength of the resonant harmonic pulses. In addition, we also found that HHG dynamics from the k channel around the boundary of the Brillouin zone can be selectively enhanced by adjusting the frequency of the resonant high-order harmonic pulse. The resonance-enhanced HHG and k channel selection effect in solids is also investigated by using the three-band semi-conductor Bloch equation for HHG in ZnO. We also find that the harmonic in the plateau region driven by adding a resonant light field to the strong MIR driving field has less red-shifted compared with the case driven by the MIR driving field alone.
Relativistic coupled-cluster calculations for the molecular properties of AlX+ (X: F, Cl, Br, I, At and Ts) ions
Authors: Thakur Ankush , Bala Renu , Nataraj H S , Prasannaa V S
Published: September 2024

In this article, the molecular permanent electric dipole moments and components of static dipole polarizabilities for the electronic ground state of singly charged aluminum monohalides are reported. The coupled-cluster method by considering single and double excitations (CCSD) together with relativistic Dyall basis sets have been used to carry out these molecular property calculations. The contribution from triple excitations are incorporated through perturbative triples (CCSD(T)). The results from a series of progressively larger basis sets are extrapolated to the complete basis set limit. Further, the role of correlation and relativistic effects, and also the effect of augmentation over the considered basis sets on the valence molecular properties are studied. Our results are compared with those available in the literature.
Effect of AFM ordering on thermoelectric responses of Mg3X2 (X: C, Si, Ge) monolayers : a DFT insight
Authors: Basak Krishnanshu , Ghosal Supriya , Nath Subhadip , Jana Susmita , Jana Debnarayan
Published: September 2024

Two-dimensional materials have gained a lot of attention in the last few decades due to their potential applications in thermoelectric and nano-electronic devices. This study systematically presents the mechanical, electronic and thermoelectric characteristics of two-dimensional honeycomb-kagome

Mg

3

X

2

(

X

:

C

,

Si

,

Ge

) structures in the framework of density functional theory computations and by solving semiclassical Boltzmann transport equation. The geometrical stability of these structures is validated by phonon spectrum and molecular dynamics simulations. Following the elastic constants, we have inferred that all the systems are mechanically stable and brittle in nature. Lower values of Debye temperature of all structures suggest that

Mg

3

X

2

monolayers should have lower values of lattice thermal conductivity compared to graphene. Electronic structure calculations indicate that these materials are semimetallic in their nonmagnetic phase. All the structures display remarkably low lattice thermal conductivity (0.9-1.5 W (mK)−1) due to a large scattering factor and higher anharmonicity. The presence of sharp density of states peaks close to the Fermi level, arising from nearly flat and dispersionless band in the antiferromagnetic (AFM) arrangement, is poised to enhance the Seebeck coefficient, thereby potentially boosting the thermoelectric performance. The estimated values of thermoelectric figure of merit (ZT) are around 0.78 and 0.67 for

Mg

3

Si

2

and

Mg

3

Ge

2

structure respectively in AFM phase at T = 700 K. These outcomes of our findings suggest that

Mg

3

X

2

monolayers exhibit substantial promise for thermoelectric device application.
Coincidence detection probability of

(
γ
,
2
e
)

photoemission measurement
Authors: Su Yuehua , Cao Kun , Zhang Chao
Published: September 2024

In the study of strongly correlated electrons, one of the challenging core tasks is to develop the potential techniques for direct detection of the many-body correlations of strongly correlated electrons. The

(
γ
,
2
e
)

photoemission technique has been developed to investigate the two-body correlations of the target correlated electrons. In this article, we will focus on this technique for the correlated electrons near the Fermi energy in condensed matter. The coincidence detection probability of the two emitted electrons in the

(
γ
,
2
e
)

photoemission measurement is shown to be relevant to a two-body Bethe–Salpeter wave function, which describes the dynamical two-body correlations of the target correlated electrons near the Fermi energy. As the coincidence detection probability involves an electron–electron interaction matrix element, the arbitrary momentum and/or energy transfer due to this electron–electron interaction makes the

(
γ
,
2
e
)

photoemission technique fail to reveal the inner-pair structures of the two-body Bethe–Salpeter wave function. However, the center-of-mass momentum and energy of the two-body Bethe–Salpeter wave function can be distinctly resolved. Thus, the

(
γ
,
2
e
)

photoemission technique can provide the center-of-mass physics of the two-body correlations of the target correlated electrons. It will be one potential technique to study the center-of-mass physics of the Cooper pairs in superconductor.
Distribution of radon in large workplaces: an analysis performed on radon levels measured in UK schools
Authors: Kouroukla E , Gooding T D
Published: September 2024

Radon is a radioactive, carcinogenic gas formed by the radioactive decay of uranium and radium that occur naturally in small amounts in all rocks and soils. It is the largest single source of radiation exposure to the UK population, contributing to more than 1 100 lung cancer deaths each year according to an analysis conducted in 2005. Regulations exist to protect employees (and other persons) where radon concentrations exceed the reference level of 300 Bq m−3. Once the reference level is exceeded, annual doses of more than the public dose limit of 1 mSv a−1 are considered to be excessive. A radon measurement campaign for schools, which started in 2009, generated a large dataset, including those with high numbers of simultaneous radon measurements. Radon data between buildings (e.g. homes) have been shown to correspond broadly to the lognormal distribution, after the additive contribution of outside air has been removed. However, there are fewer studies of the distribution of radon levels within a single, large property. Radon data collected from 533 UK schools with at least 20 valid, simultaneous results were analysed against several statistical models. In approximately 50% of schools the radon levels could be represented by the lognormal distribution and in 60% by the loglogistic lognormal distribution, the latter being a better fit probably owing to its lower sensitivity to the tails of the distribution. Qualitatively, the lognormal and the loglogistic probability plots appeared to be indistinguishable. These findings indicate that the lognormal and loglogistic might be appropriate models to characterise the distribution of radon in most large workplaces. For each statistical model, the two distribution parameters can be used to provide a better estimate of the average dose to the occupants. However, caution is required when assessing doses, since the average estimator of the radon concentration does not predict the highest value and may significantly underestimate or overestimate the dose in specific areas.
Measurement method of flexible component pose based on discrete motion actuators
Authors: Wu Zhengtao , Li Shuanggao , Chu Wenmin , Huang Xiang
Published: September 2024

In order to address the limitations of traditional large discrete motion actuator mechanisms in realizing high-precision inter-axis relationship calibration in manufacturing environments, this paper proposes a new convolutional neural network-based attitude mapping estimation method, component pose using convolutional neural network (CPCNN). The method implicitly encodes the inter-axis relation matrix into the weight parameters of the training neural network, which results in a high degree of integration with existing large discrete motion actuator mechanisms. The CPCNN-based method directly obtains the attitude change of the adjustment cabin by reading the change of each axis of the current motion actuator mechanism in its own coordinate system. This method can overcome the limitations of the experimental process in the traditional calibration methods and improve the accuracy of attitude mapping under the influence of self-weight by selecting better motion parameters through redundant degrees of freedom. The application of this new method will provide an effective solution for the high-precision inter-axis relationship calibration of large discrete motion actuator mechanisms in manufacturing environments, offering new possibilities for improving production efficiency and product quality.
A comprehensive bearing prognosis framework based on piecewise function stacking convolution auto-encoder and XGBoost algorithm
Authors: Chi Huashan , Wei Yuanyu , Yuan Bo , Sun Qingchao , Shu Liming
Published: September 2024

Accurately forecasting the remaining useful life (RUL) stands as a pivotal and formidable task within the realm of prognostics and health management. However, there is limited research that considers integrating early fault diagnosis during the bearing’s lifecycle with the prediction of its RUL. In this article, a comprehensive bearing prognosis framework based on piecewise function stacking convolution auto-encoder (AE) and XGBoost algorithm is proposed. To achieve this, an unsupervised piecewise function-based deep stacked convolutional AE was designed to construct the health indicator (HI) of the bearing for reducing the dependency on prior knowledge and furnishing a dynamic foundation for predicting RUL. The 4σ criterion based on HI’s increment was proposed for determining the fault occurrence time (FOT) of the bearing’s operational process. Subsequently, an XGBoost algorithm model was utilized to predict the RUL of faulty bearings. The efficacy of the bearing prognosis framework was validated by two real bearing test datasets. Results indicate the employed criterion of construct HI can flexibly adjust to various operational conditions and accurately pinpoint the bearing’s FOT. Furthermore, the findings demonstrate the proposed bearing prognosis framework achieves superior performance compared with several conventional anomaly detection methods.
Vibration displacement measurement of bridge structural models using image super-resolution reconstruction and visual object detection network
Authors: Wang Sen , Yang Rongliang , Chen Mingfang , Lin Sen , Wang Qingjian
Published: September 2024

Visual vibration measurement has emerged in the field of structural health monitoring in recent years, but it still has some shortcomings in terms of resolution, recognition rate and real-time performance. Considering the three aspects of recovering high-frequency image details, improving the compactness of the target bounding box, and reducing the computational time, we use the constructed image super-resolution reconstruction model and target detection model to measure the vibration displacement of the bridge structural model. First, we integrate the Transformer module into the Unet network with a simple structure. The Swin and Global Transformer Unet (SGTU) module constructed in this form can reduce the computational cost while reconstructing the large-resolution feature map target, and it can sharply edge information of the vibration target. We use the framework of the YOLOv5 algorithm as the backbone, and use the GhostBottleneck (GB) module to reduce the time for convolution operations to generate similar features. In addition, the proposed DWCBottleneck (DWCB) fusion module is also able to achieve high-level semantic fusion and network depth expansion with minimal computational cost. Finally, the center point offset of the bounding box predicted by the model can be used to obtain the displacement offset of the object in the image sequence. The position information of the target in the first frame image is used as the reference frame for calculating the offset, and the vibration displacement of the flexible structure in the image coordinate system is obtained by calculating the deviation of the displacement between the remaining frames and the first frame. We perform qualitative and quantitative comparisons in three aspects: video super-resolution reconstruction, visual detection robustness, and sensor vibration measurement displacement using a homemade vibration image dataset. The time–frequency domain displacement curves regressed by the visual vibration measurement algorithm are compared with the curves acquired after accelerometer acquisition, indicating the necessity of super-resolution reconstruction in visual vibration measurement.
In-flight pixel degradation of the Sentinel 5 Precursor TROPOMI-SWIR HgCdTe detector
Authors: van Kempen Tim A , Lobanova Marina , van Hees Richard , Masarotto Valentina , Tol Paul , Kurchaba Solomiia , Hoogeveen Ruud W M
Published: September 2024

The TROPOMI-SWIR HgCdTe detector on the Sentinel-5 Precursor mission has been performing in-orbit measurements of molecular absorption in Earth’s atmosphere since its launch in October 2017. In its polar orbit the detector is continuously exposed to potentially harmful energetic particles. Calibration measurements taken during the eclipse are used to inspect the performance of this detector. This paper explores the in-orbit degradation of the HgCdTe detector. After five years, the detector is still performing within specifications, even though pixels are continuously hit by cosmic radiation. The bulk of the impacts have no lasting effects, and most of the damaged pixels (95%) appear to recover on the order of a few days to several months, attributed to a slow spontaneous recovery of defects in the HgCdTe detector material. This is observed at the operational temperature of 140 K. The distribution of the observed recovery times has a mean around nine days with a significant tail towards several months. Pixels that have degraded have a significant probability to degrade again. The location of faulty pixels follows a Poissonian distribution across the detector. No new clusters have appeared, revealing that impacts are dominated by relatively low energetic protons and electrons. Due to the observed spontaneous recovery of pixels, the fraction of pixels meeting all quality requirements in the nominal operations phase has always been over 98.7%. The observed performance of the TROPOMI-SWIR detector in-flight impacts selection criteria of HgCdTe detectors for future space instrumentation.
Hair-YOLO: a hair follicle detection model based on YOLOv8
Authors: Zhu Zhibo , Wei Guoliang , Wu Junke , Liu Shuting , Chen Bo , Zhang Zhenyu , Li Qimin
Published: September 2024

Hair follicle detection technology has developed rapidly in recent years. Traditional manual detection methods are labor-intensive and inefficient. To address this problem, we propose a real-time hair follicle detection model called Hair-YOLO based on YOLOv8. This model focuses on accurately identifying the number of hairs within each follicle, providing precise data that help doctors assess hair density and follicle health of patients. First of all, we incorporate the re-parameterization Ghost module into the backbone, reducing the parameters and computational load. Then, the deformable convolution v3 operator is integrated into the neck network, enhancing adaptation to follicle shapes. Next, we propose a novel multi-scale feature perception separated and enhancement attention (Multi-SEAM) module, building upon the SEAM module, to address complex scalp scenarios. Furthermore, we enhance bounding box regression by replacing the standard complete intersection over union loss, with a modified point distance intersection over union loss. Finally, we construct a new hair follicle dataset and use it for a comparative analysis of Hair-YOLO and established models. Our model shows excellent performance, with a 14.26% increase in mAP@0.5:0.95, a 2.98% increase in Recall, and a 4.31% increase in Precision compared to the baseline.
A multi-scale deep residual network-based guided wave imaging evaluation method for fatigue crack quantification
Authors: Jing Hutao , Yuan Shenfang , Chen Jian , Meng Yixing
Published: September 2024

As a promising structural health monitoring technology, guided wave (GW) imaging is gaining increasing attention for crack monitoring of aircraft structures. However, actual fatigue crack propagation is a complex dynamically evolving process affected by various variabilities. It is still challenging to accurately track and quantify the dynamic fatigue crack propagation with GW imaging methods. Therefore, in order to achieve more accurate fatigue crack quantification, this paper proposes a multi-scale deep residual network-based GW imaging evaluation method. A convolutional neural network (CNN) is utilized to evaluate the entire pixel distribution of GW imaging maps to fuse damage-related information from multiple GW monitoring paths. By designing multi-scale convolutional kernels and deep residual learning, a robust quantitative image feature extraction is ensured with the dynamic evolution process of fatigue crack growth and the performance degradation is avoided as the CNN goes deeper, thereby improving the quantification accuracy. The method is validated on a fatigue test of landing gear beams, which are important load-carrying aircraft structural components. The results demonstrate that the proposed method can extract multi-scale crack length-related features and accurately track fatigue crack propagations. For batch specimens, the maximum quantification error is reduced from the original 6.1 mm to 1.6 mm, marking a significant improvement.
Research on fault diagnosis for three-phase rectifier device in direct current transmission system based on continuous wavelet transform and vision transformer
Authors: Wang Siyu , Jia Zhen , Li Yang , Yang Qiqi
Published: September 2024

As a core component of photovoltaic power generation systems, the three-phase rectifier device plays a crucial role, and its failure can potentially reduce energy conversion efficiency and output quality. Presently, the performance of fault time-domain signal diagnosis methods based on three-phase rectifier circuits is challenging to enhance. This paper proposes a novel fault detection method for three-phase rectifier devices based on Vision Transformer, referred to as CWT-ViT, to address this issue. This method transforms time-domain fault signals into images through Continuous Wavelet Transform (CWT), subsequently inputting these images into a Vision Transformer model. Relying on its powerful self-attention mechanism and fully connected layers, it realizes the extraction and learning of rectifier device image features. A Simulink simulation model of a three-phase bridge controllable rectifier circuit is established for fault injection to collect fault signals. Fault diagnosis experiments demonstrate that the proposed diagnostic method achieves a prediction accuracy of 98.6%, maintaining a relatively high precision level. In comparison to four excellent classification models currently available: AlexNet, RepVGG, ResNet, and GoogLeNet, the proposed method demonstrates superior diagnostic performance. Additionally, this paper conducts ablation experiments to meticulously analyze the impact of each module in the fault diagnosis process. This research achieves more precise and efficient fault diagnosis in photovoltaic power generation systems, thereby reducing downtime and maintenance costs for actual equipment and enhancing the stability of photovoltaic power generation systems. This research provides an innovative, intelligent solution for the intelligent operations and maintenance of photovoltaic power generation.
Applications of deep learning-based denoising methodologies for scanning electron microscope images
Authors: Shin Seoleun , Lee In-Ho , Park Byong Chon , Song Joo-Hyun
Published: September 2024

In this paper, we use five types of deep-learning algorithms for denoising scanning electron microscope (SEM) measurement data. Denoising of SEM images is an important task since the images often suffer from noise, which can make it difficult to accurately interpret the data. We also investigate realistic SEM denoising characteristics using a variety of metrics to assess the quality of denoised images. Overall, we find that the trained generative models provide superior denoising performance and that it is crucial to objectively quantify the performance, just like in the scanning process itself. It is anticipated that the deep-learning based technique can accelerate image measurements, which can be utilized for very fast analytical investigations. We also demonstrate that the success of a generative model may depend on the appropriate assessment of noise characteristics in the specific image data analysis of interest. Moreover, it is addressed that denoising performance can be properly evaluated when a relevant metrics that aligns well with human visual systems.
Three-dimensional reconstruction of bubble geometry from single-perspective images based on ray tracing algorithm
Authors: Song Yuchen , Huang Guangyuan , Yin Junlian , Wang Dezhong
Published: September 2024

An improved shadow-based imaging method combined with a ray-tracing algorithm is proposed for three-dimensional (3D) reconstruction of bubble mesostructures. The 3D micro-scale interface measurement of bubbles categorized as transparent objects is challenging at the forefront of research in the field of multiphase flows. In the study, a reconstruction algorithm is developed using a single high-speed camera under a small-angle diffused backlight source based on Helmholtz reciprocity, Gaussian optics, and Snell’s law. The accuracy of the algorithm is assessed by comparing the reconstruction results of the rendered images generated from the 3D model using Blender. Standard models include a transparent hollow sphere model and several irregular bubble models. The accuracy of the algorithm is determined by analyzing and comparing the contour lines along the edges of the bubble models. The error of the method in the paper can be improved below 5% with the ray tracing optimization. The average uncertainty U
c is 2.8%, according to the evaluation of the models in Blender. The extreme deformation of the bubbles in a turbulent flow field enhanced by ultrasonic is performed to evaluate the 3D reconstruction algorithm. Prior to the fragmentation of bubbles into micro/nanobubbles by ultrasonication, the bubble surface undergoes severe deformation under continuous bombardment by small-scale turbulence eddies. The proposed algorithm exhibited high accuracy and easily performing in experiments.
A new method for thermal runaway warning of electric vehicle charging
Authors: JiaQi Zhang , DeXin Gao , YuanMing Cheng , Qing Yang
Published: September 2024

With the large-scale development of electric vehicle (EV) in China, the frequent occurrence of EV fire accidents has attracted the attention of insiders to the fault monitoring and early warning during the charging process of EV. According to data from the National Emergency Management Ministry, there were over 3,000 EV fire accidents nationwide in 2023, underscoring the urgency for enhanced fault monitoring and early warning measures. In response to these issues, this article proposes an EV thermal runaway early warning method based on Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) by combining the two technologies. The method aims to improve EV safety by monitoring battery status for early thermal runaway warning. First, the historical normal charging data of the battery are preprocessed and feature extracted using the TCN, and then features fed into GRU for time-series modeling and forecasting. This combined model not only demonstrates high prediction accuracy and stability but also swiftly responds to abnormal conditions during charging, effectively preventing thermal runaway accidents and ensuring charging safety. Furthermore, this model possesses excellent generalization capabilities and can adapt to different types and specifications of EV battery systems.