370 research outputs found
Online_Appendix – Supplemental material for Making the A Priori Procedure Work for Differences Between Means
No full textSupplemental material, Online_Appendix for Making the A Priori Procedure Work for Differences Between Means by David Trafimow, Cong Wang and Tonghui Wang in Educational and Psychological Measurement</p
Reliability-based co-design and its applications to wind energy and mobile energy storage systems
No full textAutonomous systems, such as autonomous driving vehicles, unmanned aerial vehicles (UAVs), and field robots, received much attentions recently. The performance of autonomous systems relies on both its physical design and the appropriate control strategies, which often takes place at an early stage of design. The plant design and the control design are strongly coupled. Neglecting this coupling effect may cause an imbalance in the feasible design spaces of plant design and control design, such as over-constrained operation conditions, over design, or requirement of skilled operators, which hinders the development of autonomous systems. On the other hand, the products are manufactured goods and usually operate in environments with uncertainty. Reliable operation of such systems ask for balanced physical design and feasible control decisions to address the parametric uncertainty and stochastic environmental disturbances.
While integrated physical and control system co-design has been demonstrated successfully on several engineering system design applications, it has been primarily applied in a deterministic manner without considering uncertainties. An opportunity exists to study non-deterministic co-design strategies, taking into account various uncertainties in an integrated co-design framework. While significant advancements have been made in co-design and RBDO separately, little is known about methods where reliability-based dynamic system design and control design optimization are considered jointly. In this research, we investigate optimal design and control of dynamical systems with model parametric uncertainties, which presumably operate in uncertain environments. Techniques in control co-design (CCD) and reliability-based design optimization (RBDO) are adapted and integrated to solve the proposed problem. Since the proposed method adopts the idea of multi-disciplinary design optimization, it can improve the performance of autonomous systems without leveraging the difficulty in design and control for systems with uncertainties.
First, the problem formulation and strategies to solve the reliability-based control co-design problem is presented. A comparison of accuracy and efficiency is made using numerical and simple engineering case studies. The method is then applied to a horizontal axis wind turbine. The uncertain wind load and model parameters of a wind turbine are compensated through active control or endured by a reliable design regarding its aerodynamics and structural dynamics. Different strategies of reliability assessment are also compared, which provides insights on their advantages and limits under different cases.
In the second application, reliability-based control co-design is applied to Lithium-ion battery. The electrode and charging current are optimized to minimize its charging time while regulating its aging effect for reasonable cycle life. The multi-scale nature of the problem requires first principle model to preserve the coupling effect between electrode design at the micro scale and the charging control at the macro scale. However, it is not feasible to use the first principle model for control optimization. A hybrid physics and machine learning strategy is proposed in this work, which extends the applicability of reliability-based control co-design to multi-scale problems.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-08-01The student, Tonghui Cui, accepted the attached license on 2021-07-14 at 12:23.The student, Tonghui Cui, submitted this Dissertation for approval on 2021-07-14 at 12:46.This Dissertation was approved for publication on 2021-07-16 at 14:17.DSpace SAF Submission Ingestion Package generated from Vireo submission #16820 on 2022-01-12 at 13:04:15Made available in DSpace on 2022-01-12T22:55:01Z (GMT). No. of bitstreams: 2
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Supplementary materials [code] to: Incorporating machine learning into factor mixture modeling: Identification of covariate interactions to explain population heterogeneity
No full textSupplementary materials [code] to: Wang, Y., Xu, T., & Shen, J. (2023). Incorporating machine learning into factor mixture modeling: Identification of covariate interactions to explain population heterogeneity. Methodology, 19(3). https://doi.org/10.5964/meth.9487The supplementary materials provided are the annotated codes for unconditional FMM analyses, annotated codes for SEM Trees, and the annotated codes for the three-step approach to estimate covariate and covariate interaction effect on latent class membership.unknownunknow
Supplementary materials [code] to: The a priori procedure for estimating the mean in both log-normal and gamma populations and robustness for assumption violations
No full textSupplementary materials [code] to: Cao, L., Tong, T., Trafimow, D., Wang, T., & Chen, X. (2022). The a priori procedure for estimating the mean in both log-normal and gamma populations and robustness for assumption violations. Methodology, 18(1), 24–43. https://doi.org/10.5964/meth.7321Supplementary materials include three parts. The first one is the R-code for the link of required sample size for Gamma distribution. The second one is the R-code for the link of required sample size for log-normal distribution. The third one is the R-code for simulations and real data analysis
Multi-channel quasi-adaptive processing based on low and slow targets in complex environment
No full text
High-Throughput Experimentation for the Study of Structure-Property Relationships in Metal Halide Perovskites for Optoelectronic Applications.
No full textChronic stress induces depression through MDGA1-Neuroligin2 mediated suppression of inhibitory synapses in the lateral habenula
No full textRationale: The hyperactivity of lateral habenula (LHb) has been implicated in the pathophysiology of depression, but the regulatory mechanisms of inhibitory synapses in this context remains unclear. MDGA1 and neuroligin2 (Nlgn2), both regulators of inhibitory synapses, selectively interact in the LHb. We aimed to investigate if their interaction contributes to chronic restrained stress (CRS)-induced depression by modulating inhibitory synapses.Methods: Transgenic mouse models were established to conditional knockout/recover of MDGA1 expression or knockin Nlgn2 variant incapable of binding MDGA1 in the LHb, using viral Cre-recombinase expression. Synaptic function and density were assessed through electrophysiology and immunostaining, respectively. An acute restrained stress (ARS) model and chemogenetic activation of the lateral hypothalamus (LH) were used to stimulate the LHb. Behavioral tests related to depression were conducted following CRS.Results: MDGA1 and Nlgn2 selectively interacted in the LHb, which was elevated following CRS. Germline knockout of MDGA1 increased inhibitory transmission and GABAergic synapse density in the LHb, effects that were reversed by adult re-expression of MDGA1. Introduction of the Nlgn2 variant incapable of binding MDGA1 similarly enhanced inhibitory transmission and increased GABAergic synapse density in the LHb. Both germline MDGA1 deficiency and introduction of the Nlgn2 variant mitigated ARS- and LH activation-induced LHb neuron hyperactivation. MDGA1 deficiency in the LHb during adulthood increased inhibitory synaptic strength and conferred significant resistance to CRS-induced depressive behaviors, similar to the effects of introducing the Nlgn2 variant in the LHb.Conclusions: Our findings suggests that MDGA1-mediated suppression of Nlgn2 facilitates depression onset through limiting GABAergic synapse formation within the LHb. Targeting MDGA1/Nlgn2 complexes residing at GABAergic synapses within the lateral habenula may be viable for alleviating core behavioral symptoms of major depression
Supplementary materials to: Surprising implications of differences in locations versus differences in means
No full textSupplementary materials to: Trafimow, D., Roth, N., Xu, L., Toomasian, D., Perrello, A., Tong, T., Wang, T., Choy, S. T. B., Chen, X., Wang, C., & Hu, L. (2023). Surprising implications of differences in locations versus differences in means. Methodology, 19(2). https://doi.org/10.5964/meth.10969Appendix defining the skew normal distributions and parameter moment estimations.unknownunknow
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