Metabolic regulation by biomaterials in osteoblast

The repair of bone defects resulting from high-energy trauma, infection, or pathological fracture remains a challenge in the field of medicine. The development of biomaterials involved in the metabolic regulation provides a promising solution to this problem and has emerged as a prominent research area in regenerative engineering. While recent research on cell metabolism has advanced our knowledge of metabolic regulation in bone regeneration, the extent to which materials affect intracellular metabolic remains unclear. This review provides a detailed discussion of the mechanisms of bone regeneration, an overview of metabolic regulation in bone regeneration in osteoblasts and biomaterials involved in the metabolic regulation for bone regeneration. Furthermore, it introduces how materials, such as promoting favorable physicochemical characteristics (e.g., bioactivity, appropriate porosity, and superior mechanical properties), incorporating external stimuli (e.g., photothermal, electrical, and magnetic stimulation), and delivering metabolic regulators (e.g., metal ions, bioactive molecules like drugs and peptides, and regulatory metabolites such as alpha ketoglutarate), can affect cell metabolism and lead to changes of cell state. Considering the growing interests in cell metabolic regulation, advanced materials have the potential to help a larger population in overcoming bone defects

Eliminating Gradient Conflict in Reference-based Line-Art Colorization

Reference-based line-art colorization is a challenging task in computer vision. The color, texture, and shading are rendered based on an abstract sketch, which heavily relies on the precise long-range dependency modeling between the sketch and reference. Popular techniques to bridge the cross-modal information and model the long-range dependency employ the attention mechanism. However, in the context of reference-based line-art colorization, several techniques would intensify the existing training difficulty of attention, for instance, self-supervised training protocol and GAN-based losses. To understand the instability in training, we detect the gradient flow of attention and observe gradient conflict among attention branches. This phenomenon motivates us to alleviate the gradient issue by preserving the dominant gradient branch while removing the conflict ones. We propose a novel attention mechanism using this training strategy, Stop-Gradient Attention (SGA), outperforming the attention baseline by a large margin with better training stability. Compared with state-of-the-art modules in line-art colorization, our approach demonstrates significant improvements in Fr\'echet Inception Distance (FID, up to 27.21%) and structural similarity index measure (SSIM, up to 25.67%) on several benchmarks. The code of SGA is available at https://github.com/kunkun0w0/SGA .Comment: Accepted by ECCV202

InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization

Estimating mutual correlations between random variables or data streams is essential for intelligent behavior and decision-making. As a fundamental quantity for measuring statistical relationships, mutual information has been extensively studied and utilized for its generality and equitability. However, existing methods often lack the efficiency needed for real-time applications, such as test-time optimization of a neural network, or the differentiability required for end-to-end learning, like histograms. We introduce a neural network called InfoNet, which directly outputs mutual information estimations of data streams by leveraging the attention mechanism and the computational efficiency of deep learning infrastructures. By maximizing a dual formulation of mutual information through large-scale simulated training, our approach circumvents time-consuming test-time optimization and offers generalization ability. We evaluate the effectiveness and generalization of our proposed mutual information estimation scheme on various families of distributions and applications. Our results demonstrate that InfoNet and its training process provide a graceful efficiency-accuracy trade-off and order-preserving properties. We will make the code and models available as a comprehensive toolbox to facilitate studies in different fields requiring real-time mutual information estimation

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Energy Absorption of Square Tubes Filled by Modularized Honeycombs with Multiple Gradients

The Uniform Honeycomb-filled Tube (UHT) is one of the composite structures that has shown huge potential in absorbing energy. In this paper, Uniform Honeycomb (UH) filler is replaced by an enhanced Modularized Honeycomb (MH). The biggest advantage of MH is that it can significantly enhance energy absorption without adding weight compared with its uniform counterpart. Finite element models are created, and then validated by theoretical models. The energy absorption of the Modularized Honeycomb-filled Tube (MHT) is compared with that of the empty tube and UHT. The results show that the MHT is superior to them in Specific Energy Absorption (SEA). It is also found that the tube can help the MH improve its deformation stability, which is the key of the MHT’s excellent energy absorption capacity. Then, effects of design parameters on the SEA of the MHT are investigated and discussed. The results show that the MH with a large graded coefficient is good for enhancing the SEA of the MHT. However, the SEA also relies on the match between the honeycomb filler and tube walls. The work could inspire designs of modularized filler with various types of cells and benefit the development of advanced energy absorbers with lighter weight and more excellent energy absorption capacity

Performance of Volcano-Like Laser Textured Cutting Tools: An Experimental and Simulative Investigation

In recent years, surface texturing in micro-scale has been attempted on the surface of cutting tools for multiple purposes, e.g., cutting force reduction, prolonging life-span, anti-adhesion, etc. With respect to machinability and performance, micro-groove texture (MGT) has dominated in this field compared to other textured patterns. In this study, a novel volcano-like texture (VLT) was fabricated on the rake face of cemented carbide inserts (WC-Co, YG6) by fiber laser. The following cutting experiment tested the flat, MGT and VLT tools in turning aluminum alloy 6061. The effects of coolant and cutting conditions were investigated. In addition, a validated FEM model was employed to explore the distribution of stress and temperature fields in the tool-chip interface. The initial forming process of adhesion layer on rake face was investigated as well. The results indicated that lower cutting force and less adhesion can be achieved by small scale VLT. This study not only introduced VLT on cutting tools but also revealed its comprehensive performance

Survey on the scheme evaluation, opportunities and challenges of software defined‐information centric network

Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers

Simultaneously Improving Microstructures and Wear Properties of Ni60 Coating by Heat Treatment

Ni60 self-lubricated anti-wear composite coatings were successfully precipitated on the 35CrMoV substrate by laser cladding technology. The effects of heat treatment on the macro-morphology, microstructure, precipitated phase, microhardness, and wear properties of the composite coatings with different heat treatment temperatures (25 °C, 500 °C, 600 °C, and 700 °C for 1 h) were investigated systemically. The macro-morphology, microstructure, precipitated phases, and elements distribution of laser cladding layers were detected by optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy dispersive spectroscopy (EDS), respectively. The mechanical and tribological properties of the cladding layers were tested using a microscopic Vickers hardness tester and friction and wear tester, respectively. The results show that the main phases of Ni60 coatings are composed of γ-(Ni, Fe), Cr7C3, Cr23C6, CrB, CrFeB, and Cr2Ni3. In particular, the micro-structure and mechanical properties reach the best levels after heat treatment at 600 °C. The micro-hardness, average friction coefficient, and wear volume of the cladding layer are 771.4 to 915.8 HV1 and 0.434 and 2.9546 × 10−5 mm3, respectively. In conclusion, the micro-structure and mechanical properties of the cladding layer are greatly improved by the proper heat treatment temperature