| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
- Du, Wanyi, et al.
(författare)
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Photodoping of graphene/silicon van der Waals heterostructure observed by terahertz emission spectroscopy
- 2020
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Ingår i: Applied Physics Letters. - : AIP Publishing. - 0003-6951 .- 1077-3118. ; 117:8
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Tidskriftsartikel (refereegranskat)abstract
- Photodoping as a nonvolatile and reversible method can be used to modify the carrier distribution at the heterojunction interface. Herein, we explore the 2D/3D van der Waals (vdW) graphene/silicon (G/Si) heterostructure in real time by terahertz (THz) emission spectroscopy. Photoinduced doping is introduced by a continuous wave laser, which leads to a screening effect to the built-in electric field at the interface. The resulting decrease in transient photocurrent reduces the THz emission amplitude from the G/Si heterostructure. The photoinduced doping effect suggests a 40% THz intrinsic modulation depth at external reverse bias. This work provides an effective way to actively control the THz emission process from the G/Si interface and paves the way for analyzing the interfacial process under photoinduced doping in vdW heterostructures.
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| 3. |
- He, Mingshu, et al.
(författare)
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Deep-Feature-Based Autoencoder Network for Few-Shot Malicious Traffic Detection
- 2021
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Ingår i: Security and Communication Networks. - : Hindawi Limited. - 1939-0114 .- 1939-0122. ; 2021
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Tidskriftsartikel (refereegranskat)abstract
- With the increase of Internet visits and connections, it is becoming essential and arduous to protect the networks and different devices of the Internet of Things (IoT) from malicious attacks. The intrusion detection systems (IDSs) based on supervised machine learning (ML) methods require a large number of labeled samples. However, the number of abnormal behaviors is far less than that of normal behaviors, let alone that the shots of malicious behavior samples which can be intercepted as training dataset are actually limited. Consequently, it is a key research topic to conduct the anomaly detection for the small number of abnormal behavior samples. This paper proposes an anomaly detection model with a few abnormal samples to solve the problem in few-shot detection based on convolutional neural networks (CNN) and autoencoder (AE). This model mainly consists of the CNN-based supervised pretraining module and the AE-based data reconstruction module. Only a few abnormal samples are utilized to the pretrain module to build the structure of extracting deep features. The data reconstruction module simply chooses the deep features of normal samples as training data. There also exist some effective attention mechanisms in the pretraining module. Through the pretraining of small samples, the accuracy of abnormal detection is improved compared with merely training normal samples with AE. The simulation results prove that this solution can solve the above problems occurring in network behavior anomaly detection. In comparison to the original AE model and other clustering methods, the proposed model advances the detection results in a visible way.
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| 4. |
- Jiang, Haiyang, et al.
(författare)
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Machine-Learning-Based User Position Prediction and Behavior Analysis for Location Services
- 2021
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Ingår i: Information. - : MDPI AG. - 2078-2489. ; 12:5
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning (ML)-based methods are increasingly used in different fields of business to improve the quality and efficiency of services. The increasing amount of data and the development of artificial intelligence algorithms have improved the services provided to customers in shopping malls. Most new services are based on customers' precise positioning in shopping malls, especially customer positioning within shops. We propose a novel method to accurately predict the specific shops in which customers are located in shopping malls. We use global positioning system (GPS) information provided by customers' mobile terminals and WiFi information that completely covers the shopping mall. According to the prediction results, we learn some of the behavior preferences of users. We use these predicted customer locations to provide customers with more accurate services. Our training dataset is built using feature extraction and screening from some real customers' transaction records in shopping malls. In order to prove the validity of the model, we also cross-check our algorithm with a variety of machine learning algorithms. Our method achieves the best speed-accuracy trade-off and can accurately locate the shops in which customers are located in shopping malls in real time. Compared to other algorithms, the proposed model is more accurate. User preference behaviors can be used in applications to efficiently provide more tailored services.
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| 5. |
- Senchenkova, Sof'ya N., et al.
(författare)
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Structure and gene cluster of the O-antigen of Escherichia coli O165 containing 5-N-acetyl-7-N-[(R)-3-hydroxybutanoyl]pseudaminic acid
- 2016
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Ingår i: Glycobiology. - : Oxford University Press (OUP). - 0959-6658 .- 1460-2423. ; 26:4, s. 335-342
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Tidskriftsartikel (refereegranskat)abstract
- Upon mild acid degradation of the lipopolysaccharide of Escherichia coli O165, the O-polysaccharide chain was cleaved at the glycosidic linkage of 5-N-acetyl-7-N-[(R)-3-hydroxybutanoyl]pseudaminic acid (Pse5Hb7Ac). Analysis of the resulting linear tetrasaccharide and alkali-treated lipopolysaccharide by 1H/13C 1D and 2D nuclear magnetic resonance spectroscopy enabled elucidation of the following structure of the O-polysaccharide: →8)-α-Psep5Hb7Ac-(2 → 6)-β-D-Galp-(1 → 4)-β-D-Glсp-(1 → 3)-α-DGlсpNAc-(1→. The β-D-Galp-(1 → 4)-β-D-Glсp-(1 → 3)-D-GlсpNAc structural element is also present in the O-polysaccharide of E. coli O82. The content of the O-antigen gene cluster of E. coli O165 was found to be consistent with the O-polysaccharide structure established. Functions of proteins encoded in the gene cluster, including enzymes involved in the Pse5Hb7Ac biosynthesis and glycosyltransferases, were putatively assigned by comparison with sequences in available databases.
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