• Korean Journal of Microbiology
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• v.11 no.2
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• pp.63-68
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• 1973

Thirtythree strains of the Aspergillus spp. isolated from foodstuffs were observed through some physiological characteristics for detection of identification key of Aspergillus spp. 1) Each strain of Aspergillus spp. had their specific characteristics and could be used for identification of species. 2) Excellent amylase-producing fungi were observed among the isolated strains of Aspergillus spp. 3) Amylase activities increased for one week incubation period. 4) In the tests of common characters of aflatoxin-producing fungi among the 33 strains of Aspergillus spp., for example, conidial size, presence of sclerotia, kojic acid, and pigment production, coloration of phenol, reduction of methylene blue, etc.

• The Microorganisms and Industry
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• v.26 no.1
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• pp.8-17
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• 2000

Thirtythree strains of the Aspergillus spp. isolated from foodstuffs were observed through some physiological characteristics for detection of identification key of Aspergillus spp. 1) Each strain of Aspergillus spp. had their specific characteristics and could be used for identification of species. 2) Excellent amylase-producing fungi were observed among the isolated strains of Aspergillus spp. 3) Amylase activities increased for one week incubation period. 4) In the tests of common characters of aflatoxin-producing fungi among the 33 strains of Aspergillus spp., for example, conidial size, presence of sclerotia, kojic acid, and pigment production, coloration of phenol, reduction of methylene blue, etc.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

• Smart Structures and Systems
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• v.21 no.5
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• pp.583-590
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• 2018

Nowadays, many tunnels have been commissioned for several decades, which require effective inspection methods to assess their health conditions. The ambient vibration test has been widely adopted for the damage identification of concrete structures. In this study, the vibration characters of tunnel lining shells built with forepoling method was analyzed based on the analytical solutions of the Donnell-Mushtari shell theory. The broken rock, foreploing, rock-concrete contacts between rock mass and concrete lining, was represented by elastic boundaries with normal and shear stiffness. The stiffness of weak contacts has significant effects on the natural frequency of tunnel lining. Numerical simulations were also carried out to compare with the results of the analytical methods, showing that even though the low nature frequency is difficult to distinguish, the presented approach is convenient, effective and accurate to estimate the natural frequency of tunnel linings. Influences of the void, the lining thickness and the concrete type on natural frequencies were evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3364-3382
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• 2023

Remote sensing image segmentation plays an important role in realizing intelligent city construction. The current mainstream segmentation networks effectively improve the segmentation effect of remote sensing images by deeply mining the rich texture and semantic features of images. But there are still some problems such as rough results of small target region segmentation and poor edge contour segmentation. To overcome these three challenges, we propose an improved semantic segmentation model, referred to as MRU-Net, which adopts the U-Net architecture as its backbone. Firstly, the convolutional layer is replaced by BasicBlock structure in U-Net network to extract features, then the activation function is replaced to reduce the computational load of model in the network. Secondly, a hybrid multi-scale recognition module is added in the encoder to improve the accuracy of image segmentation of small targets and edge parts. Finally, test on Massachusetts Buildings Dataset and WHU Dataset the experimental results show that compared with the original network the ACC, mIoU and F1 value are improved, and the imposed network shows good robustness and portability in different datasets.

• Journal of Veterinary Science
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• v.25 no.1
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• pp.18.1-18.27
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• 2024

Mastitis is one of the most widespread infectious diseases that adversely affects the profitability of the dairy industry worldwide. Accurate diagnosis and identification of pathogens early to cull infected animals and minimize the spread of infection in herds is critical for improving treatment effects and dairy farm welfare. The major pathogens causing mastitis and pathogenesis are assessed first. The most recent and advanced strategies for detecting mastitis, including genomics and proteomics approaches, are then evaluated. Finally, the advantages and disadvantages of each technique, potential research directions, and future perspectives are reported. This review provides a theoretical basis to help veterinarians select the most sensitive, specific, and cost-effective approach for detecting bovine mastitis early.

• BMB Reports
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• v.43 no.3
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• pp.193-198
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• 2010

In this study, we report the identification and characterization of a novel C2H2 zinc finger protein, ZNF552, from a human embryonic heart cDNA library. ZNF552 is composed of three exons and two introns and maps to chromosome 19q13.43. The cDNA of ZNF552 is 2.3 kb, encoding 407 amino acids with an amino-terminal KRAB domain and seven carboxyl-terminal C2H2 zinc finger motifs in the nucleus and cytoplasm. Northern blotting analysis indicated that a 2.3 kb transcript specific for ZNF552 was expressed in liver, lung, spleen, testis and kidney, especially with a higher level in the lung and testis in human adult tissues. Reporter gene assays showed that ZNF552 was a transcriptional repressor, and overexpression of ZNF552 in the COS-7 cells inhibited the transcriptional activities of AP-1 and SRE, which could be relieved through RNAi analysis. Deletion studies showed that the KRAB domain of ZNF552 may be involved in this inhibition.

• Molecules and Cells
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• v.38 no.10
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• pp.859-865
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• 2015

Most imprinted genes are concerned with embryonic development, especially placental development. Here, we identified a placenta-specific imprinted gene Qpct. Our results show that Qpct is widely expressed during early embryonic development and can be detected in the telecephalon, midbrain, and rhombencephalon at E9.5-E11.5. Moreover, Qpct is strikingly expressed in the brain, lung and liver in E15.5. Expression signals for Qpct achieved a peak at E15.5 during placental development and were only detected in the labyrinth layer in E15.5 placenta. ChIP assay results suggest that the modification of histone H3K4me3 can result in maternal activating of Qpct.

• Journal of Microbiology and Biotechnology
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• v.30 no.10
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• pp.1467-1479
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• 2020

Profiling the transcriptome changes involved in xylose metabolism by the fungus Trichoderma reesei allows for the identification of potential targets for ethanol production processing. In the present study, the transcriptome of T. reesei HJ-48 grown on xylose versus glucose was analyzed using next-generation sequencing technology. During xylose fermentation, numerous genes related to central metabolic pathways, including xylose reductase (XR) and xylitol dehydrogenase (XDH), were expressed at higher levels in T. reesei HJ-48. Notably, growth on xylose did not fully repress the genes encoding enzymes of the tricarboxylic acid and respiratory pathways. In addition, increased expression of several sugar transporters was observed during xylose fermentation. This study provides a valuable dataset for further investigation of xylose fermentation and provides a deeper insight into the various genes involved in this process.