Deep Cost-sensitive Learning for Wheat Frost Detection

Frost damage is one of the main factors leading to wheat yield reduction. Therefore, the detection of wheat frost accurately and efficiently is beneficial for growers to take corresponding measures in time to reduce economic loss. To detect the wheat frost, in this paper we create a hyperspectral wheat frost data set by collecting the data characterized by temperature, wheat yield, and hyperspectral information provided by the handheld hyperspectral spectrometer. However, due to the imbalance of data, that is, the number of healthy samples is much higher than the number of frost damage samples, a deep learning algorithm tends to predict biasedly towards the healthy samples resulting in model overfitting of the healthy samples. Therefore, we propose a method based on deep cost-sensitive learning, which uses a one-dimensional convolutional neural network as the basic framework and incorporates cost-sensitive learning with fixed factors and adjustment factors into the loss function to train the network. Meanwhile, the accuracy and score are used as evaluation metrics. Experimental results show that the detection accuracy and the score reached 0.943 and 0.623 respectively, this demonstration shows that this method not only ensures the overall accuracy but also effectively improves the detection rate of frost samples.Comment: 7 pages, 4 figures, accepted by ICBAIE 202

Aeromonas veronii, a potential pathogen of enteritis in snakehead fish Ophiocephalus argus

Enteritis is known as a major disease in snakehead fish Ophiocephalus argus aquaculture and has resulted in large economic losses. Yet only scarce information is available on Aeromonas veronii as a causal agent for enteritis in O. argus. In this study, a virulent strain, temporarily named HY2, was isolated from diseased snakehead fish suffering from enteritis, and was identified as A. veronii through molecular and phenotypic methods. In addition, the HY2 isolate showed an LD50 value of 2.8×105 CFU mL-1, and was highly sensitive to aminoglycosides, macrolides, polypeptides, quinolones, sulfonamides and tetracyclines antibiotics. To the best of our knowledge, this is the first report of A. veronii as a potential pathogen of enteritis in snakehead fish

Rethinking Image Editing Detection in the Era of Generative AI Revolution

The accelerated advancement of generative AI significantly enhance the viability and effectiveness of generative regional editing methods. This evolution render the image manipulation more accessible, thereby intensifying the risk of altering the conveyed information within original images and even propagating misinformation. Consequently, there exists a critical demand for robust capable of detecting the edited images. However, the lack of comprehensive dataset containing images edited with abundant and advanced generative regional editing methods poses a substantial obstacle to the advancement of corresponding detection methods. We endeavor to fill the vacancy by constructing the GRE dataset, a large-scale generative regional editing dataset with the following advantages: 1) Collection of real-world original images, focusing on two frequently edited scenarios. 2) Integration of a logical and simulated editing pipeline, leveraging multiple large models in various modalities. 3) Inclusion of various editing approaches with distinct architectures. 4) Provision of comprehensive analysis tasks. We perform comprehensive experiments with proposed three tasks: edited image classification, edited method attribution and edited region localization, providing analysis of distinct editing methods and evaluation of detection methods in related fields. We expect that the GRE dataset can promote further research and exploration in the field of generative region editing detection

Bacillus amyloliquefaciens G1: A Potential Antagonistic Bacterium against Eel-Pathogenic Aeromonas hydrophila

Recent studies have revealed that the use of probiotics is an alternative to control marine aeromonas. However, few probiotics are available against Aeromonas hydrophila infections in eels. In the present study, a potential antagonistic strain G1 against the eel-pathogenic A. hydrophila was isolated from sediment underlying brackish water. Its extracellular products with antibacterial activities were shown to be stable under wide range of pH, temperature, and proteinase K. It was initially identified as Bacillus amyloliquefaciens using API identification kits and confirmed to be B. amyloliquefaciens strain (GenBank accession number DQ422953) by phylogenetic analysis. In addition, it was shown to be safe for mammalians, had a wide anti-A. hydrophila spectrum, and exhibited significant effects on inhibiting the growth of the eel-pathogenic A. hydrophila both in vitro and in vivo. To the best of our knowledge, this is the first report on a promising antagonistic Bacillus amyloliquefaciens strain from brackish water sediment against eel-pathogenic A. hydrophila

Seismic behavior of bifurcated concrete filled steel tube columns with a multi-cavity structure

In order to meet the architecture and construction needs of high rise buildings, the special-shaped columns are becoming more and more widely used. In this study, cyclic tests on seven special-shaped bifurcated Concrete Filled Steel Tube (CFST) columns are carried out. Test variables are the column cross section types and the loading directions. The strength, ductility, hysteretic behavior, energy dissipation ability, failure modes and seismic mechanisms are analyzed. Test results show that: the cross-section type of the column is the main factor influencing the seismic behavior of the specimens. Compared with the basic cross section type, the strength, ductility and energy dissipation capacity of the strengthened cross section type all significantly increased. The cross sections with the inserted angle steel or circular steel tube have the best comprehensive seismic behavior. Also, the loading direction has a considerable influence on the seismic behavior. Compares with the short axis loading specimen C1-Y, the strength of the long axis specimen C1-X and 45° axis C1-Z increase by 92.5 % and 44.0 %, respectively, indicating that the differences in loading direction should be taken into consideration in the seismic design. Based on the test results, the FEM analysis are also carried out. The FEM results show a satisfactory agreement with experimental results. The concrete constitutive relationship and modelling method proposed is suitable for the simulation of special-shaped bifurcated CFST columns with multiple cavities

Combined Preconditioning and Postconditioning Provides Synergistic Protection against Liver Ischemic Reperfusion Injury

Hepatic Ischemia and Reperfusion Injury (IRI) is a major cause of liver damage during liver surgery and transplantation. Ischemic preconditioning and postconditioning are strategies that can reduce IRI. In this study, different combined types of pre- and postconditioning procedures were tested in a murine warm hepatic IRI model to evaluate their protective effects. Proanthocyanidins derived from grape seed was used before ischemia process as pharmacological preconditioning to combine with technical preconditioning and postconditioning. Three pathways related to IRI, including reactive oxygen species (ROS) generation, pro-inflammatory cytokines release and hypoxia responses were examined in hepatic IRI model. Individual and combined pre- and postconditioning protocols significantly reduce liver injury by decreasing the liver ROS and cytokine levels, as well as enhancing the hypoxia tolerance response. Our data also suggested that in addition to individual preconditioning or postconditioning, the combination of these two treatments could reduce liver ischemia/reperfusion injury more effectively by increasing the activity of ROS scavengers and antioxidants. The utilization of grape seed proanthocyanidins (GSP) could improve the oxidation resistance in combined pre- and postconditioning groups. The combined protocol also further increased the liver HIF-1 alpha protein level, but had no effect on pro-inflammatory cytokines release compared to solo treatment

Bacillus cereus, a potential pathogen of snakehead fish Ophiocephalus argus

Bacillus cereus is an emerging pathogen that has caused high mortalities in aquaculture animals. Yet the pathogenicity of B. cereus in snakehead fish Ophiocephalus argus is still unclear. In this study, a virulent strain (CA4) was isolated from diseased snakehead fish suffering from a typical symptom of hepatic hemorrhage with blood vessel congestion and macrophage infiltration, and was identified molecularly and phenotypically as B. cereus. It was β-hemolytic, showed an LD50 value of 2.57×106 CFU mL-1 for snakehead fish, and developed multiple resistances to cotrimoxazole, doxycycline, florfenicol, neomycin, sulfisoxazole, and tetracycline in aquaculture use. To the best of our knowledge, this is the first report of snakehead fish- pathogenic B. cereus. The findings of this study provide new insights into the potential threat of pathogenic B. cereus to snakehead fish