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Articles 1 - 7 of 7
Full-Text Articles in Engineering
A Novel Bayesian Framework Infers Driver Activation States And Reveals Pathway-Oriented Molecular Subtypes In Head And Neck Cancer, Zhengping Liu, Chunhui Cai, Xiaojun Ma, Jinling Liu, Lujia Chen, Vivian Wai Yan Lui, Gregory F. Cooper, Xinghua Lu
A Novel Bayesian Framework Infers Driver Activation States And Reveals Pathway-Oriented Molecular Subtypes In Head And Neck Cancer, Zhengping Liu, Chunhui Cai, Xiaojun Ma, Jinling Liu, Lujia Chen, Vivian Wai Yan Lui, Gregory F. Cooper, Xinghua Lu
Engineering Management and Systems Engineering Faculty Research & Creative Works
Head and neck squamous cell cancer (HNSCC) is an aggressive cancer resulting from heterogeneous causes. To reveal the underlying drivers and signaling mechanisms of different HNSCC tumors, we developed a novel Bayesian framework to identify drivers of individual tumors and infer the states of driver proteins in cellular signaling system in HNSCC tumors. First, we systematically identify causal relationships between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) for each TCGA HNSCC tumor using the tumor-specific causal inference (TCI) model. Then, we generalize the most statistically significant driver SGAs and their regulated DEGs in TCGA HNSCC cohort. Finally, we …
Push Them Forward: Challenges In Intergovernmental Organizations' Influence On Rural Broadband Infrastructure Expansion, Javier Valentín-Sívico, Casey I. Canfield, Ona Egbue
Push Them Forward: Challenges In Intergovernmental Organizations' Influence On Rural Broadband Infrastructure Expansion, Javier Valentín-Sívico, Casey I. Canfield, Ona Egbue
Engineering Management and Systems Engineering Faculty Research & Creative Works
Many rural US communities lack access to adequate broadband services. This paper draws on semi-structured interviews conducted in 2019 with 16 Regional Planning Commissions to uncover dynamics of how these intergovernmental organizations contribute to the deployment of broadband infrastructure in rural Missouri. The proposed framework integrates the decomposed Theory of Planned Behavior (TPB), the Theory of Reasoned Goal Pursuit, and Stakeholder Theory. Many participants reported a low level of involvement in broadband infrastructure initiatives even though supporting infrastructure development to promote economic growth is one of the Regional Planning Commissions' primary goals. Regional Planning Commissions are highly influenced by four …
Robust And Accurate Estimation Of Cellular Fraction From Tissue Omics Data Via Ensemble Deconvolution, Manqi Cai, Molin Yue, Tianmeng Chen, Jinling Liu, Erick Forno, Xinghua Lu, Timothy Billiar, Juan Celedón, Chris Mckennan, Wei Chen, Jiebiao Wang
Robust And Accurate Estimation Of Cellular Fraction From Tissue Omics Data Via Ensemble Deconvolution, Manqi Cai, Molin Yue, Tianmeng Chen, Jinling Liu, Erick Forno, Xinghua Lu, Timothy Billiar, Juan Celedón, Chris Mckennan, Wei Chen, Jiebiao Wang
Engineering Management and Systems Engineering Faculty Research & Creative Works
Motivation: Tissue-level omics data such as transcriptomics and epigenomics are an average across diverse cell types. To extract cell-type-specific (CTS) signals, dozens of cellular deconvolution methods have been proposed to infer cell-type fractions from tissue-level data. However, these methods produce vastly different results under various real data settings. Simulation-based benchmarking studies showed no universally best deconvolution approaches. There have been attempts of ensemble methods, but they only aggregate multiple single-cell references or reference-free deconvolution methods. Results: To achieve a robust estimation of cellular fractions, we proposed EnsDeconv (Ensemble Deconvolution), which adopts CTS robust regression to synthesize the results from 11 …
Encouraging Voluntary Government Action Via A Solar-Friendly Designation Program To Promote Solar Energy In The United States, Xue Gao, Casey I. Canfield, Tian Tang, Hunter Hill, Morgan Higman, John Cornwell
Encouraging Voluntary Government Action Via A Solar-Friendly Designation Program To Promote Solar Energy In The United States, Xue Gao, Casey I. Canfield, Tian Tang, Hunter Hill, Morgan Higman, John Cornwell
Engineering Management and Systems Engineering Faculty Research & Creative Works
Sustainable development requires an accelerated transition toward renewable energy. In particular, substantially scaling up solar photovoltaics (PV) adoption is a crucial component of reducing the impacts of climate change and promoting sustainable development. However, it is challenging to convince local governments to take action. This study uses a combination of propensity score matching (PSM) and difference-in-differences (DID) models to assess the effectiveness of a voluntary environmental program (VEP) called SolSmart that targets local governments to engage in solar-friendly practices to promote the local solar PV market in the United States. Via specific designation requirements and technical assistance, SolSmart simplifies the …
Resource Availability And Implications For The Development Of Plug‐In Electric Vehicles, Ona Egbue, Suzanna Long, Seong Dae Kim
Resource Availability And Implications For The Development Of Plug‐In Electric Vehicles, Ona Egbue, Suzanna Long, Seong Dae Kim
Engineering Management and Systems Engineering Faculty Research & Creative Works
Plug‐in electric vehicles (PEVs) have immense potential for reducing greenhouse gas emissions and dependence on fossil fuels, and for smart grid applications. Although a great deal of research is focused on technological limitations that affect PEV battery performance targets, a major and arguably equal concern is the constraint imposed by the finite availability of elements or resources used in the manufacture of PEV batteries. Availability of resources, such as lithium, for batteries is critical to the future of PEVs and is, therefore, a topic that needs attention. This study addresses the issues related to lithium availability and sustainability, particularly supply …
Maintenance Optimization In A Digital Twin For Industry 4.0, Abhijit Gosavi, Vy Khoi Le
Maintenance Optimization In A Digital Twin For Industry 4.0, Abhijit Gosavi, Vy Khoi Le
Engineering Management and Systems Engineering Faculty Research & Creative Works
The advent of Internet of Things and artificial intelligence in the era of Industry 4.0 has transformed decision-making within production systems. In particular, many decisions that previously required significant human activity are now made automatically with minimal human intervention via so-called digital twins (DTs). In the context of maintenance and reliability modeling, this naturally calls for new paradigms that can be seamlessly integrated within DTs for decision-making. The input data for time to failure needed in reliability computations are directly collected from the work center in a digital setting and often do not satisfy a known distribution. A neural network …
Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin
Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Future action anticipation aims to infer future actions from the observation of a small set of past video frames. In this paper, we propose a novel Jointly learnt Action Anticipation Network (J-AAN) via Self-Knowledge Distillation (Self-KD) and cycle consistency for future action anticipation. In contrast to the current state-of-the-art methods which anticipate the future actions either directly or recursively, our proposed J-AAN anticipates the future actions jointly in both direct and recursive ways. However, when dealing with future action anticipation, one important challenge to address is the future's uncertainty since multiple action sequences may come from or be followed by …