Fusion Process Research Articles

Unraveling dual fusion mechanisms in BmNPV GP64: critical roles of CARC motifs and signal peptide retention.

Viral membrane fusion is a critical process enabling viruses to invade host cells, driven by viral membrane fusion proteins (MFPs). Cholesterol plays a pivotal role in this process, which is essential for the infectivity of many enveloped viruses. The interaction between MFPs and cholesterol is often facilitated by specific amino acid motifs known as cholesterol recognition/interaction amino acid consensus (CRAC) motifs and reverse CARC motifs. In a previous study, we demonstrated that CRAC1 and CRAC2 in GP64 are required for Bombyx mori nucleopolyhedrovirus (BmNPV) infection. This study further investigates the role of CARC in the GP64 protein of BmNPV, revealing their complex interaction with cholesterol and the influence of signal peptide (SP) retention on viral infectivity. We identified six putative CARC motifs in GP64 and generated mutants to assess their function. Our findings show that CARC1, CARC2, CARC3, and CARC4 are indispensable for viral fusion and infection when the SP is retained, whereas only CARC2 and CARC3 remain essential after SP cleavage. In contrast, CARC1 and CARC4 are necessary for viral infection through a cholesterol-independent mechanism resulting from double mutations in the CRAC1 and CRAC2 motifs of GP64. These insights not only deepen our understanding of BmNPV GP64-mediated fusion but also highlight potential antiviral targets, underscoring the adaptability and resilience of viral fusion mechanisms.IMPORTANCEUnderstanding viral membrane fusion mechanisms is crucial for developing antiviral strategies. This study provides novel insights into the intricate roles of CARC and CRAC motifs in the GP64 protein of BmNPV, particularly their interaction with cholesterol and the influence of signal peptide retention. The discovery that certain CARC motifs are essential for cholesterol-dependent fusion, whereas others function in a cholesterol-independent context advances our understanding of viral fusion processes. These findings emphasize the potential of targeting CARC motifs for therapeutic interventions and underline the importance of cholesterol interactions in viral infections. This research not only deepens our understanding of BmNPV fusion mechanisms but also has broader implications for other enveloped viruses.

An Image Fusion Algorithm for Sustainable Development Goals Satellite-1 Night-Time Light Images Based on Optimized Image Stretching and Dual-Domain Fusion

The Glimmer Imager of Urbanization (GIU) on SDGSAT-1 provides high-resolution and global-coverage images of night-time lights (NLs) with 10 m panchromatic (PAN) and 40 m multispectral (MS) imagery. High-resolution 10 m MS NL images after ideal fusion can be used to better study subtle manifestations of human activities. Most existing remote sensing image-fusion methods are based on the fusion of daytime optical remote sensing images, which do not apply to lossless compressed images of the GIU. To address this limitation, we propose a novel approach for 10 m NL data fusion, namely, a GIU NL image fusion model based on PAN-optimized OIS (OIS) and DDF (DDF) fusion for SDGSAT-1 high-resolution products. The OIS of PAN refers to the optimized stretching method that integrates linear and gamma stretching while DDF indicates a fusion process that separately merges the dark and light regions of NL images using different fusion methods, then stitches them together. In this study, fusion experiments were conducted in four study areas—Beijing, Shanghai, Moscow, and New York—and the proposed method was compared to traditional methods using visual evaluation and five quantitative evaluation metrics. The results demonstrate that the proposed method achieves superior visual quality and outperforms conventional methods across all quantitative metrics. Additionally, the ablation study confirmed the necessity of the methodological steps employed in this study.

Recent advances in solid‐state nuclear magnetic resonance studies on membrane fusion proteins

Membrane fusion is an essential biological process that merges two separate lipid bilayers into a whole one. Membrane fusion proteins facilitate this process by bringing lipid bilayers in close proximity to reduce the repulsive energy between membranes. Along with their interactions with membranes, the structures and dynamics of membrane fusion proteins are key to elucidating the mechanisms of membrane fusion. Solid‐state NMR (SSNMR) spectroscopy has unique advantages in determining the structures and dynamics of membrane fusion proteins in their membrane‐bound states. It has been extensively applied to reveal conformational changes in intermediate states of viral membrane fusion proteins and to characterize the critical lipid–membrane interactions that drive the fusion process. In this review, we summarize recent advancements in SSNMR techniques for studying membrane fusion proteins and their applications in elucidating the mechanisms of membrane fusion.

GRP78 mediates mitochondrial fusion and fission in cigarette smoke-induced inflammatory responses in airway epithelial cells

Objective Chronic obstructive pulmonary disease (COPD) is characterized by persistent airway inflammation, with cigarette smoke being a major contributor to epithelial injury. Recent studies have shown that abnormal mitochondrial function is closely linked to the onset and progression of airway inflammation. This study aims to explore the role and underlying molecular mechanisms of mitochondrial dynamics in cigarette smoke-induced airway inflammation. Materials and Methods Human bronchial epithelial (HBE) cells were exposed to cigarette smoke extract (CSE) to assess the expression of mitochondrial fusion markers MFN2 and OPA1, the fission marker DRP1, and the glucose-regulated protein GRP78. The siRNA and pharmaceutics targeting DRP1, MFN2, and GRP78 were employed. Both cells and supernatants were analyzed for inflammatory factor levels and the related signaling pathways. Results In this study, HBE cells exposed to CSE showed a significant decrease in the proteins MFN2 and OPA1 and an increase in DRP1. The inhibition of DRP1 expression mitigated inflammation while silencing MFN2 exacerbated it. This was similarly corroborated by the use of the DRP1 inhibitor mdivi-1 and the MFN2 activator leflunomide. Additionally, we proved that GRP78 played an important regulatory role as an essential endoplasmic reticulum protein, regulating the mitochondrial fusion/fission process and subsequently activating the NF-κB pathway to regulate airway inflammation. Discussion and Conclusion Taken together, these results suggested that the GRP78-mediated mitochondrial fusion and fission process played a vital role in cigarette smoke-induced airway inflammation and might be a potential therapeutic target in this regard.

Key Takeaways From the ISASS Webinar Series on Current and Emerging Techniques in Endoscopic Spine Surgery | Part 2: Polytomous Rasch Analysis of Learning Curve and Surgeon Endorsement of Biportal, Interlaminar, and Transforaminal Endoscopic Stenosis Decompression, Discectomy, and Laminectomy in Combination With Interspinous Process Spacers.

The International Society for the Advancement of Spine Surgery hosted the second of a series of 4 webinars on endoscopic spine surgery techniques. The second webinar focused on the application of unilateral biportal endoscopy for discectomy and laminectomy in combination with interbody fusion and interspinous process spacers. This series was intended to identify current trends with contemporary modern endoscopic spine surgery techniques. To analyze the level of surgeon endorsement for the presented endoscopic spine surgery techniques before and after the webinar utilizing polytomous Rasch analysis, as well as to evaluate the potential for these insights to inform clinical guideline recommendations. A survey was available to 667 potential respondents during the Zoom webinar, collecting data on surgeon endorsements using a Likert scale. The polytomous Rasch model was employed to analyze responses while considering the complexity of decisions against surgeon expertise, developing a logarithmic measurement scale, allowing objective statistical analysis of categorical variables, highlighting incongruent or out of order items vs congruent and in order items, and driving improvement in clinical guidelines. Of the 667 surgeons who participated in the webinar, 224 accessed, 122 started, and 61 completed the prewebinar survey, achieving a 50.0% completion rate. Respondents comprised primarily orthopedic surgeons (70.5%) and neurosurgeons (24.6%), with fellows and medical students each making up 1.6%. These surgeons estimated that mastering the learning curve of endoscopic spine surgery required an average of 18.08 cases corroborated by postwebinar responses averaging 15.78 cases. Descriptive statistics revealed an acknowledgment of a learning curve in mastering endoscopic spine surgery, with a slight increase in recognition postwebinar (81.8% up from 80.3%). The data underscored the importance of cadaver courses and high-volume surgical practice before the webinar and highlighted the value of mentorship afterward, indicating a preference shift toward more interactive learning. The confidence in various endoscopic techniques saw notable changes, particularly for procedures involving interlaminar lateral canal decompression and the combined use of transforaminal endoscopic decompression with interspinous process spacers, which saw an increase in high-level endorsements postwebinar. Polytomous Rasch analysis provided insights into training methods and procedural techniques, with mentorship and cadaver courses emerging as key elements for mastering the learning curve. The analysis also highlighted a general consensus on the effectiveness of percutaneous endoscopic interlaminar decompression for lateral canal stenosis, reflecting evolving surgeon preferences and consensus on best practices. Infit and outfit statistics from the Rasch analysis suggested a good fit between the survey responses and the Rasch model both before and after the webinar, indicating minimal data distortion due to bias. Differential item functioning analysis showed no significant bias in item responses between orthopedic surgeons and neurosurgeons in the prewebinar survey, but it identified potential bias for one item postwebinar-unilateral biportal endoscopic laminectomy for central stenosis. This webinar highlighted the importance of hands-on training methods such as cadaver courses and mentorship in mastering the complex spinal endoscopy procedures. The application of polytomous Rasch analysis provided a detailed understanding of surgeons' current preferences and perceptions, as well as the evolving consensus on best practices in endoscopic spine surgery, displaying wide acceptance of the percutaneous interlaminar endoscopic decompression for lateral canal stenosis decompression and a growing interest in integrating endoscopic techniques for more comprehensive spinal care, including wide decompression and spinal stabilization. Assessing surgeon confidence and acceptance of endoscopic spinal surgeries using polytomous Rasch analysis. Level 2 (inferential) and 3 (observational) evidence because Rasch analysis provides statistical validation of instruments rather than direct clinical outcomes.

Tribological effects of varying volumetric energy density in additive manufacturing of inconel 718

Abstract This study investigates the novel effects of varying volumetric energy density (VED) ratios on the tribological characteristics of Inconel 718 alloy fabricated using Laser Powder Bed Fusion (LPBF) process. Nine VED ratios were investigated, and samples underwent non-contact surface roughness tests, Vickers microhardness tests, and residual stress analysis. Notably, this study identified specific VED conditions where superior wear resistance was achieved, contributing new insights into optimizing LPBF parameters for tribological performance. Based on preliminary analysis, samples 1, 3, and 8 were selected for ball-on-disc wear testing. Sample 8, fabricated with 330 W laser power, 50 mm s−1 scan speed, 0.10 mm hatch spacing, and 0.05 mm layer thickness, demonstrated superior tribological behaviour with a 32.12% and 52.11% lower friction coefficient and 31% and 29.92% less mass loss compared to samples 1 and 3, respectively. The presence of γ-Ni, γ′-Ni3 (Al, Ti), γ-FCC, and γ′-L12 phases, along with microstructural features such as columnar and cellular dendritic structures, were confirmed via SEM and x-ray diffraction analyses. This study’s novel findings contribute valuable knowledge for optimizing Inconel 718 production via LPBF, particularly in enhancing wear resistance through tailored VED settings.

Surface analysis in additive manufacturing: A systematic literature review regarding powder bed fusion processes

Abstract The analysis of surface effects in powder bed fusion additive manufacturing is the subject of intensive research activities. The aim of this paper is to provide an overview of the current state of knowledge and to gain a comprehensive understanding of this subject area. The paper is intended to enable researchers to select specific articles for their own further research context. In addition, a bibliometric analysis validates the data base. A discussion of the findings suggests that the criticality of the surface should be considered as a quality factor in the field of additive manufacturing by powder bed fusion processes. An accurate and reliable measurement is crucial for predicting component quality. There is a clear trend from two-dimensional measurements to three-dimensional measurements. Conducting comprehensive research is essential to improve the reliability and comparability of measurement results and to promote broad acceptance and application of this technology in the industry.

Optimized Build Orientation and Laser Scanning Strategies for Reducing Thermal Residual Stress in Topology-Optimized Automotive Components

This study investigates the reduction in thermal residual stress during the powder bed fusion (PBF) process in a non-standardized shape generated by topology optimization method in lightweight automotive part of brake caliper. While the caliper of the braking system for reducing the CO2 consumption in vehicle systems undergoes a redesign to increased strength and reduced weight, challenges arise due to biased melting area ratios in the topologically optimized design, causing the thermal deformation. To address this, our research proposes an efficient PBF scan strategy aimed at minimizing anisotropy and residual stress—a critical consideration for successful manufacturing. The effectiveness of the laser scan strategy is validated through testing on a brake dynamometer, following the JASO C406 test procedure, an authorized standard for commercial brake calipers. Furthermore, a comparative analysis between the conventional product and the proposed brake caliper highlights superior performance, particularly under lightweight conditions. This comprehensive approach contributes valuable insights to the field, offering a potential solution for overcoming manufacturing challenges associated with topologically optimized designs in automotive components.

Intraocular Lens Rotational Stability after Cataract Surgery with and without Primary Posterior Continuous Curvilinear Capsulorrhexis.

To evaluate intraocular lens (IOL) rotational stability and capsular fusion process after cataract surgery with and without primary posterior continuous curvilinear capsulorrhexis (PPCCC). Fujian Provincial Hospital, Fujian, China. Prospective, intraindividual, randomized clinical trial. This study included 56 adult patients (112 eyes) with bilateral cataract undergoing phacoemulsification cataract surgery with PPCCC in one eye (PPCCC group) and conventional cataract surgery in the contralateral eye (NPCCC group). IOL axis orientation and fusion footprint length were measured at 1 day, 1 week, 1 month, 3 months, and 1 year after surgery using OPD-Scan III, while capsular bend index (CBI) was assessed at the same time points using Pentacam AXL. No between-group difference was found in the absolute rotation from 1 day to 1 year (2.93 ± 1.72 vs 2.66 ± 1.61 degrees, P=0.54). The absolute rotation from 1 week to 1 month in NPCCC group was higher than that in PPCCC group (1.65 ± 0.68 vs 1.27 ± 0.32 degrees, P=0.01). At 1 month after surgery, both fusion footprint length (9.11 ± 2.74 vs. 10.67 ± 2.06 mm, P = 0.02) and CBI (2.92 ± 0.60 vs. 3.25 ± 0.59, P = 0.03) were lower in NPCCC group. Cataract surgery involving PPCCC demonstrates comparable outcomes to conventional procedures regarding long-term IOL rotational stability, therefore is a promising option for adult cataract patients scheduled for toric IOL implantation. PPCCC slightly reduces IOL rotation in the early postoperative period, which can be attributed to accelerated capsular fusion.

Enhanced detection of surface deformations in LPBF using deep convolutional neural networks and transfer learning from a porosity model

Our previous research papers have shown the potential of deep-learning models for real-time detection and control of porosity defects in 3D printing, specifically in the laser powder bed fusion (LPBF) process. Extending these models to identify other defects like surface deformation poses a challenge due to the scarcity of available data. This study introduces the use of Transfer Learning (TL) to train models on limited data for high accuracy in detecting surface deformations, marking the first attempt to apply a model trained on one defect type to another. Our approach demonstrates the power of transfer learning in adapting a model known for porosity detection in LPBF to identify surface deformations with high accuracy (94%), matching the performance of the best existing models but with significantly less complexity. This results in faster training and evaluation, ideal for real-time systems with limited computing capabilities. We further employed Gradient-weighted Class Activation Mapping (Grad-CAM) to visualize the model’s decision-making, highlighting the areas influencing defect detection. This step is vital for developing a trustworthy model, showcasing the effectiveness of our approach in broadening the model’s applicability while ensuring reliability and efficiency.

Vahagn: VisuAl Haptic Attention Gate Net for slip detection.

Slip detection is crucial for achieving stable grasping and subsequent operational tasks. A grasp action is a continuous process that requires information from multiple sources. The success of a specific grasping maneuver is contingent upon the confluence of two factors: the spatial accuracy of the contact and the stability of the continuous process. In this paper, for the task of perceiving grasping results using visual-haptic information, we propose a new method for slip detection, which synergizes visual and haptic information from spatial-temporal dual dimensions. Specifically, the method takes as input a sequence of visual images from a first-person perspective and a sequence of haptic images from a gripper. Then, it extracts time-dependent features of the whole process and spatial features matching the importance of different parts with different attention mechanisms. Inspired by neurological studies, during the information fusion process, we adjusted temporal and spatial information from vision and haptic through a combination of two-step fusion and gate units. To validate the effectiveness of method, we compared it with traditional CNN net and models with attention. It is anticipated that our method achieves a classification accuracy of 93.59%, which is higher than that of previous works. Attention visualization is further presented to support the validity.

The characterization of an IncN-IncR fusion plasmid co-harboring blaTEM−40, blaKPC−2, and blaIMP−4 derived from ST1393 Klebsiella pneumoniae

Plasmids, as important genetic elements apart from chromosomes, often carry multiple resistance genes and various mobile genetic elements, enabling them to acquire more exogenous genes and confer additional resistance phenotypes to bacteria. Various carbapenem resistance genes are often located on IncN plasmids, and several reports have linked fusion plasmids to IncN plasmids. Therefore, this study aims to explore the emergence, molecular structure characteristics, and resistance features mediated by IncN fusion plasmids carrying multiple carbapenem resistance genes. In this study, species identification was performed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS). Polymerase chain reaction (PCR) was employed to detect the presence of carbapenem resistance genes in the strains. PCR-based replicon typing (PBRT) was used to identify IncN plasmids. Plasmids were analyzed through S1-nuclease pulsed-field gel electrophoresis (S1-PFGE), Southern blotting, conjugation experiments, and stability tests. Whole-genome sequencing (WGS) and antimicrobial susceptibility testing (AST) were conducted to characterize the target strains. Four strains containing IncN plasmids were identified: two Klebsiella pneumoniae, one Escherichia coli, and one Enterobacter cloacae, all harboring carbapenem resistance genes. Among them, two IncN plasmids (pFAHZZU7605-KPC-IMP and pFAHZZU7865-IMP) contained blaIMP−4 and exhibited similar molecular structure characteristics. Notably, the pFAHZZU7605-KPC-IMP plasmid harbored both IncN and IncR replicons. We hypothesize that the pFAHZZU7605-KPC-IMP fusion plasmid resulted from the recombination of a pFAHZZU7865-IMP-like plasmid and an IncR-like plasmid. Further analysis of the plasmid’s genetic elements revealed that insertion sequences ISKpn19 and ISKpn27 played crucial roles in the plasmid recombination and fusion process. In clinical settings, plasmids carrying different resistance genes can undergo fusion, mediated by genetic elements, thereby expanding the resistance spectrum of host bacteria. Hence, it is essential to enhance the monitoring and research of transposable elements to control the spread of multidrug-resistant bacteria.

Cloud Platform Business Scenario Modeling Based on Multi-Model Fusion Recommendation Algorithm

In the era of cloud computing, businesses are increasingly relying on cloud platforms to streamline their operations and deliver services efficiently. Recommendation systems play a pivotal role in suggesting suitable services and resources to enhance user experience and optimize resource allocation. This paper presents a novel approach, the Multi-Model Fusion Recommendation Algorithm (MMFRA), which integrates multiple recommendation models using advanced fusion techniques to enhance the accuracy of recommendations in cloud platform business scenarios. The implementation process of MMFRA involves combining diverse recommendation models, such as collaborative filtering, content-based filtering, and matrix factorization, into a unified framework that leverages their strengths while mitigating individual limitations. This fusion process is designed to achieve higher precision in service recommendations by considering various aspects of user behavior and preferences. Through a comprehensive evaluation in a simulated cloud platform environment, MMFRA demonstrates superior performance in terms of recommendation accuracy and user satisfaction. The proposed algorithm offers significant potential for enhancing the effectiveness of cloud platform services, ultimately benefiting both service providers and users.

Electrostatic Assembly of Gold Nanoclusters in Reverse Emulsion Enabling Nanoassemblies with Tunable Structure and Size for Enhanced NIR-II Fluorescence Imaging.

The precise control of the assembly structure and size of gold nanoclusters (AuNCs) can potentially amplify their near-infrared II (NIR-II) fluorescence imaging and targeting properties. However, the conventional electrostatic assembly of AuNCs and charged molecules faces challenges in balancing the inherent electrostatic repulsions among charged units and regulating the diffusion of assembly units. These difficulties limit precise control over assembly size and structure, along with limited options for coassembled molecules, thereby restricting imaging properties and targeting capability. To circumvent this challenge, we developed a reverse emulsion-confined electrostatic assembly method. This technique efficiently constructs AuNC nanoassemblies with diverse coassembled molecules, allowing for the fine-tuning of assembly size and structure, including both core-satellite and homogeneous AuNC nanoassemblies. The development of two distinct nanoassemblies can be partially attributed to the varying diffusive rates of AuNCs or the AuNCs/polymer complex within the fused emulsion droplets. This variance arises from steric hindrances encountered during the emulsion fusion process. Interestingly, core-satellite nanoassemblies exhibit the strongest NIR-II fluorescence enhancement. Finally, the introduction of a hyaluronic acid coating on the surfaces of nanoassemblies with varying sizes enables the nanoprobes to achieve enhanced lymph node imaging through size modulation and macrophage targeting, which are used for surgical navigation to remove lymph node metastases. We envision that this self-assembly strategy can be extended to a wide range of electrostatic assembly systems for the development of multicomponent functional materials.

A microfluidic approach for controllable synthesis of TiO2 submicrospheres

TiO2 submicrospheres are used in dye-sensitized solar cells and Li-ion batteries to enhance energy conversion efficiency and volumetric performance. In this study, a microfluidic chip was designed for the realization of the continuous controllable synthesis of TiO2 submicrospheres. The chip utilizes two T-channels to discrete dispersed phases into droplets, and a Y-channel to fuse the two dispersed phase droplets. The droplets generation process, the influencing factors of droplet length and the fusion process of droplets were investigated. The effects of the flow rate ratio of titanium oxysulfate and ammonia solutions, microchannel geometrical profiles including the Y-channel entrance angle on the size of the synthesized TiO2 were studied. The length of the generated droplets was found to decrease with increasing continuous-phase flow rate, and increase with increasing dispersed-phase flow rate and microchannel cross-section area. When the flow rate ratio of titanium oxysulfate solution and ammonia solution was 1:1, the average diameter of TiO2 spheres synthesized was the smallest, around 300 nm. Increasing the microchannel cross-section and Y-channel entrance angle were beneficial in obtaining larger TiO2 submicrospheres. This proposed microfluidic strategy has the potential for applications required continuous synthesis of TiO2 submicrospheres with controllable sizes.

Object Tracking Algorithm Based on Integrated Multi-Scale Templates Guided by Judgment Mechanism

The object tracking algorithm TransT, based on Transformer, achieves significant improvements in accuracy and success rate by fusing the extracted features of convolutional neural networks with the structure of Transformer. However, when dealing with the deformation of the object’s appearance, the algorithm exhibits issues such as insufficient tracking accuracy and drift, which directly affect the stability of the algorithm. In order to overcome this problem, this paper demonstrates how to expand scene information at the scale level during the fusion process and, on this basis, achieve accurate recognition and positioning. The predicted results are promptly fed back to the subsequent tracking process, from which temporal templates are embedded. Starting from both location and time can effectively improve the adaptive ability of the tracking model. In the final experimental comparison results, the algorithm proposed in this paper can adapt well to the situation of object deformation, and the overall performance of the tracking model has also been improved.

Visualizing the “Hidden” Triplet–Triplet Fusion Process to Fluorescence in Typical Organic/Polymer Light‐Emitting Diodes

AbstractFluorescence emission of a typical poly(9,9‐dialkylfluorene) derivative (PF Green B)‐based polymer light‐emitting diodes (PLEDs) clearly demonstrates that it partially involves the contribution of triplet excitons by the triplet–triplet fusion (TTF) process through measuring the magneto‐electroluminescence (MEL) responses of devices at different bias conditions and temperatures. The TTF process to fluorescence intrinsically correlates with the concentration, lifetime, and polaron quenching of triplet excitons, as modulated by different bias regimes and conditions. Varying the cathode configurations of PLEDs by an additional exciton blocking layer and cathode buffer layers in PLEDs, such as a thin layer of bathocuproine, tetractylammonium bromide, or poly(ethylene glycol) dimethyl ether with metal cathodes, changes the carrier dynamics and regulates the magnitude of TTF process to fluorescence. The performance of the devices has increased due to the enhanced TTF process in fluorescence, as characterized by the measurement of MEL responses. The results in this work unveil the “hidden” component of fluorescence emission, which originates from the fusion of triplet excitons to singlet excitons in typical PLEDs. The results elucidate that TTF of triplet excitons to fluorescence emission can be a practicable mechanism that contributes to enhancing the performance of devices.

Representation-Enhanced Status Replay Network for Multisource Remote-Sensing Image Classification.

Deep-learning-based methods are widely used in multisource remote-sensing image classification, and the improvement in their performance confirms the effectiveness of deep learning for classification tasks. However, the inherent underlying problems of deep-learning models still hinder the further improvement of classification accuracy. For example, after multiple rounds of optimization learning, representation bias and classifier bias are accumulated, which prevents the further optimization of network performance. In addition, the imbalance of fusion information among multisource images also leads to insufficient information interaction throughout the fusion process, thus making it difficult to fully utilize the complementary information of multisource data. To address these issues, a Representation-enhanced Status Replay Network (RSRNet) is proposed. First, a dual augmentation including modal augmentation and semantic augmentation is proposed to enhance the transferability and discreteness of feature representation, to reduce the impact of representation bias in the feature extractor. Then, to alleviate the classifier bias and maintain the stability of the decision boundary, a status replay strategy (SRS) is built to regulate the learning and optimization of the classifier. Finally, aiming to improve the interactivity of modal fusion, a novel cross-modal interactive fusion (CMIF) method is employed to jointly optimize the parameters of different branches by combining multisource information. Quantitative and qualitative results on three datasets demonstrate the superiority of RSRNet in multisource remote-sensing image classification, and its outperformance compared with other state-of-the-art methods.

Effects of mass diffusion on Rayleigh–Taylor instability under a large gravity

Rayleigh–Taylor instabilities (RTI) play an important role in the evolution of inertial confinement fusion (ICF) processes, while analytical prediction of the RTI growth rate often fails to reach an agreement with the experimental and simulation results. Accurate analytical prediction of RTI growth is of great significance to the success of ICF schemes. In this paper, we study the effects of mass diffusion and exponential density distribution on RTI under a large gravity by solving the Rayleigh equation with a linear approximation to the density distribution of the mixing layer. The width of the mixing layer is assigned by evaluating the length scale of concentration diffusion and gravitational sedimentation. The latter term is missing in the former isobaric diffusion treatment and is supposed to change the structure of the mixing layer under the gravity. While both effects tend to dampen the instability growth, mass diffusion dominates the damping of perturbations of larger wavenumber and exponential density distribution dominates those of smaller wavenumber, resulting in a non-monotonicity of the density suppression factor of the instability growth rate over perturbation wavenumbers.

Advancing laser powder bed fusion with non-spherical powder: Powder-process-structure-property relationships through experimental and analytical studies of fatigue performance

This study investigates the multifaceted interdependencies among powder characteristics (i.e., non-spherical morphology and particle size ranging 50-120 or 75-175µm), laser powder bed fusion (L-PBF) process condition (i.e., contouring), post-process treatments (i.e., hot isostatic pressing (HIP) and mechanical grinding) on the pore, microstructure, surface finish, and fatigue behavior of additively manufactured Ti-6Al-4V samples. Microstructure analysis shows a phase transformation α′ → α+β microstructure after HIP treatment (at 899±14 °C for 2h under the applied pressure of 1034±34bar) of the as-built Ti-6Al-4V parts. The findings from pore analysis using micro-computed tomography (μ-CT) show an increase in sub-surface pores when relatively smaller powders are L-PBF processed including contouring. Surface optical profilometry reveals a decrease in surface roughness when fine powder is L-PBF including contouring. Pore analysis conducted through μ-CT reveals that the presence of lack-of-fusion pores within the L-PBF processed coarse powder is more pronounced when compared to the fine powder. Furthermore, HIP treatment does not eliminate these pores. The fracture failure in as-printed parts occurs at the surface, while the combination of HIP and mechanical grinding alters crack initiation to subsurface pore defects. Fractography reveals that HIP and as-built samples followed the facet formation and pseudo-brittle fracture mechanisms, respectively. Fatigue life assessments, supported by statistical analysis, indicate that mechanical grinding and HIP significantly enhanced fatigue resistance, approaching the benchmarks set by wrought Ti-6Al-4V alloy. A fatigue prediction model which considers the surface roughness as a micro-notch has been used.