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  • 1
    Online Resource
    Online Resource
    A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder
    Oxford University Press (OUP) ; 2023
    In:  Nucleic Acids Research Vol. 51, No. 21 ( 2023-11-27), p. e110-e110
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 51, No. 21 ( 2023-11-27), p. e110-e110
    Abstract: RNAs play essential roles in diverse physiological and pathological processes by interacting with other molecules (RNA/protein/compound), and various computational methods are available for identifying these interactions. However, the encoding features provided by existing methods are limited and the existing tools does not offer an effective way to integrate the interacting partners. In this study, a task-specific encoding algorithm for RNAs and RNA-associated interactions was therefore developed. This new algorithm was unique in (a) realizing comprehensive RNA feature encoding by introducing a great many of novel features and (b) enabling task-specific integration of interacting partners using convolutional autoencoder-directed feature embedding. Compared with existing methods/tools, this novel algorithm demonstrated superior performances in diverse benchmark testing studies. This algorithm together with its source code could be readily accessed by all user at: https://idrblab.org/corain/ and https://github.com/idrblab/corain/.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkad929
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    The DESI One-Percent survey: exploring the Halo Occupation Distribution of Emission Line Galaxies with AbacusSummit simulations
    IOP Publishing ; 2023
    In:  Journal of Cosmology and Astroparticle Physics Vol. 2023, No. 10 ( 2023-10-01), p. 016-
    Details
    In: Journal of Cosmology and Astroparticle Physics, IOP Publishing, Vol. 2023, No. 10 ( 2023-10-01), p. 016-
    Abstract: The One-Percent survey of the Dark Energy Spectroscopic Instrument collected ∼ 270 k emission line galaxies (ELGs) at 0.8 〈 z 〈 1.6. The high completeness of the sample allowed the clustering to be measured down to scales never probed before, 0.04 Mpc/ h in r p for the projected 2-point correlation function (2PCF) and 0.17 Mpc/ h in galaxy pair separation s for the 2PCF monopole and quadrupole. The most striking feature of the measurements is a strong signal at the smallest scales, below 0.2 Mpc/ h in r p and 1 Mpc/ h in s . We analyse these data in the halo occupation distribution framework. We consider different distributions for central galaxies, a standard power law for satellites with no condition on the presence of a central galaxy and explore several extensions of these models. For all considered models, the mean halo mass of the sample is found to be log 10 ⟨ M h ⟩ ∼ 11.9. We obtain a satellite mean occupation function which agrees with physically motivated ELG models only if we introduce central-satellite conformity, meaning that the satellite occupation is conditioned by the presence of central galaxies of the same type. To achieve in addition a good modelling of the clustering between 0.1 and 1 Mpc/ h in r p , we allow for ELG positioning outside of the halo virial radius and find 0.5% of ELGs residing in the outskirts of halos. Furthermore, the satellite velocity dispersion inside halos is found to be ∼ 30% larger than that of the halo dark matter particles. These are the main findings of our work. We investigate assembly bias as a function of halo concentration, local density or local density anisotropies and observe no significant change in our results. We split the data sample in two redshift bins and report no significant evolution with redshift. Lastly, changing the cosmology in the modelling impacts only slightly our results.
    Type of Medium: Online Resource
    ISSN: 1475-7516
    URL: Article
    DOI: 10.1088/1475-7516/2023/10/016
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2023
    detail.hit.zdb_id: 2104147-7
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  • 3
    Online Resource
    Online Resource
    Table_2.pdf
    Frontiers Media SA ; 2022
    In:  Frontiers in Microbiology Vol. 12 ( 2022-1-17)
    Details
    In: Frontiers in Microbiology, Frontiers Media SA, Vol. 12 ( 2022-1-17)
    Abstract: Streptococcus pneumoniae ( S. pneumoniae ) is a common major human pathogen associated with community-acquired pneumonia, septicemia, meningitis, and otitis media. It is difficult to isolate and identify S. pneumoniae form clinical samples. To evaluate a novel, rapid, sensitive, and specific loop-mediated isothermal amplification (LAMP) assay to detect S. pneumoniae pneumonia in children, we designed specific LAMP primers targeting lytA and psaA genes. We optimized the reaction time and reaction system, and evaluated its sensitivity and specificity of detection using real-time turbidity monitoring and visual observation. We also analyzed the molecular characteristics of the isolates obtained from the positive samples. The primer sets LytA-1 and PsaA-2 amplified the genes in the shortest times, and 63°C was confirmed as the optimum reaction temperature. The detection sensitivity of each reaction was 10 and 100 copies/μL with primer sets LytA-1 and PsaA-2, respectively. This LAMP assay showed no cross-reactivity with other 27 pathogens. To describe the availability of this method, we collected 748 clinical samples from children with pneumonia. Among them, 135 were confirmed to be S. pneumoniae positive by LAMP. The sensitivity was 100% (95% CI 96.4–100%), specificity 99.0% (95% CI 97.8–99.6%). Including them, 50 were co-infected with Mycoplasma pneumoniae . This LAMP assay detected S. pneumoniae in 1 h and the results can be identified with visual naked eyes. Thus, it will be a powerful tool for S. pneumoniae early diagnosis and effective antibiotic therapy.
    Type of Medium: Online Resource
    ISSN: 1664-302X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fmicb.2021.816997
    DOI: 10.3389/fmicb.2021.816997.s001
    DOI: 10.3389/fmicb.2021.816997.s002
    DOI: 10.3389/fmicb.2021.816997.s003
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2587354-4
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  • 4
    Online Resource
    Online Resource
    Error analysis of received signal strength-based visible-light positioning using dilution of precision
    SPIE-Intl Soc Optical Eng ; 2021
    In:  Optical Engineering Vol. 60, No. 10 ( 2021-10-5)
    Details
    In: Optical Engineering, SPIE-Intl Soc Optical Eng, Vol. 60, No. 10 ( 2021-10-5)
    Type of Medium: Online Resource
    ISSN: 0091-3286
    URL: Article
    DOI: 10.1117/1.OE.60.10.106102
    Language: Unknown
    Publisher: SPIE-Intl Soc Optical Eng
    Publication Date: 2021
    detail.hit.zdb_id: 2010512-5
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  • 5
    Online Resource
    Online Resource
    Machine learning models for orthokeratology lens fitting and axial length prediction
    Wiley ; 2023
    In:  Ophthalmic and Physiological Optics
    Details
    In: Ophthalmic and Physiological Optics, Wiley
    Abstract: In order to improve the efficiency of orthokeratology (OK) lens fitting and predict the axial length after 1 year of OK lens wear, machine learning models were proposed. Methods Clinical data from 1302 myopic subjects were collected retrospectively, and two machine learning models were implemented. Demographic and corneal topographic data were collected as input variables. The output variables were the parameters of the OK lens and the axial length after 1 year. Eighty percent of input variables was used as the training set and the remaining 20% was used as the validation set. The first alignment curve (AC1) of the OK lenses, deduced using machine learning models and formula calculation, were compared. Multiple regression models (support vector machine, Gaussian process, decision tree and random forest) were used to predict the axial length after 1 year. In addition, we classified data based on lens brand, and carried out more detailed parameter fitting and analysis for spherical and toric OK lenses. Results The OK lens fitting model showed higher ( R 2  = 0.93) and lower errors (mean absolute error [MAE] = 0.19, mean square error [MSE]  = 0.09) when predicting AC1, compared with the formula calculation ( R 2  = 0.66, MAE = 0.44, MSE = 0.25). The machine learning model still had high R 2 values ranging from 0.91 to 0.96 when considering the brand and design of the OK lenses. Further, the R 2 value for the axial length prediction model was 0.94, which indicated that the machine learning model had high accuracy and good robustness. Conclusion The OK lens fitting model and the axial length prediction model played an important role in guiding OK lens fitting, with high accuracy and robustness in prediction performance.
    Type of Medium: Online Resource
    ISSN: 0275-5408 , 1475-1313
    URL: Article
    DOI: 10.1111/opo.13212
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2008422-5
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  • 6
    Online Resource
    Online Resource
    Defect passivation strategy for inorganic CsPbI2Br perovskite solar cell with a high-efficiency of 16.77%
    Elsevier BV ; 2021
    In:  Journal of Materials Science & Technology Vol. 82 ( 2021-08), p. 40-46
    Details
    In: Journal of Materials Science & Technology, Elsevier BV, Vol. 82 ( 2021-08), p. 40-46
    Type of Medium: Online Resource
    ISSN: 1005-0302
    URL: Article
    DOI: 10.1016/j.jmst.2020.08.051
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2431914-4
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  • 7
    Online Resource
    Online Resource
    Image_1.pdf
    Frontiers Media SA ; 2024
    In:  Frontiers in Medicine Vol. 10 ( 2024-1-4)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 10 ( 2024-1-4)
    Abstract: The current study designed a unique type of corneal topography evaluation method based on deep learning and traditional image processing algorithms. The type of corneal topography of patients was evaluated through the segmentation of important medical zones and the calculation of relevant medical indicators of orthokeratology (OK) lenses. Methods The clinical data of 1,302 myopic subjects was collected retrospectively. A series of neural network-based U-Net was used to segment the pupil and the treatment zone in the corneal topography, and the decentration, effective defocusing contact range, and other indicators were calculated according to the image processing algorithm. The type of corneal topography was evaluated according to the evaluation criteria given by the optometrist. Finally, the method described in this article was used to evaluate the type of corneal topography and compare it with the type classified by the optometrist. Results When the important medical zones in the corneal topography were segmented, the precision and recall of the treatment zone reached 0.9587 and 0.9459, respectively, and the precision and recall of the pupil reached 0.9771 and 0.9712. Finally, the method described in this article was used to evaluate the type of corneal topography. When the reviewed findings based on deep learning and image processing algorithms were compared to the type of corneal topography marked by the professional optometrist, they demonstrated high accuracy with more than 98%. Conclusion The current study provided an effective and accurate deep learning algorithm to evaluate the type of corneal topography. The deep learning algorithm played an auxiliary role in the OK lens fitting, which could help optometrists select the parameters of OK lenses effectively.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    URL: Article
    DOI: 10.3389/fmed.2023.1264659
    DOI: 10.3389/fmed.2023.1264659.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2775999-4
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  • 8
    Online Resource
    Online Resource
    LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MRI for early recurrence risk stratification after curative resection
    Springer Science and Business Media LLC ; 2021
    In:  European Radiology Vol. 31, No. 4 ( 2021-04), p. 2289-2302
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 31, No. 4 ( 2021-04), p. 2289-2302
    Abstract: To explore the role of preoperative gadoxetic acid–enhanced MRI in stratifying the risk of early recurrence in patients with LR-5 hepatocellular carcinoma (HCC) by LI-RADS v2018 after curative resection. Methods Between July 2015 and August 2018, this study evaluated consecutive treatment-naïve at-risk LR-5 HCC patients who underwent gadoxetic acid–enhanced MRI examination within 2 weeks before curative resection. The Cox regression analysis was performed to identify potential predictors of early recurrence. Disease-free survival (DFS) rates were analyzed and compared by using the Kaplan-Meier method and log-rank tests. Results Fifty-three of 103 (51.5%) patients experienced early recurrence. Three MRI findings were significantly associated with early recurrence: corona enhancement (hazard ratio [HR]: 2.116; p  = 0.013), peritumoral hypointensity on hepatobiliary phase (HBP) (HR: 2.262; p  = 0.007), and satellite nodule (HR: 2.777; p  = 0.005). An additional risk factor was AFP level 〉  400 ng/mL (HR: 1.975; p  = 0.016). Based on the number of MRI predictors, LR-5 HCC patients were stratified into three subgroups: LR-5a (60/103; no predictor), LR-5b (26/103; one predictor), and LR-5c (17/103; two or three predictors), with low, medium, and high risk of early recurrence, respectively. The 2-year DFS rate of LR-5a, LR-5b, and LR-5c patients was 65.0%, 38.5%, and 5.9%, respectively, while the corresponding median DFS was undefined, 17.1 months, and 5.1 months, respectively ( p   〈  0.001). Conclusions In at-risk LR-5 HCC patients, corona enhancement, peritumoral hypointensity on HBP, and satellite nodule could be used to preoperatively stratify the risk of early recurrence after hepatectomy. Key Points • Corona enhancement, peritumoral hypointensity on HBP, satellite nodule, and serum AFP level 〉  400 ng/mL were significant predictors of early recurrence in patients with LR-5 HCC after hepatectomy. • Based on the number of predictive MRI findings, LR-5 HCC patients could be preoperatively stratified into three subgroups: LR-5a, LR-5b, and LR-5c, with significantly different risk of early recurrence and disease-free survival. • Preoperative risk stratification is essential for the identification of patients at increased risk of postoperative early recurrence, which may contribute to risk-based personalized management for LR-5 HCC patients.
    Type of Medium: Online Resource
    ISSN: 0938-7994 , 1432-1084
    URL: Article
    DOI: 10.1007/s00330-020-07303-9
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 1472718-3
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  • 9
    Online Resource
    Online Resource
    Hollow-core fiber-based mid-infrared photothermal spectroscopy for multi-component gas sensing
    Institute of Electrical and Electronics Engineers (IEEE) ; 2024
    In:  IEEE Journal of Selected Topics in Quantum Electronics
    Details
    In: IEEE Journal of Selected Topics in Quantum Electronics, Institute of Electrical and Electronics Engineers (IEEE)
    Type of Medium: Online Resource
    ISSN: 1077-260X , 1558-4542
    URL: Article
    DOI: 10.1109/JSTQE.2024.3388522
    RVK:
    UA 1000
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2024
    detail.hit.zdb_id: 2025385-0
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  • 10
    Online Resource
    Online Resource
    Ultra-thin high-efficiency mid-infrared transmissive Huygens meta-optics
    Springer Science and Business Media LLC ; 2018
    In:  Nature Communications Vol. 9, No. 1 ( 2018-04-16)
    Details
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2018-04-16)
    Abstract: The mid-infrared (mid-IR) is a strategically important band for numerous applications ranging from night vision to biochemical sensing. Here we theoretically analyzed and experimentally realized a Huygens metasurface platform capable of fulfilling a diverse cross-section of optical functions in the mid-IR. The meta-optical elements were constructed using high-index chalcogenide films deposited on fluoride substrates: the choices of wide-band transparent materials allow the design to be scaled across a broad infrared spectrum. Capitalizing on a two-component Huygens’ meta-atom design, the meta-optical devices feature an ultra-thin profile ( λ 0 /8 in thickness) and measured optical efficiencies up to 75% in transmissive mode for linearly polarized light, representing major improvements over state-of-the-art. We have also demonstrated mid-IR transmissive meta-lenses with diffraction-limited focusing and imaging performance. The projected size, weight and power advantages, coupled with the manufacturing scalability leveraging standard microfabrication technologies, make the Huygens meta-optical devices promising for next-generation mid-IR system applications.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    URL: Article
    DOI: 10.1038/s41467-018-03831-7
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
    detail.hit.zdb_id: 2553671-0
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