Coordinated Formation Control for Intelligent and Connected Vehicles in Multiple Traffic Scenarios

In this paper, a unified multi-vehicle formation control framework for Intelligent and Connected Vehicles (ICVs) that can apply to multiple traffic scenarios is proposed. In the one-dimensional scenario, different formation geometries are analyzed and the interlaced structure is mathematically modelized to improve driving safety while making full use of the lane capacity. The assignment problem for vehicles and target positions is solved using Hungarian Algorithm to improve the flexibility of the method in multiple scenarios. In the two-dimensional scenario, an improved virtual platoon method is proposed to transfer the complex two-dimensional passing problem to the one-dimensional formation control problem based on the idea of rotation projection. Besides, the vehicle regrouping method is proposed to connect the two scenarios. Simulation results prove that the proposed multi-vehicle formation control framework can apply to multiple typical scenarios and have better performance than existing methods

Experimental Validation of DeeP-LCC for Dissipating Stop-and-Go Waves in Mixed Traffic

We present results on the experimental validation of leading cruise control (LCC) for connected and autonomous vehicles (CAVs). In a mixed traffic situation that is dominated by human-driven vehicles, LCC strategies are promising to smooth undesirable stop-and-go waves. Our experiments are carried out on a mini-scale traffic platform. We first reproduce stop-and-go traffic waves in a miniature scale, and then show that these traffic instabilities can be dissipated by one or a few CAVs that utilize Data-EnablEd Predicted Leading Cruise Control (DeeP-LCC). Rather than identifying a parametric traffic model, DeeP-LCC relies on a data-driven non-parametric behavior representation for traffic prediction and CAV control. DeeP-LCC also incorporates input and output constraints to achieve collision-free guarantees for CAVs. We experimentally demonstrate that DeeP-LCC is able to dissipate traffic waves caused by car-following behavior and significantly improve both driving safety and travel efficiency. CAVs utilizing DeeP-LCC may bring additional societal benefits by mitigating stop-and-go waves in practical traffic.Comment: 8 pages, 6 figure

Divergent Protein Motifs Direct EF-P Mediated Translational Regulation in \u3cem\u3eSalmonella\u3c/em\u3e and \u3cem\u3eEscherichia coli\u3c/em\u3e

Elongation factor P (EF-P) is a universally conserved bacterial translation factor homologous to eukaryotic/archaeal initiation factor 5A. In Salmonella, deletion of the efp gene results in pleiotropic phenotypes, including increased susceptibility to numerous cellular stressors. Only a limited number of proteins are affected by the loss of EF-P, and it has recently been determined that EF-P plays a critical role in rescuing ribosomes stalled at PPP and PPG peptide sequences. Here we present an unbiased in vivo investigation of the specific targets of EF-P by employing stable isotope labeling of amino acids in cell culture (SILAC) to compare the proteomes of wild-type and efp mutant Salmonella. We found that metabolic and motility genes are prominent among the subset of proteins with decreased production in the Δefp mutant. Furthermore, particular tripeptide motifs are statistically overrepresented among the proteins downregulated in efp mutant strains. These include both PPP and PPG but also additional motifs, such as APP and YIRYIR, which were confirmed to induce EF-P dependence by a translational fusion assay. Notably, we found that many proteins containing polyproline motifs are not misregulated in an EF-P-deficient background, suggesting that the factors that govern EF-P-mediated regulation are complex. Finally, we analyzed the specific region of the PoxB protein that is modulated by EF-P and found that mutation of any residue within a specific GSCGPG sequence eliminates the requirement for EF-P. This work expands the known repertoire of EF-P target motifs and implicates factors beyond polyproline motifs that are required for EF-P-mediated regulation

Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes.

Epigenetics contributes to the pathogenesis of immune-mediated diseases like rheumatoid arthritis (RA). Here we show the first comprehensive epigenomic characterization of RA fibroblast-like synoviocytes (FLS), including histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3), open chromatin, RNA expression and whole-genome DNA methylation. To address complex multidimensional relationship and reveal epigenetic regulation of RA, we perform integrative analyses using a novel unbiased method to identify genomic regions with similar profiles. Epigenomically similar regions exist in RA cells and are associated with active enhancers and promoters and specific transcription factor binding motifs. Differentially marked genes are enriched for immunological and unexpected pathways, with "Huntington's Disease Signaling" identified as particularly prominent. We validate the relevance of this pathway to RA by showing that Huntingtin-interacting protein-1 regulates FLS invasion into matrix. This work establishes a high-resolution epigenomic landscape of RA and demonstrates the potential for integrative analyses to identify unanticipated therapeutic targets

Deciphering the Genetic Code of DNA Methylation

DNA methylation plays crucial roles in many biological processes and abnormal DNA methylation patterns are often observed in diseases. Recent studies have shed light on cis-acting DNA elements that regulate locus-specific DNA methylation. More importantly, these new discoveries have shown potentials in clinical application. In this thesis, I first interrogate the current biological foundation for the cis-acting genetic code that regulates DNA methylation. This process involves transcription factors, histone modifications, and DNA secondary structure. In chapter 2, we demonstrate how to find the functional motifs that regulate DNA methylation. We have analyzed 34 diverse whole-genome bisulfite sequencing datasets and have identified 313 identified motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. We show that these motifs are associated with local methylation level, and motif disruption of by mutation leads to significantly altered methylation level of the CpGs in the neighbor regions. Combined with somatic mutations, these motifs improve the prediction of cancer subtypes and patient survival. DNA motif analysis frequently requires intuitive understanding and convenient representation of motifs. In chapter 3, I review how the motifs are typically represented as position weight matrices (PWMs) and propose a new wildcard-style consensus sequence representation based on mutual information theory and Jenson-Shannon Divergence. We name this representation as sequence Motto and have implemented an efficient algorithm with flexible options for converting motif PWMs into Motto from nucleotides, amino acids, and customized alphabets. On the other hand, experimental validation of cis-acting DNA elements benefits from the recent advancement of CRISPR/Cas9 mediated genetic screening. In chapter 4, I present CRISPY, a lightweight, robust CRISPR screening pipeline that unifies single-sgRNA and CREST-seq screening protocols and is capable of profiling peak candidates with existing data of histone modifications, DHS, and ATAC-seq in human and mouse. Combined together, our studies have provided new insights on how genetic code regulates DNA methylation and can be applied to clinical applications. In addition, we provide the tools to efficiently represent the motifs and evaluate their functions in a high-throughput manner

Deciphering the Genetic Code of DNA Methylation

DNA methylation plays crucial roles in many biological processes and abnormal DNA methylation patterns are often observed in diseases. Recent studies have shed light on cis-acting DNA elements that regulate locus-specific DNA methylation. More importantly, these new discoveries have shown potentials in clinical application. In this thesis, I first interrogate the current biological foundation for the cis-acting genetic code that regulates DNA methylation. This process involves transcription factors, histone modifications, and DNA secondary structure. In chapter 2, we demonstrate how to find the functional motifs that regulate DNA methylation. We have analyzed 34 diverse whole-genome bisulfite sequencing datasets and have identified 313 identified motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. We show that these motifs are associated with local methylation level, and motif disruption of by mutation leads to significantly altered methylation level of the CpGs in the neighbor regions. Combined with somatic mutations, these motifs improve the prediction of cancer subtypes and patient survival. DNA motif analysis frequently requires intuitive understanding and convenient representation of motifs. In chapter 3, I review how the motifs are typically represented as position weight matrices (PWMs) and propose a new wildcard-style consensus sequence representation based on mutual information theory and Jenson-Shannon Divergence. We name this representation as sequence Motto and have implemented an efficient algorithm with flexible options for converting motif PWMs into Motto from nucleotides, amino acids, and customized alphabets. On the other hand, experimental validation of cis-acting DNA elements benefits from the recent advancement of CRISPR/Cas9 mediated genetic screening. In chapter 4, I present CRISPY, a lightweight, robust CRISPR screening pipeline that unifies single-sgRNA and CREST-seq screening protocols and is capable of profiling peak candidates with existing data of histone modifications, DHS, and ATAC-seq in human and mouse. Combined together, our studies have provided new insights on how genetic code regulates DNA methylation and can be applied to clinical applications. In addition, we provide the tools to efficiently represent the motifs and evaluate their functions in a high-throughput manner