Low-complexity full-field ultrafast nonlinear dynamics prediction by a convolutional feature separation modeling method

The modeling and prediction of the ultrafast nonlinear dynamics in the optical fiber are essential for the studies of laser design, experimental optimization, and other fundamental applications. The traditional propagation modeling method based on the nonlinear Schr\"odinger equation (NLSE) has long been regarded as extremely time-consuming, especially for designing and optimizing experiments. The recurrent neural network (RNN) has been implemented as an accurate intensity prediction tool with reduced complexity and good generalization capability. However, the complexity of long grid input points and the flexibility of neural network structure should be further optimized for broader applications. Here, we propose a convolutional feature separation modeling method to predict full-field ultrafast nonlinear dynamics with low complexity and high flexibility, where the linear effects are firstly modeled by NLSE-derived methods, then a convolutional deep learning method is implemented for nonlinearity modeling. With this method, the temporal relevance of nonlinear effects is substantially shortened, and the parameters and scale of neural networks can be greatly reduced. The running time achieves a 94% reduction versus NLSE and an 87% reduction versus RNN without accuracy deterioration. In addition, the input pulse conditions, including grid point numbers, durations, peak powers, and propagation distance, can be flexibly changed during the predicting process. The results represent a remarkable improvement in the ultrafast nonlinear dynamics prediction and this work also provides novel perspectives of the feature separation modeling method for quickly and flexibly studying the nonlinear characteristics in other fields.Comment: 15 pages,9 figure

Regulation of antibiotic biosynthesis in actinomycetes: Perspectives and challenges

Actinomycetes are the main sources of antibiotics. The onset and level of production of each antibiotic is subject to complex control by multi-level regulators. These regulators exert their functions at hierarchical levels. At the lower level, cluster-situated regulators (CSRs) directly control the transcription of neighboring genes within the gene cluster. Higher-level pleiotropic and global regulators exert their functions mainly through modulating the transcription of CSRs. Advances in understanding of the regulation of antibiotic biosynthesis in actinomycetes have inspired us to engineer these regulators for strain improvement and antibiotic discovery. Keywords: Antibiotic biosynthesis, Regulation, Actinomycetes, Genetic manipulation, Strain improvement, Antibiotic discover

Autoaggregation Response of Fusobacterium nucleatum▿ †

Fusobacterium nucleatum is a gram-negative oral bacterial species associated with periodontal disease progression. This species is perhaps best known for its ability to adhere to a vast array of other bacteria and eukaryotic cells. Numerous studies of F. nucleatum have examined various coaggregation partners and inhibitors, but it is largely unknown whether these interactions induce a particular genetic response. We tested coaggregation between F. nucleatum ATCC strain 25586 and various species of Streptococcus in the presence of a semidefined growth medium containing saliva. We found that this condition could support efficient coaggregation but, surprisingly, also stimulated a similar degree of autoaggregation. We further characterized the autoaggregation response, since few reports have examined this in F. nucleatum. After screening several common coaggregation inhibitors, we identified l-lysine as a competitive inhibitor of autoaggregation. We performed a microarray analysis of the planktonic versus autoaggregated cells and found nearly 100 genes that were affected after only about 60 min of aggregation. We tested a subset of these genes via real-time reverse transcription-PCR and confirmed the validity of the microarray results. Some of these genes were also found to be inducible in cell pellets created by centrifugation. Based upon these data, it appears that autoaggregation activates a genetic program that may be utilized for growth in a high cell density environment, such as the oral biofilm

GouR, a TetR Family Transcriptional Regulator, Coordinates the Biosynthesis and Export of Gougerotin in Streptomyces graminearus

Waterworks, view of a trough made to carry water; Was principal city of Crete throughout Antiquity; flourished ca. 2000-1400 BCE; was seat of legendary king Minos and labyrinth of Daedalus; best known for ruins of the great Minoan palace and Neolithic deposits. Source: Thesaurus of Geographic Names (Notes) [website]; http://www.getty.edu/research/conducting_research/vocabularies/tgn/ (accessed 2/14/2008

The Streptococcus mutans IrvR Repressor Is a CI-Like Regulator That Functions through Autocleavage and Clp-Dependent Proteolysis▿

Previous work has shown that irvR is required for the proper regulation of genetic competence and dextran-dependent aggregation due to its ability to repress the transcription regulator irvA. In this study, we determined the mechanism used to relieve the repression of irvA. We demonstrate that IrvR is a “LexA-like” protein with four conserved amino acid residues likely required for IrvR autocleavage activity. Furthermore, recombinant IrvR protein purified from Escherichia coli was competent to undergo autocleavage in vitro. Using several truncated IrvR constructs, we show that the amino acids adjacent to the autocleavage site are essential for relieving irvA repression and engaging the irvA-dependent regulatory pathway primarily through the ClpXP and ClpCP proteases. By extending the IrvR C terminus with an epitope derived from the autocleavage site, we were also able to create a constitutive Clp-dependent degradation of the full-length IrvR protein. This suggests that the derepression of irvA occurs through a two-step mechanism involving the initial autocleavage of IrvR and exposure of a proteolytic degradation sequence followed by Clp-dependent degradation of the IrvR DNA binding domain. Thus, irvA derepression is highly analogous to the genetic switch mechanism used to regulate lysogeny in bacteriophages

Biosynthesis and Chemical Synthesis of Albomycin Nucleoside Antibiotics

The widespread emergence of antibiotic-resistant bacteria highlights the urgent need for new antimicrobial agents. Albomycins are a group of naturally occurring sideromycins with a thionucleoside antibiotic conjugated to a ferrichrome-type siderophore. The siderophore moiety serves as a vehicle to deliver albomycins into bacterial cells via a “Trojan horse” strategy. Albomycins function as specific inhibitors of seryl-tRNA synthetases and exhibit potent antimicrobial activities against both Gram-negative and Gram-positive bacteria, including many clinical pathogens. These distinctive features make albomycins promising drug candidates for the treatment of various bacterial infections, especially those caused by multidrug-resistant pathogens. We herein summarize findings on the discovery and structure elucidation, mechanism of action, biosynthesis and immunity, and chemical synthesis of albomcyins, with special focus on recent advances in the biosynthesis and chemical synthesis over the past decade (2012–2022). A thorough understanding of the biosynthetic pathway provides the basis for pathway engineering and combinatorial biosynthesis to create new albomycin analogues. Chemical synthesis of natural congeners and their synthetic analogues will be useful for systematic structure–activity relationship (SAR) studies, and thereby assist the design of novel albomycin-derived antimicrobial agents

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

Airborne (or satellite) gravity measurement is a commonly used remote sensing method to obtain the underground density distribution. Airborne gravity gradiometry data have a higher horizontal resolution to shallower causative sources than airborne gravity anomaly, so joint exploration of airborne gravity and its gradient data can simultaneously obtain the anomaly feature of sources with different depths. The most commonly used joint inversion method of gravity and its gradient data is the data combined method, which is to combine all the components into a data matrix as mutual constraints to reduce ambiguity and non-uniqueness. In order to obtain higher resolution results, we proposed a cooperate density-integrated inversion method of airborne gravity and its gradient data, which firstly carried out the joint inversion using cross-gradient constraints to obtain two density structures, and then fused two recovered models into a result through Fourier transform; finally, data combined joint inversion of airborne gravity, and gradient data were reperformed to achieve high-resolution density result using fused density results as a reference model. Compared to the data combined joint inversion method, the proposed cooperate density-integrated inversion method can obtain higher resolution and more accurate density distribution of shallow and deep bodies meanwhile. We also applied it to real data in the mining area of western Liaoning Province, China. The results showed that the depth of the skarn-type iron mine in the region is about 900–1300 m and gives a more specific distribution compared to the geological results, which provided reliable data for the next exploration plan

Friction Stir Welding of Dissimilar Aluminum Alloy Combinations: State-of-the-Art

Friction stir welding (FSW) has enjoyed great success in joining aluminum alloys. As lightweight structures are designed in higher numbers, it is only natural that FSW is being explored to join dissimilar aluminum alloys. The use of different aluminum alloy combinations in applications offers the combined benefit of cost and performance in the same component. This review focuses on the application of FSW in dissimilar aluminum alloy combinations in order to disseminate research this topic. The review details published works on FSWed dissimilar aluminum alloys. The detailed summary of literature lists welding parameters for the different aluminum alloy combinations. Furthermore, auxiliary welding parameters such as positioning of the alloy, tool rotation speed, welding speed and tool geometry are discussed. Microstructural features together with joint mechanical properties, like hardness and tensile strength measurements, are presented. At the end, new directions for the joining of dissimilar aluminum alloy combinations should guide further research to extend as well as to improve the process, which is expected to raise further interest on the topic

Robust core tensor dictionary learning with modified Gaussian mixture model for multispectral image restoration

The multispectral remote sensing image (MS-RSI) is degraded existing multi-spectral camera due to various hardware limitations. In this paper, we propose a novel core tensor dictionary learning approach with the robust modified Gaussian mixture model for MS-RSI restoration. First, the multispectral patch is modeled by three-order tensor and high-order singular value decomposition is applied to the tensor. Then the task of MS-RSI restoration is formulated as a minimum sparse core tensor estimation problem. To improve the accuracy of core tensor coding, the core tensor estimation based on the robust modified Gaussian mixture model is introduced into the proposed model by exploiting the sparse distribution prior in image. When applied to MS-RSI restoration, our experimental results have shown that the proposed algorithm can better reconstruct the sharpness of the image textures and can outperform several existing state-of-the-art multispectral image restoration methods in both subjective image quality and visual perception.Published versio