Structure Model Research Articles

Research on Support Structure of Rectangular Cryogenic Infrared Lens with Large Aperture

This paper presents the design and optimization of a composite flexible support structure aimed at addressing the challenges associated with maintaining the positional accuracy and surface integrity of large-aperture cryogenic infrared lenses with long focal lengths. The primary objective of the structure is to maintain precise lens alignment while preserving the surface shape under operational conditions. The design complexities and underlying principles of the flexible support structure are systematically explored. A mechanical model of the flexible support structure was derived based on its structural characteristics, and the equilibrium equation was established to ensure the lens meets thermal deformation requirements in various directions. Optimization of key design parameters was conducted for a lens operating at 200 K, measuring 304 mm × 230 mm. The gravitational deformation of the optimized lens exhibited a root mean square (RMS) surface accuracy of 7.72 nm in the X direction, 7.08 nm in the Y direction, and 9.60 nm in the Z direction for lens surface 1. For lens surface 2, RMS values were 8.62 nm in the X direction, 8.41 nm in the Y direction, and 9.64 nm in the Z direction. At 200 K and lower temperatures, the RMS values of lens surfaces 1 and 2 were 2.41 nm and 2.74 nm, respectively, with a first-order mode frequency of 143.37 Hz.

Bioinformatics analysis to design a multi-epitope mRNA vaccine againstS. agalactiaeexploiting pathogenic proteins.

Antibiotic resistance in bacterial pathogen infections is a growing global issue that occurs due to their adaptation to changing environmental conditions. Therefore, producing an efficient vaccine as an alternative approach can improve the immune system, eradicate related pathogens, and overcome this growing problem.Streptococcus agalactiaebelongs to group B Streptococcus (GBS). Colonization of GBS during pregnancy is a significant risk factor for infants and young children. S. agalactiae infected population exhibits resistance to beta-lactams, including penicillin and the second-line antibiotics erythromycin and clindamycin.On the other hand, there are currently no commercial vaccines against this pathogen. Vaccination of pregnant women is a highly effective method to protect newborns and infants from S. agalactiaeinfection, and it has been identified as an urgent demand by the World Health Organization. This study employed various immunoinformatic tools to develop an effective vaccine that could trigger both humoral and cell-mediated immunity and prevent disease. For this purpose, three conserved antigenic proteins of the main pathogenic strains ofS. agalactiaewere utilized to predict CTL, HTL, and B-cell epitopes for producing an mRNA vaccine against different strains ofS. agalactiae. The selected epitopes were fused using proper linkers. The Resuscitation promoting factor E (RpfE) sequence was incorporated in the designed vaccine construct as an adjuvant to boost its immune response. Different physicochemical characteristics of the final designed vaccine, modeling of the three-dimensional structure, molecular docking, molecular dynamics simulation, and immunological response simulation were screened following vaccine administration in an in vivo model.Computational immune simulation data identified that IgG1, IgM, INF γ, IL-2, T helper, and B-cell populations increased significantly after vaccination. These findings suggested that the vaccine candidate may provide good protection againstS. agalactiaeinfection. However,experimental and animal model studies are required for additional validation and implementation in human vaccination programs.

Noise schemas aid hearing in noise

Human hearing is robust to noise, but the basis of this robustness is poorly understood. Several lines of evidence are consistent with the idea that the auditory system adapts to sound components that are stable over time, potentially achieving noise robustness by suppressing noise-like signals. Yet background noise often provides behaviorally relevant information about the environment and thus seems unlikely to be completely discarded by the auditory system. Motivated by this observation, we explored whether noise robustness might instead be mediated by internal models of noise structure that could facilitate the separation of background noise from other sounds. We found that detection, recognition, and localization in real-world background noise were better for foreground sounds positioned later in a noise excerpt, with performance improving over the initial second of exposure to a noise. These results are consistent with both adaptation-based and model-based accounts (adaptation increases over time and online noise estimation should benefit from acquiring more samples). However, performance was also robust to interruptions in the background noise and was enhanced for intermittently recurring backgrounds, neither of which would be expected from known forms of adaptation. Additionally, the performance benefit observed for foreground sounds occurring later within a noise excerpt was reduced for recurring noises, suggesting that a noise representation is built up during exposure to a new background noise and then maintained in memory. These findings suggest that noise robustness is supported by internal models-"noise schemas"-that are rapidly estimated, stored over time, and used to estimate other concurrent sounds.

Seismic horizon tracking based on TransUnet model

Seismic horizons are of paramount importance for building structure models and stratigraphic interpretations. However, currently, horizon tracking is generally obtained through manual tracking or a combination of traditional automatic tracking and manual tracking, which is a highly time-consuming and error-prone process. Despite the many methods proposed for automated horizon tracking, tracking horizons with complex features still face numerous challenges.This paper proposes a method for horizon tracking using the TransUnet model, which can be applied to track both individual horizons and multiple horizons simultaneously. This method is implemented through deep learning semantic segmentation. Training is conducted using a deep learning encoder-decoder structure to establish the mapping relationship between seismic data and horizon data. The TransUnet model builds upon the Unet model by incorporating Transformer modules, enabling the model to possess both local and global attention capabilities. The ultimate results of horizon tracking reveal that the TransUnet model is more proficient at tracking horizons in areas with complex seismic reflections compared to the Unet model. In single and multiple horizon tracking, the root mean square error (RMSE) and coefficient of determination (R2 ) calculated from horizons predicted by the TransUNet model and manually tracked horizons are significantly lower than those of the U-Net model, this research demonstrates that the proposed method is more efficient and accurate in tracking the horizons of three-dimensional seismic volumes compared to traditional approaches.

Enabling Industry 5.0-Driven Circular Economy Transformation: A Strategic Roadmap

Because Industry 4.0 is not a better solution to the problems of the circular economy development process, the European Union proposed Industry 5.0 as a supplement to Industry 4.0. However, presently, no relevant research exists on the promotion of a circular economy under Industry 5.0, and the limited understanding of this process is the fundamental obstacle for enterprises to pursue digitalization and sustainable operations. This study addresses this knowledge gap by developing a roadmap explaining the use of the drivers of Industry 5.0 to support and promote the transformation to a circular economy. This study first screens the literature and determines 11 drivers of Industry 5.0. Secondly, on this basis, a fuzzy explanatory structure model of these drivers promoting a circular economy is constructed. Finally, a strategic roadmap is constructed for Industry 5.0 to promote a circular economy. The results reveal that the 11 key factors driving the circular economy are complementary, among which the quantitative criteria and indicators are the most critical and are present at the bottom of the strategic map. Value chain integration and the transformation into a sustainable business model are the most complex drivers. The strategic roadmap can explain the effects of the various drivers on the transformation to a circular economy and the order required to promote this transformation. The resulting management mindset is expected to assist manufacturers, industrialists, academia, and governments in providing services, thus forming a strategic guideline driven by Industry 5.0 factors to promote the circular economy.

Stellar expansion or inflation?

While stellar expansion after core-hydrogen exhaustion related to thermal imbalance has been documented for decades, the physical phenomenon of stellar inflation that occurs close to the Eddington limit has only come to the fore in recent years. We aim to elucidate the differences between these physical mechanisms for stellar radius enlargement, especially given that additional terms such as `bloated' and `puffed-up' stars have been introduced in the recent massive star literature. We employ single and binary star MESA structure and evolution models for constant mass, as well as models allowing the mass to change due to winds or binary interaction. We find cases that were previously attributed to stellar inflation in fact to be due to stellar expansion. We also highlight that while the opposite effect of expansion is contraction, the removal of an inflated zone should not be referred to as contraction but rather deflation as the star is still in thermal balance.

3D Hydrogeological Structure Modeling Based on Quantitative Correlation and Identification of Aquifer Types Within Stratigraphic Layers

3D Hydrogeological Structure Modeling Based on Quantitative Correlation and Identification of Aquifer Types Within Stratigraphic Layers

Secondary Structure Detection and Structure Modeling for Cryo-EM.

Rapid advancements in cryogenic electron microscopy (cryo-EM) have revolutionized the field of structural biology by enabling the determination of complex macromolecular structures at unprecedented resolutions. When cryo-EM density maps have a resolution around 3Å, the atomic structure can be modeled manually. However, as the resolution decreases, analyzing these density maps becomes increasingly challenging. For modeling structures in lower resolution maps, deep learning can be used to identify structural features in the maps to assist in structure modeling.Here, we present a suite of deep learning-based tools developed by our lab that enable structural biologists to work with cryo-EM maps of a wide range of resolutions. For cryo-EM maps at near-atomic resolution (5Å or better), DeepMainmast automatically models all-atom structures by tracing the main chain from local map features of amino acids and atoms detected by deep learning; DAQ score quantifies map-model fit and indicates potential misassignments in protein models. In intermediate resolution maps (5-10Å), Emap2sec and Emap2sec+ can accurately detect protein secondary structures and nucleic acids. These tools and more are available at our web server: https://em.kiharalab.org/ .

Investigation of the mechanism of [M-H]+ ion formation in photoionized N-alkyl-substituted thieno[3,4-c]-pyrrole-4,6-dione derivatives during higher order MSn high-resolution mass spectrometry.

The mechanism underlying dopant-assisted atmospheric pressure photoionization's (APPI) formation of ions is unclear and still under debate for many chemical classes. In this study, we reexamined the gas-phase reaction mechanisms responsible for the generation of [M-H]+ precursor ions, resulting from the loss of a single hydrogen atom, in a series of N-alkyl-substituted thieno[3,4-c]-pyrrole-4,6-dione (TPD) derivatives. Atmospheric pressure photoionization combined with higher order MS/MSn using high-resolution mass spectrometry (APPI-HR-CID-MSn) and electronic structure calculations using density functional theory were used to determine the chemical structure of observed [M-H]+ ions. As a result, the higher order MSn (n = 3) experiments revealed a reversed Diels-Alder fragmentation mechanism, leading to a common fragment ion at m/z 322 from the studied [M1-5-H]+ ion species. In addition, the calculation for two chemical structure models (N-alkyl-TPD1 and N-alkyl-TPD5) showed that the fragment structure, resulting from the removal of the hydrogen atom connected to the third carbon atom of the N-alkyl side chain, has a more stable cyclic form compared with the linear one. The proposed chemical structure of the N-alkyl TPD ion species, following the loss of a single hydrogen atom, was revealed during APPI-HR-CID-MSn (n= 3) experiments on the [M-H]+ species. Hydrogen radical (H•) abstraction from the alkyl side chain (e.g., hexyl, heptyl, octyl, 2-ethylhexyl, and nonyl) triggered a rearrangement in the radical cation structure of the N-alkyl-TPD derivatives, initiating cyclization and forming a six-membered ring that connects the oxygen atom to the third carbon atom in the alkyl chain. In addition, theoretical calculations supported the APPI-HR-CID-MSn (n = 3) experiments by demonstrating that the proposed chemical structure, resulting from the intramolecular cyclization of the N-alkyl-TPD ion species, was stable in the presence of chlorobenzene. These findings will aid the structural determination and elucidation of molecules with similar core structures.

Trabecular bone structural units (BSU) and their cement lines change with age, bone volume fraction, structure, and strength in female human vertebrae

Abstract A lifetime of successive bone remodeling events leads to trabeculae, which are composed of a patchwork of bone structural units (BSU) called hemi-osteons or trabecular packets. Traditionally, only intact surface BSU have been studied, which are those that have been created most recently. Accordingly, the complex changes in the size and distribution of BSU throughout the trabeculae have been overlooked. In this study, the BSU within the trabeculae of the second lumbar vertebrae were manually traced using ImageJ software, in osteopontin immunostained sections of eight young women (aged 19–38 years) and eight older women (aged 69–96 years). A series of BSU profile properties including area, width, length, and perimeter were quantified, along with properties of each trabecular profile such as the number of BSU and cement line length. The relationships between these properties and age, as well as selected trabecular microstructural properties assessed with microcomputed tomography, and bone strength assessed on the neighboring third lumbar vertebrae, were investigated. The median BSU profile length and perimeter decreased with age, while median BSU profile area and width was unchanged. Moreover, age was associated with an increase in the number of BSU profiles and cement line length per trabecular profile area. However, changes in BSU profile geometry, the number of BSU profiles, and the cement line length per trabecular profile were strongly correlated with trabecular bone volume fraction, structure model index, and bone strength. Further research is needed to understand how these changes in BSU properties affect the mechanical and failure properties of trabecular bone.

Research on 3D humanoid robot pose estimation based on HRNet-Epipolar and CRF robot model by multiple view

Purpose This paper aims to present an unmarked method including entire two-dimensional (2D) and three-dimensional (3D) methods to recover absolute 3D humanoid robot poses from multiview images. Design/methodology/approach The method consists of two separate steps: estimating the 2D poses in multiview images and recovering the 3D poses from the multiview 2D heatmaps. The 2D one is conducted by High-Resolution Net with Epipolar (HRNet-Epipolar), and the Conditional Random Fields Humanoid Robot Pictorial Structure Model (CRF Robot Model) is proposed to recover 3D poses. Findings The performance of the algorithm is validated by experiments developed on data sets captured by four RGB cameras in Qualisys system. It illustrates that the algorithm has higher Mean Per Joint Position Error than Direct Linear Transformation and Recursive Pictorial Structure Model algorithms when estimating 14 joints of the humanoid robot. Originality/value A new unmarked method is proposed for 3D humanoid robot pose estimation. Experimental results show enhanced absolute accuracy, which holds important theoretical significance and application value for humanoid robot pose estimation and motion performance testing.

AI Predictive Analytics for Verifying Pharmaceutical Authenticity and Combating Drug Counterfeiting

A significant worry in recent years has been the counterfeiting of medicines. The distribution and manufacture of fake or falsified drugs are both criminal and harmful to the public's health. The severity of this issue differs significantly from one country to another, primarily due to variations in the adherence to national regulations and processes. Thus, preventing the sale of fake drugs has become an urgent matter, particularly in poor and developing nations. The study presents a new multi-layered validation structure for pharmaceutical authenticity verification that uses Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNNs) and blockchain technology for artificial intelligence predictive analytics. The goal is to tackle the widespread problem of counterfeit drugs. Using GANs to sift through past data, the suggested strategy improves the detection of minor package variations by identifying trends and traits linked to counterfeit drugs. Using the GAN-generated enhanced dataset, a CNN is trained to accurately and specifically categorize drug packaging.Further, the framework uses blockchain technology to provide trustworthy and transparent recordkeeping of drugs in realtime as they move through the supply chain. Increased patient safety directly results from our system's thorough audit trail, which solves the problems of fake medications and regulatory compliance. The suggested approach reduces counterfeit dangers and provides a scalable paradigm for other industries to use when dealing with similar authenticity verification issues, which means it can find more uses in safety-critical fields. The success of the multi-layered validation structure model is evaluated using performance metrics such as accuracy, recall, and F1-score. It achieves a fantastic accuracy rate of over 95%.

Risk assessment of homologous variants of biotech trait proteins using a bridging approach

ABSTRACT A transgenic protein is frequently expressed as different homologous variants in genetically modified crops due to differential processing of targeting peptides or optimization of activity and specificity. The aim of this study was to develop a science-based approach for risk assessment of homologous protein variants using dicamba mono-oxygenase (DMO) as a case study. In this study, DMO expressed in the next-generation dicamba-tolerant maize, sugar beet and soybean crops exhibited up to 27 amino acid sequence differences in the N-terminus. Structure modeling using AlphaFold, ESMFold and OpenFold demonstrates that these small N-terminal extensions lack an ordered secondary structure and do not disrupt the DMO functional structure. Three DMO variants were demonstrated to have equivalent immunoreactivity and functional activity ranging from 214 to 331 nmol/min/mg. Repeated toxicity studies using each DMO variant found no test substance-related adverse effects. These results support that homologous protein variants, which have demonstrated physicochemical and functional equivalence, can leverage existing safety data from one variant without requiring additional de novo safety assessments.

A unified Jacobi-Ritz-spectral BEM for vibro-acoustic behavior of spherical shell

In order to solve the vibration and acoustic characteristics of spherical shell in light fluid environment, based on Jacobi-Ritz-spectral BEM, a unified analysis formula for acoustic vibration of spherical shell under arbitrary boundary conditions is established. Based on the First-order shear deformation theory (FSDT) and domain decomposition method (DDM), the theoretical model of spherical shell structure is established. The improved Jacobi polynomial is innovatively used to construct the displacement tolerance function of the spherical shell. Based on the spectral Kirchhoff-Helmholtz integral formula, the theoretical model of the acoustic fluid outside the spherical shell is established. The special form of Jacobi polynomial Chebyshev polynomial is used to describe the excitation sound pressure on the spherical shell segment, so as to ensure that the generalized coordinates of the structure can be perfectly matched with the acoustic boundary element nodes. In addition, the integration along the meridian of the shell is used to control the movement of the fluid, which simplifies the surface integration. The CHIEF method is used to solve the problem of non-unique solution of acoustic variables of rotary structure. Compared with the published literature, numerical simulation results and experimental results, the proposed method has higher calculation accuracy. In addition, based on this method, the influence of boundary conditions, geometric dimensions and other factors on the acoustic and vibration characteristics of spherical shells is discussed, which accumulates data for analyzing the acoustic and vibration behavior of spherical shells.

An improved coupled beam method for predicting longitudinal bending behaviour in luxury cruise ships

ABSTRACT This paper describes an improved coupled beam method, designated as MBS-CB, that estimates elastic response in the longitudinal bending of a cruise ship. Initially, the ship structure is discretised into beams, and the coupling relationships between adjacent beams are analysed. Secondly, connector elements with equal stiffness constraints are refined to simulate the coupling behaviour between adjacent beam elements. Meshed beam sections are introduced to simplify the beams involved in total longitudinal bending. A spatial beam system model of the ship structure is established to predict the interaction between adjacent beams and to characterise the longitudinal bending behaviour of the ship. Ultimately, the accuracy of the method is validated through instance analysis. Furthermore, the method is employed to investigate the longitudinal bending characteristics of a large passenger ship, and the participation of different superstructures in the ship's longitudinal bending is obtained through moment distribution coefficients and length proportions.

Identification of novel ABCB4 variants and genotype-phenotype correlation in progressive familial intrahepatic cholestasis type 3

Progressive familial intrahepatic cholestasis type 3 (PFIC3) is a severe hepatic disorder characterized by cholestasis. Elucidating the genotype-phenotype correlations and expanding the mutational spectrum of the ABCB4 gene are crucial for enhancing diagnostic accuracy and therapeutic strategies.Clinical and genetic data from 2 original PFIC3 patients from our institution, along with 118 additional cases identified through a comprehensive literature review, were integrated for a comprehensive analysis. The study included statistical analysis of clinical information, genetic analysis, multi-species sequence alignment, protein structure modeling, and pathogenicity assessment. Machine learning techniques were applied to identify genotype-phenotype relationships. We identified three novel ABCB4 mutations: two missense mutations (c.904G > T and c.2493G > C) and one splicing mutation (c.1230 + 1G > A). Homozygous mutations were associated with significantly earlier disease onset compared to compound heterozygous mutations (p < 0.0001). Missense mutations were predominant (76.9%), with Exon 7 being the most frequently affected region. A random forest model indicated that Exon 10 had the highest feature importance score (9.9%). Liver transplantation remains the most effective treatment modality for PFIC3. This investigation broadens the known mutation spectrum of the ABCB4 gene and identifies key variant sites associated with clinical manifestations. These insights lay a foundation for early diagnosis, optimal treatment selection, and further research into PFIC3.

The cross-cultural big two: A culturally decentered theoretical and measurement model for personality traits.

A "big two" model has shown stronger cross-cultural replicability and links to theory than other contemporary models of personality trait structure. However, its theoretical and measurement models require better specification. We address this to create an initial English-language version of the Cross-Cultural Big Two Inventory with an empirically informed and culturally decentered approach, meaning that input from global contexts is used from the outset, without prioritizing Western perspectives. Four studies are reported: (1) Fifty-five items were identified from commonalities among 11 global lexical studies to define two factors. Communion/Social Self-Regulation captures the internalization of versus resistance to the normative codes of one's society, with components of warmth, morality, respect, industriousness, and even temper. Agency/Dynamism captures approach versus avoidance tendencies, with components of competence, confidence, fearlessness, positive mood, sociability, and surgency. (2) Items were reduced to the 45 most consistent across English-speaking contexts based on (a) frequency of use in World English corpora; (b) familiarity and exploratory factor analysis results among Africa Long Life Study participants, who were 18-year-olds from Namibia, Kenya, and South Africa (N = 2,958); and (c) distribution test statistics, exploratory factor analysis results, and test-retest reliability in online data from 13 diverse English-speaking countries (N = 63,720). (3) The 45-item Cross-Cultural Big Two Inventory was assessed psychometrically and validated against external criteria in the Africa Long Life Study samples and (4) in the online data and additionally compared to existing two-factor frameworks. The relation of the cross-cultural big two to other two-factor models and theories, its future development, and the potential and importance of culturally decentered models and inventories are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

H_2-H_2O demixing in Uranus and Neptune: Adiabatic structure models

Demixing properties of major planetary constituents influence the interior structure and evolution of planets. Comparing experimental and computational data on the miscibility of hydrogen and water to adiabatic profiles suggests that phase separation between these two components occurs in the ice giants Uranus and Neptune. We aim to predict the atmospheric water abundance and transition pressure between the water-poor outer envelope and the water-rich deep interior in Uranus and Neptune. We constructed seven H$_ $-H$_ $O phase diagrams from the available experimental and computational data. We computed interior adiabatic structure models and compared these to the phase diagrams to infer whether demixing occurred. We obtain a strong water depletion in the top layer due to the rain-out of water and find upper limits on the atmospheric water-mass fraction Zatm of 0.21 for Uranus and 0.16 for Neptune. The transition from the water-poor to the water-rich layer is sharp and occurs at pressures $P_Z$ between 4 and 11 GPa. Using these constraints on Zatm and $P_Z$, we find that the observed gravitational harmonics $J_2$ and $J_4$ can be reproduced if $P_Z 10$ GPa in Uranus and $ 5$ GPa in Neptune, and if the deep interior has a high primordial water-mass fraction of 0.8, unless rocks are also present. The agreement with $J_4$ is improved if rocks are confined deeper than $P_Z$, for instance, below a rock cloud level at 2000 K (20--30 GPa). These findings confirm classical few-layer models and suggest that a layered structure may result from a combination of primordial mass accretion and subsequent phase separation. Reduced observational uncertainty in $J_4$ and its dynamic contribution, atmospheric water abundance measurements from the Uranus Orbiter and Probe (UOP) or a Neptune mission, and better understanding of the mixing behaviour of constituents are needed to constrain the interiors of ice giants.

Identification and in vivo functional analysis of a novel missense mutation in GATA3 causing hypoparathyroidism, sensorineural deafness and renal dysplasia syndrome in a Chinese family.

Hypoparathyroidism, sensorineural deafness, and renal dysplasia (HDR) syndrome is a rare autosomal dominant genetic disease associated with mutations in the GATA3 gene, which encodes GATA3 that plays essential roles in vertebrate development. This study aimed to identify and report the pathogenic mutation in GATA3 in a Chinese family diagnosed with HDR syndrome and determine its functional impacts in vivo. The clinical features of a 25-year-old male patient with HDR syndrome and his parents were collected. GATA3 gene exome sequencing and Sanger sequencing were performed on the proband and his family, respectively. Functional analyses of GATA3 were performed using bioinformatics tools and zebrafish assays to determine pathogenicity and phenotype spectrum. A novel, heterozygous, missense mutation in exon 4 of the GATA3 gene, c.863 G > A, p.Cys288Tyr, in the proband and his mother who presented the complete HDR triad, was predicted to be deleterious by in silico tools. 3D structure modeling showed that the variant caused significant structural changes. In vivo studies using a zebrafish animal model revealed the deleterious impact of the variant on the gill buds, otoliths, and pronephros. We identified a novel missense mutation, GATA3 p.Cys288Tyr, within a family with HDR syndrome and delineated it as a loss-of-function variant in vivo. This expands the spectrum of GATA3 mutations associated with HDR syndrome in the Chinese population and mimics HDR-related changes in vivo.

Numerical simulation study on discharge characteristics of the Dual hollow cathode plasma source using magnetic mirror field

The Dual hollow cathode plasma source uses hollow cathode cylindrical sputtering and ionizing metal elements, which has a high material utilization rate and has potential application in the field of material modification. Its performance index requires the cooperation of electrode discharge parameters and the rational utilization of the inner surface of the hollow cathode. In this paper, a two-dimensional fluid model of a Dual hollow cathode structure is developed to simulate the basic distribution of the Dual hollow cathode discharge, which fills the central region of the Dual hollow cathode structure and the electrons oscillate on the axis. The effects of electrode parameters and hollow cathode radius on the discharge were investigated. The results show that the radial electron density of the hollow cathode increases with increasing heated cathode voltage, but as the hot cathode voltage continues to expand beyond 1200 V this trend becomes less obvious. The enhancement of the wall ion current by the heated cathode voltage is very pronounced, and the hollow cathode discharge is the result of the mutual enhancement of the heated cathode voltage and the hollow cathode voltage. Hollow cathode sputtering needs to reach a voltage threshold of 300 V, and the existence of an optimal radius (r = 4 mm−6 mm) to achieve a high plasma density and at the same time favor hollow cathode sputtering.