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  1. Book ; Online: Medicinal Plants for Cardiovascular and Neurodegenerative Aging-related Diseases: From Bench to Bedside

    Liu, Yue / Echeverria Moran, Valentina / Xu, Youhua

    2020  

    Keywords Science: general issues ; Pharmacology ; medicinal plants ; aging ; age-related diseases ; cardiovascular disease ; neurodegenerative diseases
    Size 1 electronic resource (294 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021230427
    ISBN 9782889661602 ; 2889661601
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Efficient Cross-Modality Insulator Augmentation for Multi-Domain Insulator Defect Detection in UAV Images.

    Liu, Yue / Huang, Xinbo

    Sensors (Basel, Switzerland)

    2024  Volume 24, Issue 2

    Abstract: Regular inspection of the insulator operating status is essential to ensure the safe and stable operation of the power system. Unmanned aerial vehicle (UAV) inspection has played an important role in transmission line inspection, replacing former manual ... ...

    Abstract Regular inspection of the insulator operating status is essential to ensure the safe and stable operation of the power system. Unmanned aerial vehicle (UAV) inspection has played an important role in transmission line inspection, replacing former manual inspection. With the development of deep learning technologies, deep learning-based insulator defect detection methods have drawn more and more attention and gained great improvement. However, former insulator defect detection methods mostly focus on designing complex refined network architecture, which will increase inference complexity in real applications. In this paper, we propose a novel efficient cross-modality insulator augmentation algorithm for multi-domain insulator defect detection to mimic real complex scenarios. It also alleviates the overfitting problem without adding the inference resources. The high-resolution insulator cross-modality translation (HICT) module is designed to generate multi-modality insulator images with rich texture information to eliminate the adverse effects of existing modality discrepancy. We propose the multi-domain insulator multi-scale spatial augmentation (MMA) module to simultaneously augment multi-domain insulator images with different spatial scales and leverage these fused images and location information to help the target model locate defects with various scales more accurately. Experimental results prove that the proposed cross-modality insulator augmentation algorithm can achieve superior performance in public UPID and SFID insulator defect datasets. Moreover, the proposed algorithm also gives a new perspective for improving insulator defect detection precision without adding inference resources, which is of great significance for advancing the detection of transmission lines.
    Language English
    Publishing date 2024-01-10
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s24020428
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Flexible gating between subspaces by a disinhibitory motif: a neural network model of internally guided task switching.

    Liu, Yue / Wang, Xiao-Jing

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. ...

    Abstract Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks' dynamical trajectories for different rules reside in separate subspaces of population activity; they become virtually identical and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, demonstrating that rule-based gating critically depends on the disinhibitory motif.
    Language English
    Publishing date 2024-01-28
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.08.15.553375
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: MARR-GAN: Memristive Attention Recurrent Residual Generative Adversarial Network for Raindrop Removal.

    Chai, Qiuyue / Liu, Yue

    Micromachines

    2024  Volume 15, Issue 2

    Abstract: Since machine learning techniques for raindrop removal have not been capable of completely removing raindrops and have failed to take into account the constraints of edge devices with limited resources, a novel software-hardware co-designed method with a ...

    Abstract Since machine learning techniques for raindrop removal have not been capable of completely removing raindrops and have failed to take into account the constraints of edge devices with limited resources, a novel software-hardware co-designed method with a memristor for raindrop removal, named memristive attention recurrent residual generative adversarial network (MARR-GAN), is introduced in this research. A novel raindrop-removal network is specifically designed based on attention gate connections and recurrent residual convolutional blocks. By replacing the basic convolution unit with recurrent residual convolution unit, improved capturing of the changes in raindrop appearance over time is achieved, while preserving the position and shape information in the image. Additionally, an attention gate is utilized instead of the original skip connection to enhance the overall structural understanding and local detail preservation, facilitating a more comprehensive removal of raindrops across various areas of the image. Furthermore, a hardware implementation scheme for MARR-GAN is presented in this paper, where deep learning algorithms are seamlessly integrated with neuro inspired computing chips, utilizing memristor crossbar arrays for accelerated real-time image-data processing. Compelling evidence of the efficacy and superiority of MARR-GAN in raindrop removal and image restoration is provided by the results of the empirical study.
    Language English
    Publishing date 2024-01-31
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2620864-7
    ISSN 2072-666X
    ISSN 2072-666X
    DOI 10.3390/mi15020217
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Thesis ; Online: Good things come in small packages

    Liu, Yue

    delivery of vitamin K2 to human cells by extracellular vesicles from Lactococcus lactis

    2022  

    Abstract: Vitamin K2 is essential for maintaining human health. It is required for blood coagulation and contributes to cardiovascular and bone health. Therefore, vitamin K2 enrichment in the diet is of high interest for human health. Bacteria are the natural ... ...

    Abstract Vitamin K2 is essential for maintaining human health. It is required for blood coagulation and contributes to cardiovascular and bone health. Therefore, vitamin K2 enrichment in the diet is of high interest for human health. Bacteria are the natural producers of vitamin K2, and known producers such as Lactococcus lactis are key players in the production of fermented foods. This fact offers opportunities to enhance vitamin K2 levels in food. Knowledge on vitamin K2 production in L. lactis is important for vitamin K2 enriched in fermented foods (a background introduction is provided in chapter 1).In this thesis study, initially, L. lactis strains were screened for vitamin K2 content, and the impact of various cultivation conditions was examined (chapter 3). It was observed that significant strain diversity existed in terms of specific concentrations and titers of vitamin K2. In L. lactis ssp. cremoris MG1363, aerated cultivation conditions and carbon sources like fructose or trehalose, were found to increase the vitamin K2 content as compared to static cultivation and glucose as carbon source. In quark fermentation, it was consistently observed that altered carbon source (fructose) and aerobic cultivation of the L. lactis MG1363 pre-culture resulted in elevated vitamin K2 concentrations in the quark product.Next, an adaptive laboratory evolution (ALE) strategy was applied to obtain natural vitamin K2 overproducing L. lactis strains (chapter 4). By propagating strain MG1363 in aerated conditions, Three evolved strains were selected that showed improved stationary phase survival in oxygenated conditions. In comparison to the original strain MG1363, the evolved strains showed increased vitamin K2 content and exhibited high resistance against hydrogen peroxide-induced oxidative stress. Genome sequencing and proteomic analysis provided explanations for the enhanced oxidative stress resistance, but the mechanisms underlying elevated vitamin K2 content in the evolved strains remain to be elucidated.Besides the long-chain ...
    Keywords cum laude
    Subject code 500
    Language English
    Publisher Wageningen University
    Publishing country nl
    Document type Thesis ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article: Artificial Intelligence-Based Neural Network for the Diagnosis of Diabetes: Model Development.

    Liu, Yue

    JMIR medical informatics

    2020  Volume 8, Issue 5, Page(s) e18682

    Abstract: Background: The incidence of diabetes is increasing in China, and its impact on national health cannot be ignored. Smart medicine is a medical model that uses technology to assist the diagnosis and treatment of disease.: Objective: The aim of this ... ...

    Abstract Background: The incidence of diabetes is increasing in China, and its impact on national health cannot be ignored. Smart medicine is a medical model that uses technology to assist the diagnosis and treatment of disease.
    Objective: The aim of this paper was to apply artificial intelligence (AI) in the diagnosis of diabetes.
    Methods: We established an AI diagnostic model in the MATLAB software platform based on a backpropagation neural network by collecting data for the cases of integration and extraction and selecting an input feature vector. Based on this diagnostic model, using an intelligent combination of the LabVIEW development platform and the MATLAB software-designed diabetes diagnosis system with user data, we called the neural network diagnostic module to correctly diagnose diabetes.
    Results: Compared to conventional diagnostic procedures, the system can effectively improve diagnostic efficiency and save time for physicians.
    Conclusions: The development of AI applications has utility to aid diabetes diagnosis.
    Language English
    Publishing date 2020-05-27
    Publishing country Canada
    Document type Journal Article
    ZDB-ID 2798261-0
    ISSN 2291-9694
    ISSN 2291-9694
    DOI 10.2196/18682
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Barriers to Transportation in Rural Communities: Perspective of Older Adult Users.

    Yu, Jie / Liu, Yue

    The journals of gerontology. Series B, Psychological sciences and social sciences

    2023  Volume 79, Issue 1

    Abstract: Objectives: Rural older adults who require transportation assistance face more challenges than their urban counterparts. By focusing on a historically underserved population, this study examined specific barriers from the perspective of older adult ... ...

    Abstract Objectives: Rural older adults who require transportation assistance face more challenges than their urban counterparts. By focusing on a historically underserved population, this study examined specific barriers from the perspective of older adult users and explored potential policy and technology solutions.
    Methods: A cross-sectional study was conducted throughout rural Wisconsin to identify specific barriers to transportation, uncover personal factors associated with identified barriers, and measure causal relationships between identified barriers and travel satisfaction.
    Results: A total of 580 older adult respondents from 92% of rural counties across the state provided clear answers regarding specific transportation barriers. Of these, 67.6% identified at least one barrier, but only 12.8% had stopped using transportation due to any identified barriers. Top barriers to accessing transportation included service hours, service areas, trip destinations, getting in/out of service vehicles, service reservations, and operational scheduling. Although specific barriers were associated with different sociodemographics, trip purposes, and frequency of transportation usage, logistic regression findings suggested that concerns about service hours, service areas, and service reservation were the only 3 major determinants driving rural older adults' attitudes toward transportation usage.
    Discussion: Rural older adults relying on transportation assistance have demonstrated diverse needs and constraints. Rural transportation could provide better support by extending service availability in terms of hours, areas, and destinations, improving door-to-door accessibility by providing "arm through arm" services, enhancing service responsiveness and reliability via age-friendly technology solutions, and implementing a sliding scale subsidy program that takes income level and trip frequency into account.
    MeSH term(s) Humans ; Aged ; Health Services Accessibility ; Rural Population ; Cross-Sectional Studies ; Reproducibility of Results ; Transportation
    Language English
    Publishing date 2023-09-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1223664-0
    ISSN 1758-5368 ; 1079-5014
    ISSN (online) 1758-5368
    ISSN 1079-5014
    DOI 10.1093/geronb/gbad135
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Learning styles of medical students from a university in China.

    Liu, Hai-Ping / Liu, Yue-Hui

    BMC medical education

    2023  Volume 23, Issue 1, Page(s) 237

    Abstract: Background: Investigating students' learning styles can generate useful information that can improve curriculum design. This study adopts diverse measures to identify the learning styles of students despite limited literature related to clinical medical ...

    Abstract Background: Investigating students' learning styles can generate useful information that can improve curriculum design. This study adopts diverse measures to identify the learning styles of students despite limited literature related to clinical medical students in China. We utilized Felder's Index of Learning Styles to examine the learning style characteristics of clinical medical students at Inner Mongolia Minzu University.
    Methods: Cluster sampling (probability sampling) was used. This cross-sectional study investigated clinical medicine students with regard to their learning style preference and the difference across genders. This study also analysed data collected from other published studies. A total of 411 students from the medical school at Inner Mongolia Minzu University completed the Index of Learning Styles Questionnaire. The questionnaire assessed the learning styles of students in four dimensions: visual-verbal learning, sequential-global learning, active-reflective leaning, and sensing-intuitive learning.
    Results: The analysis results show that clinical medicine students choose to receive visual information (73.97% of the student sample) instead of verbal information. These students prioritize sensory information (67.15%) rather than intuitive information and process reflective information (51.82%) rather than active information. They prefer to process information sequentially (59.85%) instead of globally. Our results also show that male students present a higher preference for an active learning style over a reflective learning style, while female students seem to present a higher preference for a reflective learning style over an active learning style. These preferences vary between cohorts (gender), but the difference is not statistically significant. Compared to data collected from other published studies, active, visual, sensing, and sequential are the most popular styles of learning adopted by medical science students.
    Conclusions: The identification of medical students' learning style in China provides information that medical educators and others can use to make informed choices about modification, development and strengthening of medical educational programs. Our outcomes may potentially improve motivation, engagement and deep learning in medical education when used as a supplement to teaching/learning activities.
    MeSH term(s) Humans ; Male ; Female ; Students, Medical ; Universities ; Cross-Sectional Studies ; Cognition ; Surveys and Questionnaires ; China
    Language English
    Publishing date 2023-04-12
    Publishing country England
    Document type Journal Article
    ZDB-ID 2044473-4
    ISSN 1472-6920 ; 1472-6920
    ISSN (online) 1472-6920
    ISSN 1472-6920
    DOI 10.1186/s12909-023-04222-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Application of quantitative orbital analysis to assess the activity of Graves' ophthalmopathy.

    Li, Shuang / Liu, Yue-Jun

    American journal of nuclear medicine and molecular imaging

    2023  Volume 13, Issue 6, Page(s) 259–268

    Abstract: This study aimed to evaluate the diagnostic value of uptake ratios in the extraocular muscles (EOMs), lacrimal glands, and optic nerves to detect the inflammation activity of Graves' ophthalmopathy (GO) using quantitative analysis of 99m technetium ( ...

    Abstract This study aimed to evaluate the diagnostic value of uptake ratios in the extraocular muscles (EOMs), lacrimal glands, and optic nerves to detect the inflammation activity of Graves' ophthalmopathy (GO) using quantitative analysis of 99m technetium (
    Language English
    Publishing date 2023-12-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2623515-8
    ISSN 2160-8407
    ISSN 2160-8407
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Sacral endometriosis.

    Liu, Yue / Lan, Haitao

    American journal of obstetrics and gynecology

    2023  Volume 229, Issue 1, Page(s) 69

    MeSH term(s) Female ; Humans ; Endometriosis/surgery ; Sacrococcygeal Region ; Laparoscopy
    Language English
    Publishing date 2023-01-12
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80016-8
    ISSN 1097-6868 ; 0002-9378
    ISSN (online) 1097-6868
    ISSN 0002-9378
    DOI 10.1016/j.ajog.2023.01.009
    Database MEDical Literature Analysis and Retrieval System OnLINE

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