bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial intelligence control of flow separation from a curved ramp
Authors: Wu Zhi , Xu Ge , He Shengtai , Zhou Yu
Published: November 2024

This work aims to control flow separation from a two-dimensional curved ramp. The Reynolds number examined is Reθ = 5700 based on the momentum thickness of the turbulent boundary layer right before the ramp. Three steady jets, blowing tangentially along the ramp from three spanwise slits, are deployed at the most likely flow separation position, upstream and downstream of this position, respectively. Three different control modes are investigated, i.e., a single jet, multiple jets, and genetic algorithm-optimized blowing rates of three jets. The single jet placed at the time-averaged flow separation position is found to be most effective and efficient in eliminating flow separation among the first and second control modes. However, it is the third control mode that may not only eliminate the separation bubble completely but also cut down the energy consumption, by up to 30%, compared to the single jet blowing at the flow separation position. The flow physics underlying the control modes is also discussed.
Pulse electroosmotic flow of Newtonian fluids in parallel plate microchannels under triangular and half-sinusoidal pulse electric fields
Authors: Li Dongsheng , Li Haibin , Liu Jiaofei
Published: November 2024

Unlike the conventional electroosmotic flow (EOF) driven by direct current and alternating current electric fields, this study investigates the pulse EOF of Newtonian fluids through a parallel plate microchannel actuated by pulse electric fields. Specifically, the pulses considered encompass triangular and half-sinusoidal pulse waves. By applying the Laplace transform method and the residual theorem, the analytical solutions for the velocity and volumetric flow rate of the pulse EOF associated with these two pulse waves are derived, respectively. The influence of pulse width a¯ and electrokinetic width K on velocity is further considered, while the volumetric flow rate as a function of time t¯ and electrokinetic width K is examined separately. A comparison of the volumetric flow rates related to these two pulse waves under varying parameters is also conducted. The research findings indicate that irrespective of the pulse wave, a broader pulse width results in a prolonged period and increased amplitude of the velocity profile. Elevating the electrokinetic width yields higher near-wall velocities, with negligible effect on near-center velocities. It is noteworthy that regardless of the electrokinetic width, the near-wall velocity exceeds that of the near-center during the first half-cycle, while the situation reverses during the second half-cycle. The volumetric flow rate varies periodically with time, initially surging rapidly with electrokinetic width before gradually stabilizing at a constant level. More interestingly, independent of pulse width and electrokinetic width, the volumetric flow rates linked to the half-sinusoidal pulse wave consistently surpass those of the triangular pulse wave. For any pulse width, the volumetric flow rates corresponding to the two pulse waves grow with higher electrokinetic widths, especially prominent at alternating intervals of the two half-cycles within a complete cycle. These findings have important implications for improving the design and optimization of microfluidic devices in engineering and biomedical applications utilizing pulse EOF.
Experimental investigation on fracture propagation in shale fractured by high-temperature carbon dioxide
Authors: Ge Jiao , Yao Chuanjin , Zhang Qi , Huang Xingheng , Guo Tiankui , Guo Shenglai
Published: November 2024

The productivity of shale reservoirs was significantly enhanced by the high-temperature CO2 fracturing technique. The injection of high-temperature CO2 into the formation induced rock fracture propagation, creating advantageous pathways for fluid flow. In this research, a self-developed in situ high-temperature convective heat simulation experimental apparatus was employed to systematically conduct simulated experiments on high-temperature CO2 fractured shale under different influencing factors. The experimental results demonstrated that the permeability of CO2 increased as the injection temperature increased. The rock fracture pressure was effectively reduced by high-temperature CO2 fractured shale. Higher complexity was observed in fracture propagation, accompanied by a substantial increase in microcracks and branching fractures. The shale fracture pressure increased with increasing triaxial stress and CO2 injection rate. The confining pressure restricted the further propagation of fractures under relatively high stress conditions, thereby reducing the width and density of fractures, lowering the fracture complexity. Nevertheless, the thermal shock effect of the fluid was exacerbated as the injection rate of high-temperature CO2 increased. The initiation of microcracks was facilitated by the intensification of local thermal stress in shale, inducing multiple curved fractures and forming a more complex fracture network. Compared to horizontal bedding shale, the fracture pressure of vertical bedding shale was relatively higher during high-temperature CO2 fracturing. In addition, the geometric morphology of fracture propagation was more complex, characterized by rougher fracture surfaces, leading to a greater improvement in reservoir reconstruction volume. This research contributed to the optimization of CO2 resource utilization, provided experimental evidence for the application of high-temperature convection fracturing technology in in situ shale conversion projects.
Redifining RADEN’s high-resolution neutron imaging capabilities
Authors: Sans-Planell Oriol , Shinohara Takenao , Grazzi Francesco , Cantini Francesco , Su Yuhua , Matsumoto Yoshihiro , Parker Joseph D. , Manke Ingo
Published: November 2024

This study presents a significant development in the Energy-Resolved Neutron Imaging System RADEN, in the Japan Proton Accelerator Research Complex, Japan. Through a systematic study, the collimation power of the facility was reevaluated. What was initially considered to be values of 230, 420, and 760 have been proven to be much higher. To perform the calculation of the L/D factor of the beam, a state-of-the-art method has been used, along with a standard reference sample to measure the resolution of neutron images. To add robustness to the results, the study compares five different scintillators of different composition and thickness [6LiF:ZnS(Ag) of 50, 100, 200, and 300 μm and Gd2O2S of 50 μm]. The calculated collimating power of the beam ranges between 470 and 1520. These results place a spotlight on an existing discrepancy between the geometrically calculated L/D and the actual measurable quantity, as well as highlight the superior performance of the RADEN beamline.
Novel chaotic image cryptosystem based on dynamic RNA and DNA computing
Authors: Zhou Shuang , Wei Yi , Wang Shiyu , Iu Herbert Ho-Ching , Zhang Yingqian
Published: November 2024

In view of the security problems of image encryption algorithms encoded by single DNA or RNA, to increase the randomness of the diffusion process and the uncertainty of the coding rules, we propose a combining dynamic RNA and DNA computing based chaotic image encryption algorithm, which has a more complicated encryption process for improving the security of the encryption algorithm and increases the difficulty of decoding. First, a new three-dimensional hyperchaotic map is proposed, which exhibits a rich set of dynamic behaviors. Second, the sequences generated by the proposed map are passed to NIST test with good randomness and implemented by digital signal processing hardware, which shows the feasibility of the proposed chaotic map for industrial applications. Second, the K-means algorithm is used to split the plaintext into two parts. Third, the chaotic sequence is used to displace and diffuse the two parts of the plaintext, respectively. Then, chaotic sequences were used to encode using dynamic DNA and RNA of these two parts, respectively. Then, the chaotic sequences were used to compute the dynamic DNA and RNA computing of these two parts, respectively. Finally, the cipher text is decoded accordingly. The experimental results show that compared with some related encryption algorithms, our method has higher security.
Ultra-wideband tunable transparent all-dielectric absorber based on a saline water-filled PMMA periodic structure
Authors: Pan Zeyu , Wu Haibin , Tian Ye , Lv Bo
Published: November 2024

With the rapid development of electromagnetic technology, the demand for high-performance microwave absorbing materials is increasing. This paper proposes a novel design for an ultra-wideband, transparent, and tunable all-dielectric absorber based on a saline water-filled polymethyl methacrylate periodic structure. The performance of the absorber is comprehensively evaluated through theoretical analysis, numerical simulations, and effective medium theory. The results demonstrate that the designed absorber achieves an absorption rate of over 90% in the frequency range of 23.75–47.01 GHz, showcasing excellent wideband characteristics. The absorber also exhibits good angular stability, maintaining high absorption efficiency even at a large incidence angle of 60°. By adjusting the temperature and concentration of the saline water, dynamic tuning of the absorption band can be achieved, providing flexibility for different application scenarios. Analysis of the electric field distribution and power loss density reveals the absorption mechanism, confirming the critical role of saline water in the absorption process. The effective medium theory further explains the wideband characteristics and excellent impedance matching of the absorber. This study not only presents a novel absorber design but also provides important theoretical and practical guidance for the development of high-performance, environmentally friendly, and tunable microwave absorbing materials, with potential applications in addressing electromagnetic environmental pollution and electromagnetic compatibility issues.
Theoretically grounded approaches to account for polarization effects in fixed-charge force fields
Authors: Jorge Miguel
Published: November 2024

Non-polarizable, or fixed-charge, force fields are the workhorses of most molecular simulation studies. They attempt to describe the potential energy surface (PES) of the system by including polarization effects in an implicit way. This has historically been done in a rather empirical and ad hoc manner. Recent theoretical treatments of polarization, however, offer promise for getting the most out of fixed-charge force fields by judicious choice of parameters (most significantly the net charge or dipole moment of the model) and application of post facto polarization corrections. This Perspective describes these polarization theories, namely the “halfway-charge” theory and the molecular dynamics in electronic continuum theory, and shows that they lead to qualitatively (and often, quantitatively) similar predictions. Moreover, they can be reconciled into a unified approach to construct a force field development workflow that can yield non-polarizable models with charge/dipole values that provide an optimal description of the PES. Several applications of this approach are reviewed, and avenues for future research are proposed.
Improved neural ordinary differential equation-based reduced model for impinging jet using wall shear stress
Authors: Mjalled A. , El Hassan M. , Boldocky J. , Gulan M. , Mönnigmann M.
Published: November 2024

Modeling the complex flow behavior of impingement jets is a problem of great importance in many industrial applications. Traditional modeling methods often fail to accurately predict these flows due to their nonlinear nature. This paper presents a neural network-based reduced-order model for experimental data of a circular impinging jet and compares several data assimilation frameworks for incorporating wall shear stress measurements obtained from different radial positions. The high-dimensional velocity field and the corresponding wall shear stress measurements are obtained using time-resolved particle image velocimetry and polarographic measurements, respectively. The developed reduced-order model results from a proper orthogonal decomposition (POD) step for dimensionality reduction with a neural ordinary differential equation (NODE) for temporal modeling. The performance of the POD-NODE framework is compared with dynamic mode decomposition and nonlinear temporal modeling using long short-term memory. Assessments are based on root mean squared error and spectral proper orthogonal decomposition of the reconstructed predicted solution. It is found that the POD-NODE framework provides the most accurate dynamical model. Furthermore, it is evident that incorporating wall shear stress measurements in the NODE model as additional states significantly improves the prediction accuracy, outperforming traditional filtering techniques such as extended Kalman filters.
Optimization analysis of the particle focusing and separation parameters of a sheathless microfluidic device using standing surface acoustic waves
Authors: Wang Min-Haw , Lee Yi-Chen , Tu Ting-Yuan , Huang Pao-cheng , Jang Ling-Sheng , Chen Chun-Hong
Published: November 2024

Flow-based particle separation usually requires a sheath flow for particle manipulation. Sheath fluid is a specialized buffer solution that directs the alignment of particles or cells into the center of the stream. By utilizing sheath flow, the particles or cells can be focused on the middle line of the microchannel, where they can be individually analyzed. However, the method requires an additional design for creating a suitable sheath flow. Purity and separation efficiency may also be influenced by the sheath flow. In this study, we present a sheathless device for particle focusing and separation using standing surface acoustic waves (SSAWs). The device comprises two regions: the focusing and separation regions. In the focusing region, particles in a continuous flow are aligned in the middle of the microchannel by SSAWs; in the separation region, tilted-angle SSAW-based particle separation is used to control particle migration. Varying particle sizes were focused in the focusing region and then separated in the separation region in the sheathless device. Experiments and simulations were also utilized to optimize a sheathless device. 10 and 20 μm particle focusing and separation were conducted in a sheathless device for the first time. We demonstrate that the separation of particles with a diameter of 10 and 20 μm has 90.8 ± 1.75% and 99.5 ± 0.8% separation efficiency, and 98 ± 3.4 and 97.9 ± 0.9% purity. Compared with other focusing and separation technologies, our device can also provide high purity, high separation efficiency, and high device density.
A coupled peridynamics–smoothed particle hydrodynamics model for fluid–structure interaction with large deformation
Authors: Huang Xieping , Zhu Bin , Chen Yunmin
Published: November 2024

Fluid–structure interaction (FSI) is ubiquitous in various engineering disciplines, and effectively managing FSI often appears to be the key for successful failure analysis and safety-oriented design. Smoothed particle hydrodynamics (SPH) serves as a potent nonlocal meshfree method for fluid dynamics modeling, while peridynamics (PD) demonstrates exceptional capability in addressing structural dynamics involving large deformations and discontinuities. Thus, leveraging their respective strengths in a combined approach holds significant promise for tackling FSI challenges. In this work, we propose a new peridynamics–smoothed particle hydrodynamics (PD-SPH) coupling model for addressing FSI. A stable and efficient coupling algorithm for data transfer between PD and SPH is put forward. In this coupling strategy, a PD particle directly participates in solving the SPH governing equations when it is identified to be within the support domain of an SPH particle. This can be done since the SPH quantities including the density, velocity, and pressure of a PD particle are naturally attainable within the framework of non-ordinary state-based peridynamics theory. Concurrently, in solving PD governing equations, reaction forces from SPH particles act as external forces for PD particles, determined straightforwardly through Newton's third law. As such, the proposed PD-SPH coupling strategy is straightforward to implement and offers high computational efficiency. Validation examples demonstrate that the proposed PD-SPH coupling model is computationally robust and adept at capturing physical phenomena in diverse FSI scenarios involving breaking free surfaces of fluid and large structural deformations of solid. Moreover, the proposed PD-SPH coupling model is flexible introducing no constraint conditions for applications and can accommodate different particle resolutions for PD and SPH domains. These features enable a broad application range of the proposed PD-SPH coupling model including simulations of explosion-induced soil fragmentation, rock fracture, and concrete dam failure, which will be conducted by authors in the near future.
Genetic barcodes for species identification and phylogenetic estimation in ghost spiders (Araneae: Anyphaenidae: Amaurobioidinae)
Authors: Barone Mariana L. , Wilson Jeremy D. , Zapata Lorena , Soto Eduardo M. , Haddad Charles R. , Grismado Cristian , Izquierdo Matías , Arias Elizabeth , Pizarro-Araya Jaime , Briones Raúl , Barriga Juan Enrique , Peralta Luciano , Ramírez Martín J.
Published: November 2024

The identification of spider species presents many challenges, since in most cases the characters used are from genital structures that are only fully developed in the adult stage, hence the identification of immatures is most often not possible. Additionally, these structures usually also present some intra-specific variability, which in some cases makes the identification of closely related species difficult. The genetic barcode technique (DNA barcodes), based on sequencing of the mitochondrial marker cytochrome c oxidase subunit I (COI), has proven a useful, complementary tool to overcome these limitations. In this work, the contribution of DNA barcoding to the taxonomy of the subfamily Amaurobioidinae is explored using the refined single linkage analysis (RESL) algorithm for the delimitation of operational taxonomic units (OTUs), in comparison with the assemble species by automatic partitioning (ASAP) algorithm, and presented in conjunction with an updated molecular phylogenetic analysis of three other markers (28S rRNA, 16S rRNA, Histone H3), in addition to COI. Of a total of 97 included species identified by morphology, 82 species were concordant with the operational taxonomic units obtained from RESL, representing an 85% correspondence between the two methods. Similar results were obtained using the ASAP algorithm. Previous observations of morphological variation within the same species are supported, and this technique provides new information on genetic structure and potentially cryptic species. Most of the discrepancies between DNA barcoding and morphological identification are explained by low geographic sampling or by divergent or geographically structured lineages. After the addition of many specimens with only COI data, the multi-marker phylogenetic analysis is consistent with previous results and the support is improved. The markers COI, closely followed by 28S, are the most phylogenetically informative. We conclude that the barcode DNA technique is a valuable source of data for the delimitation of species of Amaurobioidinae, in conjunction with morphological and geographic data, and it is also useful for the detection of cases that require a more detailed and meticulous study.
Plant morphological traits and leaf nutrient concentration are associated with flammability and phylogenetic relationships in sub-alpine vegetation, New Zealand
Authors: Budha-Magar Shanta , Day Nicola J. , Buckley Hannah L. , Burge Olivia R. , Richardson Sarah J. , Schwilk Dylan W. , Ross Ruby R. , Curran Timothy J.
Published: November 2024

Background Understanding relationships among leaf nutrient concentrations, morphological traits and plant flammability aids predictions of plant flammability. Few studies have simultaneously examined these relationships in a phylogenetic context. Aim Quantify relationships among plant flammability, leaf nutrient concentrations, morphological traits and phylogenetic pattern. Methods We measured shoot and whole plant flammability (for small-sized species), shoot and leaf morphological traits, and leaf nutrient concentrations for 29 vascular plant taxa. Shared and unique plant flammability variation explained by nutrient traits, leaf morphology and shoot traits was estimated, incorporating phylogenetic relationships among species via variance partitioning. Key results Flammability had a substantial phylogenetic proportion; 28% of variation in flammability was explained either independently by phylogenetic relatedness or as shared variation with morphology and shoot traits (49%), or nutrient concentrations (20%). Twig dry matter content and retained dead material were positively and moisture content and most nutrient traits were negatively correlated with plant flammability. Conclusions Variation in leaf nutrient concentrations and plant morphology showed a strong phylogenetic pattern, suggesting that features of plants that determine their flammability are strongly underpinned by evolution. Implications The substantial shared variation between leaf nutrient concentrations, morphological traits and phylogenetic relationships suggests that morphological traits will be more useful than nutrient traits when predicting flammability.
Tracking the topology of neural manifolds across populations
Authors: Yoon Iris H. R. , Henselman-Petrusek Gregory , Yu Yiyi , Ghrist Robert , Smith Spencer LaVere , Giusti Chad
Published: November 2024

Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising the possibility of studying how these manifolds relate across populations. However, when the manifolds are nonlinear and possibly code for multiple unknown variables, it is challenging to extract robust and falsifiable information about their relationships. We introduce a framework, called the method of analogous cycles, for matching topological features of neural manifolds using only observed dissimilarity matrices within and between neural populations. We demonstrate via analysis of simulations and in vivo experimental data that this method can be used to correctly identify multiple shared circular coordinate systems across both stimuli and inferred neural manifolds. Conversely, the method rejects matching features that are not intrinsic to one of the systems. Further, as this method is deterministic and does not rely on dimensionality reduction or optimization methods, it is amenable to direct mathematical investigation and interpretation in terms of the underlying neural activity. We thus propose the method of analogous cycles as a suitable foundation for a theory of cross-population analysis via neural manifolds.
Functions of the particles tõesti ‘really’ and tõepoolest ‘indeed’ in the spoken,
online and printed registers of Estonian
Authors: Laanesoo-Kalk Kirsi
Published: November 2024

The article examines the use of two Estonian pragmatic particles, tõesti ‘really’ and
tõepoolest ‘indeed, truly’, in everyday conversations, online news comments and academic prose. The data is
drawn from the Estonian Pragmatic Corpus. The material analyzed reveals that the main function of both particles in the different
registers is to confirm and emphasize some statement, fact, general knowledge, etc., either in the previous text or in the current
utterance or sentence. Both particles can add an element of surprise or bewilderment to the sentence or utterance. The use of
tõepoolest is associated with higher degrees of formality, whereas tõesti, being a
relatively frequent particle, can occur in both formal and informal texts.
Functions of the particle üldse ‘at all’ in questions in Estonian everyday
conversations
Authors: Rääbis Andriela
Published: November 2024

The goal of the paper is to examine the use of the particle üldse ‘at all; ever; generally;
absolutely (not)’ in questions in Estonian everyday face-to-face and telephone conversations. The analysis is based on the
methodological framework of interactional linguistics.

The particle üldse is found to serve three central functions in questions: (a) marking topic
shifts and topic changes, (b) intensifying doubt or challenges, (c) emphasizing someone’s norm-violating behavior. Questions
containing the particle üldse can be divided into two groups: neutral information-seeking questions and
multifunctional questions that perform several social actions simultaneously. The particle üldse is commonly
backward looking and serves both interpersonal and textual functions. Its use is often associated with non-preference,
disagreement, or contradiction.
Hangul — A hybrid orthography
Authors: O’Grady William
Published: November 2024

Hangul is widely categorized as a classic example of a morphophonemic orthography, in which each morpheme receives
a single spelling, even if its pronunciation varies from context to context. This paper makes the case that Hangul is in fact a
hybrid orthography that adheres to a morphophonemic strategy for spelling consonants but adopts the conventions of a phonetic
writing system for representing vowels. Various explanations for this arrangement are considered.
The role of university in a Korean heritage language student’s identity development
Authors: Park Mi Yung , Chung Katalina
Published: November 2024

Drawing on autobiographical narratives of a second-generation Korean heritage language (HL) student who grew up in
Auckland, New Zealand, this study examines the role of university study in HL students’ identity development. In her narratives,
the participant describes feeling inferior about her Korean HL and culture as a child but finding that university offered space
for the (re)construction and positive reinforcement of her HL and cultural identities over time. The university provided her with
a multicultural community, and HL and other identity- and heritage-culture-related courses, which enabled her both to
(re)construct her sense of self and to critically examine the challenges she faced in a White European-dominated society. The
findings shed light on second-generation immigrant-background students’ HL and related identity development processes, and the
importance of creating bilingual and bicultural educational spaces in tertiary education for their ongoing identity
development.
PI(3,5)P2 asymmetry during mitosis is essential for asymmetric vacuolar inheritance
Authors: Huda Mariam , Koyuncu Mukadder , Dilege Cansu , Caydasi Ayse Koca
Published: November 2024

Phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2) is a low-abundance signaling lipid that plays crucial roles in various cellular processes, including endolysosomal system structure/function, stress response, and cell cycle regulation. PI(3,5)P2 synthesis increases in response to environmental stimuli, yet its behavior in cycling cells under basal conditions remains elusive. Here, we analyzed spatiotemporal changes in PI(3,5)P2 levels during the cell cycle of S. cerevisiae. We found that PI(3,5)P2 accumulates on the vacuole in the daughter cell while it disappears from the vacuole in the mother cell during mitosis. Concomitant with the changes in PI(3,5)P2 distribution, the daughter vacuole became more acidic, whereas the acidity of the mother vacuole decreased during mitosis. Our data further showed that both PI(3,5)P2 and the PI(3,5)P2 effector protein Atg18 are determinants of vacuolar-pH asymmetry and acidity. Our work, thus, identifies PI(3,5)P2 as a key factor for the establishment of vacuolar-pH asymmetry, providing insights into how the mother cell ages while the daughter cell is rejuvenated.
Topological Hall effect instigated in kagome Mn3–xSn due to Mn-deficit induced noncoplanar spin structure
Authors: Low Achintya , Ghosh Susanta , Thirupathaiah Setti
Published: November 2024

Magnetic topological semimetals are manifestations of the interplay between electronic and magnetic phases of matter, leading to peculiar characteristics such as the anomalous Hall effect (AHE) and the topological Hall effect (THE). Mn3Sn is a time-reversal symmetry-broken magnetic Weyl semimetal showing topological characteristics within the Kagome lattice network. This study reveals a large THE in Mn2.8Sn (6% Mn deficit Mn3Sn) at room temperature in the xy-plane, despite being an antiferromagnet. We argue that the magnetocrystalline anisotropy induced noncoplanar spin structure is responsible for the observed THE in these systems. Further, the topological properties of these systems are highly anisotropic, as we observe a large AHE in the zx-plane. We find that Fe doping at the Mn site, Mn

3
−
x

Fe
x
Sn (x = 0.2, 0.25, & 0.35), tunes the topological properties of these systems. These findings promise the realization of potential topotronic applications at room temperature.
A three-stage cross-domain intelligent fault diagnosis method for multiple new faults
Authors: Zhang YeFeng , Tang HeSheng , Ren Yan
Published: November 2024

Recently, transfer learning (TL) has been widely investigated to tackle the cross-domain fault diagnosis issue in machinery, and most research works follow the same assumption that the diagnosis domain shares the same fault categories. However, due to the randomness and complexity of mechanical faults, the new fault modes usually occur unexpectedly in the actual scenarios. The emergence of new faults also presents severe challenges to TL. In response to these challenges, a three-stage cross-domain intelligent fault diagnosis method is presented in this article. First, partial domain alignment is achieved based on an improved target weighted mechanism, and an outlier identifier is constructed to automatically separate the new fault classes. Then, an unsupervised learning model with silhouette coefficients is built to determine the number of new fault categories. Finally, the simulation signals are further adopted to distinguish the specific fault categories. Sufficient experiments on axial piston pump and public bearing datasets validate that the proposed method can predict a number of new fault categories and identify specific fault categories. The results indicate that the proposed method outperforms the other methods and has promising practical applications in fault diagnosis with multiple new faults.
Research on damage identification of simply supported bridge based on effect size method for vehicle-bridge coupled vibration
Authors: Guo Yihang , Wang Jiangfei , Wu Yanni , Xu Jianguo , Huang Liang , Zhou Qi , Kou Lei
Published: November 2024

This paper presents a novel bridge damage identification method employing Cohen’s d as an effect size indicator, predicated on the detection of bridge damage through the coupled vibration between a vehicle and the bridge. By analysing the dynamic response of the bridge as a vehicle passes over, this method effectively extracts the modal parameters of the bridge and facilitates the identification of bridge damage. Numerical models of the bridge under various damage conditions, including no damage, mid-span damage, and damage at the 1/4 and 3/4 span locations, have been constructed to substantiate the efficacy and precision of the effect size as a damage indicator. Furthermore, to address the challenge of accurately identifying damage at boundaries, which is often confounded by boundary effects, a boundary subdivision method has been defined for the detection of boundary damage. Through the implementation of a real-bridge test based on indirect measurement technology, the self-vibration frequency of the bridge was successfully extracted. This empirical data was then compared and analysed against results from ANSYS numerical simulations, thereby validating the practicality and accuracy of the proposed method. In the final analysis, the influence of random traffic flow on the bridge damage identification results was examined. The findings indicate that the vibrations in simply supported beam bridges are intensified due to the impact of random traffic flow, which aids in enhancing the accuracy of damage identification. The introduction of this method provides a new quantitative tool for bridge health monitoring, enabling the rapid and accurate identification of bridge damage without interrupting traffic. It holds significant value for engineering applications in bridge maintenance and safety assessment.
A novel epilepsy detection approach using intrinsic multiscale entropy analysis and DSEAM-enhanced 1D-ResNets
Authors: Jing Xiaolong , Yuan Rui , Lv Yong , Liu Hanwen , Li Hewenxuan , Zhu Weihang
Published: November 2024

Epilepsy, a prevalent neurological disorder, typically requires a complex diagnostic process involving medical history inquiry, physical examination, head computed tomography, and electroencephalogram (EEG) visual examination. Among the existing epilepsy automated detection algorithms, machine learning methods require manual feature selection. Most of deep learning algorithms for automatic detection have high complexity and computational complexity. To address this issue, this study proposes a high-precision, robust, and low computational epilepsy automatic detection algorithm based on EEG signal processing. The study utilizes ensemble empirical mode decomposition to preprocess the original EEG signal, breaking it down into intrinsic mode functions (IMFs) across various frequency bands. These IMFs contain information about epilepsy occurrence within the signal at different frequency bands. To enhance computational efficiency and reduce data dimension, the refined composite multiscale dispersion entropy of each IMF is further computed at different scales, referred to as intrinsic multiscale entropy (IME) analysis. IME analysis consolidates epilepsy occurrence information from EEG signals across different frequency bands and scales, linking entropy values to generate feature vectors. Drawing inspiration from successful deep residual networks and Squeeze-and-Excitation (SE) networks, the study introduces a double SE attention module enhanced one-dimensional residual network to classify one-dimensional feature vectors. The proposed method was tested on epilepsy dataset from University of Bonn, and the results demonstrated superior classification performance. In the experiment, the distinction between normal and epileptic EEG signals achieved 100% accuracy rate, while distinguishing between normal, epileptic interval, and epileptic EEG signals achieved accuracy rate of 99.41%.
Turbulence statistics estimation across a step change in roughness via interpretable network-based modelling
Authors: Iacobello Giovanni , Placidi Marco , Ding Shan–Shan , Carpentieri Matteo
Published: November 2024

This study proposes a data-driven methodology to complement existing time-series measurement tools for turbulent flows. Specifically, a cluster-based transition network model is employed for the estimation of velocity time traces and their corresponding statistics. The method is tested on a laboratory-modelled turbulent boundary layer over a step change in surface roughness, where velocity time series are recorded for training and validation purposes via Laser Doppler Anemometry. Results show that our approach can estimate velocity and momentum flux statistics within experimental uncertainty over a rough surface through an unsupervised approach, and across the step change in roughness through a semi-supervised variant. The friction velocity across the domain is also estimated with 10% relative error compared to the measured value. The proposed methodology is interpretable and robust against the main methodological parameters. A reliable data-driven framework is hence provided that can be integrated within existing laboratory setups to supplement or partially replace measurement systems, as well as to reduce wind tunnel running times.
Research on oil and gas pipeline leak detection method based on 1DCNN-DBO-LSTM
Authors: Song Jinbo , Yan Rongxi , Lu Jingyi , Liu Xingyu , Yang Dandi
Published: November 2024

Leak detection of oil and gas pipelines is essential for safe pipeline operation. Existing methods for detecting oil and gas pipeline leaks are inadequate and do not exploit the temporal characteristics of the leak signal. In this paper, a fusion recognition model of a long short-term memory network (LSTM) optimized by a one-dimensional convolutional neural network (1DCNN) and dung beetle optimization algorithm (DBO) is proposed. First, the one-dimensional signal is input into the 1DCNN. Then the adaptively extracted data features from the 1DCNN are input into the optimized DBO-LSTM for classification. The model is evaluated using the precision and duration metrics. In comparison to extant advanced models, the proposed model improves recognition precision and decreases detection time. The model proposed in this paper is able to extract pipeline data features more rapidly and precisely, thereby improving classification accuracy.
Method for rail surface defect detection based on neural network architecture search
Authors: Min Yongzhi , Jing Qinglong , Li Yaxing
Published: November 2024

This study addresses the inherent limitations of implementing neural network architecture search algorithms for rail surface defect detection, including low search efficiency and the oversight of edge features on the rail surface. A sophisticated multi-level neural network architecture search framework is proposed that integrates and emphasizes rail surface edge features. The framework utilizes the Z-Score normalization method to quantify the edge concern of rail surface defect samples, combined with an Edge-Loss function to enhance edge feature recognition capabilities. Furthermore, acknowledging the sensitivity of defect features to spatial resolution changes, a multi-level neural network architecture search space is meticulously designed. In the cell-level search space, a method combining partial channel sampling with operation pruning is employed to enhance model search efficiency and regularization. In the network-level search space, optimal paths for resolution change are established, allowing for the screening and aggregation of defect features at various levels to facilitate the adaptive extraction of multi-scale edge defect features. Experimental outcomes indicate that this method significantly reduces computational resource usage by approximately 75% and increases mIOU by 2.6% relative to traditional architecture search methods. Moreover, it demonstrates robust capability in accurately recognizing defective edges on rail surfaces, thereby substantiating the method’s effectiveness.
High-precision roundness measuring system for tungsten ball tips with the diameter of less than 100 µm
Authors: Zu Chuan , Zhao Wenkai , Li Rui-jun , Liu Yunlong , Cheng Zhenying
Published: November 2024

Tungsten balls with a diameter of less than 100 μm can function as probe tips for micro-coordinate measuring machines to measure ultraprecise workpieces with complex features. A high-precision measuring system was developed to evaluate the roundness of self-made tungsten ball tips. The system, based on the two-point method, is composed of two oppositely placed interferometers and a turntable. The turntable rotates the tested ball, and the interferometers measure the variation in radius. A new model based on the minimum zone method is proposed to evaluate roundness. The fabrication principle of tungsten balls is introduced and an analysis is conducted on the maximum permissible contact force and bending stress of tungsten ball tips. The elastic mechanism is designed, based on the analysis. A ruby sphere with a sphericity of 130 nm is measured to verify the system’s effectiveness. Repeated experiments are performed for two tungsten ball tips. The results show that the roundness error of tungsten ball-A is between 550.9 and 586.2 nm with a standard deviation of 11.0 nm while tungsten ball-B’s roundness error is between 898.5 and 959.9 nm with a standard deviation of 21.7 nm. The uncertainty is calculated as 144.6 nm. The developed system can stably measure the roundness of tungsten ball tips.
From interacting agents to Boltzmann-Gibbs distribution of money
Authors: Cao Fei , Jabin Pierre-Emmanuel
Published: November 2024

We investigate the unbiased model for money exchanges: agents give at random time a dollar to one another (if they have one). Surprisingly, this dynamics eventually leads to a geometric distribution of wealth (shown empirically by Dragulescu and Yakovenko, and rigorously by several follow-up papers). We prove a uniform-in-time propagation of chaos result as the number of agents goes to infinity, which links the stochastic dynamics to a deterministic infinite system of ordinary differential equations. This deterministic description is then analyzed by taking advantage of several entropy–entropy dissipation inequalities and we provide a quantitative almost-exponential rate of convergence toward the equilibrium (geometric distribution) in relative entropy.
Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning
Authors: Ambaye Dagnachew Tessema , Tessema Abel Worku , Jeong Jiwoo , Ryu Jiwon , Yu Tosol , Lee Jimin , Cho Hyungjoon
Published: November 2024

Objective. This study aims to investigate the feasibility of utilizing generative adversarial networks (GANs) to synthesize high-fidelity computed tomography (CT) images from lower-resolution MR images. The goal is to reduce patient exposure to ionizing radiation while maintaining treatment accuracy and accelerating MR image acquisition. The primary focus is to determine the extent to which low-resolution MR images can be utilized to generate high-quality CT images through a systematic study of spatial resolution-dependent magnetic resonance imaging (MRI)-to-CT image conversion. Approach. Paired MRI-CT images were acquired from healthy control and tumor models, generated by injecting MDA-MB-231 and 4T1 tumor cells into the mammary fat pad of nude and BALB/c mice to ensure model diversification. To explore various MRI resolutions, we downscaled the highest-resolution MR image into three lower resolutions. Using a customized U-Net model, we automated region of interest masking for both MRI and CT modalities with precise alignment, achieved through three-dimensional affine paired MRI-CT registrations. Then our customized models, Nested U-Net GAN and Attention U-Net GAN, were employed to translate low-resolution MR images into high-resolution CT images, followed by evaluation with separate testing datasets. Main Results. Our approach successfully generated high-quality CT images (0.142 mm2) from both lower-resolution (0.282 mm2) and higher-resolution (0.142 mm2) MR images, with no statistically significant differences between them, effectively doubling the speed of MR image acquisition. Our customized GANs successfully preserved anatomical details, addressing the typical loss issue seen in other MRI-CT translation techniques across all resolutions of MR image inputs. Significance. This study demonstrates the potential of using low-resolution MR images to generate high-quality CT images, thereby reducing radiation exposure and expediting MRI acquisition while maintaining accuracy for radiotherapy.
The identification of traps in HfO2-based FeFET with SiON as an interlayer using current transient method
Authors: Zhou Lixing , Cui Jialu , Wang Xiaolei , Tian Fengbin , Zhu Hui , Gong Manru , Dai Cong , Zhang Yamin , Feng Shiwei
Published: November 2024

This work investigates the current transient and trap characteristics of Si FeFET with HfZrO ferroelectric and SiON as the interfacial layer. The trap characteristics in the trapping/detrapping process based on the drain current and gate leakage current transients are analyzed. Four traps, denoted as DP1 (τ ∼ 0.1 s), DP2 (τ ∼ 1 s), DP3 (τ ∼ 10 s), and DP4 (τ ∼ 50 s), with different time constants are demonstrated. It is discovered that DP1 and DP2 are thermally activated with activation energies of 0.2 eV and 0.05 eV, respectively. DP3 and DP4 are not thermally activated. According to the different time constants and activation energies as well as the dependence of the gate and drain trapping voltages, the possible positions of these traps are identified as follows: DP1 is the HfZrO bulk trap, and DP2 is near the HfZrO/SiON interface. DP3 and DP4 are traps with different time constants near the Si/SiON interface.
On topological indices of certain families of graphs
Authors: Imran Muhammad , Farahani Muhammad Reza , Cancan Murat , Alaeiyan Mehdi , Akgül Ali
Published: November 2024

The aim of this paper is to compute topological indices such as general randic index, general sum connectivity index, atom bond connectivity index, geometric arithmetic index, forgotten index, first zagreb index, second zagreb index, first multiple zagreb index, second multiple zagreb index and hyper zagreb index of different families of graphs.
Meander line loaded 2-port stepped impedance feed slotted MIMO antenna for C and lower X-band communication
Authors: Singh Aditya Kumar , Dwivedi Ajay Kumar , Varma Kalidindi Naga Venkata Suresh , Pandey Akhilesh Kumar , Singh Vivek
Published: November 2024

In this communication, a wideband 2-Port Multiple-Input-Multiple-Output (MIMO) antenna of the dimension of 0.13 λ0 × 0.68 λ0 × 0.02 λ0 mm3 (λ0, measured at a lower frequency is 4.43 GHz) is investigated for the C-band and Partial X-Band Applications. The concept of defective ground is introduced to enhance the impedance bandwidth by engraving the rectangular slots. In the proposed configuration a mender line is incorporated as a decoupling network between the antenna elements to enhance the isolation (>18 dB). The quarter wavelength long stepped impedance matched transmission line is used to excite the proposed configurations. The impedance bandwidth of the proposed antenna is (4.43–9.85 GHz)/ 83%. To explore the diversity of the MIMO system the ECC < 0.04, DG > 9.8 dB, and CCL< 0.3 bps Hz−1 are reported. Excellent agreement between simulation and measured results is obtained, justifying the MIMO antenna’s applicability for wireless applications.
A novel plasma optical emission spectroscopy method with neural network model for improving the accuracy of plasma diagnostics in low-temperature xenon plasma
Authors: Wang Yan-Fei , Zhu Xi-Ming
Published: November 2024

Optical emission spectroscopy (OES) is an important technique for plasma diagnostics. However, random deviations in emission spectra measurements are inevitable due to instrumental imperfections and other interferences. In scenarios requiring high temporal resolution measurements, where repeated measurements are impractical, these random errors pose significant challenges for accurate plasma diagnostics. This work introduces a novel OES method that utilizes a neural network model to suppress random deviations in emission spectra measurements. The dataset for training neural network is generated using a comprehensive collisional-radiative model combined with an instrument disturbance model. The novel method is demonstrated on a microwave electron-cyclotron-resonance discharge chamber. The results show that the novel method reduces the random deviation in electron temperature and density to less than 3%, which represents a significant improvement over traditional methods. Additionally, the new OES method offers enhanced timeliness, making it particularly promising for online monitoring applications.