摘要：
Deep hashing cross-modal image-text retrieval has the advantage of low storage cost and high retrieval efficiency by mapping different modal data into a Hamming space. However, the existing unsupervised deep hashing methods generally relied on the intrinsic similarity information of each modal for structural matching, failing to fully consider the heterogeneous characteristics and semantic gaps of different modalities, which results in the loss of latent semantic correlation and co-occurrence information between the different modalities. To address this problem, this paper proposes an unsupervised deep hashing with multiple similarity preservation (UMSP) method for cross-modal image-text retrieval. First, to enhance the representation ability of the deep features of each modality, a modality-specific image-text feature extraction module is designed. Specifically, the image network with parallel structure and text network are constructed with the vision-language pre-training image encoder and multi-layer perceptron to capture the deep semantic information of each modality and learn a common hash code representation space. Then, to bridge the heterogeneous gap and improve the discriminability of hash codes, a multiple similarity preservation module is builded based on three perspectives: joint modal space, cross-modal hash space and image modal space, which aids the network to preserve the semantic similarity of modalities. Experimental results on three benchmark datasets (Wikipedia, MIRFlickr-25K and NUS-WIDE) show that UMSP outperforms other unsupervised methods for cross-modal image-text retrieval.
摘要：
Solid-state LiDARs have become an important perceptual device for simultaneous localization and mapping (SLAM) due to its low-cost and high-reliability compared to mechanical LiDARs. Nevertheless, existing solid-state LiDARs-based SLAM methods face challenges, including drift and mapping inconsistency, when operating in dynamic environments over extended periods and long distances. To this end, this paper proposes a robust, high-precision, real-time LiDAR-inertial SLAM method for solid-state LiDARs. At the front-end, the raw point cloud is segmented to filter dynamic points in preprocessing process. Subsequently, features are extracted using a combination of Principal Component Analysis (PCA) and Mean Clustering to reduce redundant points and improve data processing efficiency. At the back-end, a hierarchical fusion method is proposed to improve the accuracy of the system by fusing the feature information to iteratively optimize the LiDAR frames, and then adaptively selecting the LiDAR keyframes to be fused with the IMU. The proposed method is extensively evaluated using a Livox Avia solid-state LiDAR collecting datasets on two different platforms. In experiments, the end-to-end error is reduced by 35% and the single-frame operational efficiency is improved by 12% compared to LiLi-OM.
作者机构：
[She, Kang; Sheng, Guo; Shan, Zhengping; Xu, Piaorong; Liu, Exian] China College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China
通讯机构：
[Exian Liu] C;China College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China
关键词：
Attenuation coefficient;Chemical vapor deposition;Finite element method;Graphene;Nonlinear effects;Thin films
摘要：
Controlling the output light-intensity and realizing the light-switch function in hollow-core anti-resonant fibers (HC-ARFs) is crucial for their applications in polarizers, lasers, and sensor systems. Here, we theoretically propose a hybrid light-intensity-tunable HC-ARF deposited with the sandwiched graphene/hexagonal boron nitride/graphene based on the typical six-circular-tube and the nested structures. Changing the external drive voltage from 12.3 to 31.8 V, the hybrid HC-ARF experiences a high-low alterative attenuation coefficient with a modulation depth 3.87 and 1.91 dB/cm for the six-circular-tube and nested structures respectively, serving as a well-performance light-switch at the optical communication wavelength of 1.55 µm. This response is attributed to the variation of the Fermi level of graphene and is obviously influenced by the core size, fiber length, and the number of graphene and hBN layers. Moreover, one attenuation dip of the modulation depth was found because of the epsilon-near-zero effect in graphene. Our design provides a feasible paradigm for integrating graphene with anti-resonant fibers and high-performance electro-optic modulators.
作者机构：
[Ai, Wei; Meng, Tao; Meng, T; Xu, Jia; Shao, Hongen] Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha 410082, Hunan, Peoples R China.;[Li, Keqin] State Univ New York New Paltz, Dept Comp Sci, New York, NY 12561 USA.
通讯机构：
[Meng, T ] C;Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha 410082, Hunan, Peoples R China.
摘要：
Entity event deduplication is the task of identifying all duplication entity events that have described the same entity within a set of events. However, the traditional entity event deduplication method has two challenges. First, the traditional method usually used global comparison when finding the duplication entity event, are all entity events in the dataset need to be compared, leading to low performance. Second, when the entity event evolves, the traditional method does not identify it well and reduces the effectiveness. To address these two problems and improve the performance and effectiveness, we propose a two-stage deduplication method based on graph node selection and optimization (TS-NSNO) strategy. In the first stage (TS-NS), we propose a graph node selection strategy, which transforms the global comparison into a local comparison by selecting the leader node, greatly reduces the number of calculations and improves the performance. In the second stage (TS-NO), we propose a graph node optimization strategy, by combining the spatiotemporal distance and entity event importance change of the event evolution, which optimizes the entity event with incorrect judgment to improve the effectiveness. We conduct extensive experiments on real entity event datasets of different sizes, and the results show that our method performs better in terms of performance and effectiveness.
作者机构：
[Qin, Jiaohua; Li, Chunzhi; Tan, Yun; Wang, Zhenxu] Central South University of Forestry and Technology, Hunan, China;[Li, Jingyu; Tan, Ling; Deng, Chao; Tang, Hao] The Second Xiangya Hospital of Central South University, Hunan, China
摘要：
BACKGROUND: Aortic dissection refers to the true and false two-lumen separation of the aortic wall, in which the blood in the aortic lumen enters the aortic mesomembrane from the tear of the aortic intima to separate the mesomembrane and expand along the long axis of the aorta. PURPOSE: In view of the problems of individual differences, complex complications and many small targets in clinical aortic dissection detection, this paper proposes a convolution neural network MFF-FPN (Multi-scale Feature Fusion based Feature Pyramid Network) for the detection of aortic dissection complications. METHODS: The proposed model uses Resnet50 as the backbone for feature extraction and builds a pyramid structure to fuse low-level and high-level feature information. We add an attention mechanism to the backbone network, which can establish inter-dependencies between feature graph channels and enhance the representation quality of CNN. RESULTS: The proposed method has a mean average precision (MAP) of 99.40% in the task of multi object detection for aortic dissection and complications, which is higher than the accuracy of 96.3% on SSD model and 99.05% on YoloV7 model. It greatly improves the accuracy of small target detection such as cysts, making it more suitable for clinical focus detection. CONCLUSIONS: The proposed deep learning model achieves feature reuse and focuses on local important information. By adding only a small number of model parameters, we are able to greatly improve the detection accuracy, which is effective in detecting small target lesions commonly found in clinical settings, and also performs well on other medical and natural datasets.
摘要：
The ultrasensitive detection of hepatitis C virus (HCV) nucleic acid is crucial for the early diagnosis of hepatitis C. In this study, by combining Ag@Au core/shell nanoparticle (Ag@AuNP)-based surface-enhanced Raman scattering (SERS) tag with hybridization chain reaction (HCR), a novel SERS-sensing method was developed for the ultrasensitive detection of HCV nucleic acid. This SERS-sensing system comprised two different SERS tags, which were constructed by modifying Ag@AuNP with a Raman reporter molecule of 4-ethynylbezaldehyde, two different hairpin-structured HCR sequences (H1 or H2), and a detection plate prepared by immobilizinga capture DNA sequence onto the Ag@AuNP layer surface of the detection wells. When thetarget nucleic acid was present, the two SERS tags were captured on the surface of the Ag@AuNP-coated detection well to generate many "hot spots" through HCR, forming a strong SERS signal and realizing the ultrasensitive detection of thetarget HCV nucleic acid. The limit of detection of the SERS-sensing method for HCV nucleic acid was 0.47 fM, and the linear range was from 1 to 10(5) fM.
摘要：
Our results highlight the regulatory role of the negative bacterial‐fungal association in enhancing the correlation between bacterial diversity and C mineralisation. This suggests that promoting short‐term successive planting in the management of Eucalyptus plantations can mitigate the impact of this association on SOC decomposition. Taken together, our study advances the understanding of bacterial‐fungal negative associations to mediate carbon mineralisation in Eucalyptus plantations, giving us a new insight into SOC cycling dynamics in artificial forests. Abstract Bacteria and fungi are core microorganisms in diverse ecosystems, and their cross‐kingdom interactions are considered key determinants of microbiome structure and ecosystem functioning. However, how bacterial‐fungal interactions mediate soil organic carbon (SOC) dynamics remains largely unexplored in the context of artificial forest ecosystems. Here, we characterised soil bacterial and fungal communities in four successive planting of Eucalyptus and compared them to a neighbouring evergreen broadleaf forest. Carbon (C) mineralisation combined with five C‐degrading enzymatic activities was investigated to determine the effects of successive planting of Eucalyptus on SOC dynamics. Our results indicated that successive planting of Eucalyptus significantly altered the diversity and structure of soil bacterial and fungal communities and increased the negative bacterial‐fungal associations. The bacterial diversity significantly decreased in all Eucalyptus plantations compared to the evergreen forest, while the fungal diversity showed the opposite trend. The ratio of negative bacterial‐fungal associations increased with successive planting of Eucalyptus due to the decrease in SOC, ammonia nitrogen (NH4+‐N), nitrate nitrogen (NO3−‐N) and available phosphorus (AP). Structural equation modelling indicated that the potential cross‐kingdom competition, based on the ratio of negative bacterial‐fungal correlations, was significantly negatively associated with the diversity of total bacteria and keystone bacteria, thereby increasing C‐degrading enzymatic activities and C mineralisation. Synthesis and applications: Our results highlight the regulatory role of the negative bacterial‐fungal association in enhancing the correlation between bacterial diversity and C mineralisation. This suggests that promoting short‐term successive planting in the management of Eucalyptus plantations can mitigate the impact of this association on SOC decomposition. Taken together, our study advances the understanding of bacterial‐fungal negative associations to mediate carbon mineralisation in Eucalyptus plantations, giving us a new insight into SOC cycling dynamics in artificial forests.
摘要：
The utilization of bamboo as a substitute for wood or plastic signifies an imperative pathway towards achieving global sustainable development. The conduct of comprehensive and systematic research on the variations in the fundamental chemical compositions can offer scientific and theoretical guidance for the efficient and rational high-value utilization of bamboo. In this study, the variations of the content of primary chemical components in Moso bamboo (Phyllostachys pubescens) were systematically investigated by considering height and radial locations. This was achieved through using comprehensive chemical analysis and infrared spectroscopy methods, with an additional investigation into the impact of nodes on these variations. The results indicated that the fundamental chemical components of Moso bamboo consisted of cellulose, hemicelluloses and lignin. The cellulose content ranged from 36% to 40%, the hemicelluloses content ranged from 25% to 28%, and the lignin content ranged from 26% to 34%. The cellulose content decreased with increasing culm height, while it demonstrated a gradual increase during the transition from the inner to the outer layer of the wall. The cellulose content of the internodes was higher than that of the nodes. The variation in cellulose content was more pronounced in the radial direction compared to that in vertical direction. However, the hemicelluloses and lignin content in the bamboo culm showed no statistical differences. The abundant resource advantage of bamboo in China can provide a valuable resource benefit for the classification and utilization of its three fundamental chemical components. The findings derived can provide a reliable basis for establishing a scientific theoretical foundation to optimize the value-added utilization of bamboo.
作者：
Jie Ouyang;Liangliang Zhou;Yi Tian;Wanning Xiong;Lixin Wang;...
期刊：
Journal of Cleaner Production,2024年446:141503 ISSN：0959-6526
通讯作者：
Yongfeng Luo
作者机构：
[Jie Ouyang; Liangliang Zhou; Yi Tian; Wanning Xiong; Lixin Wang; Xi Ren; Qingquan Sheng; Zejun Li; Xiubo Liu; Yongfeng Luo] Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, College of Science, Material Science and Engineering School, Central South University of Forestry and Technology, Changsha, Hunan, 410004, PR China
通讯机构：
[Yongfeng Luo] H;Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, College of Science, Material Science and Engineering School, Central South University of Forestry and Technology, Changsha, Hunan, 410004, PR China
摘要：
The utilization of wood-derived carbon thick electrodes has demonstrated remarkable structural advantages in the realm of electrochemical energy storage and catalysis. Its exceptional structural stability, mechanical strength, and well-organized pore structure position it as a promising material for self-supporting electrodes. The multi-scale cross-linking of lignin, cellulose, and hemicellulose within the wood tracheid wall establishes a convenient prerequisite for structural modification. However, the significance of dynamic nanopores on wood tracheid walls in enhancing the microporous/mesoporous structure of wood-derived carbon electrodes has been overlooked due to the focus on operability of microscale array pores and wood decomposition processes. Here, we employ a straightforward, highly efficient, and environmentally sustainable solvent infiltration strategy to enhance the nanopore content within the wood tracheid wall, ultimately resulting in a significant enhancement of the microporous/mesoporous composition within the wood-derived electrode. The charge storage capacity of wood-derived carbon electrode is doubled through the implementation of a solvent permeation modification strategy, while its abundant micro/mesoporous structure also endows it with significant potential in the field of electrocatalysis. Therefore, this thermal and solvent permeation modification strategy is anticipated to supplant the conventional acid-base etching method and offer a novel research concept for the advancement of wood-based carbon electrodes with abundant pore structure and exceptional electrochemical properties.
摘要：
Breathable and comfortable sensing textiles that can detect multi-biomarkers existing in human sweat are a promising way to achieve comprehensive health monitoring in our daily life. However, current wearable and flexible electrochemical textiles lack stretchability, which can result in unstable signals or device damage during movement. Additionally, these textiles have limited integration of multiple indicators, needing a large surface area and a significant amount of sweat to activate the sensors. Herein, we report an integrated all-in-one multifunctional electrochemical biosensor fiber constructed with a helical core-sheath structure, offering the stretchability and ability to detect biomarkers with trace amounts of sweat. The biosensor was fabricated by arranging multi-functionalized carbon nanotube strips in a spiral pattern alongside a pre-stretched polymer fiber core acting as microelectrodes with robust interface. Additionally, a super-hydrophilic sheath layer is incorporated to enhance the sweat capture efficiency of the biosensor. The biosensor has the capability to simultaneously monitor six biomarkers including pH, K+, Na+, glucose, lactate and uric acid, demonstrating stable sensing performance under 300% strain. Merely 1 of sweat is needed to initiate the detection of all six biomarkers. The resulting textile sensing system presents continuous and real-time monitoring of multi-biomarker information, allowing for the assessment of our health condition.
作者机构：
Authors to whom correspondence should be addressed.;Key Laboratory of National Forestry and Grassland Administration on Control of Artificial Forest Diseases and Pests in South China, Central South University of Forestry and Technology, Changsha 410004, China;Key Laboratory of Cultivation and Protection for Non-Wood Forest Trees, Central South University of Forestry and Technology, Changsha 410004, China;Hunan Provincial Key Laboratory for Control of Forest Diseases and Pests, Central South University of Forestry and Technology, Changsha 410004, China;[Junang Liu; Guoying Zhou] Authors to whom correspondence should be addressed.<&wdkj&>Key Laboratory of National Forestry and Grassland Administration on Control of Artificial Forest Diseases and Pests in South China, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Key Laboratory of Cultivation and Protection for Non-Wood Forest Trees, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Hunan Provincial Key Laboratory for Control of Forest Diseases and Pests, Central South University of Forestry and Technology, Changsha 410004, China
通讯机构：
[Junang Liu; Guoying Zhou] A;Authors to whom correspondence should be addressed.<&wdkj&>Key Laboratory of National Forestry and Grassland Administration on Control of Artificial Forest Diseases and Pests in South China, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Key Laboratory of Cultivation and Protection for Non-Wood Forest Trees, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Hunan Provincial Key Laboratory for Control of Forest Diseases and Pests, Central South University of Forestry and Technology, Changsha 410004, China
关键词：
C. oleifera anthracnose;antagonistic endophytic bacterium;growth-promoting;inducing immunity
摘要：
Camellia oleifera (C. oleifera) is one of the four main, woody, edible oil tree species in the world, while C. oleifera anthracnose is mainly caused by the fungus Colletotrichum fructicola (C. fructicola), which severely affects the yield of C. oleifera and the quality of tea oil. Bacillus velezensis (B. velezensis) CSUFT-BV4 is an antagonistic endophytic bacterium isolated from healthy C. oleifera leaves. This study aimed to investigate the biocontrol potential of strain CSUFT-BV4 against C. oleifera anthracnose and its possible functional mechanism, and to determine its growth-promoting characteristics in host plants. In vitro, CSUFT-BV4 was shown to have efficient biofilm formation ability, as well as significant functions in the synthesis of metabolic substances and the secretion of probiotic substances. In addition, the CSUFT-BV4 fermentation broth also presented efficient antagonistic activities against five major C. oleifera anthracnose pathogens, including C. fructicola, C. gloeosporioides, C. siamense, C. camelliae, and C. kahawae, and the inhibition rate was up to 73.2%. In vivo, it demonstrated that the growth of C. oleifera treated with CSUFT-BV4 fermentation broth was increased in terms of stem width, plant height, and maximum leaf area, while the activities of various defense enzymes, e.g., superoxide dismutase (SOD), phenylalanine aminotransferase (PAL), and polyphenol oxidase (PPO), were effectively increased. The remarkable antagonistic activities against C. oleifera anthracnose, the growth-promoting characteristics, and the induction of host defense responses indicate that endophytic bacterium CSUFT-BV4 can be effectively used in the biological control of C. oleifera anthracnose in the future, which will have a positive impact on the development of the C. oleifera industry.
