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Cao, Qing

Publications and source records attributed to Cao, Qing.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

2D Amorphous Carbon Dielectric Prepared from Solution Precursor for Nanoelectronics

The preparation of amorphous 2D nanodielectrics represents a major challenge due to the metastable nature of amorphous phases. We describe a scalable and solution-based strategy to prepare wafer-scale 2D amorphous carbon with thickness down to 1–2 atomic layers from coal-derived carbon quantum dots as precursors. The prepared atomically thin 2D amorphous carbon can be suspended over cavities as freestanding membranes with high modulus of 400±100 GPa and demonstrate robust dielectric properties with dielectric strength above 20 MV·cm-1 and leakage current density below 10-4 A·cm-2 through a scaled thickness of three-atomic layers. When implemented as ultrathin gate dielectrics in 2D transistors or ion-transport media in memristors, they enable exceptional device performance and spatiotemporal uniformity, resulting from their amorphous form, intrinsic ultrathinness, and 2D atomic structures.

Pham, Viet Hung↗
DOE OSTI2020

Machine Committee Framework for Power Grid Disturbances Analysis Using Synchrophasors Data

Events detection is a key challenge in power grid frequency disturbances analysis. Accurate detection of events is crucial for situational awareness of the power system. In this paper, we study the problem of events detection in power grid frequency disturbance analysis using synchrophasors data streams. Current events detection approaches for power grid rely on individual detection algorithm. This study integrates some of the existing detection algorithms using the concept of machine committee to develop improved detection approaches for grid disturbance analysis. Specifically, we propose two algorithms—an Event Detection Machine Committee (EDMC) algorithm and a Change-Point Detection Machine Committee (CPDMC) algorithm. Both algorithms use parallel architecture to fuse detection knowledge of its individual methods to arrive at an overall output. The EDMC algorithm combines five individual event detection methods, while the CPDMC algorithm combines two change-point detection methods. Each method performs the detection task separately. The overall output of each algorithm is then computed using a voting strategy. The proposed algorithms are evaluated using three case studies of actual power grid disturbances. Compared with the individual results of the various detection methods, we found that the EDMC algorithm is a better fit for analyzing synchrophasors data; it improves the detection accuracy; and it is suitable for practical scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Adaptive Anomaly Detection for Dynamic Clinical Event Sequences

Over the past decade, health information technology (IT) has enabled the amount of digital information stored in electronic health records (EHRs) to expand greatly. However, according to some studies, hazards in health IT can lead to changes in clinical decisions, care processes, and care outcomes, as well as other issues. Thus, the effects of health IT hazards on patient safety have been at the forefront of recent patient safety research. Nonetheless, hazard detection in health IT remains a challenge. In this paper, the authors assume that safety-related issues in health IT would exhibit anomalous characteristics in EHR data. Although all hazards will exhibit some anomalous characteristics, not all anomalies can be regarded as hazards. The authors hypothesize that errors in health IT could lead to interruptions in the sequence of clinical actions. To this end, the problem of detecting anomalous sequences in big EHR data is considered. This paper focuses on dynamic event sequences, which are a series of clinical actions in motion. The authors propose an adaptive anomaly detection approach that uses higher-order network representation to detect anomalous sequences. Furthermore, the authors propose a contiguous subsequence anomaly detection approach that identifies abnormal subsequences in the detected anomalous sequences. The proposed approaches are tested by using synthetic and real-world EHR data. The proposed methods outperform existing state of the art anomaly detection techniques. To reduce the computational complexity associated with the operational implementation of the proposed approaches, the Apache Spark environment was leveraged, and a much shorter run time together with improved performance were achieved, especially for data with more than 60,000 sequences.

Niu, Haoran↗
DOE OSTI2020

Anomaly Detection in Sequential Health Care Data using Higher-Order Network Representation

The ever-increasing use of information technology (IT) in health care presents new challenges to patient care. Information errors arising from the use of Health IT and their implications on care delivery and patient outcomes have been widely reported. Information errors can lead to changes in clinical decisions, care processes, and care outcomes, among others. An altered care process, for example, could interrupt the sequence of care, which could lead to changes in care decisions and/or changes in care outcomes. We define interruptions in the care process as anomalies in the care sequence. In this paper, we present a new approach based on the higher-order network (HON) representation to detect anomalies in sequential health care data using electronic health records. The results show that there are higher-order dependencies in health care data; and that the use of HON representation is more effective than the first-order network representation for detecting anomalies in sequential health care data.

Niu, Haoran↗
DOE OSTI2019

Real-Time Automated Health Information Technology Hazard Detection

The objective of this project is to develop an automated surveillance tool that will help the US Department of Veterans Affairs (VA) to detect potential hazards in health information technology (HIT) systems. To achieve this objective, Oak Ridge National Laboratory (ORNL) researchers have developed computational methods and a surveillance tool that will detect safety concerns and identify opportunities to improve HIT and safety within the VA system using Corporate Data Warehouse (CDW) data. This work is limited to the safe operation and safe use of HIT. It does not address the use of HIT to make health care safer. This project leveraged ORNL expertise in computational sciences and its computing resources accordingly.This report documents the FY 2019 accomplishments on this project. There were three major tasks. The first task developed data extraction approaches, which helped provide a better overall understanding of the important data elements in CDW. The outputs of this task served as inputs into the second task, which is the hazard detection and characterization task. This second task involved development of three methods that can be categorized into probabilistic model, event-based hazards detection, and system-based reliability performance evaluation. The third task dealt with the design, development, and demonstration of the automated surveillance tool. The tool currently resides in ORNL’s Private Health Information enclave at Oak Ridge, Tennessee, and operates on the VA’s CDW data. The developed capabilities and tool have been tested on CDW data from different clinical domains including Consult, Radiology, Laboratory, and Medication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Development of a Novel B-Cell Lymphoma 6 (BCL6) PROTAC To Provide Insight into Small Molecule Targeting of BCL6

B-cell lymphoma 6 (BCL6) inhibition is a promising mechanism for treating hematological cancers but high quality chemical probes are necessary to evaluate its therapeutic potential. In this paper we report potent BCL6 inhibitors that demonstrate cellular target engagement and exhibit exquisite selectivity for BCL6 based on mass spectrometry analyses following chemical proteomic pull down. Importantly, a proteolysis-targeting chimera (PROTAC) was also developed and shown to significantly degrade BCL6 in a number of diffuse large B-cell lymphoma (DLBCL) cell lines, but neither BCL6 inhibition nor degradation selectively induced marked phenotypic response. To investigate, we monitored PROTAC directed BCL6 degradation in DLBCL OCI-Ly1 cells by immunofluorescence and discovered a residual BCL6 population. Analysis of subcellular fractions also showed incomplete BCL6 degradation in all fractions despite having measurable PROTAC concentrations, together providing a rationale for the weak antiproliferative response seen with both BCL6 inhibitor and degrader. In summary, we have developed potent and selective BCL6 inhibitors and a BCL6 PROTAC that effectively degraded BCL6, but both modalities failed to induce a significant phenotypic response in DLBCL despite achieving cellular concentrations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Mathematical Investigation of Fluid Flow, Mass Transfer, and Slag-steel Interfacial Behavior in Gas-stirred Ladles

In this study, the Euler-Euler and Euler-Lagrange modeling approaches were applied to simulate the multiphase flow in the water model and gas-stirred ladle systems. Detailed comparisons of the computational and experimental results were performed to establish which approach is more accurate for predicting the gas-liquid multiphase flow phenomena. It was demonstrated that the Euler-Lagrange approach is more accurate than the Euler-Euler approach. The Euler-Lagrange approach was applied to study the effects of the free surface setup, injected bubble size, gas flow rate, and slag layer thickness on the slag-steel interaction and mass transfer behavior. Detailed discussions on the flat/non-flat free surface assumption were provided. Significant inaccuracies in the prediction of the surface fluid flow characteristics were found when the flat free surface was assumed. The variations in the main controlling parameters (bubble size, gas flow rate, and slag layer thickness) and their potential impact on the multiphase fluid flow and mass transfer characteristics (turbulent intensity, mass transfer rate, slag-steel interfacial area, flow patterns, etc.,) in gas-stirred ladles were quantitatively determined to ensure the proper increase in the ladle refining efficiency. It was revealed that by injecting finer bubbles as well as by properly increasing the gas flow rate and the slag layer thickness, the ladle refining efficiency can be enhanced significantly.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Numerical Investigation of Desulfurization Kinetics in Gas-Stirred Ladles by a Quick Modeling Analysis Approach

A quick modeling analysis approach for predicting the slag-steel reaction and desulfurization kinetics in argon gas-stirred ladles has been developed in this study. The model consists of two uncoupled components: (i) a computational fluid dynamics (CFD) model for predicting the fluid flow and the characteristics of slag-steel interface, and (ii) a multicomponent reaction kinetics model for calculating the desulfurization evolution. The steel-slag interfacial area and mass transfer coefficients predicted by the CFD simulation are used as the processing data for the reaction model. Since the desulfurization predictions are uncoupled from the CFD simulation, the computational time of this uncoupled predictive approach is decreased by at least 100 times for each case study when compared with the CFD-reaction kinetics fully coupled model. The uncoupled modeling approach was validated by comparing the evolution of steel and slag compositions with the experimentally measured data during ladle metallurgical furnace (LMF) processing at Nucor Steel Tuscaloosa, Inc. Then, the validated approach was applied to investigate the effects of the initial steel and slag compositions, as well as different types of additions during the refining process on the desulfurization efficiency. The results revealed that the sulfur distribution ratio and the desulfurization reaction can be promoted by making Al and CaO additions during the refining process. It was also shown that by increasing the initial Al content in liquid steel, both Al oxidation and desulfurization rates rapidly increase. In addition, it was found that the variation of the initial Si content in steel has no significant influence on the desulfurization rate. Lastly, if the initial CaO content in slag is increased or the initial Al{sub 2}O{sub 3} content is decreased in the fluid-slag compositional range, the desulfurization rate can be improved significantly during the LMF process.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Optimizing checkpoint data placement with guaranteed burst buffer endurance in large-scale hierarchical storage systems

Non-volatile devices, such as SSDs, will be an integral part of the deepening storage hierarchy on large-scale HPC systems. These devices can be on the compute nodes as part of a distributed burst buffer service or they can be external. Wherever they are located in the hierarchy, one critical design issue is the SSD endurance under the write-heavy workloads, such as the checkpoint I/O for scientific applications. For these environments, it is widely assumed that checkpoint operations can occur once every 60 min and for each checkpoint step as much as half of the system memory can be written out. Unfortunately, for large-scale HPC applications, the burst buffer SSDs can be worn out much more quickly given the extensive amount of data written at every checkpoint step. One possible solution is to control the amount of data written by reducing the checkpoint frequency. However, a direct effect caused by reduced checkpoint frequency is the increased vulnerability window of system failures and therefore potentially wasted computation time, especially for large-scale compute jobs.

Computer Science↗
DOE OSTI2017

A human Fab exclusively binding to the extracellular domain of LMP2A

In the areas of North Africa, Southeast Asia as well as South China, Nasopharyngeal carcinoma (NPC) is among the most widespread cancers. Plenty of research findings confirmed that Epstein-Barr virus (EBV) played a crucial role in NPC. EBV-encoded Latent membrane protein 2A (LMP2A) which continuously expressed in cell membrane protein induced an epithelial-mesenchymal transition and increased the number of side population stem-like cancer cells in NPC. This reveals that LMP2A could contribute to the development and recurrence in NPC. Above evidences suggest that LMP2A could be the potential target molecule in the treatment of NPC. In the current study, a novel human antibody Fab (Fab29) against the extracellular domain of LMP2A was produced with success. Through immunofluorescence experiment it was proved that human antibody Fab29 exclusively combined the surface of SUNE cells (LMP2A-positive). Then flow cytometry result exhibited that the fluorescent intensities of SUNE cells and CNE cells were distinct (96.89% and 0.02% respectively). After that, it was shown by affinity test that the Fab29 fragment had high affinity (KD (M) 1.79E-09) with LMP2A. It was also revealed by immunohistochemical analysis that the Fab29 fragment could combine with LMP2A-positive human NPC tissues in comparison with the control group. Finally, the MTT result indicated that the Fab29 fragment could inhibit the proliferation of LMP2A-positive NPC cells. The inhibiting rate to SUNE cell proliferation reached a peak by Fab29 (19.67%) compared with unrelated Fab and CNE with Fab29 at a concentration of 500 μg/L in first 24 h and in the next 24 h the inhibition rate grew to 22.54%. In brief, it was shown that Fab29, a characteristic human antibody, could recognize LMP2A protein and inhibit the proliferation of LMP2A-expressing NPC cells in vitro.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A Bloom Filter Based Scalable Data Integrity Check Tool for Large-Scale Dataset

Large scale HPC applications are becoming increasingly data intensive. At Oak Ridge Leadership Computing Facility (OLCF), we are observing the number of files curated under individual project are reaching as high as 200 millions and project data size is exceeding petabytes. These simulation datasets, once validated, often needs to be transferred to archival system for long term storage or shared with the rest of the research community. Ensuring the data integrity of the full dataset at this scale is paramount important but also a daunting task. This is especially true considering that most conventional tools are serial and file-based, unwieldy to use and/or can't scale to meet user's demand.To tackle this particular challenge, this paper presents the design, implementation and evaluation of a scalable parallel checksumming tool, fsum, which we developed at OLCF. It is built upon the principle of parallel tree walk and work-stealing pattern to maximize parallelism and is capable of generating a single, consistent signature for the entire dataset at extreme scale. We also applied a novel bloom-filter based technique in aggregating signatures to overcome the signature ordering requirement. Given the probabilistic nature of bloom filter, we provided a detailed error and trade-off analysis. Using multiple datasets from production environment, we demonstrated that our tool can efficiently handle both very large files as well as many small-file based datasets. Our preliminary test showed that on the same hardware, it outperforms conventional tool by as much as 4×. It also exhibited near-linear scaling properties when provisioned with more compute resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Medium scale carbon nanotube thin film integrated circuits on flexible plastic substrates

The present invention provides device components geometries and fabrication strategies for enhancing the electronic performance of electronic devices based on thin films of randomly oriented or partially aligned semiconducting nanotubes. In certain aspects, devices and methods of the present invention incorporate a patterned layer of randomly oriented or partially aligned carbon nanotubes, such as one or more interconnected SWNT networks, providing a semiconductor channel exhibiting improved electronic properties relative to conventional nanotubes-based electronic systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

A practical approach to reconciling availability, performance, and capacity in provisioning extreme-scale storage systems

The increasing data demands from high-performance computing applications significantly accelerate the capacity, capability and reliability requirements of storage systems. As systems scale, component failures and repair times increase, significantly impacting data availability. A wide array of decision points must be balanced in designing such systems. We propose a systematic approach that balances and optimizes both initial and continuous spare provisioning based on a detailed investigation of the anatomy and field failure data analysis of extreme-scale storage systems. We consider the component failure characteristics and its cost and impact at the system level simultaneously. We build a tool to evaluate different provisioning schemes, and the results demonstrate that our optimized provisioning can reduce the duration of data unavailability by as much as 52% under a fixed budget. We also observe that non-disk components have much higher failure rates than disks, and warrant careful considerations in the overall provisioning process.

Computer Science↗