bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical study and modal analysis of electrode position and energy deposition amount effects on SparkJet actuator performance
Authors: Shin Jin Young , Kim Kyu Hong
Published: January 2025

This study investigates the impact of electrode positioning and the amount of energy deposited into the flow on the performance of SparkJet actuators, utilizing computational fluid dynamics (CFD) and modal analysis. The performance metric considered is impulse, defined as the time-integrated thrust. A parametric study was conducted by varying the electrode position from near the cavity bottom to more distant locations to assess the differences in impulse. In addition, the effect of three energy deposition amounts (3.11, 5.14, and 7.17 mJ) on impulse was examined. The results indicate that, for the same energy deposition amount, the impulse can vary by up to approximately 40% depending on electrode positioning. Furthermore, the impulse exhibited a general tendency to decrease as the electrode position moved closer to the orifice, regardless of the energy deposition amount. However, it showed a considerable rebound when the electrode position was near the interface between the cavity and the nozzle. To further analyze these findings, contour analysis of CFD results and modal analysis of the velocity field were conducted. The former revealed that the behavior of the low-density region inside the actuator significantly affects impulse, while the latter demonstrated that a wave with mode 0 and order 1 (an eigenfunction with a single node along the ξ direction) exerts a dominant influence on impulse. Moreover, a new variable related to this eigenfunction was proposed, enabling the prediction of impulse trends with respect to electrode position. Thus, this study successfully analyzed the previously unexplored effect of electrode positioning on SparkJet actuator performance using modal analysis, highlighting the importance of optimizing electrode position for enhanced SparkJet actuator performance.
Assessment of algebraic anisotropic turbulent heat flux models using Reynolds stress modeling for simulating film cooling flows
Authors: Mir Emad M. , Mazaheri K. , Darbandi M.
Published: January 2025

This study evaluates the performance of various algebraic turbulent heat flux models in predicting film cooling flows using different Reynolds stress turbulence models. a priori analysis using direct numerical simulation data was used to assess the models' performance. Additionally, Reynolds-averaged Navier–Stokes (RANS) simulations based on Reynolds stress turbulence models were performed to investigate the models' practical application in film cooling. Results demonstrate that the enhanced explicit algebraic turbulent heat flux model significantly outperforms existing models. It accurately predicts both streamwise and wall-normal turbulent heat fluxes based on direct numerical simulation data in a channel flow, and exhibits superior performance in film cooling simulations respect to known turbulent heat flux models. The recommended turbulent heat flux model decreased the error norm more than 90% in channel flow. Furthermore, the study highlights the importance of selecting appropriate Reynolds stress models in conjunction with turbulent heat flux models for accurate film cooling predictions. The right choice of Reynolds stress model according to the turbulent heat flux model can significantly influence the overall accuracy of the RANS simulation.
Full-dimensional accurate potential energy surface and dynamics for the unimolecular isomerization reaction CH3NC ⇌ CH3CN
Authors: Li Junlong , Li Junhong , Li Jun
Published: January 2025

The reaction CH3NC ⇌ CH3CN, a model reaction for the study of unimolecular isomerization, is important in astronomy and atmospheric chemistry and has long been studied by numerous experiments and theories. In this work, we report the first full-dimensional accurate potential energy surface (PES) of this reaction by the permutation invariant polynomial-neural network method based on 30 974 points, whose energies are calculated at the CCSD(T)-F12a/AVTZ level. Then, ring polymer molecular dynamics is used to derive the free energy barrier of the reaction at the experimental temperature range of 472.55–532.92 K. Reaction kinetics are studied at the high-pressure limit and in the fall-off region by standard transition state theory and the master equation, respectively. The calculated temperature- and pressure-dependent rate coefficients are in good agreement with previous experimental and theoretical results. Furthermore, quasi-classical trajectory simulations are performed on this PES to study the intramolecular energy transfer dynamics at initial vibrational energies of 4.336, 5.204, and 6.505 eV.
Study on the dynamic behaviors of collision and coalescence of binary double low-viscosity droplets
Authors: Chen Yihan , Chen Xi , Fan Chaonan , Ge Shaocheng , Zhou Gang , Shi Yan
Published: January 2025

The volume of fluid method is used to track the phase interface changes while analyzing and investigating the horizontal collision behavior of binary low-viscosity droplets. The result shows that the droplets with different particle size ratios and relative velocity will have three kinds of collision results: coalescence, reflexive separation, and stretch separation when the collision angle is 0, and there is no bounce phenomenon. The kinetic energy of droplets with a large particle size ratio and relative velocity decreases faster after collision, the surface energy decreases slowly, and the energy is dissipated the most. The influence of temperature and humidity on colliding results is analyzed for the first time, and it is found that the influence is negligible. The critical Weber numbers of coalescence-reflexive separation and coalescence-stretch separation after the collision of two droplets of equal size are 22.09 and 38.74, respectively. The existing low-viscosity droplet collision transition boundary curve is modified for the first time. A new droplet collision model considering viscous dissipation is established under the interaction of particle size ratio and relative velocity.
A general description of the cavitation threshold in acoustic systems
Authors: Viciconte Gianmaria , Guida Paolo , Truscott Tadd T. , Roberts William L.
Published: January 2025

Traditionally, the cavitation threshold is defined by some combination of vapor pressure and surface tension. However, these formulations present a large discrepancy with experimental data for cases where cavitation is induced by acoustic waves. The present study aims to identify a more suitable cavitation threshold for such cases. The method adopted in this work consists of a combination of visualizations with a high-speed camera and direct measurements using a hydrophone. The data collected confirmed that vapor pressure is not a proper indicator of cavitation occurrence for an acoustic system characterized by high frequencies. The main reason behind the inability of vapor pressure to predict incipient cavitation in acoustic systems is that they evolve very quickly toward strong gradients in pressure, and the quasi-static assumptions used by traditional models are not valid. Instead, the system evolves toward a metastable state [Brennen, Cavitation and Bubble Dynamics, 2013], where the liquid exhibits an elastic behavior and can withstand negative pressures. A new cavitation number is defined to properly describe the phenomenology of acoustic cavitation. However, to provide a complete description of the cavitation threshold, future experiments, in a wide range of acoustic frequencies, are still necessary. An acoustic analogy is also proposed for the description, with the same framework, of an impulsive cavitation phenomenon.
Quantitative smoke visualization: An optical field measurement technique for measuring scalar concentration using Mie scattering from smoke particles
Authors: Cholemari Murali R. , Mathur Manish Kumar
Published: January 2025

We present an optical field measurement technique for measuring scalar concentration field in wind tunnels using smoke particles, demonstrating its application through measurements of particle concentration and particulate dispersion in the turbulent wake of a simplified vehicle model (Ahmed body). Experiments involved the release of smoke particles (Ethylene-Glycol) from a source placed behind Ahmed body in the wind tunnel (at model length based Reynolds no., Rel=1.9×105). The smoke particles were illuminated using a laser sheet and recorded using a digital camera. An optical technique similar to PLIF (Planar Laser-Induced Florescence) but adapted for the Mie-scattering of light by smoke particles is developed and implemented. A method for compensating the laser beam attenuation in the smoke medium is also discussed and implemented on the test flow. Calibration of the image intensities with absolute particle concentration has been done, and the Beer–Lambert law is shown to apply. Laser attenuation along the beam path is corrected using an extinction model based on the Beer–Lambert law. An iterative approach for the laser attenuation correction is applied. Using these, quantitative measurements of smoke concentrations are obtained. These experimental results are compared with earlier cold wire thermometry measurements. The results obtained by the current technique are in good agreement with the earlier results. It is observed that not accounting for the attenuation correction can lead to significant errors in the measured concentration field. The presented technique can be used to obtain instantaneous and time-averaged pollutant concentration fields that are resolved in space and time.
Response characteristics of siltation flow in urban rainwater pipelines using computational methods
Authors: Wang Ruoyi , Di Danyang , Fang Hongyuan , Li Bin , Shi Mingsheng , Wang Niannian , Zhang Tilang , Li Tianwei , Zhang Zhaoyang
Published: January 2025

Rainwater pipeline siltation significantly impacts the flow capacity of drainage infrastructure, increasing the risk of flood disasters. Existing studies does not consider the energy dissipation caused by the gap fluid effect and quantification of “particle–liquid–gas” coupling relationship. To address these gaps, particle–liquid–gas coupling governing equations and constraint conditions are constructed to improve the accuracy of fluid–structure coupling calculation in a silted pipeline. Then, combining semi-empirical formulas, energy dissipation theory, and elastic fluid dynamics, a contact force model with wet particle method, dry particle method, and damping coefficient is constructed to improve the simulation accuracy of particle and liquid motion. By analyzing Di Felice resistance, pressure gradient force, and virtual mass force, a high-resolution computational fluid dynamics and discrete element method coupling model of silted pipeline is constructed to formulate the response characteristics of siltation flow in rainwater pipelines. The results indicate that the error rate of the proposed simulation model is maintained within [5.83, 6.79] for siltation flow analysis, which is far better than other numerical simulation methods. The variation interval of correlation coefficients under different siltation scenarios is [0.87, 0.92], which indicates high reliability and robustness. For siltation degree of 0.2, the average flow velocity at the inlet, midpoint, and outlet sections is 27.66%, 8.42%, and 11.31% lower compared to the non-silted section, respectively. The theoretical structural formula of average flow velocity in the silted pipeline can be calculated by modified Manning formula and measured siltation parameters. These findings can provide guidance on higher precision flood numerical simulation and early warning in the future.
Nonlinear coupled constitutive relations for hypersonic reacting flows with thermal nonequilibrium effect
Authors: Zeng Shuhua , Yang Junyuan , Zhao Wenwen , Yuan Zhenyu , Fan Guochao , Chen Weifang
Published: January 2025

The complex interplay between high-temperature and rarefaction effects poses ongoing challenges to model hypersonic nonequilibrium flows, affecting the accurate prediction of aerodynamic and aerothermal loads for hypersonic vehicles. To address this issue, a multispecies Nonlinear Coupled Constitutive Relations (NCCR) model is first derived from the modified Boltzmann equations with vibrational mode. The proposed NCCR model incorporates a thermochemical nonequilibrium suite comprising chemical kinetic packages, Park's two-temperature model, and a modified Landau–Teller energy transfer formula, thereby accounting for the high-temperature effect. Furthermore, an undecomposed algorithm with popular numerical methods is also applied to solve the NCCR model within the finite volume framework. The capability of the NCCR solution to simulate thermochemical nonequilibrium flows was validated through three numerical tests, spanning the continuum to rarefied regimes. The comparative benchmark data were derived from wind tunnel experiments, in-flight tests, and direct simulation Monte Carlo method. It is noteworthy that the results of the NCCR solution show a superior alignment with the benchmark data than those obtained by the Navier–Stokes equations. Moreover, it is found that the rarefaction effect captured by the NCCR solution has a pronounced impact on the energy relaxations and chemical reaction processes in hypersonic thermochemical nonequilibrium flows. These findings underscore the potential of NCCR theory as a valuable tool for simulating thermochemical nonequilibrium flows including rarefaction effects, ultimately shedding light on the prospective development of hypersonic cross-domain vehicles.
Unequal splitting phenomenon of cavitation bubbles near rigid boundaries within a narrow gap
Authors: Shen Junwei , Ying Jiaze , Liu Wenda , Ma Shaowu , Luo Peng , Zhang Yuning , Zhang Yuning
Published: January 2025

The present work investigates the unequal splitting of cavitation bubbles near rigid boundaries within a narrow gap. Based on high-speed photographic experiments, the typical phenomenon of unequal bubble splitting is shown, and the parametric partitions of unequal bubble splitting in proximity to a cylinder and a flat wall are presented. Based on the Kelvin impulse theory, the underlying physical bubble-splitting mechanisms are explored. In addition, the impacts of the main parameters on the unequal splitting are quantitatively analyzed. The main conclusions are as follows. (1) Under different cylinder–bubble distances, the bubble splits into three typical cases: an upper larger part and a lower smaller part, two equal-sized parts, and an upper smaller part and a lower larger part. (2) The unequal bubble splitting is caused by the inconsistencies between the directions of the bubble-collapse jet and the centroid movement. (3) As the cylinder radius and the cylinder–wall distance increase, the bubble splitting shifts from case 1 to case 3, suggesting the cylinder effect increases and the flat-wall effect decreases.
Exome sequencing identifies genes for socioeconomic status in 350,770 individuals
Authors: Wu Xin-Rui , Yang Liu , Wu Bang-Sheng , Liu Wei-Shi , Deng Yue-Ting , Kang Ju-Jiao , Dong Qiang , Sahakian Barbara J. , Feng Jian-Feng , Cheng Wei , Yu Jin-Tai
Published: January 2025

Socioeconomic status (SES) is a critical factor in determining health outcomes and is influenced by genetic and environmental factors. However, our understanding of the genetic structure of SES remains incomplete. Here, we conducted a large-scale exome study of SES markers (household income, occupational status, educational attainment, and social deprivation) in 350,770 individuals. For rare coding variants, we identified 56 significant associations by gene-based collapsing tests, unveiling 7 additional SES-associated genes (
NRN1
,
CCDC36
,
RHOB
,
EP400
,
NCAM1, TPTEP2-CSNK1E
, and
LINC02881
). Exome-wide single common variant analysis revealed nine lead single-nucleotide polymorphisms (SNPs) associated with household income and 34 lead SNPs associated with EduYears, replicating previous GWAS findings. The gene–environment correlations had a substantial impact on the genetic associations with SES, as indicated by the significantly increased
P
values in several associations after controlling for geographic regions. Furthermore, we observed the pleiotropic effects of SES-associated genetic factors on a wide range of health outcomes, such as cognitive function, psychosocial status, and diabetes. This study highlights the contribution of coding variants to SES and their associations with health phenotypes.
Escalation of genome defense capacity enables control of an expanding meiotic driver
Authors: Chen Peiwei , Pan Katherine C. , Park Eunice H. , Luo Yicheng , Lee Yuh Chwen G. , Aravin Alexei A.
Published: January 2025

From RNA interference to chromatin silencing, diverse genome defense pathways silence selfish genetic elements to safeguard genome integrity. Despite their diversity, different defense pathways share a modular organization, where numerous specificity factors identify diverse targets and common effectors silence them. In the PIWI-interacting RNA (piRNA) pathway, target RNAs are first identified by complementary base pairing with piRNAs and then silenced by PIWI-clade nucleases. Such a binary architecture allows the defense systems to be readily adaptable, where new targets can be captured via innovation of specificity factors. Thus, our current understanding of genome defense against lineage-specific selfish genes has been largely limited to specificity factor innovations, while it remains poorly understood whether other types of innovations are required. Here, we describe a new type of innovation, which escalates the genome defense capacity to control a recently expanded selfish gene in
Drosophila melanogaster
. Through a targeted RNAi screen for repressors of
Stellate
—a recently evolved meiotic driver—we identified a defense factor, Trailblazer. Trailblazer is a transcription factor that promotes the expression of two PIWI-clade nucleases, Aub and AGO3, to match
Stellate
in abundance. Recent innovation in the DNA-binding domain of Trailblazer enabled it to elevate Aub and AGO3 expression, thereby escalating the silencing capacity of piRNA pathway to tame expanded
Stellate
and safeguard fertility. As copy-number expansion is a recurrent feature of diverse selfish genes across the tree of life, we envision that augmenting the defense capacity to quantitatively match selfish genes is a repeatedly employed defense strategy in evolution.
Funding rules that promote equity in climate adaptation outcomes
Authors: Pollack Adam B. , Santamaria-Aguilar Sara , Maduwantha Pravin , Helgeson Casey , Wahl Thomas , Keller Klaus
Published: January 2025

Many climate policies adopt improving equity as a key objective. A key challenge is that policies often conceive of equity in terms of individuals but introduce strategies that focus on spatially coarse administrative areas. For example, the Justice40 Initiative in the United States requires 518 diverse federal programs to prioritize funds for “disadvantaged” census tracts. This strategy is largely untested and contrasts with the federal government’s definition of equity as the “consistent and systematic fair, just and impartial treatment of all individuals (Executive Office of the President, Federal Register, 2021).” How well does the Justice40 approach improve equity in climate adaptation outcomes across
individuals
? We analyze this question using a case study of a municipality that faces repetitive flooding and struggles to effectively manage these risks due to limited resources and public investment. We find that the way the Federal Emergency Management Agency implements the Justice40 Initiative can be an obstacle to promoting equity in household flood-risk outcomes. For example, in this case study, ensuring the majority of benefits accrue in “Justice40 Communities” does not reduce risk for the most burdened households, does not reduce risk-burden inequality, and produces net costs. In contrast, we design simple funding rules based on household risk burden that cost-effectively target the most burdened households, reduce risk-burden inequality, and accrue large net benefits. Our findings suggest that “disadvantaged community” indicators defined at coarse spatial scales face the risk of poorly capturing many climate risks and can be ineffective for meeting equity promises about climate-related investments.
The (anti-)political logic of authoritarian institutionalism
Authors: Kim Seongcheol
Published: January 2025

This paper develops the concept of authoritarian institutionalism — understood as a combination of
authoritarianism as a form of discursive closure and institutionalism as a non-antagonistic construction of social relations
following the logic of difference based on Laclau’s theory — which can yield insights from a discursive angle into the workings of
“competitive authoritarian” regimes characterized by formally multi-party systems. Based on these considerations, the paper
undertakes a periodization of party politics in Russia since 1993, which presents a useful case for probing the boundaries of
authoritarian institutionalism given the regime-engineered dynamics of party competition since the days of so-called “managed
democracy.” In applying the discourse-theoretical toolkit of difference/equivalence, the analysis identifies two phases of
authoritarian consolidation since 2000 that have expanded the authoritarian dimension while curtailing the institutionalist
operation of difference in the party system, raising the question of a “GDR-ization” of party politics since Russia’s full-scale
invasion of Ukraine.
Drugs exhibit diverse binding modes and access routes in the Nav1.5 cardiac sodium channel pore
Authors: Tao Elaine , Corry Ben
Published: January 2025

Small molecule inhibitors of the sodium channel are common pharmacological agents used to treat a variety of cardiac and nervous system pathologies. They act on the channel via binding within the pore to directly block the sodium conduction pathway and/or modulate the channel to favor a non-conductive state. Despite their abundant clinical use, we lack specific knowledge of their protein–drug interactions and the subtle variations between different compound structures. This study investigates the binding and accessibility of nine different compounds in the pore cavity of the Nav1.5 sodium channel using enhanced sampling simulations. We find that most compounds share a common location of pore binding—near the mouth of the DII–III fenestration—associated with the high number of aromatic residues in this region. In contrast, some other compounds prefer binding within the lateral fenestrations where they compete with lipids, rather than binding in the central cavity. Overall, our simulation results suggest that the drug binding within the pore is highly promiscuous, with most drugs having multiple low-affinity binding sites. Access to the pore interior via two out of four of the hydrophobic fenestrations is favorable for the majority of compounds. Our results indicate that the polyspecific and diffuse binding of inhibitors in the pore contributes to the varied nature of their inhibitory effects and can be exploited for future drug discovery and optimization.
Probing the Néel order in altermagnetic RuO2 films by X-ray magnetic linear dichroism
Authors: Zhang Yi-Chi , Bai Hua , Chen Chong , Han Lei , Liang Shi-Xuan , Chu Rui-Yue , Dai Jian-Kun , Pan Feng , Song Cheng
Published: January 2025

The emerging altermagnetic RuO2 with both compensated magnetic moments and broken time-reversal symmetry possesses nontrivial magneto-electronic responses and nonrelativistic spin currents, which are closely related to magnetic easy axis. To probe the Néel order in RuO2, we conducted Ru M
3-edge X-ray magnetic linear dichroism (XMLD) measurement. For epitaxial RuO2 films, characteristic XMLD signals can be observed in either RuO2(100) and RuO2(110) at normal incidence or RuO2(001) at oblique incidence, and the signals disappear when test temperature exceeds Néel temperature. For nonepitaxial RuO2 films, the flat lines in the XMLD patterns of RuO2(100) and RuO2(110) demonstrate that there is no in-plane uniaxial alignment of Néel order in these samples, due to the counterbalanced Néel order of the twin crystals evidenced by X-ray diffraction phi-scan measurements. Our experimental results unambiguously demonstrate the antiferromagnetism in RuO2 films and reveal the spatial relation of Néel order to be parallel with RuO2 [001] crystalline axis. These research findings would deepen our understanding of RuO2 and other attractive altermagnetic materials applied in the field of spintronics.
Vacuum DC breakdown characteristics between grid electrodes with ion sputtering
Authors: Liu Hao-Yan , Liu Wen-Xuan , Sun Guang-Yu , Liu Yue-Lin , Zhang Li-Wei , Zhou Sheng , Qi Chang-Chun , Sun An-Bang , Zhang Guan-Jun
Published: January 2025

In ion thrusters, grid electrodes are biased at high voltage to extract and accelerate ions. However, they are susceptible to vacuum breakdown which considerably undermines the ion thruster performance. To optimize the grid electrode design and improve the ion thruster longevity, the impact of ion sputtering on the vacuum direct-current breakdown characteristics of grid electrodes is systematically examined. The adopted seven-aperture grid electrodes are made of three materials including molybdenum, graphite, and stainless steel, which are exposed to Ar+ and Xe+ sputtering at energies of 400 eV and 1000 eV for durations ranging from 0.5 to 8 h. It is found that the initial breakdown voltage, which means the first breakdown voltage after sputtering, generally decreased regardless of the electrode material as the sputtering time increased. However, the breakdown voltage rapidly increases with more repeated discharges. Each kind of electrode material demonstrates unique responses to ion sputtering and breakdown. In comparison with metal electrodes, the graphite surface is relatively easy to appear defects but exhibits the least insulation degradation. The metal surface remains relatively smooth, but breakdown voltage is significantly affected, with electrode materials such as stainless steel failing to recover to their initial insulation levels. Xe+ sputtering leads to greater breakdown voltage fluctuations during repeated discharges due to higher sputtering yield. Dark current is measured, and the field enhancement factor

β

FE

is calculated to reveal correlations between local electric field and the breakdown voltage. Furthermore, micro particles are identified as major contributors to the first few times breakdown. Based on above observations, two kinds of distinct discharge mechanisms, including the cascade discharge induced by micro particles and the discharge induced by field emission, are proposed to interpret experimental data.
Diffusion, mechanical and thermal properties of sT hydrogen hydrate by machine learning potential
Authors: Song Zixuan , Li Yuan , Shi Qiao , Qu Yongxiao , Hao Yongchao , Ma Rui , Zhang Zhisen , Wu Jianyang
Published: January 2025

Newly-synthesized structure T (sT) hydrate show promising practical applications in hydrogen storage and transport, yet the properties remain poorly understood. Here, we develop a machine learning potential (MLP) of sT hydrogen hydrate derived from quantum-mechanical molecular dynamics simulations. Using this MLP forcefield, the structural, hydrogen diffusion, mechanical and thermal properties of sT hydrogen hydrate are extensively explored. It is revealed that the translational and rotational mobilities of hydrogen molecule in sT hydrate are limited due to unique shape and finite dimensional cavities, and tiny windows of neighboring cavities. sT hydrogen hydrate exhibits unique uniaxial tension stress-strain response, with first nonlinear increase to GPa-level but followed by deep drop in the stretching stress, indicating brittle failure, similar to that by Density Functional Theory and empirical forcefields. Moreover, temperature-dependent thermal conductivity in sT hydrogen hydrate is mainly contributed by hydrogen-bonded network formed by host water molecules, while hydrogen guest molecules play an insignificant role in the thermal transport.
Turning tool wear state recognition based on EMDResNeStTime and sequence-global-encoding
Authors: Zhang Hucheng , Hu Fangmin , Xie Tao
Published: January 2025

Machining is the primary method used for producing parts and equipment. Tool wear is inevitable during this process and directly impacts the quality of the finished parts. Accurately recognising the tool wear status helps to reduce the risk of processing failure and improve overall processing efficiency. By establishing a mapping relationship between tool wear information and its associated status characteristics, accurate recognition of tool wear can be achieved. This paper proposes a novel intelligent recognition approach for tool wear state in machining process based on vibration signals. The EMDResNeStTime module uses empirical mode decomposition (EMD) and two-dimensional convolution to extract the main trend features of vibration signals, and the sequence-global-encoding module uses the self-attention mechanism to extract the global features of vibration signals, are designed. A new multi-feature parallel-time feature extraction backbone is constructed using these two modules. The use of this backbone effectively improves the ability of the network model to extract key features of complex trends in vibration signals. Experimental results show that the proposed method achieves 71.65%, 74.89%, 71.36% and 72.78% in accuracy, precision, recall and F1 score, respectively. Compared with other network models, it achieves higher recognition accuracy and more stable performance. The ablation experiment further confirms the classification effectiveness of the method used in this network model. The model can accurately recognise the tool status during the cutting process based on monitoring data, which will facilitate the implementation of a more effective tool change strategy in intelligent manufacturing and improving processing efficiency.
Boundary sample extraction support vector data description: a novel anomaly detection method for large-scale data
Authors: Wang Xiaofei , Chen Yongzhan , Xu Fenglei , Gao Yanli , Wang Yuanxin , Qiao Yuchuan , Dai Haomin , Wang Qiang
Published: January 2025

Support vector data description (SVDD) has been effectively used in many anomaly detection problems. Equipped with kernel functions, its training complexity grows exponentially with the increase in training data, which makes it less practical for large-scale datasets. In this paper, we propose a boundary sample extraction SVDD (BSE-SVDD) anomaly detection method based on data reduction, aiming for use with large-scale data. Firstly, the BSE mechanism is established on the basis of demonstrating that the spatial position of the sample is related to its corresponding Lagrange multiplier. Then, the BSE mechanism is used to search for the local optimal solution of the Lagrange multiplier, and all the training samples are sorted. Finally, the top p of ranked samples are extracted as boundary samples for training, while most of the training samples that may be non-support vectors are removed. Compared with SVDD studies based on data reduction, the experimental results on large-scale datasets show that BSE-SVDD can obtain comparable classification accuracy with greatly improved training speed.
TCN-MBMAResNet: a novel fault diagnosis method for small marine rolling bearings based on time convolutional neural network in tandem with multi-branch residual network
Authors: Li Yuanjiang , Yang Zhenyu , Zhang Shuo , Mao Runze , Ye Linchang , Liu Yun
Published: January 2025

Centrifugal pumps are key components of marine systems, and the health of their internal rolling bearings is critical for the normal operation of ships. In small ship replenishment systems, the rolling bearings of centrifugal pumps often have short failure times, making it difficult to gather balanced failure data. This paper addresses the challenges in extracting fault features from centrifugal pump bearings in ship water replenishment systems and the low accuracy of fault identification caused by unbalanced data samples. A fault diagnosis method is proposed that combines a time convolutional neural network (TCN) with multi-branch mixed attention residual networks (MBMAResNet). This paper introduces TCN to capture dependencies in long time series and optimize the feature distribution of raw data. The captured multi-channel 1-D feature sequences are converted into 2D feature maps to provide spatially correlated features for the designed MBMAResNet. Multiple single path fusion residual blocks with different scales are designed in the MBMAResNet to further extract effective fault features from the unbalanced samples, and a feature fusion structure is utilized for further feature enhancement. Additionally, improved convolutional block attention modules are integrated into the network to increase the significance of valid channels and spatial locations. Experiments on an unbalanced public dataset and a private centrifugal pump faulty bearing dataset achieved diagnostic accuracies of 99.71% and 98.50%, respectively, demonstrating that the proposed method offers higher accuracy and generalizability compared to other methods.
A distributed training framework for abnormal sound detection in industrial devices: aggregation strategies and performance analysis
Authors: Yang Rui , Wang Kunpeng , Li Xinrong
Published: January 2025

In today’s digital and networked industrial landscape, the detection of abnormal sounds in device has emerged as a vital aspect for guaranteeing the normal operation of industrial machinery. Nevertheless, traditional centralized training approaches demand substantial amounts of audio data, imposing considerable burdens on data storage and transmission, and concurrently presenting obstacles to data privacy and security. Federated learning, as a distributed machine learning paradigm, enables model training with local data from each client without sharing the original data, thereby effectively safeguarding data privacy. Hence, in this study, we propose a distributed training framework based on federated training, which enables multiple clients to collaboratively train an abnormal sound detection model, thereby mitigating the risk of data privacy exposure. In the distributed training framework, each client possesses data from different types of device or various machines within the same device type, posing significant challenges for distributed training. To overcome this, we devised two client device distribution scenarios and proposed aggregation strategies based on client sample size, model performance, and domain shift among clients. Additionally, we introduced a sample-performance-shift (SPS) aggregation strategy to ensure robust model performance across diverse device scenarios in industrial settings. The proposed methods were evaluated on the DCASE 2020 Challenge Task 2 dataset. Experimental results demonstrate that the SPS aggregation strategy enhances the accuracy and reliability of abnormal sound detection for industrial device within the distributed training framework while simultaneously reducing the risk of data privacy leakage.
Ameliorating macrophage pyroptosis via ANXA1/NLRP3/Caspase-1/GSDMD pathway: Ac2-26/OGP-loaded intelligent hydrogel enhances bone healing in diabetic periodontitis
Authors: Li Ruoyu , Li Wenfeng , Teng Yungshan , Li Runze , Kong Siyi , Chen Xin , Luo Haotian , Chen Danying , Guo Yuqing , Qing Yangqiao , Leong Hio Cheng , Guo Bingyan , Chen Meihan , Pan Zixin , Zheng Shushuo , Deng Yihong , Cao Yang , Zhou Chen , Zou Xuenong , Wang Weicai
Published: January 2025

Craniofacial bone defect healing in periodontitis patients with diabetes background has long been difficult due to increased blood glucose levels which cause overproduction of reactive oxygen species (ROS) and a low pH environment. These conditions negatively affect the function of macrophages, worsen inflammation and oxidative stress, and ultimately, hinder osteoblasts’ bone repair potential. In this study, we for the first time found that annexin A1 (ANXA1) expression in macrophages was reduced in a diabetic periodontitis (DP) environment, with the activation of the NLRP3/Caspase-1/GSDMD signaling pathway, and, eventually, increased macrophage pyroptosis. Next, we have developed a new GPPG intelligent hydrogel system which was ROS and pH responsive, and loaded with Ac2-26, an ANXA1 bioactive peptide, and osteogenic peptide OGP as well. We found that Ac2-26/OGP/GPPG can effectively reduce ROS, mitigates macrophage pyroptosis via the ANXA1/NLRP3/Caspase-1/GSDMD pathway and enhanced osteogenic differentiation. The effect of Ac2-26/OGP/GPPG in regulation of pyroptosis and bone defect repair was also further validated by animal experiments on periodontitis-induced tooth loss model in diabetic rats. To conclude, our study unveils the effect of ANXA1 on macrophage pyroptosis in periodontitis patients with diabetes, based on which we introduced a promising innovative hydrogel system for improvement of bone defects repair in DP patients via targeting macrophage pyroptosis and enhancing osteogenic potential.
Investigation on zinc oxide as an antireflection coating on silicon-based solar cells using ray tracing
Authors: Aziz Nur Amelia Shazana , Yahaya Bermakai Madhiyah , Mohd Yusoff Mohd Zaki
Published: January 2025

Since antireflective coating (ARC) has the ability to lessen optical loss experienced by solar cells, it is beginning to gain traction in the solar cell market. Without the use of ARC, the solar cell’s surface reflects about 30% of light and leads to a decrease in efficiency. The Zinc Oxide (ZnO) material has been chosen in this study as the ARC to study the enhancement of the solar cells’ performance using simulation approach. The ZnO layer is used as an ARC on top of the silicon based solar cell with certain thicknesses ranging from 60 to 90 nm. The optimum thickness of ZnO that results in the maximum current density is chosen for further modification on surface texturing. Four types of textured surface on the front surface of silicon based solar cell are proposed. It is shown that 80 nm thickness of ZnO ARC revealed the best performance in terms of current density generated which is reach 34.92 mA cm−2. Positive increment of current density is shown on further modification of surface texturing. Random inverted pyramids appear to be the best front surface with another 17.5% increment in current density.
Investigations on the high-temperature wear behaviour of LM25 aluminium alloy/silicon carbide foam interpenetrating phase composites synthesized using gas pressure infiltration
Authors: Senthilkumar M , T Satish V , Bright Renjin J , K Somasundara Vinoth , G Vasundhara M
Published: January 2025

Ceramic foam-based interpenetrating phase composites (IPCs) are progressively garnering interest towards the construction of brake components. To comprehend the use of IPCs for real-time braking applications, it is necessary to study their wear behaviour at elevated temperatures. The present study is solemnly envisioned to examine the high-temperature wear and friction behaviour of the novel LM25 aluminium alloy/Silicon Carbide foam (SiCf)- IPCs developed using the gas pressure infiltration process. SiCf of pore densities 10, 20 and 30 pores per inch (PPI) were used for synthesizing the IPCs. A pin-on-disc wear testing apparatus in which the pin specimen prepared from the IPCs connected to a heating element was used to perform the wear study. The experimental design for conducting the wear study was developed using response surface methodology (RSM) with four continuous factors namely pore density (PPI), applied load (N), sliding speed (m/s) and temperature (οC). Each factor was assigned with three different levels which resulted in 30 experimental runs for which wear rate and coefficient of friction were estimated. The study testified that the IPCs prepared using 30 PPI SiCf possessed a low wear rate and higher coefficient of friction compared to those prepared using 10 and 20 PPI SiCf. The worn surface morphology of the IPCs revealed the predominant wear mechanisms at low temperatures as abrasive and that at higher temperatures as adhesive mode.
Controllable anisotropic wettability behaviours of droplets by varying profile stripe structures
Authors: Wu Boqi , Dong Litong , Liu Mengnan , Hu Jing
Published: January 2025

Anisotropic wettability of bionic structures is often achieved through anisotropic patterns, so the parameters are key to managing surface wettability behaviours. In this work, we fabricate three kinds of one-dimensional (1D) stripe structures with distinct profile shapes to study the method of controlling the anisotropic wettability behaviours of water droplets. By controlling their profiles and depths, the anisotropic wettability of stripes can be effectively managed and mitigated. Even with the same stripe periods, we can achieve two opposing wetting effects, namely isotropic hydrophobicity and anisotropic hydrophilicity. The experiments show that the π-shaped stripes possess isotropic superhydrophobicity, and their adhesion force to water droplets in the direction perpendicular to the groove is approximately ten times that in the parallel direction. Meanwhile, the willow-leaf-shaped stripes show anisotropic hydrophilic properties and good ductility to water droplets. Taking advantage of inductively coupled plasma-reactive ion etching (ICP-RIE) with a low undercut, this method provides a novel perspective on the design of interfaces for droplet manipulation, pick-and-place applications, and the localised control of reactions.
A reinforcement learning approach to the design of quantum chains for optimal energy and state transfer
Authors: Sgroi S , Zicari G , Imparato A , Paternostro M
Published: January 2025

We propose a bottom–up approach, based on reinforcement learning, to the design of a chain achieving efficient excitation-transfer performances. We assume distance-dependent interactions among particles arranged in a chain under tight-binding conditions. Starting from two particles and a localised excitation, we gradually increase the number of constitutents of the system so as to improve the transfer probability. We formulate the problem of finding the optimal locations and numbers of particles as a Markov decision process: we use proximal policy optimization to find the optimal chain-building policies and the optimal chain configurations under different scenarios. We consider both the case in which the target is a sink connected to the end of the chain and the case in which the target is the right-most particle in the chain. We address the problem of disorder in the chain induced by particle positioning errors. We apply our methodology to a simplified model of a relevant physical platform, consisting of trapped ions. We are able to achieve extremely high excitation transfer in all cases, with different chain configurations and properties depending on the specific conditions.
Culpability, Consequences, and Sentencing
Authors: Ashworth Andrew
Published: January 2025

How should the relative strength of culpability and consequences be assessed in sentencing? Setting out three scenarios that currently engage the courts of England and Wales, this chapter explores the intent principle and the belief principle that underlie the emphasis on culpability, taking particular account of moral luck and the focus on trying and exertions. The chapter argues in favour of a fully subjective principle of criminal liability and of sentencing but leaves open the possibility that there may be a role for public opinion. This would require further research on public opinion and an active role for a sentencing commission.
The Evolution of Proportionality in Sentencing
Authors: Manikis Marie
Published: January 2025

The principle of proportionality has developed considerably over the years with various complementary and challenging additions to its original framing, in great part due to the substantial reflections and perspectives of Professor Roberts. Indeed, Roberts has infused this principle with relevant empirical and theoretical considerations, which have contributed to its enduring relevance, legitimacy, and influence throughout the years in theory, policy, and practice. This chapter discusses some of these developments by highlighting Roberts’ contribution towards a more dynamic form of censure; a greater individualization of harm, notably, by including victims, and an expanded understanding of moral blameworthiness. It then builds on Roberts’ commitment towards a more accurate ascription of censure and culpability within just deserts, by relying on empirical studies and experiential evidence in order to revisit the just deserts position on social deprivation and proportionality. It argues that individual background, social context, and empirical knowledge offer relevant context, which can enable a more accurate ascription of responsibility and censure within a desert-based understanding of proportionality.
Sentencing Ethically
Authors: Watson Gabrielle
Published: January 2025

The work of Julian V Roberts conveys a deep ethical sensibility that marks him out as one of the most humane sentencing scholars of our time. This chapter brings into focus the subtler ethical dimension of Roberts’ scholarship and evaluates its significance. It does so with reference to three distinctive strands of his work: first, on the sentencing of women, second, on guilty pleas, and third, on ‘second look’ sentence reviews for long-term prisoners. There, we find an implicit commitment to moral principles and values including fairness, respect, and hope, together with a distinctive orientation towards them that is worthy of sustained attention. In Roberts’ worldview, fairness, respect, and hope are not merely analytic ideals but institutional commitments: grounded, pragmatic, and attainable, with immediate implications for sentencing practice and reform.

No doubt our honorand has left an indelible mark on sentencing scholarship and practice on the global stage. It is less often observed, however, that Roberts has become one of the great mediators of our discipline, appealing to pragmatists and normative theorists alike and foregrounding both styles of scholarship in the collaborative projects he has led. Only at first glance are Roberts’ writings on criminal justice principally and inescapably pragmatic. On closer inspection, Roberts gives important contextual cues—especially in his more recent works—that he is also an ethicist of the highest calibre, with profound insights to offer on the moral rights and wrongs of the sentencing court.
In Search of Proportionate Sentencing
Authors: Doob Anthony N , Sprott Jane B
Published: January 2025

This chapter examines a sentencing concept that Julian V Roberts has addressed in a large number of publications in the past forty years or so: proportionality. It first examines the efforts that Roberts and others have made to try to find mechanisms to give weight to an offender’s criminal record in a manner that does not undermine proportionality. Second, the chapter examines the Canadian ‘conditional sentence of imprisonment’ (a version of the suspended sentence) suggesting that its inadequate legislative framing in Canada reflected the fact that its real purpose was only to reduce the use of imprisonment. In both of these areas, any attempt to come up with clever ways of maintaining the pretence that sentences are proportional may be futile. For example, since criminal records vary on a large number of dimensions, some of which will affect the manner in which a sentence is served, it may be impossible, at sentencing, to go beyond a general statement related to the importance of proportionality and an indication that sentences can be affected by criminal records. Similarly, a broad statement saying that all sentences—custodial, suspended, and community—should be roughly proportionate to the severity of the offence may be all that can be meaningfully stated.