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  1. Article: The role of pre-service physical education teachers in physical education - A bibliometric and systematic review.

    Zhou, Tong

    Heliyon

    2024  Volume 10, Issue 7, Page(s) e28702

    Abstract: Pre-service physical education teachers (PSPTs) have long been an important area of specific development in physical education and have become a significant force in the field of physical education and research over the past two decades. However, ... ...

    Abstract Pre-service physical education teachers (PSPTs) have long been an important area of specific development in physical education and have become a significant force in the field of physical education and research over the past two decades. However, exploratory research on pre-service teachers remains relatively scarce, and lack a comprehensive scientific exploration of the scope of their role. Therefore, this study provides a comprehensive overview of pre-service physical education teacher education (PETE) from both a broad and specific perspective. Specifically, it includes the current state of PETE, the most influential authors, countries, journals, and literature, as well as specific research topics and future directions within PETE. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, a total of 340 articles were included, with 84 of them being empirical studies. The findings reveal that teacher training, diversity, equity, and inclusion in education, educational attitudes and beliefs, educational quality, educational methods and technology, career motivation, teaching models and strategies, and teacher assessment and reflection are major research themes. Visual analysis of the application of pre-service physical education teacher research highlights teacher training, diversity, equity, and inclusion in education, as well as instructional technology, as key areas of future focus. These insights contribute to the reasonable application of bibliometrics in the field of pre-service physical education teacher research.
    Language English
    Publishing date 2024-03-28
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e28702
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Multi-granulariy Time-based Transformer for Knowledge Tracing

    Zhou, Tong

    2023  

    Abstract: In this paper, we present a transformer architecture for predicting student performance on standardized tests. Specifically, we leverage students historical data, including their past test scores, study habits, and other relevant information, to create a ...

    Abstract In this paper, we present a transformer architecture for predicting student performance on standardized tests. Specifically, we leverage students historical data, including their past test scores, study habits, and other relevant information, to create a personalized model for each student. We then use these models to predict their future performance on a given test. Applying this model to the RIIID dataset, we demonstrate that using multiple granularities for temporal features as the decoder input significantly improve model performance. Our results also show the effectiveness of our approach, with substantial improvements over the LightGBM method. Our work contributes to the growing field of AI in education, providing a scalable and accurate tool for predicting student outcomes.
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
    Publishing date 2023-04-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Nonparametric Identification and Estimation of Earnings Dynamics using a Hidden Markov Model

    Zhou, Tong

    Evidence from the PSID

    2023  

    Abstract: This paper presents a hidden Markov model designed to investigate the complex nature of earnings persistence. The proposed model assumes that the residuals of log-earnings consist of a persistent component and a transitory component, both following ... ...

    Abstract This paper presents a hidden Markov model designed to investigate the complex nature of earnings persistence. The proposed model assumes that the residuals of log-earnings consist of a persistent component and a transitory component, both following general Markov processes. Nonparametric identification is achieved through spectral decomposition of linear operators, and a modified stochastic EM algorithm is introduced for model estimation. Applying the framework to the Panel Study of Income Dynamics (PSID) dataset, we find that the earnings process displays nonlinear persistence, conditional skewness, and conditional kurtosis. Additionally, the transitory component is found to possess non-Gaussian properties, resulting in a significantly asymmetric distributional impact when high-earning households face negative shocks or low-earning households encounter positive shocks. Our empirical findings also reveal the presence of ARCH effects in earnings at horizons ranging from 2 to 8 years, further highlighting the complex dynamics of earnings persistence.
    Keywords Statistics - Applications ; Computer Science - Artificial Intelligence
    Subject code 310
    Publishing date 2023-05-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Improved Sales Forecasting using Trend and Seasonality Decomposition with LightGBM

    Zhou, Tong

    2023  

    Abstract: Retail sales forecasting presents a significant challenge for large retailers such as Walmart and Amazon, due to the vast assortment of products, geographical location heterogeneity, seasonality, and external factors including weather, local economic ... ...

    Abstract Retail sales forecasting presents a significant challenge for large retailers such as Walmart and Amazon, due to the vast assortment of products, geographical location heterogeneity, seasonality, and external factors including weather, local economic conditions, and geopolitical events. Various methods have been employed to tackle this challenge, including traditional time series models, machine learning models, and neural network mechanisms, but the difficulty persists. Categorizing data into relevant groups has been shown to improve sales forecast accuracy as time series from different categories may exhibit distinct patterns. In this paper, we propose a new measure to indicate the unique impacts of the trend and seasonality components on a time series and suggest grouping time series based on this measure. We apply this approach to Walmart sales data from 01/29/2011 to 05/22/2016 and generate sales forecasts from 05/23/2016 to 06/19/2016. Our experiments show that the proposed strategy can achieve improved accuracy. Furthermore, we present a robust pipeline for conducting retail sales forecasting.
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
    Subject code 330
    Publishing date 2023-05-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: Frequency Domain Identifiability and Sloppiness of Descriptor Systems with an LFT Structure

    Zhou, Tong

    2022  

    Abstract: Identifiability and sloppiness are investigated in this paper for the parameters of a descriptor system based on its frequency response samples. Two metrics are suggested respectively for measuring absolute and relative sloppiness of the parameter vector ...

    Abstract Identifiability and sloppiness are investigated in this paper for the parameters of a descriptor system based on its frequency response samples. Two metrics are suggested respectively for measuring absolute and relative sloppiness of the parameter vector at a prescribed value. In this descriptor system, system matrices are assumed to depend on its parameters through a linear fractional transformation (LFT). When an associated transfer function matrix (TFM) is of full normal row rank, a matrix rank based necessary and sufficient condition is derived for parameter identifiability with a set of finitely many frequency responses. This condition can be verified recursively which is computationally quite appealing, especially when the system is of a large scale. From this condition, an algorithm is suggested to find a set of frequencies with which the frequency responses of the system are capable to uniquely determine its parameters. An ellipsoid approximation is given for the set consisting of all the parameter values with which the associated descriptor system has a frequency response that deviates within a prescribed distance, from that corresponding to a globally identifiable parameter vector value. Explicit formulas are also derived for the suggested absolute and relative sloppiness metrics.

    Comment: 14 pages
    Keywords Electrical Engineering and Systems Science - Systems and Control ; Mathematics - Optimization and Control ; Quantitative Biology - Molecular Networks
    Subject code 515
    Publishing date 2022-06-21
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Experimental study on the effect of foam in preventing gas channeling in shale reservoir

    Xiong Xiaofei / Wang Haibo / Li Fengxia / Zhou Tong

    Frontiers in Earth Science, Vol

    2024  Volume 11

    Abstract: Shale oil resources have enormous potential and broad development prospects in China. Especially with the rapid development of horizontal well volume fracturing technology, the production of shale oil has been greatly increased, and it has become an ... ...

    Abstract Shale oil resources have enormous potential and broad development prospects in China. Especially with the rapid development of horizontal well volume fracturing technology, the production of shale oil has been greatly increased, and it has become an important position to increase oil and gas storage and production. However, due to the existence of artificial and natural fractures produced by fracturing, gas channeling will occur in the process of huff-n-puff gas injection, which will affect the production and lead to poor development effect. In this paper, foam is used as an anti-channeling agent in the process of huff-n-puff gas injection. The results of microfluidic experiments show that the production mode of foam in porous media is liquid membrane hysteresis and liquid membrane separation. In porous media, foam first blocks large channels such as fractures, and then enters the matrix. The oil recovery mechanism of foam assisted gas injection in porous media is to improve the sweep efficiency and oil displacement efficiency of gas. Compared with N2 huff-n-puff, the oil recovery of the first cycle of foam assisted N2 huff-n-puff increased by 4.50%, and the third cycle increased by 9.58%. It is proved that foam has good anti channeling effect in gas huff-n-puff injection process. The research results provide an effective method for efficient gas injection development of shale oil.
    Keywords gas huff-n-puff ; foam ; gas channeling ; shale reservoir ; oil recovery ; Science ; Q
    Subject code 660 ; 600
    Language English
    Publishing date 2024-01-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Emerging functional principles of tRNA-derived small RNAs and other regulatory small RNAs.

    Chen, Qi / Zhou, Tong

    The Journal of biological chemistry

    2023  Volume 299, Issue 10, Page(s) 105225

    Abstract: Recent advancements in small RNA sequencing have unveiled a previously hidden world of regulatory small noncoding RNAs (sncRNAs) that extend beyond the well-studied small interfering RNAs, microRNAs, and piwi-interacting RNAs. This exploration, starting ... ...

    Abstract Recent advancements in small RNA sequencing have unveiled a previously hidden world of regulatory small noncoding RNAs (sncRNAs) that extend beyond the well-studied small interfering RNAs, microRNAs, and piwi-interacting RNAs. This exploration, starting with tRNA-derived small RNAs, has led to the discovery of a diverse universe of sncRNAs derived from various longer structured RNAs such as rRNAs, small nucleolar RNAs, small nuclear RNAs, Y RNAs, and vault RNAs, with exciting uncharted functional possibilities. In this perspective, we discuss the emerging functional principles of sncRNAs beyond the well-known RNAi-like mechanisms, focusing on those that operate independent of linear sequence complementarity but rather function in an aptamer-like fashion. Aptamers use 3D structure for specific interactions with ligands and are modulated by RNA modifications and subcellular environments. Given that aptamer-like sncRNA functions are widespread and present in species lacking RNAi, they may represent an ancient functional principle that predates RNAi. We propose a rethinking of the origin of RNAi and its relationship with these aptamer-like functions in sncRNAs and how these complementary mechanisms shape biological processes. Lastly, the aptamer-like function of sncRNAs highlights the need for caution in using small RNA mimics in research and therapeutics, as their specificity is not restricted solely to linear sequence.
    Language English
    Publishing date 2023-09-09
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2997-x
    ISSN 1083-351X ; 0021-9258
    ISSN (online) 1083-351X
    ISSN 0021-9258
    DOI 10.1016/j.jbc.2023.105225
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Asymmetry in the magnetic neighbourhood.

    Zhou, Tong / Žutić, Igor

    Nature materials

    2023  Volume 22, Issue 3, Page(s) 284–285

    Language English
    Publishing date 2023-01-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 2088679-2
    ISSN 1476-4660 ; 1476-1122
    ISSN (online) 1476-4660
    ISSN 1476-1122
    DOI 10.1038/s41563-022-01466-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: A review: Mechanisms and molecular pathways of signaling lymphocytic activation molecule family 3 (SLAMF3) in immune modulation and therapeutic prospects.

    Zhou, Tong / Guan, Yanjie / Sun, Lin / Liu, Wentao

    International immunopharmacology

    2024  Volume 133, Page(s) 112088

    Abstract: The signaling lymphocytic activation molecule (SLAM) family participates in the modulation of various innate and adaptive immune responses. SLAM family (SLAMF) receptors include nine transmembrane glycoproteins, of which SLAMF3 (also known as CD229 or ... ...

    Abstract The signaling lymphocytic activation molecule (SLAM) family participates in the modulation of various innate and adaptive immune responses. SLAM family (SLAMF) receptors include nine transmembrane glycoproteins, of which SLAMF3 (also known as CD229 or Ly9) has important roles in the modulation of immune responses, from the fundamental activation and suppression of immune cells to the regulation of intricate immune networks. SLAMF3 is mainly expressed in immune cells, such as T, B, and natural killer cells. It has a unique molecular structure, including four immunoglobulin-like domains in the extracellular domain and two immunoreceptor tyrosine-based signaling motifs in the intracellular structural domains. These unique structures have important implications for protein functioning. SLAMF3 is involved in pathogenesis of various disease, particularly autoimmune diseases and cancer. However, despite its potential clinical significance, a comprehensive overview of the current paradigm of SLAMF3 research is lacking. This review summarizes the structure, functional mechanisms, and therapeutic implications of SLAMF3. Our findings highlight the significance of SLAMF3 in both physiological and pathological contexts, and underline its dual role in autoimmunity and malignancies, and including disease progression and prognosis. The review also proposes that future studies on SLAMF3 should explore its context-specific inhibitory and stimulatory effects, expand on its potential in disease mapping, investigate related signaling pathways, and explore its value as a drug target. Research in these areas related to SLAMF3 can provide more precise directions for future therapeutic strategies.
    MeSH term(s) Humans ; Signaling Lymphocytic Activation Molecule Family/metabolism ; Signaling Lymphocytic Activation Molecule Family/genetics ; Signaling Lymphocytic Activation Molecule Family/immunology ; Animals ; Signal Transduction ; Neoplasms/immunology ; Neoplasms/therapy ; Neoplasms/metabolism ; Autoimmune Diseases/immunology ; Autoimmune Diseases/therapy
    Chemical Substances Signaling Lymphocytic Activation Molecule Family ; LY9 protein, human
    Language English
    Publishing date 2024-04-15
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 2043785-7
    ISSN 1878-1705 ; 1567-5769
    ISSN (online) 1878-1705
    ISSN 1567-5769
    DOI 10.1016/j.intimp.2024.112088
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Book ; Online: Identification of Secondary Resonances of Nonlinear Systems using Phase-Locked Loop Testing

    Zhou, Tong / Kerschen, Gaetan

    2024  

    Abstract: One unique feature of nonlinear dynamical systems is the existence of superharmonic and subharmonic resonances in addition to primary resonances. In this study, an effective vibration testing methodology is introduced for the experimental identification ... ...

    Abstract One unique feature of nonlinear dynamical systems is the existence of superharmonic and subharmonic resonances in addition to primary resonances. In this study, an effective vibration testing methodology is introduced for the experimental identification of these secondary resonances. The proposed method relies on phase-locked loop control combined with adaptive filters for online Fourier decomposition. To this end, the concept of a resonant phase lag is exploited to define the target phase lag to be followed during the experimental continuation process. The method is demonstrated using two systems featuring cubic nonlinearities, namely a numerical Duffing oscillator and a physical experiment comprising a clamped-clamped thin beam. The obtained results highlight that the control scheme can accurately characterize secondary resonances as well as track their backbone curves. A particularly salient feature of the developed algorithm is that, starting from the rest position, it facilitates an automatic and smooth dynamic state transfer toward one point of a subharmonic isolated branch, hence, inducing branch switching.

    Comment: 20 pages, 24 figures
    Keywords Electrical Engineering and Systems Science - Systems and Control ; Physics - Applied Physics
    Publishing date 2024-01-02
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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