Mutual-Guided Dynamic Network for Image Fusion

Image fusion aims to generate a high-quality image from multiple images captured under varying conditions. The key problem of this task is to preserve complementary information while filtering out irrelevant information for the fused result. However, existing methods address this problem by leveraging static convolutional neural networks (CNNs), suffering two inherent limitations during feature extraction, i.e., being unable to handle spatial-variant contents and lacking guidance from multiple inputs. In this paper, we propose a novel mutual-guided dynamic network (MGDN) for image fusion, which allows for effective information utilization across different locations and inputs. Specifically, we design a mutual-guided dynamic filter (MGDF) for adaptive feature extraction, composed of a mutual-guided cross-attention (MGCA) module and a dynamic filter predictor, where the former incorporates additional guidance from different inputs and the latter generates spatial-variant kernels for different locations. In addition, we introduce a parallel feature fusion (PFF) module to effectively fuse local and global information of the extracted features. To further reduce the redundancy among the extracted features while simultaneously preserving their shared structural information, we devise a novel loss function that combines the minimization of normalized mutual information (NMI) with an estimated gradient mask. Experimental results on five benchmark datasets demonstrate that our proposed method outperforms existing methods on four image fusion tasks. The code and model are publicly available at: https://github.com/Guanys-dar/MGDN.Comment: ACMMM 2023 accepte

Neural Degradation Representation Learning for All-In-One Image Restoration

Existing methods have demonstrated effective performance on a single degradation type. In practical applications, however, the degradation is often unknown, and the mismatch between the model and the degradation will result in a severe performance drop. In this paper, we propose an all-in-one image restoration network that tackles multiple degradations. Due to the heterogeneous nature of different types of degradations, it is difficult to process multiple degradations in a single network. To this end, we propose to learn a neural degradation representation (NDR) that captures the underlying characteristics of various degradations. The learned NDR decomposes different types of degradations adaptively, similar to a neural dictionary that represents basic degradation components. Subsequently, we develop a degradation query module and a degradation injection module to effectively recognize and utilize the specific degradation based on NDR, enabling the all-in-one restoration ability for multiple degradations. Moreover, we propose a bidirectional optimization strategy to effectively drive NDR to learn the degradation representation by optimizing the degradation and restoration processes alternately. Comprehensive experiments on representative types of degradations (including noise, haze, rain, and downsampling) demonstrate the effectiveness and generalization capability of our method

Tetherin inhibits prototypic foamy virus release

Background: Tetherin (also known as BST-2, CD317, and HM1.24) is an interferon- induced protein that blocks the release of a variety of enveloped viruses, such as retroviruses, filoviruses and herpesviruses. However, the relationship between tetherin and foamy viruses has not been clearly demonstrated. Results: In this study, we found that tetherin of human, simian, bovine or canine origin inhibits the production of infectious prototypic foamy virus (PFV). The inhibition of PFV by human tetherin is counteracted by human immunodeficiency virus type 1 (HIV-1) Vpu. Furthermore, we generated human tetherin transmembrane domain deletion mutant (delTM), glycosyl phosphatidylinositol (GPI) anchor deletion mutant (delGPI), and dimerization and glycosylation deficient mutants. Compared with wild type tetherin, the delTM and delGPI mutants only moderately inhibited PFV production. In contrast, the dimerization and glycosylation deficient mutants inhibit PFV production as efficiently as the wild type tetherin. Conclusions: These results demonstrate that tetherin inhibits the release and infectivity of PFV, and this inhibition is antagonized by HIV-1 Vpu. Both the transmembrane domain and the GPI anchor of tetherin are important for the inhibition of PFV, whereas the dimerization and the glycosylation of tetherin are dispensable

Guarding Embryo Development of Zebrafish by Shell Engineering: A Strategy to Shield Life from Ozone Depletion

Background: The reduced concentration of stratospheric ozone results in an increased flux of biologically damaging midultraviolet radiation (UVB, 280 to 320 nm) reaching earth surfaces. Environmentally relevant levels of UVB negatively impact various natural populations of marine organisms, which is ascribed to suppressed embryonic development by increased radiation. Methodology/Principal Findings: Inspired by strategies in the living systems generated by evolution, we induce an extra UVB-adsorbed coat on the chorion (eggshell surrounding embryo) of zebrafish, during the blastula period. Short and long UV exposure experiments show that the artificial mineral-shell reduces the UV radiation effectively and the enclosed embryos become more robust. In contrast, the uncoated embryos cannot survive under the enhanced UVB condition. Conclusions: We suggest that an engineered shell of functional materials onto biological units can be developed as a strategy to shield lives to counteract negative changes of global environment, or to provide extra protection for the living units in biological research

Sex- and isoform-specific mechanism of neuroprotection by transgenic expression of P450 epoxygenase in vascular endothelium

Cytochrome P450 epoxygenases (CYP) metabolize arachidonic acid to epoxyeicosatrienoic acids (EETs), which exhibit vasodilatory, anti-inflammatory and neuroprotective actions in experimental cerebral ischemia. We evaluated the effect of endothelial-specific CYP overexpression on cerebral blood flow, inflammatory cytokine expression and tissue infarction after focal cerebral ischemia in transgenic mice

Quantum Fluctuations and Lineshape Anomaly in a High‐β Silver‐Coated InP‐Based Metallic Nanolaser

Metallic nanocavity lasers provide important technological advancement towards even smaller integrable light sources. They give access to widely unexplored lasing physics in which the distinction between different operational regimes, like those of thermal or a coherent light emission, becomes increasingly challenging upon approaching a device with a near-perfect spontaneous-emission coupling factor $\beta$. In fact, quantum-optical studies have to be employed to reveal a transition to coherent emission in the intensity fluctuation behavior of nanolasers when the input-output characteristic appears thresholdless for $\beta = 1$ nanolasers. Here, we identify a new indicator for lasing operation in high-$\beta$ lasers by showing that stimulated emission can give rise to a lineshape anomaly manifesting as a transition from a Lorentzian to a Gaussian component in the emission linewidth that dominates the spectrum above the lasing threshold

Crowd-Sourced Mobility Mapping for Location Tracking Using Unlabeled Wi-Fi Simultaneous Localization and Mapping

Due to the increasing requirements of the seamless and round-the-clock Location-based services (LBSs), a growing interest in Wi-Fi network aided location tracking is witnessed in the past decade. One of the significant problems of the conventional Wi-Fi location tracking approaches based on received signal strength (RSS) fingerprinting is the time-consuming and labor intensive work involved in location fingerprint calibration. To solve this problem, a novel unlabeled Wi-Fi simultaneous localization and mapping (SLAM) approach is developed to avoid the location fingerprinting and additional inertial or vision sensors. In this approach, an unlabeled mobility map of the coverage area is first constructed by using the crowd-sourcing from a batch of sporadically recorded Wi-Fi RSS sequences based on the spectral cluster assembling. Then, the sequence alignment algorithm is applied to conduct location tracking and mobility map updating. Finally, the effectiveness of this approach is verified by the extensive experiments carried out in a campus-wide area

Study on the Application of Modified Sn-Based Solder in Cable Intermediate Joints

With the increasing use of underground cables, the quantity and quality of intermediate joints demanded are also increasing. The quality of the traditional crimping intermediate joint is easily affected by the actual process of the operator, which may lead to the heating of the crimping part of the wire core, affecting the insulation performance of the cable, and finally causing the joint to break. However, aluminothermic reactive technology has some problems, such as a high welding temperature and an uncontrollable reaction. In order to solve these problems, according to the brazing principle and microalloying method, the optimal content of In in Sn-1.5Cu-based solder was explored, and then the connection of the middle joint of a 10 kV cable was completed using a connecting die and electrical connection process. The contact resistance and tensile strength of the joint were tested to verify the feasibility of this method. The results show that the maximum conductivity of the solder with 3.8% and 5% In content can reach 3.236 × 106 S/m, and the highest wettability is 93.6%. Finally, the minimum contact resistance of the intermediate joint is 7.05 μΩ, which is 43% lower than that of the aluminothermic welded joint, and the tensile strength is close to that of the welded joint, with a maximum of 7174 N

Vehicle Logo Recognition Based on Enhanced Matching for Small Objects, Constrained Region and SSFPD Network

Vehicle Logo Recognition (VLR) is an important part of vehicle behavior analysis and can provide supplementary information for vehicle identification, which is an essential research topic in robotic systems. However, the inaccurate extraction of vehicle logo candidate regions will affect the accuracy of logo recognition. Additionally, the existing methods have low recognition rate for most small vehicle logos and poor performance under complicated environments. A VLR method based on enhanced matching, constrained region extraction and SSFPD network is proposed in this paper to solve the aforementioned problems. A constrained region extraction method based on segmentation of the car head and car tail is proposed to accurately extract the candidate region of logo. An enhanced matching method is proposed to improve the detection performance of small objects, which augment each of training images by copy-pasting small objects many times in the unconstrained region. A single deep neural network based on a reduced ResNeXt model and Feature Pyramid Networks is proposed in this paper, which is named as Single Shot Feature Pyramid Detector (SSFPD). The SSFPD uses the reduced ResNeXt to improve classification performance of the network and retain more detailed information for small-sized vehicle logo detection. Additionally, it uses the Feature Pyramid Networks module to bring in more semantic context information to build several high-level semantic feature maps, which effectively improves recognition performance. Extensive evaluations have been made on self-collected and public vehicle logo datasets. The proposed method achieved 93.79% accuracy on the Common Vehicle Logos Dataset and 99.52% accuracy on another public dataset, respectively, outperforming the existing methods

A Combination of Ilizarov Frame, Externalized Locking Plate and Tibia Bridging for an Adult with Large Tibial Defect and Severe Varus Deformity Due to Chronic Osteomyelitis in Childhood: A Case Report

Background: Various techniques have been reported to treat large, segmental tibial defects, such as autogenous bone graft, vascularized free fibula transfer and bone transport. We present a case of a 24-year-old male with a 17-year history of chronic osteomyelitis with obvious lower limb length discrepancy and severe varus deformity of the tibia secondary to osteomyelitis in childhood. Aim: The aim of this work is to provide an alternative choice for treating patients in developing countries with severe lower limb deformity caused by chronic osteomyelitis. Case Presentations: Without surgical intervention for a prolonged period of time, the patient was admitted in our institute for corrective surgery. Corrective surgery consisted of three stages: lengthening with Ilizarov frame, removal of Ilizarov frame and fixation with externalized locking plate, and removal of externalized locking plate. Tibia bridging was achieved at the distal and proximal junction. The range of motion (ROM) of the knee joint was nearly normal, but the stiffness of the ankle joint was noticeable. The remaining leg discrepancy of 0.1 cm required no application of a shoe lift. Moreover, the patient could engage in daily activities without noted limping. Conclusions: Distraction–compression osteogenesis using the Ilizarov apparatus is a powerful tool to lengthen the shortened long bone and adjust the deformity of the lower limbs. Externalized locking plates provide an alternative to the traditional bulky external fixator, as its low profile makes it more acceptable to patients without compromising axial and torsional stiffness. In all, a combination of Ilizarov frame, externalized locking plate and tibia bridging is an alternative for patients in similar conditions