A Brief Review of Mueller Matrix Calculations Associated with Oceanic Particles

The complete Stokes vector contains much more information than the radiance of light for the remote sensing of the ocean. Unlike the conventional radiance-only radiative transfer simulations, a full Mueller matrix-Stokes vector treatment provides a rigorous and correct approach for solving the transfer of radiation in a scattering medium, such as the atmosphere-ocean system. In fact, radiative transfer simulation without considering the polarization state always gives incorrect results and the extent of the errors induced depends on a particular application being considered. However, the rigorous approach that fully takes the polarization state into account requires the knowledge of the complete single-scattering properties of oceanic particles with various sizes, morphologies, and refractive indices. For most oceanic particles, the comparisons between simulations and observations have demonstrated that the “equivalent-spherical” approximation is inadequate. We will therefore briefly summarize the advantages and disadvantages of a number of light scattering methods for non-spherical particles. Furthermore, examples for canonical cases with specifically oriented particles and randomly oriented particles will be illustrated

Application of 640-Volume CT in Idiopathic Pulmonary Hemosiderosis in Adults

Objective: To have a deep understanding about idiopathic pulmonary hemosiderosis (IPH). Methods: Clinical and imaging data of 6 patients of IPH in adults were collected and analyzed. Results: Imaging findings must be combined with clinical laboratory examination to make a diagnosis of IPH. Transbronchial lung biopsy (TBLB) is the gold standard for evaluation of suspected patients. Conclusion: IPH is extremely rare amid adults, and imaging results on single chest CT are nonspecific. The longitudinal follow-up is critical for diagnosis and posttreatment evaluation

Pressure-Arching Characteristics of Fractured Strata Structure during Shallow Horizontal Coal Mining

It is an important problem for the alternated strong and weak roof weighting to threat the safety of working face during shallow coal mining and the total thickness breaking of the thin bedrock to cause the serious ground subsidence. To reveal the mechanism of the abnormal mining damage, the pressure-arching rule in overlying strata was studied. Based on the monitoring data of the typical shallow coal working face, the mechanical models of the symmetrical stress arch, the squeezed arch and the hinged structure of the fractured strata were established, and the difference of the load bearing capacity between the structures and the influencing factors was analysed by the deduced formula calculation. Then the evolution characteristics of the pressure-arch in the fractured strata were revealed by the numerical simulation analysis. The results show that the global pressure-arch of multilayer strata always exits in the surrounding rock and moves forward with continuous mining. The single pressure-arch and hinged structure are formed in each stratum under the global pressure-arch. The pressure-arch enables the fractured strata to carry load efficiently, and the instability of the pressure-arch can cause strong roof weighting and ground subsidence. These conclusions provide a theoretical reference for the stability control of the overlying strata structure under shallow coal mining

Bacterial regulon modeling and prediction based on systematic \u3ci\u3ecis\u3c/i\u3e regulatory motif analyses

Regulons are the basic units of the response system in a bacterial cell, and each consists of a set of transcriptionally co-regulated operons. Regulon elucidation is the basis for studying the bacterial global transcriptional regulation network. In this study, we designed a novel co-regulation score between a pair of operons based on accurate operon identification and cis regulatory motif analyses, which can capture their co-regulation relationship much better than other scores. Taking full advantage of this discovery, we developed a new computational framework and built a novel graph model for regulon prediction. This model integrates the motif comparison and clustering and makes the regulon prediction problem substantially more solvable and accurate. To evaluate our prediction, a regulon coverage score was designed based on the documented regulons and their overlap with our prediction; and a modified Fisher Exact test was implemented to measure how well our predictions match the co-expressed modules derived from E. coli microarray gene-expression datasets collected under 466 conditions. The results indicate that our program consistently performed better than others in terms of the prediction accuracy. This suggests that our algorithms substantially improve the state-of-the-art, leading to a computational capability to reliably predict regulons for any bacteria

An Integrative and Applicable Phylogenetic Footprinting Framework for \u3cem\u3ecis\u3c/em\u3e-regulatory Motifs Identification in Prokaryotic Genomes

Background: Phylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction. Results: Here we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP3 ). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP3 consistently outperformed other popular motif finding tools. We have integrated MP3 into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes. Conclusion: The performance evaluation indicated that MP3 is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance progress in elucidating transcription regulation mechanism, thus provide benefit to the genomic research community and prokaryotic genome researchers in particular

Oxygen-Vacancy Abundant Ultrafine Co_3O_4/Graphene Composites for High-Rate Supercapacitor Electrodes

The metal oxides/graphene composites are one of the most promising supercapacitors (SCs) electrode materials. However, rational synthesis of such electrode materials with controllable conductivity and electrochemical activity is the topical challenge for high-performance SCs. Here, the Co_3O_4/graphene composite is taken as a typical example and develops a novel/universal one-step laser irradiation method that overcomes all these challenges and obtains the oxygen-vacancy abundant ultrafine Co_3O_4 nanoparticles/graphene (UCNG) composites with high SCs performance. First-principles calculations show that the surface oxygen vacancies can facilitate the electrochemical charge transfer by creating midgap electronic states. The specific capacitance of the UCNG electrode reaches 978.1 F g^(−1) (135.8 mA h g^(−1)) at the current densities of 1 A g^(−1) and retains a high capacitance retention of 916.5 F g^(−1) (127.3 mA h g^(−1)) even at current density up to 10 A g^(−1), showing remarkable rate capability (more than 93.7% capacitance retention). Additionally, 99.3% of the initial capacitance is maintained after consecutive 20 000 cycles, demonstrating enhanced cycling stability. Moreover, this proposed laser-assisted growth strategy is demonstrated to be universal for other metal oxide/graphene composites with tuned electrical conductivity and electrochemical activity

Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework

The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whereupon the rules governing protein-DNA binding are being revealed. Here, we developed a new method (DEep Sequence and Shape mOtif or DESSO) for cis-regulatory motif prediction using deep neural networks and the binomial distribution model. DESSO outperformed existing tools, including DeepBind, in predicting motifs in 690 human ENCODE ChIP-sequencing datasets. Furthermore, the deep-learning framework of DESSO expanded motif discovery beyond the state-of-the-art by allowing the identification of known and new protein-protein-DNA tethering interactions in human transcription factors (TFs). Specifically, 61 putative tethering interactions were identified among the 100 TFs expressed in the K562 cell line. In this work, the power of DESSO was further expanded by integrating the detection of DNA shape features. We found that shape information has strong predictive power for TF-DNA binding and provides new putative shape motif information for human TFs. Thus, DESSO improves in the identification and structural analysis of TF binding sites, by integrating the complexities of DNA binding into a deep-learning framework

Oxygen-Vacancy Abundant Ultrafine Co_3O_4/Graphene Composites for High-Rate Supercapacitor Electrodes

The metal oxides/graphene composites are one of the most promising supercapacitors (SCs) electrode materials. However, rational synthesis of such electrode materials with controllable conductivity and electrochemical activity is the topical challenge for high-performance SCs. Here, the Co_3O_4/graphene composite is taken as a typical example and develops a novel/universal one-step laser irradiation method that overcomes all these challenges and obtains the oxygen-vacancy abundant ultrafine Co_3O_4 nanoparticles/graphene (UCNG) composites with high SCs performance. First-principles calculations show that the surface oxygen vacancies can facilitate the electrochemical charge transfer by creating midgap electronic states. The specific capacitance of the UCNG electrode reaches 978.1 F g^(−1) (135.8 mA h g^(−1)) at the current densities of 1 A g^(−1) and retains a high capacitance retention of 916.5 F g^(−1) (127.3 mA h g^(−1)) even at current density up to 10 A g^(−1), showing remarkable rate capability (more than 93.7% capacitance retention). Additionally, 99.3% of the initial capacitance is maintained after consecutive 20 000 cycles, demonstrating enhanced cycling stability. Moreover, this proposed laser-assisted growth strategy is demonstrated to be universal for other metal oxide/graphene composites with tuned electrical conductivity and electrochemical activity

IRIS3: integrated cell-type-specific regulon inference server from single-cell RNA-Seq

group of genes controlled as a unit, usually by the same repressor or activator gene, is known as a regulon. The ability to identify active regulons within a specific cell type, i.e., cell-type-specific regulons (CTSR), provides an extraordinary opportunity to pinpoint crucial regulators and target genes responsible for complex diseases. However, the identification of CTSRs from single-cell RNA-Seq (scRNA-Seq) data is computationally challenging. We introduce IRIS3, the first-of-its-kind web server for CTSR inference from scRNA-Seq data for human and mouse. IRIS3 is an easy-to-use server empowered by over 20 functionalities to support comprehensive interpretations and graphical visualizations of identified CTSRs. CTSR data can be used to reliably characterize and distinguish the corresponding cell type from others and can be combined with other computational or experimental analyses for biomedical studies. CTSRs can, therefore, aid in the discovery of major regulatory mechanisms and allow reliable constructions of global transcriptional regulation networks encoded in a specific cell type. The broader impact of IRIS3 includes, but is not limited to, investigation of complex diseases hierarchies and heterogeneity, causal gene regulatory network construction, and drug development