University of Illinois, Urbana-Champaign
Recent publications
Background: Previous studies have indicated that chlorinated polyfluorinated ether sulfonic acids (Cl-PFESAs), when used as an alternative to per- and polyfluoroalkyl substances (PFASs), result in kidney toxicity. However, their co-exposure with heavy metals, has not yet been described. Objectives: To explore the joint effects of Cl-PFESAs and heavy metal exposure on renal health in Chinese adults, and identify specific pollutants driving the associations. Methods: Our sample consists of 1312 adults from a cross-sectional survey of general communities in Guangzhou, China. We measured Cl-PFESAs, legacy PFASs (perfluorooctanoic acid [PFOA] and perfluorooctane sulfonated [PFOS]), and heavy metals (arsenic, cadmium, and lead). The relationship between single pollutant and glomerular filtration rate (eGFR) and the odds ratio (OR) of chronic kidney disease (CKD) was studied using Generalized additive models (GAMs). Bayesian Kernel Machine Regression (BKMR) models were applied to assess joint effects of Cl-PFESAs and heavy metals. Additionally, we conducted a sex-specific analysis to determine the modification effect of this variable. Results: In single pollutant models, CI-PFESAs, PFOA, PFOS and arsenic were negatively associated with eGFR. Additionally, PFOA and heavy metals were positively correlated with the OR of CKD. For example, the estimated change with 95% confidence intervals (CI) of eGFR at from the highest quantile of 6:2 Cl-PFESA versus the lowest quantile was -5.65 ng/mL (95% CI: -8.21, -3.10). Sex played a role in modifying the association between 8:2 Cl-PFESA, PFOS and eGFR. In BKMR models, pollutant mixtures had a negative joint association with eGFR and a positive joint effect on CKD, especially in women. Arsenic appeared to be the primary contributing pollutant. Conclusion: We provide epidemiological evidence that Cl-PFESAs independently and jointly with heavy metals impaired kidney health. More population-based human and animal studies are needed to confirm our results.
This article aims to first focus on an improvement of finite control-set model predictive control strategy for power converters that is based on reinforcement learning event-triggered predictive control architecture with the help of adaptive dynamic programming technique and event-triggered mechanism subject to system uncertainties. Our development, endowed with the merits of reinforcement learning and event-triggered control as well as predictive control solution, is able to alleviate the issues of parametric uncertainties and high switching frequency inherent in the existing scheme, while retaining the merits of the finite control-set model predictive control. Finally, this proposal is experimentally evaluated, where robust performance tests confirm the interest and applicability of the proposed control methodology.
Multi-robot motion planning (MRMP) is the problem of finding collision-free paths for a set of robots in a continuous state space. The difficulty of MRMP increases with the number of robots and is exacerbated in environments with narrow passages that robots must pass through, like warehouse aisles where coordination between robots is required. In single-robot settings, topology-guided motion planning methods have shown improved performance in these constricted environments. In this work, we extend an existing topology-guided single-robot motion planning method to the multi-robot domain to leverage the improved efficiency provided by topological guidance. We demonstrate our method's ability to efficiently plan paths in complex environments with many narrow passages, scaling to robot teams of size up to 25 times larger than existing methods in this class of problems. By leveraging knowledge of the topology of the environment, we also find higher-quality solutions than other methods.
We consider a discrete-time dynamical system over a discrete state-space, which evolves according to a structured Markov model called Bernoulli Autoregressive (BAR) model. Our goal is to obtain sample complexity bounds for the problem of estimating the parameters of this model using an indirect Maximum Likelihood Estimator. Our sample complexity bounds exploit the structure of the BAR model and are established using concentration inequalities for random matrices and Lipschitz functions.
Purpose: The purpose of this study was to examine children’s, camp counselors’, and activity leaders’ perceptions toward the effects of a 4-week teaching personal and social responsibility model-based summer learning and enrichment program and its ability to reduce bullying behaviors among school-age children. Method: Data collection included semistructured interviews with 30 children and eight camp staff. Child participants completed the following pre- and postsurveys: Personal and Social Responsibility Questionnaire and the Illinois Bullying Scale. In addition, daily observations over a 4-week period were recorded in a field notes log. Survey data were analyzed using descriptive statistics and bivariate correlations, and all observational and interview data were coded using inductive and deductive techniques. Results: The results indicated that the implementation of teaching personal and social responsibility model was perceived to be associated with reduction in the bullying. Conclusion: Findings from the present study suggested teaching personal and social responsibility facilitated social and emotional learning and improved children’s personal and social responsibility.
Municipal solid waste management and disposal in China have significantly evolved since 2000. Due to China's vast land area and significant socioeconomic and geographic disparities, nationwide waste management strategies need to be further evaluated. This study quantified the effect of social, economic, and geographic drivers on municipal waste disposal activities in 31 provincial-level administrative regions from 2003 to 2020, by establishing a methodology integrated by two-way fixed effects regression model, panel random forest, and spatial Durbin model. The results showed, in the past two decades, socio-economic-geo indicators significantly co-decided the landfill and incineration activities. In particular, the explanatory ability of GDP per capita was above 45%, while land resources and city size also showed great significance. Spatial autocorrelation analysis showed that the relationship between landfill/incineration rates and socio-economic-geo drivers changed notably from unobvious to significant with economic growth. Furthermore, the local economy and land resources displayed more impact than those of the neighboring regions, while sci-tech and education showed clear spatial spillover effects. Chinese government would carefully assess the full-scale promotion policy of incineration plants, landfill is still hold as a reasonable option for regions with specific socio-economic-geo conditions.
The Gaussian stationary point in an inequality motivated by the Z-interference channel was recently conjectured by Costa, Nair, Ng, and Wang to be the global optimizer, which, if true, would imply the optimality of the Han-Kobayashi region for the Gaussian Z-interference channel. This conjecture was known to be true for some parameter regimes, but the validity for all parameters, although suggested by Gaussian tensorization, was previously open. In this paper we construct several counterexamples showing that this conjecture may fail in certain regimes: A simple construction without Hermite polynomial perturbation is proposed, where distributions far from Gaussian are analytically shown to be better than the Gaussian stationary point. As alternatives, we consider perturbation along geodesics under either the L <sup xmlns:mml="" xmlns:xlink="">2</sup> or Wasserstein-2 metric, showing that the Gaussian stationary point is unstable in a certain regime. Similarity to stability of the Levy-Cramer theorem is discussed. The stability phase transition point admits a simple characterization in terms of the maximum eigenvalue of the Gaussian maximizer. Similar to the Holley-Stroock principle, we can show that in the stable regime the Gaussian stationary point is optimal in a neighborhood under the L <sup xmlns:mml="" xmlns:xlink="">∞</sup> -norm with respect to the Gaussian measure. Allowing variable power control, we show that the Gaussian optimizers for the Han-Kobayashi region always lie in the stable regime. Finally, an amended conjecture is proposed.
DC power grid is considered as the future trend for distribution networks. However, the pure medium voltage DC (MVDC) grid faces great challenges in designing power supplies with high voltage input but small power output requirements. The continuous power supply from the MVDC bus typically requires power converters with complex circuit structures and control algorithms. This paper presents a power supply with a simple circuit structure for medium-voltage DC systems. The proposed power supply is comprised of cascaded standardized submodules to cope with high voltage input and reduce the isolation requirement, and the voltage balance of all DC link capacitors can be ensured with submodules operating independently. A start-up strategy and a simple self-powering strategy for the proposed converter are proposed in this paper, and the average current model is established to characterize the proposed power supply. To verify the analysis, an average model and a switching model are constructed and simulated in Simulink and a 600 W prototype comprised of five submodules is built and tested to validate the design, and the maximum input voltage can reach 2700 V.
Solid-state transformer(SST) based on Vienna cell features with less semiconductor devices and high-power density, providing a promising concept for super charging stations and UPS for data centers. However, the presence of numerous switching devices in SSTs raises the possibility of faults. Bypassing faulty cells not only adds to the cost by requiring additional bypass switches but may also result in a loss of system power capacity. To address the above problems, this paper proposes a fault-tolerant operation strategy for Vienna-based SSTs. The proposed strategy allows all faulty cells to continue operating, thereby avoiding system power capacity loss. Firstly, an improved zero sequence voltage injection method, conforming to Vienna characteristics, is presented to address issues of three-phase unbalance and current distortion. Secondly, an extra power control mechanism for the dc-dc stage is developed to regulate the capacitor voltages of the faulty cell, ensuring that the capacitor voltage of SST can be balanced to the rated value. Furthermore, an enhanced modulation based on a sort algorithm is introduced to match the configuration of faulty cells, preventing the mismatch between the reference voltage and the output voltage. Experiments are presented to prove that SST can operate continuously with the proposed fault-tolerant control.
The modular multilevel resonant dc-dc converters (MMRDC) are becoming one of the most attractive candidates in medium voltage applications, but they would usually face technical challenges in high-efficient operation with wide input range and wide load condition. Firstly, this paper provides an elaborate review of the voltage control dimensions in MMRDC, and their corresponding operation principles, regulation capabilities and efficiency influences for MMRDC are also analyzed respectively. Then for the wide input range, a tailored voltage regulation method combining both phase shift angle control and inserted submodule number control is proposed, and the optimal regulation principles of these two control dimensions are further investigated to realize high-efficient operation for MMRDC with wide load condition. Finally, the effectiveness of the proposed strategy is demonstrated through a simulation model and a full-scale MMRDC prototype with 9-18kV input and 60kW power rating.
In inductive power transfer systems, some applications require working at higher power levels, transferring power with longer air gaps, and meeting geometric constraints. Many situations will decrease system coupling and affect performance. In this paper, a three-coil configuration based on an all-detuned design is proposed to optimize overall coupling and system efficiency. Primary and tertiary coils of the proposed topology are mounted on the same side. The three coil resonances in the proposed system, as extra degrees of freedom, do not match the switching frequency or each other. The key objectives of the proposed all-detuned design are to: 1) achieve a constant current output and unity power factor based on an equivalent two-coil circuit model, 2) maximize the overall coupling coefficient to reduce switching frequency or coil inductances by selecting a suitable tertiary resonant frequency, and 3) optimize efficiency to be superior to those in a conventional two-coil system by minimizing coil currents. A 1 kW prototype has been prepared to verify the method. For example, when the main coupling coefficient is only 0.077, dc-dc efficiency of the proposed method ranges from 90.2% to 91.2% over a 2:1 load range, while that of the conventional two-coil system does not exceed 90%.
A lightweight and compliant manipulator design has been considered crucial in safe physical human–robot interaction. Remote actuation relocating the massive parts to the robot base and transmitting power to the distal joint minimizes the actuator inertia and provides series elasticity to the actuator. Rolling diaphragm hydrostatic transmission (RDHT), one of the remote actuation, has recently been studied in physically interacting robots, which can tackle the remaining issues in hydraulic actuation, such as low backdrivability and fluid leakage. However, existing RDHTs are challenging to achieve the desired safety and control performance simultaneously due to their fixed stiffness. This article presents a stiffness-switchable hydrostatic transmission (SwHST) consisting of an RDHT and valve-controlled pneumatic springs. The SwHST has a wide stiffness range of 15–290 N $\cdot$ m/rad and a fast response in stiffness transition of less than 50 ms without any complex stiffness tuning mechanism. It is one of the most efficient transmissions in remote actuation and stiffness adjustment. Its static friction is less than 0.4% of full-range torque, and the stiffness-switching module consumes only 6 W of power when valves are open. The dynamic characteristics of the SwHST are experimentally scrutinized under various operational conditions. Safety performance is verified in unconstrained and constrained collision tests, demonstrating that the SwHST can effectively mitigate the clamping force of more than 50% for both the tests. Control performance is evaluated on position tracking tests. We foresee the proposed SwHST being utilized in human–robot collaboration without jeopardizing control performance through a rapid and efficient stiffness-switching mechanism.
The TrackDLO algorithm estimates the shape of a Deformable Linear Object (DLO) under occlusion from a sequence of RGB-D images. TrackDLO is vision-only and runs in real-time. It requires no external state information from physics modeling, simulation, visual markers, or contact as input. The algorithm improves on previous approaches by addressing three common scenarios which cause tracking failure: tip occlusion, mid-section occlusion, and self-occlusion. This is achieved through the application of Motion Coherence Theory to impute the spatial velocity of occluded nodes, the use of the topological geodesic distance to track self-occluding DLOs, and the introduction of a non-Gaussian kernel that only penalizes lower-order spatial displacement derivatives to reflect DLO physics. Improved real-time DLO tracking under mid-section occlusion, tip occlusion, and self-occlusion is demonstrated experimentally. The source code and demonstration data are publicly released.
Diamond p-type lateral Schottky barrier diodes (SBDs) with a 2-μm-thick drift layer are fabricated with and without Al2O3 field plates. Schottky contacts composed of Mo (50 nm) / Pt (50 nm) / Au (100 nm) showed a barrier height of 1.02 ± 0.01 eV and ohmic contacts of Ti (30 nm) / Pt (30 nm) / Au (100 nm) achieved a specific ohmic contact resistance of 1.25 ± 0.98 × 10-4 Ω-cm2. Their forward and reverse bias characteristics are studied in detail. Both SBDs, with and without Al2O3 field plates, exhibit rectifying ratios larger than 107 at room temperature, and a peak current density of 5.39 mA/mm under 40 V forward bias at 200 °C. The leakage current density at room temperature is stable at approximately 0.01 mA/mm for both diodes. The SBD without the Al2O3 field plate exhibited a breakdown voltage of 1159 V, while the SBD with the Al2O3 field plate is stable under a reverse voltage of 4612 V, which is higher than many diamond SBDs previously reported.
Synaptic potentiation underlies various forms of behavior and depends on modulation by multiple activity-dependent transcription factors to coordinate the expression of genes necessary for sustaining synaptic transmission. Our current study identified the tumor suppressor p53 as a novel transcription factor involved in this process. We first revealed that p53 could be elevated upon chemically induced long-term potentiation (cLTP) in cultured primary neurons. By knocking down p53 in neurons, we further showed that p53 is required for cLTP-induced elevation of surface GluA1 and GluA2 subunits of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR). Because LTP is one of the principal plasticity mechanisms underlying behaviors, we employed forebrain-specific knockdown of p53 to evaluate the role of p53 in behavior. Our results showed that, while knocking down p53 in mice does not alter locomotion or anxiety-like behavior, it significantly promotes repetitive behavior and reduces sociability in mice of both sexes. In addition, knocking down p53 also impairs hippocampal LTP and hippocampus-dependent learning and memory. Most importantly, these learning-associated defects are more pronounced in male mice than in female mice, suggesting a sex-specific role of p53 in these behaviors. Using RNA sequencing (RNAseq) to identify p53-associated genes in the hippocampus, we showed that knocking down p53 up- or down-regulates multiple genes with known functions in synaptic plasticity and neurodevelopment. Altogether, our study suggests p53 as an activity-dependent transcription factor that mediates the surface expression of AMPAR, permits hippocampal synaptic plasticity, represses autism-like behavior, and promotes hippocampus-dependent learning and memory.
A microbial community maintains its ecological dynamics via metabolite crosstalk. Hence, knowledge of the metabolome, alongside its populace, would help us understand the functionality of a community and also predict how it will change in atypical conditions. Methods that employ low-cost metagenomic sequencing data can predict the metabolic potential of a community, that is, its ability to produce or utilize specific metabolites. These, in turn, can potentially serve as markers of biochemical pathways that are associated with different communities. We developed MMIP (Microbiome Metabolome Integration Platform), a web-based analytical and predictive tool that can be used to compare the taxonomic content, diversity variation and the metabolic potential between two sets of microbial communities from targeted amplicon sequencing data. MMIP is capable of highlighting statistically significant taxonomic, enzymatic and metabolic attributes as well as learning-based features associated with one group in comparison with another. Furthermore, MMIP can predict linkages among species or groups of microbes in the community, specific enzyme profiles, compounds or metabolites associated with such a group of organisms. With MMIP, we aim to provide a user-friendly, online web server for performing key microbiome-associated analyses of targeted amplicon sequencing data, predicting metabolite signature, and using learning-based linkage analysis, without the need for initial metabolomic analysis, and thereby helping in hypothesis generation.
This paper explores whether particles within uniformly-spaced generating cells falling at terminal velocity within observed 2-D wind fields and idealized deformation flow beneath cloud top can be reorganized consistent with the presence of single and multi-banded structures present on WSR-88D radars. In the first experiment, two-dimensional wind fields, calculated along cross-sections normal to the long-axis of snow bands observed during three Northeast U.S. winter storms, were taken from the initialization of the High Resolution Rapid Refresh model. This experiment demonstrated that the greater the residence time of the particles in each of the three storms, the greater particle reorganization occurred. For experiments with longer residence times, increases in particle concentrations were nearly or directly collocated with reflectivity bands. For experiments with shorter residence times, particle reorganization still conformed to the band features but with less concentration enhancement. This experiment demonstrates that the combination of long particle residence time and net convergent cross-sectional flow through the cloud depth is sufficient to re-organize particles into locations consistent with precipitation bands. Increased concentrations of ice particles can then contribute, along with any dynamic forcing, to the low-level reflectivity bands seen on WSR-88D radars. In a second experiment, the impact of flow deformation on the re-organization of falling ice particles was investigated using an idealized kinematic model with stretching deformation flow of different depths and magnitudes. These experiments showed that deformation flow provides for little particle reorganization given typical deformation layer depths and magnitudes within the comma head of such storms.
Seismic design of water retaining structures relies heavily on the response of the retained water to shaking. The water dynamic response has been evaluated by means of analytical, numerical, and experimental approaches. In practice, it is common to use simplified code‐based methods to evaluate the added demands imposed by water sloshing. Yet, such methods were developed with an inherent set of assumptions that might limit their application. Alternatively, numerical modeling methods offer a more accurate way of quantifying the water response and have been commonly validated using 1 g shake table experiments. In this study, a unique series of five centrifuge tests was conducted with the goal of investigating the hydrodynamic behavior of water by varying its height and length. Moreover, sine wave and earthquake motions were applied to examine the water response at different types and levels of excitation. Arbitrary Lagrangian‐Eulerian finite element models were then developed to reproduce 1 g shake table experiments available in the literature in addition to the centrifuge tests conducted in this study. The results of the numerical simulations as well as the simplified and analytical methods were compared to the experimental measurements, in terms of free surface elevation and hydrodynamic pressures, to evaluate their applicability and limitations. The comparison showed that the numerical models were able to reasonably capture the water response of all configurations both under earthquake and sine wave motions. The analytical solutions performed well except for cases with resonance under harmonic motions. As for the simplified methods, they provided acceptable results for the peak responses under earthquake motions. However, under sine wave motions, where convective sloshing is significant, they underpredict the response. Also, beyond peak ground accelerations of 0.5 g., a mild nonlinear increase in peak dynamic pressures was measured which deviates from assumed linear response in the simplified methods. The study confirmed the reliability of numerical models in capturing water dynamic responses, demonstrating their broad applicability for use in complex problems of fluid‐structure‐soil interaction.
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Bill Cope
  • Department of Education Policy, Organization and Leadership
Norma I. Scagnoli
  • College of Business
Ratnakar Singh
  • Department of Comparative Biosciences
Manfredo Seufferheld
  • Department of Entomology / Illinois Natural History Survey
Sebastien Huot
  • Illinois State Geological Survey
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