186 research outputs found
Spatial clustering and common regulatory elements correlate with coordinated gene expression
Many cellular responses to surrounding cues require temporally concerted
transcriptional regulation of multiple genes. In prokaryotic cells, a
single-input-module motif with one transcription factor regulating multiple
target genes can generate coordinated gene expression. In eukaryotic cells,
transcriptional activity of a gene is affected by not only transcription
factors but also the epigenetic modifications and three-dimensional chromosome
structure of the gene. To examine how local gene environment and transcription
factor regulation are coupled, we performed a combined analysis of time-course
RNA-seq data of TGF-\b{eta} treated MCF10A cells and related epigenomic and
Hi-C data. Using Dynamic Regulatory Events Miner (DREM), we clustered
differentially expressed genes based on gene expression profiles and associated
transcription factors. Genes in each class have similar temporal gene
expression patterns and share common transcription factors. Next, we defined a
set of linear and radial distribution functions, as used in statistical
physics, to measure the distributions of genes within a class both spatially
and linearly along the genomic sequence. Remarkably, genes within the same
class despite sometimes being separated by tens of million bases (Mb) along
genomic sequence show a significantly higher tendency to be spatially close
despite sometimes being separated by tens of Mb along the genomic sequence than
those belonging to different classes do. Analyses extended to the process of
mouse nervous system development arrived at similar conclusions. Future studies
will be able to test whether this spatial organization of chromosomes
contributes to concerted gene expression.Comment: 30 pages, 9 figures, accepted in PLoS Computational Biolog
Adaptive supervisory switching control system design for active noise suppression of duct-like application
Active noise suppression for applications where the controlled system response varies with time is a difficult problem, especially for time varying nonlinear systems with large model error. On the basis of adaptive switching supervisory control theory, an adaptive supervisory switching control algorithm is proposed with a new controller switching strategy for active noise suppression of duct-like application. Real time experimental verification tests show that the proposed algorithm is effective with good noise suppression performance
Analysis and implementation of adaptive filtered-X LMS algorithm based on reference signal self-extraction
By comparing conventional FXLMS (filtered-X least mean square) control algorithms, the present paper introduces an improved adaptive vibration control FXLMS algorithm based on reference signal self-extraction. It overcomes the problem of reference signal which correlated with external excitation signal is needed to be predicted in advance, namely, the reference signal is extracted from structural vibration in real time in the process of control algorithm. Its theoretical basis is: get an original vibration signal estimation using the error signal of the system and the estimation value is taken as the reference signal of adaptive filtering. In addition, to verify the feasibility and advantage of the proposed algorithm, we simulate solar panels with piezoelectric smart flexible plate and construct the corresponding experimental platform. Finally, the results presented in this paper demonstrate that the proposed algorithm is feasible, effective and achieve improvement with significantly faster convergence speed and better control effect compared with other algorithms
Construction of all-in-focus images assisted by depth sensing
Multi-focus image fusion is a technique for obtaining an all-in-focus image
in which all objects are in focus to extend the limited depth of field (DoF) of
an imaging system. Different from traditional RGB-based methods, this paper
presents a new multi-focus image fusion method assisted by depth sensing. In
this work, a depth sensor is used together with a color camera to capture
images of a scene. A graph-based segmentation algorithm is used to segment the
depth map from the depth sensor, and the segmented regions are used to guide a
focus algorithm to locate in-focus image blocks from among multi-focus source
images to construct the reference all-in-focus image. Five test scenes and six
evaluation metrics were used to compare the proposed method and representative
state-of-the-art algorithms. Experimental results quantitatively demonstrate
that this method outperforms existing methods in both speed and quality (in
terms of comprehensive fusion metrics). The generated images can potentially be
used as reference all-in-focus images.Comment: 18 pages. This paper has been submitted to Computer Vision and Image
Understandin
A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns
This letter presents a novel method to estimate the relative poses between
RGB-D cameras with minimal overlapping fields of view in a panoramic RGB-D
camera system. This calibration problem is relevant to applications such as
indoor 3D mapping and robot navigation that can benefit from a 360
field of view using RGB-D cameras. The proposed approach relies on
descriptor-based patterns to provide well-matched 2D keypoints in the case of a
minimal overlapping field of view between cameras. Integrating the matched 2D
keypoints with corresponding depth values, a set of 3D matched keypoints are
constructed to calibrate multiple RGB-D cameras. Experiments validated the
accuracy and efficiency of the proposed calibration approach, both superior to
those of existing methods (800 ms vs. 5 seconds; rotation error of 0.56 degrees
vs. 1.6 degrees; and translation error of 1.80 cm vs. 2.5 cm.Comment: 6 pages, 7 figures, under review by IEEE Robotics and Automation
Letters & ICR
Standardized Volume Power Density Boost in Frequency-Up Converted Contact-Separation Mode Triboelectric Nanogenerators
The influence of a mechanical structure’s volume increment on the volume power density (VPD) of triboelectric nanogenerators (TENGs) is often neglected when considering surface charge density and surface power density. This paper aims to address this gap by introducing a standardized VPD metric for a more comprehensive evaluation of TENG performance. The study specifically focuses on 2 frequency-up mechanisms, namely, the integration of planetary gears (PG-TENG) and the implementation of a double-cantilever structure (DC-TENG), to investigate their impact on VPD. The study reveals that the PG-TENG achieves the highest volume average power density, measuring at 0.92 W/m3. This value surpasses the DC-TENG by 1.26 times and the counterpart TENG by a magnitude of 69.9 times. Additionally, the PG-TENG demonstrates superior average power output. These findings introduce a new approach for enhancing TENGs by incorporating frequency-up mechanisms, and highlight the importance of VPD as a key performance metric for evaluating TENGs
Fast and non-destructive detection on the EVA gel content in photovoltaic modules by optical reflection
Poly(ethylene-co-vinyl acetate) (EVA) has been the dominating material in the photovoltaic (PV) encapsulant market for decades, owing to its superior cost-performance balance. To achieve its desired material properties, EVA undergoes a curing reaction during the module encapsulation process. The resulting EVA gel content after encapsulation is an important criterion for the module encapsulation quality control. Normally, the determination of gel content is achieved using a tedious solvent extraction method. In this paper, a fast and nondestructive detection method on the EVA gel content based on the optical reflection is explored. First, the homogeneity of the EVA gel content distribution after the standard EVA encapsulation process is studied. Then, the feasibility of the proposed optical approach applied to transparent modules is investigated. After that, a method is developed to apply it to opaque modules by incorporating a mirror into the module construction. It was found that the haze factor of the reflected light correlates well with the EVA gel content in the opaque modules. This proof-of-concept work could lead to the development of a fast and nondestructive tool for detecting the EVA gel content in both transparent and opaque PV modules, which is promising for integration as an inline diagnostic tool in the module manufacturing line
Hainan sport tourism development—A SWOT analysis
Hainan, as a popular tourism destination, is well-promoted by the Chinese central government. In particular, both central and local governments encourage Hainan’s sport tourism-related professionals to develop sport tourism as one of the most important tourist activities in Hainan. However, previous research has not reported on Hainan’s sport tourism strengths, weaknesses, opportunities, and threats as a tourism destination or a sports event host. This study uses SWOT analysis to identify the strengths, weaknesses, opportunities, and threats in the context of Hainan’s sport tourism development. A total of 12 dimensions, including branding, culture, finance, infrastructure, location, market, nature, policy, product, specialty, sustainability, and tourist were generated from our data analysis. In addition, a total of five future directions, including emphasizing event-oriented sport tourism, prioritizing sport motivation, identifying major sport tourism markets, making the rational use of sport tourism resources, and nurturing sport culture, are recommended as a result of this study
Size-Controlled Large-Diameter and Few-Walled Carbon Nanotube Catalysts for Oxygen Reduction
We demonstrate a new strategy for tuning the size of large-diameter and few-walled nitrogen-doped carbon nanotubes (N-CNTs) from 50 to 150 nm by varying the transition metal (TM = Fe, Co, Ni or Mn) used to catalyze graphitization of dicyandiamide. Fe yielded the largest tubes, followed by Co and Ni, while Mn produced a clot-like carbon morphology. We show that morphology is correlated with electrocatalytic activity for the oxygen reduction reaction (ORR). A clear trend of Fe \u3e Co \u3e Ni \u3e Mn for the ORR catalytic activity was observed, in both alkaline media and more demanding acidic media. The Fe-derived N-CNTs exhibited the highest BET (∼870 m2 g−1) and electrochemically accessible (∼450 m2 g−1) surface areas and, more importantly, the highest concentration of nitrogen incorporated into the carbon planes. Thus, in addition to the intrinsic high activity of Fe-derived catalysts, the high surface area and nitrogen doping contribute to high ORR activity. This work, for the first time, demonstrates size-controlled synthesis of large-diameter N-doped carbon tube electrocatalysts by varying the metal used in N-CNT generation. Electrocatalytic activity of the Fe-derived catalyst is already the best among studied metals, due to the high intrinsic activity of possible Fe–N coordination. This work further provides a promising route to advanced Fe–N–C nonprecious metal catalysts by generating favorable morphology with more active sites and improved mass transfer
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