Real Fusion Research Articles

Recording Reflection Volume Holographic Gratings with Enhanced Performance by Two‐Stage Photopolymers Containing Bifunctional Monomers

AbstractA holographic optical waveguide (HOW) is an optimal solution for augmented reality (AR) displays, in which reflection volume holographic gratings are core optical elements. In this study, five high‐refractive‐index (≈1.6) bifunctional acrylate monomers (TPBSAs) are designed and synthesized. A series of two‐stage photopolymers are prepared using TPBSAs as writing monomers. Among them, one containing 9 wt.% TPBSA‐3 shows the best holographic recording performance with a sensitivity as high as 26.59 cm mJ−1. Using it as the recording medium, a reflection VHG can be obtained with high spatial frequency (5634 lines per mm), diffraction efficiency (97.14%), refractive index modulation (0.029), and good transparency within 400−800 nm after photobleaching. Furthermore, a HOW capable of achieving virtual and real image fusion is fabricated.

A Virtual Assembly Technology for Virtual–Real Fusion Interaction of Ship Structure Based on Three-Level Collision Detection

With the rapid advancement of new-generation information technology, the virtual–real fusion interaction has increasingly become a crucial technique for structural analysis to determine the strength envelope of hulls. A high-precision assembly of the experimental devices in a virtual environment is vital. A virtual assembly method for a structural virtual–real fusion test based on the oriented bounding box (OBB) algorithm, the Devillers and Guigue algorithm, and differential triangle facets algorithm are proposed in this paper. The experiment of the connector in a typical offshore floating platform is performed as a case, which indicates that the virtual assembly method proposed in this paper enables the assessment of assembly virtually prior to the actual experiment, and the assembly accuracy can reach 0.01 mm. The digitalization and virtual–real fusion interaction for the mechanical experiment of hulls are advanced to ensure efficiency, safety, and economy.

Seracam: characterisation of a new small field of view hybrid gamma camera for nuclear medicine

BackgroundPortable gamma cameras are being developed for nuclear medicine procedures such as thyroid scintigraphy. This article introduces Seracam® – a new technology that combines small field of view gamma imaging with optical imaging – and reports its performance and suitability for small organ imaging.MethodsThe count rate capability, uniformity, spatial resolution, and sensitivity for 99mTc are reported for four integrated pinhole collimators of nominal sizes of 1 mm, 2 mm, 3 mm and 5 mm. Characterisation methodology is based on NEMA guidelines, with some adjustments necessitated by camera design. Two diagnostic scenarios – thyroid scintigraphy and gastric emptying – are simulated using clinically relevant activities and geometries to investigate application-specific performance. A qualitative assessment of the potential benefits and disadvantages of Seracam is also provided.ResultsSeracam’s performance across the measured characteristics is appropriate for small field of view applications in nuclear medicine. At an imaging distance of 50 mm, corresponding to a field of view of 77.6 mm × 77.6 mm, spatial resolution ranged from 4.6 mm to 26 mm and sensitivity from 3.6 cps/MBq to 52.2 cps/MBq, depending on the collimator chosen. Results from the clinical simulations were particularly promising despite the challenging scenarios investigated. The optimal collimator choice was strongly application dependent, with gastric emptying relying on the higher sensitivity of the 5 mm pinhole whereas thyroid imaging benefitted from the enhanced spatial resolution of the 1 mm pinhole. Signal to noise ratio in images was improved by pixel binning. Seracam has lower measured sensitivity when compared to a traditional large field of view gamma camera, for the simulated applications this is balanced by advantages such as high spatial resolution, portability, ease of use and real time gamma-optical image fusion and display.ConclusionThe results show that Seracam has appropriate performance for small organ 99mTc imaging. The results also show that the performance of small field of view systems must be considered holistically and in clinically appropriate scenarios.

Aided assembly technology of satellite honeycomb sandwich panel insert based on virtual and real fusion

Abstract Aiming at the problems of frequent low-level quality and difficulty in improving assembly efficiency in the assembly process of satellite honeycomb sandwich panel insert, the 3D model of the honeycomb sandwich panel is formed into high-definition model projection image by feature processing and extraction for 3D process information, and the virtual-real fusion insert aided assembly system is constructed, which is composed of core components such as camera, high-definition projector, and measurement software. Through structured light projection technology and projection algorithm based on landmark point transformation, the projection image can be accurately matched with the contour and hole position of the physical, structural panel, which can effectively assist the assembly process of the insert and reduce the low-level quality problems such as wrong use of parts and reverse polarity assembly. Compared with the traditional manual assembly method, the efficiency is improved by more than 200%, and the error rate is reduced by more than 300%.

Project Metaverse: Creating a Well-being Society through Real and Cyber Fusion

Project Metaverse: Creating a Well-being Society through Real and Cyber Fusion

Adversarial attacks on GAN-based image fusion

Image fusion has achieved significant success, owing to the rapid development of digital computing and Generative Adversarial Networks (GANs). GAN-based fusion techniques fuse latent codes through spatial or arithmetic operations to achieve real image fusion, facilitated by encoders. However, security concerns have arisen due to the vulnerability of deep neural networks to adversarial perturbations. This vulnerability extends to the GAN-based image fusion task. In this paper, we introduce two methods for creating adversarial examples in the context of GAN-based image fusion: adding subtle perturbations to input images or applying the adversarial patch to the input images. The subtle perturbation is meticulously crafted to be imperceptible yet capable of misleading a specific output, regardless of the input images. Conversely, the adversarial patch is a universal perturbation that, when applied to input images as a patch, induces meaningless output images. Our comprehensive experiments, conducted on datasets such as FFHQ (3 × 1024 × 1024) and Stanford Cars (3 × 512 × 512), include both quality and quantity evaluations. According to our experimental results, the subtle perturbation results in almost identical output images, while the adversarial patch induces meaningless fused images and can be transferred to other datasets. By demonstrating that image fusion models are highly vulnerable to adversarial attacks, this study highlights serious concerns regarding the security of these models.

Characterisation of the neutron field for streaming analyses in TT operations at JET

Assessing radiation fields in the biological shield penetrations of fusion reactors is a challenging task. At the Joint European Torus (JET) the neutron field at larger distances from the torus has been calculated and measured. JET operated in 2021–22 with a tritium-tritium plasma and neutronics experiments were performed for validating in a real fusion environment the neutronics codes and nuclear data applied in ITER nuclear analyses. In particular, the fluence of neutrons passing through the penetrations of the JET vacuum vessel and the torus hall was measured and compared with calculations in order to assess the capability of state-of-the-art numerical tools to correctly predict the radiation streaming in large and complex geometries. The neutron fluence was monitored at several locations inside the torus hall at larger distances from the tokamak with activation foils and thermo-luminescent detectors. The calculations have been performed in a two-step process using the deterministic code ADVANTG to determine the variance reduction parameters and with MCNP for subsequent calculation of the neutron field with the Monte Carlo method. The paper presents results of calculations and the first comparison to experimentally obtained values.

Robust Classification and 6D Pose Estimation by Sensor Dual Fusion of Image and Point Cloud Data

It is an important aspect to fully leverage complementary sensors of images and point clouds for objects classification and six-dimensional (6D) pose estimation tasks. Prior works extract objects category from a single sensor such as RGB camera or LiDAR, limiting their robustness in the event that a key sensor is severely blocked or fails. In this work, we present a robust objects classification and 6D object pose estimation strategy by dual fusion of image and point cloud data. Instead of solely relying on 3D proposals or mature 2D object detectors, our model deeply integrates 2D and 3D information of heterogeneous data sources by a robustness dual fusion network and an attention-based nonlinear fusion function Attn-fun(.), achieving efficiency as well as high accuracy classification for even missed some data sources. Then, our method is also able to precisely estimate the transformation matrix between two input objects by minimizing the feature difference to achieve 6D object pose estimation, even under strong noise or with outliers. We deploy our proposed method not only to ModelNet40 datasets but also to a real fusion vision rotating platform for tracking objects in outer space based on the estimated pose.

Prospects for a high-field, compact break-even axisymmetric mirror (BEAM) and applications

This paper explores the feasibility of a break-even-class mirror referred to as BEAM (break-even axisymmetric mirror): a neutral-beam-heated simple mirror capable of thermonuclear-grade parameters and $Q\sim 1$ conditions. Compared with earlier mirror experiments in the 1980s, BEAM would have: higher-energy neutral beams, a larger and denser plasma at higher magnetic field, both an edge and a core and capabilities to address both magnetohydrodynamic and kinetic stability of the simple mirror in higher-temperature plasmas. Axisymmetry and high-field magnets make this possible at a modest scale enabling a short development time and lower capital cost. Such a $Q\sim 1$ configuration will be useful as a fusion technology development platform, in which tritium handling, materials and blankets can be tested in a real fusion environment, and as a base for development of higher- $Q$ mirrors.

Fusion Assessment of Oblique Lumbar Interbody Fusion Using Demineralized Bone Matrix: A 2-Year Prospective Study.

Although several studies have reported successful fusion rates after oblique lumbar interbody fusion (OLIF) using allografts or dimerized bone matrix (DBM) instead of autografts, whether OLIF can achieve satisfactory solid fusion without the use of autografts remains unclear. This study investigated the real fusion rates after OLIF using allografts and DBM, which were evaluated using both dynamic radiographs and computed tomography scans. We enrolled 79 consecutive patients who underwent minimally invasive OLIF followed by percutaneous pedicle screw fixation. All patients were treated with OLIF between L2 and L5 and underwent radiographic and clinical follow-ups at 12, 18, and 24 months after surgery. Radiographic assessment of fusion was performed using the modified BrantigaSteffee-Fraser (mBSF) scale, which was categorized as follows: grades I (radiographic pseudoarthrosis), II (indeterminate fusion), and III (solid radiographic fusion). Other radiologic and clinical outcomes were evaluated using the following parameters: vertebral slippage distance, disc height, subsidence, Oswestry Disability Index (ODI), and visual analogue scale (VAS). Clinical outcomes demonstrated significant improvements in the VAS scores for back pain, leg pain, and ODI after surgery. Subsidence was present in 34 cases (35.4%) at 12 months postoperatively, which increased to 47.9% and reached 50.0% at 1.5 years and 2 years after surgery, respectively. The solid fusion rate after OLIF was 32.3% at 1 year, increased to 58.3% at 1.5 years, and reached 72.9% at 2 years. Radiographic pseudoarthrosis was 24.0% at 1 year, which decreased to 6.3% at 1.5 years and 3.1% at 2 years. OLIF is a safe and effective surgical procedure for the treatment of degenerative lumbar diseases. The mBSF scale, which simultaneously evaluates both dynamic angles and bone bridge formation, offers great reliability for the radiological assessment of fusion. Moreover, OLIF using allografts and DBM, which is performed on one or 2 levels at L2-5, can achieve satisfactory fusion rates within 2 years after surgery.

Multimodal Image Synthesis and Editing: A Survey and Taxonomy.

As information exists in various modalities in real world, effective interaction and fusion among multimodal information plays a key role for the creation and perception of multimodal data in computer vision and deep learning research. With superb power in modeling the interaction among multimodal information, multimodal image synthesis and editing has become a hot research topic in recent years. Instead of providing explicit guidance for network training, multimodal guidance offers intuitive and flexible means for image synthesis and editing. On the other hand, this field is also facing several challenges in alignment of multimodal features, synthesis of high-resolution images, faithful evaluation metrics, etc. In this survey, we comprehensively contextualize the advance of the recent multimodal image synthesis and editing and formulate taxonomies according to data modalities and model types. We start with an introduction to different guidance modalities in image synthesis and editing, and then describe multimodal image synthesis and editing approaches extensively according to their model types. After that, we describe benchmark datasets and evaluation metrics as well as corresponding experimental results. Finally, we provide insights about the current research challenges and possible directions for future research. A project associated with this survey is available at https://github.com/fnzhan/MISE.

Frescoes restoration via virtual-real fusion: Method and practice

In the era of artificial intelligence, image-based virtual restoration of cultural relics is one of the methods used in the restoration of cultural relics. As the most informative representative of cultural heritage in the study of historical materials, murals occupy a significant position in archaeology and ancient culture. Currently, most of the existing virtual restoration of murals is limited to the restoration of image information for local damage. The scenes of murals have large spatial scales and complex semantic contents. In order to enhance the semantic relevance of the virtual restoration of murals and the immersion of a visual perception, this paper proposes a kind of mural virtual-real fusion restoration display method based on visual attention mechanism. Based on the case study on the immersive fusion restoration of Dunhuang grotto murals, the feasibility of regional mural image restoration and real space scene fusion restoration is verified. A new paradigm of mural heritage protection in the context of virtual-real fusion is realized.

Virtual lighting environment and real human fusion based on multiview videos

The realistic fusion of human bodies and virtual lighting environments has important application value in digital tourism, virtual conferences, and other fields. To achieve this goal, it is necessary not only to reconstruct the geometry of the human body but also to estimate the reflectance for the human relighting in a virtual environment. Existing methods only focus on either reconstructing the human body geometry or relighting the human body under specific poses and cannot accommodate new poses in fusion-relighting images. In this paper, we propose a novel approach that enables the relighting of new poses from multiview human videos under unknown illumination, whereby a relationship is established between the observation space and canonical space through a pose-mapping process that connects the geometry and reflectance at different temporal and spatial locations. The geometry and reflectance results obtained from the neural fields are input into the physically based renderer along with the optimized environment map. Human relighting in new poses can be generated by inputting skeletal poses, and the entire pipeline can be trained in a self-supervised manner. The proposed technique was verified on multiple datasets. The experimental results show that the proposed method is capable of fulfilling the goal of a virtual lighting environment and real human fusion under new human poses, outperforming recent methods both subjectively and quantitatively.

PEMFCs Model-Based Fault Diagnosis: A Proposal Based on Virtual and Real Sensors Data Fusion.

Proton Exchange Membrane Fuel Cells (PEMFCs) are critical components in renewable hybrid systems, demanding reliable fault diagnosis to ensure optimal performance and prevent costly damages. This study presents a novel model-based fault diagnosis algorithm for commercial hydrogen fuel cells using LabView. Our research focused on power generation and storage using hydrogen fuel cells. The proposed algorithm accurately detects and isolates the most common faults in PEMFCs by combining virtual and real sensor data fusion. The fault diagnosis process began with simulating faults using a validated mathematical model and manipulating selected input signals. A statistical analysis of 12 residues from each fault resulted in a comprehensive fault matrix, capturing the unique fault signatures. The algorithm successfully identified and isolated 14 distinct faults, demonstrating its effectiveness in enhancing reliability and preventing performance deterioration or system shutdown in hydrogen fuel cell-based power generation systems.

Real-Time Information Fusion System Implementation Based on ARM-Based FPGA

In this study, an information fusion system displayed fusion information on a transparent display by considering the relationships among the display, background exhibit, and user’s gaze direction. We used an ARM-based field-programmable gate array (FPGA) to perform virtual–real fusion of this system as well as evaluated the virtual–real fusion execution speed. The ARM-based FPGA used Intel® RealsenseTM D435i depth cameras to capture depth and color images of an observer and exhibit. The image data was received by the ARM side and fed to the FPGA side for real-time object detection. The FPGA accelerated the computation of the convolution neural networks to recognize observers and exhibits. In addition, a module performed by the FPGA was developed for rapid registration between the color and depth images. The module calculated the size and position of the information displayed on a transparent display according to the pixel coordinates and depth values of the human eye and exhibit. A personal computer with GPU RTX2060 performed information fusion in ~47 ms, whereas the ARM-based FPGA accomplished it in 25 ms. Thus, the fusion speed of the ARM-based FPGA was 1.8 times faster than on the computer.

Hydrodynamics and electrical insulation of PbLi flow with SiC flow channel inserts in a strong magnetic field

Experimental and numerical research in a strong magnetic field is described in this article testing silicon carbide (SiC) flow channel inserts (FCI) in lead-lithium (PbLi) liquid metal flow. The study aims to further develop the High-Temperature Dual-Coolant Lead-Lithium nuclear fusion blanket concept by testing new variations of SiC inserts operating in the relevant electromagnetic conditions. These inserts act as electrical insulators in magnetohydrodynamic lead-lithium flow and can also play the role of the thermal insulator in the potentially real fusion environment. The liquid metal pressure and integral flowrate measurements were performed on up to 5T DC magnetic field created by a superconducting magnet at high temperatures up to 700 °C, which is close to the real fusion environment. Comparisons of several cases with and without inserts are provided, demonstrating their impact on hydraulic resistance. Additionally, electrical potential distribution is recorded on the lead-lithium channel walls, which can be used to evaluate the character of liquid metal velocity distribution in the lead-lithium channel.

The Significance of Chinese Art Songs by Huang Tzu (1904 - 1938)

Chinese art song, a type of Chinese New Music, was a musical genre referring to the songs composed particularly in the 1920s. It is undeniable that it was a product of the real contact and fusion of Chinese and Western cultures. Imagine listening to music like Schubert or Puccini, you may suddenly realise that the language is not German or Italian, but an exotic language (Mandarin, also mixed with different Chinese dialects). Chinese art songs indeed had such characteristics. Its appearance was epoch-making. Before the 19th century, the gate of Chinese traditional culture was closed and self-sufficient, but due to the invasion of Western powers, this gate soon collapsed. Western culture also swept China along with the military trend in the early 20th century, causing earth-shaking changes in China, in which Western music was also introduced into China. Some intellectuals enlightened by modern thoughts and knowledge believed that in addition to learning western military and technology, they should also absorb their philosophy and culture, so that China could rise in all directions and catch up with Western powers. The theme of this research revolves around one of the intellectuals (composers) of this period, Huang Tzu (1904-1938) who challenged and responded to the culture shock through composing Chinese New Music. After studying in the United States in 1926, he returned to Shanghai, China. Like the intellectuals at that time, in addition to being proficient in various fields like science, he also dabbled in music. Many of Huang Tzu’s music revolved around the concept of "nationality". It refers to an approach: borrowing Western compositional techniques to highlight the values of traditional Chinese aesthetics. This research did not aim at describing the characteristics of music or literature in Chinese art songs itself. Yet, it finally allowed me to discover more about how intellectuals dealt with issues of cultural exchange between the East and the West a hundred years ago. What would be the effects if Western music elements, such as harmony, form, techniques and musical instruments were added to the Chinese traditional music language and habits? From a cultural perspective, what significance did this incur?

Smart Task Assistance in Mixed Reality for Astronauts.

Mixed reality (MR) registers virtual information and real objects and is an effective way to supplement astronaut training. Spatial anchors are generally used to perform virtual-real fusion in static scenes but cannot handle movable objects. To address this issue, we propose a smart task assistance method based on object detection and point cloud alignment. Specifically, both fixed and movable objects are detected automatically. In parallel, poses are estimated with no dependence on preset spatial position information. Firstly, YOLOv5s is used to detect the object and segment the point cloud of the corresponding structure, called the partial point cloud. Then, an iterative closest point (ICP) algorithm between the partial point cloud and the template point cloud is used to calculate the object's pose and execute the virtual-real fusion. The results demonstrate that the proposed method achieves automatic pose estimation for both fixed and movable objects without background information and preset spatial anchors. Most volunteers reported that our approach was practical, and it thus expands the application of astronaut training.

Abstract 1401: Landscape of known and novel myeloid neoplasia fusions identified by a multimodal comprehensive genomic profiling test in 789 patients

Abstract Background: WHO recognizes 23 genomic rearrangements or fusions which define subclasses of AML, MDS/MPN and related neoplasms, and their detection is essential for patient management. Discerning true fusions from artificial calls in RNAseq-based tests is challenging due to biological and technical noise. We previously developed a method to identify fusion transcripts by a single-tube NGS assay capable of concurrent analysis of DNA and RNA alterations in ALL patients. We expanded the assay with an improved fusion calling algorithm and used it to study the landscape of myeloid RNA fusions in the clinical setting. Methods: Total nucleic acid (TNA) from bone marrow or peripheral blood was analyzed in our clinical laboratory by a CLIA grade custom amplicon-based multimodal NGS assay, targeting 302 genes by DNA-seq and 185 genes by RNA-seq. Libraries were sequenced on a NovaSeq6000 instrument, and fusions were called from RNA: de-duplicated and error-corrected UMI reads were processed by an in-house developed BI pipeline leveraging machine learning, to assign a final confidence score (F1). Deidentified patient data was used according to an approved IRB. Results: Distribution of F1 scores was used to improve the discrimination between technical noise and real fusion calls. Analytical validation of RNA fusion calling against FISH and Sanger-seq in 74 hematologic disorder samples demonstrated 98.2% specificity and 97.0% sensitivity. Data from 789 patients was used to study the distribution of myeloid fusion events in community cases. 17% of patients had fusions involving genes from WHO/NCCN recommendations. Frequencies for most common fusions were 2.3% (18/789) for KMT2A, 2% for PML::RARA, 1.9% for BCR::ABL1, 0.8% for RUNX1::RUNX1T1 and CBFB::MYH11 and 0.6% for NUP98. Fusions of PDGFRA, ETV6, ZNF384, FGFR1 and other genes were also observed and BCR::ABL1 fusions were seen not only in CML patients but also in a patient with AML. For KMT2A, 25% (2/8) fusions detected by NGS were confirmed by Sanger-seq but missed by FISH, which correlates with higher sensitivity of the NGS assay. Novel fusions were called in ~8% of patients. This included an AML patient with a CCND2::MGP fusion, resulting in cyclin D2 (CCND2), frequently activated by DNA mutations in AML, fused to matrix Gla protein, a highly expressed gene in hematopoietic progenitor cells. The fusion was confirmed by Sanger-seq, and shown to lack ex5 of CCND2, which contains Thr280, a residue required for ccnd2 degradation. This fusion is thus predicted to generate high cellular levels of oncogenic ccnd2-mgp. Conclusions: Frequencies of well-known fusions in real world data obtained by a robust low-noise RNA fusion assay were similar to other studies done in academic setting. Reliable detection of bona-fide RNA fusions with this clinical test is invaluable for patient care and novel fusion identification. Citation Format: Michal Krawczyk, Chaugiang Duong, Lina Zelinger, Fei Ye, Hyunjun Nam, Brad Thomas, Vincent Funari, Shashikant Kulkarni, Fernando Lopez-Diaz. Landscape of known and novel myeloid neoplasia fusions identified by a multimodal comprehensive genomic profiling test in 789 patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1401.

TS-CGANet: A Two-Stage Complex and Real Dual-Path Sub-Band Fusion Network for Full-Band Speech Enhancement

Speech enhancement based on deep neural networks faces difficulties, as modeling more frequency bands can lead to a decrease in the resolution of low-frequency bands and increase the computational complexity. Previously, we proposed a convolution-augmented gated attention unit (CGAU), which captured local and global correlation in speech signals through the fusion of the convolution and gated attention unit. In this paper, we further improved the CGAU, and proposed a two-stage complex and real dual-path sub-band fusion network for full-band speech enhancement called TS-CGANet. Specifically, we proposed a dual-path CGA network to enhance low-band (0–8 kHz) speech signals. In the medium band (8–16 kHz) and high band (16–24 kHz), noise suppression is only performed in the magnitude domain. The Voice Bank+DEMAND dataset was used to conduct experiments on the proposed TS-CGANet, which consistently outperformed state-of-the-art full-band baselines, as evidenced by the results.