350 research outputs found

    Testing Measurement Invariance with Ordinal Missing Data: A Comparison of Estimators and Missing Data Techniques

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    Ordinal missing data are common in measurement equivalence/invariance (ME/I) testing studies. However, there is a lack of guidance on the appropriate method to deal with ordinal missing data in ME/I testing. Five methods may be used to deal with ordinal missing data in ME/I testing, including the continuous full information maximum likelihood estimation method (FIML), continuous robust FIML (rFIML), FIML with probit links (pFIML), FIML with logit links (lFIML), and mean and variance adjusted weight least squared estimation method combined with pairwise deletion (WLSMV_PD). The current study evaluates the relative performance of these methods in producing valid chi-square difference tests (Δχ2) and accurate parameter estimates. The result suggests that all methods except for WLSMV_PD can reasonably control the type I error rates of (Δχ2) tests and maintain sufficient power to detect noninvariance in most conditions. Only pFIML and lFIML yield accurate factor loading estimates and standard errors across all the conditions. Recommendations are provided to researchers based on the results

    A Comprehensive Python Library for Deep Learning-Based Event Detection in Multivariate Time Series Data and Information Retrieval in NLP

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    Event detection in time series data is crucial in various domains, including finance, healthcare, cybersecurity, and science. Accurately identifying events in time series data is vital for making informed decisions, detecting anomalies, and predicting future trends. Despite extensive research exploring diverse methods for event detection in time series, with deep learning approaches being among the most advanced, there is still room for improvement and innovation in this field. In this paper, we present a new deep learning supervised method for detecting events in multivariate time series data. Our method combines four distinct novelties compared to existing deep-learning supervised methods. Firstly, it is based on regression instead of binary classification. Secondly, it does not require labeled datasets where each point is labeled; instead, it only requires reference events defined as time points or intervals of time. Thirdly, it is designed to be robust by using a stacked ensemble learning meta-model that combines deep learning models, ranging from classic feed-forward neural networks (FFNs) to state-of-the-art architectures like transformers. This ensemble approach can mitigate individual model weaknesses and biases, resulting in more robust predictions. Finally, to facilitate practical implementation, we have developed a Python package to accompany our proposed method. The package, called eventdetector-ts, can be installed through the Python Package Index (PyPI). In this paper, we present our method and provide a comprehensive guide on the usage of the package. We showcase its versatility and effectiveness through different real-world use cases from natural language processing (NLP) to financial security domains.Comment: 2023 International Conference on Machine Learning and Applications (ICMLA

    Event Detection in Time Series: Universal Deep Learning Approach

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    Event detection in time series is a challenging task due to the prevalence of imbalanced datasets, rare events, and time interval-defined events. Traditional supervised deep learning methods primarily employ binary classification, where each time step is assigned a binary label indicating the presence or absence of an event. However, these methods struggle to handle these specific scenarios effectively. To address these limitations, we propose a novel supervised regression-based deep learning approach that offers several advantages over classification-based methods. Our approach, with a limited number of parameters, can effectively handle various types of events within a unified framework, including rare events and imbalanced datasets. We provide theoretical justifications for its universality and precision and demonstrate its superior performance across diverse domains, particularly for rare events and imbalanced datasets.Comment: To be submitted to ICML 202

    Nonlinear dynamics of waves and modulated waves in 1D thermocapillary flows. I: General presentation and periodic solutions

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    We present experimental results on hydrothermal traveling-waves dynamics in long and narrow 1D channels. The onset of primary traveling-wave patterns is briefly presented for different fluid heights and for annular or bounded channels, i.e., within periodic or non-periodic boundary conditions. For periodic boundary conditions, by increasing the control parameter or changing the discrete mean-wavenumber of the waves, we produce modulated waves patterns. These patterns range from stable periodic phase-solutions, due to supercritical Eckhaus instability, to spatio-temporal defect-chaos involving traveling holes and/or counter-propagating-waves competition, i.e., traveling sources and sinks. The transition from non-linearly saturated Eckhaus modulations to transient pattern-breaks by traveling holes and spatio-temporal defects is documented. Our observations are presented in the framework of coupled complex Ginzburg-Landau equations with additional fourth and fifth order terms which account for the reflection symmetry breaking at high wave-amplitude far from onset. The second part of this paper (nlin.PS/0208030) extends this study to spatially non-periodic patterns observed in both annular and bounded channel.Comment: 45 pages, 21 figures (elsart.cls + AMS extensions). Accepted in Physica D. See also companion paper "Nonlinear dynamics of waves and modulated waves in 1D thermocapillary flows. II: Convective/absolute transitions" (nlin.PS/0208030). A version with high resolution figures is available on N.G. web pag

    EB1 regulates microtubule dynamics and tubulin sheet closure in vitro.

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    International audienceEnd binding 1 (EB1) is a plus-end-tracking protein (+TIP) that localizes to microtubule plus ends where it modulates their dynamics and interactions with intracellular organelles. Although the regulating activity of EB1 on microtubule dynamics has been studied in cells and purified systems, the molecular mechanisms involved in its specific activity are still unclear. Here, we describe how EB1 regulates the dynamics and structure of microtubules assembled from pure tubulin. We found that EB1 stimulates spontaneous nucleation and growth of microtubules, and promotes both catastrophes (transitions from growth to shrinkage) and rescues (reverse events). Electron cryomicroscopy showed that EB1 induces the initial formation of tubulin sheets, which rapidly close into the common 13-protofilament-microtubule architecture. Our results suggest that EB1 favours the lateral association of free tubulin at microtubule-sheet edges, thereby stimulating nucleation, sheet growth and closure. The reduction of sheet length at microtubule growing-ends together with the elimination of stressed microtubule lattices may account for catastrophes. Conversely, occasional binding of EB1 to the microtubule lattice may induce rescues

    Capability of Neutrophils to Form NETs Is Not Directly Influenced by a CMA-Targeting Peptide

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    During inflammatory reaction, neutrophils exhibit numerous cellular and immunological functions, notably the formation of neutrophil extracellular traps (NETs) and autophagy. NETs are composed of decondensed chromatin fibers coated with various antimicrobial molecules derived from neutrophil granules. NETs participate in antimicrobial defense and can also display detrimental roles and notably trigger some of the immune features of systemic lupus erythematosus (SLE) and other autoimmune diseases. Autophagy is a complex and finely regulated mechanism involved in the cell survival/death balance that may be connected to NET formation. To shed some light on the connection between autophagy and NET formation, we designed a number of experiments in human neutrophils and both in normal and lupus-prone MRL/lpr mice to determine whether the synthetic peptide P140, which is capable of selectively modulating chaperone-mediated autophagy (CMA) in lymphocytes, could alter NET formation. P140/Lupuzor™ is currently being evaluated in phase III clinical trials involving SLE patients. Overall our in vitro and in vivo studies established that P140 does not influence NET formation, cytokine/chemokine production, or CMA in neutrophils. Thus, the beneficial effect of P140/Lupuzor™ in SLE is apparently not directly related to modulation of neutrophil function

    Capability of Neutrophils to Form NETs Is Not Directly Influenced by a CMA-Targeting Peptide

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    During inflammatory reaction, neutrophils exhibit numerous cellular and immunological functions, notably the formation of neutrophil extracellular traps (NETs) and autophagy. NETs are composed of decondensed chromatin fibers coated with various antimicrobial molecules derived from neutrophil granules. NETs participate in antimicrobial defense and can also display detrimental roles and notably trigger some of the immune features of systemic lupus erythematosus (SLE) and other autoimmune diseases. Autophagy is a complex and finely regulated mechanism involved in the cell survival/death balance that may be connected to NET formation. To shed some light on the connection between autophagy and NET formation, we designed a number of experiments in human neutrophils and both in normal and lupus-prone MRL/lpr mice to determine whether the synthetic peptide P140, which is capable of selectively modulating chaperone-mediated autophagy (CMA) in lymphocytes, could alter NET formation. P140/Lupuzor™ is currently being evaluated in phase III clinical trials involving SLE patients. Overall our in vitro and in vivo studies established that P140 does not influence NET formation, cytokine/chemokine production, or CMA in neutrophils. Thus, the beneficial effect of P140/Lupuzor™ in SLE is apparently not directly related to modulation of neutrophil function

    Determinants of low bone mineral density in people with multiple sclerosis: Role of physical activity

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    Background People with multiple sclerosis (PwMS) have reduced bone mineral density (BMD), but the causes are unclear. Some factors that may cause reduced BMD in PwMS have been understudied, including physical activity, inflammation, cortisol, symptomatic fatigue, and depression. The aim of this study was to investigate factors that may uniquely contribute to reduced BMD in PwMS as compared to people without MS. We hypothesized that physical activity would be the primary determinant of low BMD in PwMS, with additional contributions from inflammation and sympathetic nervous system activation. Methods We tested 23 PwMS (16 women; median EDSS: 2) and 22 control participants (16 women). BMD was measured from the femoral neck and lumbar spine with dual x-ray absorptiometry. Disability was measured with the Expanded Disability Status Scale, and functional capacity was measured with the Multiple Sclerosis Functional Composite. Questionnaires measured symptomatic fatigue and depression. A blood draw was used to measure calcium, phosphate, vitamin D, N-terminal telopeptide, osteopontin, and cytokine markers of inflammation. Physical activity was measured with accelerometry. Salivary cortisol and cardiac heart rate variability also were obtained. All outcome variables were compared between groups with independent samples t-tests. Variables that were different between groups and significantly correlated (Pearson product-moment) with femoral neck BMD, were included in a theoretical model to explain femoral neck BMD. The expected direction of relations in the theoretical model were developed based upon the results of previous research. A Bayesian path analysis was used to test the relations of predictive variables with femoral neck BMD and interrelations among predictive variables, as detailed in the theoretical model. Results PwMS had lower BMD at the femoral neck than controls (p = =0.04; mean difference: -0.09; 95% CI: -0.2, -0.004; Cohen\u27s d = =0.65), and there was a smaller, statistically non-significant difference in BMD at the lumbar spine (p = =0.07; mean difference: -0.08; 95% CI: -0.17, 0.007; Cohen\u27s d = =0.59). PwMS also had lower functional capacity (p ≤ 0.001; Cohen\u27s d = =1.50), greater fatigue (pd = =1.88), greater depression (pd = =1.31), and decreased physical activity (p = =0.03; Cohen\u27s d = =0.62). Using path analysis to test our theoretical model, we found that disability (standardized estimate= -0.17), physical activity (standardized estimate=0.39), symptomatic fatigue (standardized estimate= -0.36), depression (standardized estimate= -0.30), and inflammatory markers (standardized estimate=0.27) explained 51% of the variance in femoral neck BMD. Inflammatory markers were also predictive of disability (standardized estimate=0.44) and physical activity (standardized estimate= -0.40). Symptomatic fatigue and depression were correlated (r = =0.64). Conclusion Physical activity, symptomatic fatigue, depression, disability, and inflammation all contributed independently to decreased femoral neck BMD in PWMS. Bone metabolism in PwMS is complex. Efforts to increase physical activity and address symptomatic fatigue and depression may improve bone mineral density in PwMS. Future research should investigate the mechanisms through which symptomatic fatigue and depression contribute to reduced BMD in PwMS

    Capability of Neutrophils to Form NETs Is Not Directly Influenced by a CMA-Targeting Peptide

    Get PDF
    During inflammatory reaction, neutrophils exhibit numerous cellular and immunological functions, notably the formation of neutrophil extracellular traps (NETs) and autophagy. NETs are composed of decondensed chromatin fibers coated with various antimicrobial molecules derived from neutrophil granules. NETs participate in antimicrobial defense and can also display detrimental roles and notably trigger some of the immune features of systemic lupus erythematosus (SLE) and other autoimmune diseases. Autophagy is a complex and finely regulated mechanism involved in the cell survival/death balance that may be connected to NET formation. To shed some light on the connection between autophagy and NET formation, we designed a number of experiments in human neutrophils and both in normal and lupus-prone MRL/lpr mice to determine whether the synthetic peptide P140, which is capable of selectively modulating chaperone-mediated autophagy (CMA) in lymphocytes, could alter NET formation. P140/Lupuzor™ is currently being evaluated in phase III clinical trials involving SLE patients. Overall our in vitro and in vivo studies established that P140 does not influence NET formation, cytokine/chemokine production, or CMA in neutrophils. Thus, the beneficial effect of P140/Lupuzor™ in SLE is apparently not directly related to modulation of neutrophil function
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