Novel Cluster AZ Arthrobacter phages Powerpuff, Lego, and YesChef exhibit close functional relationships with Microbacterium phages

Bacteriophages exhibit a vast spectrum of relatedness and there is increasing evidence of close genomic relationships independent of host genus. The variability in phage similarity at the nucleotide, amino acid, and gene content levels confounds attempts at quantifying phage relatedness, especially as more novel phages are isolated. This study describes three highly similar novel Arthrobacter globiformis phages–Powerpuff, Lego, and YesChef–which were assigned to Cluster AZ using a nucleotide-based clustering parameter. Phages in Cluster AZ, Microbacterium Cluster EH, and the former Microbacterium singleton Zeta1847 exhibited low nucleotide similarity. However, their gene content similarity was in excess of the recently adopted Microbacterium clustering parameter, which ultimately resulted in the reassignment of Zeta1847 to Cluster EH. This finding further highlights the importance of using multiple metrics to capture phage relatedness. Additionally, Clusters AZ and EH phages encode a shared integrase indicative of a lysogenic life cycle. In the first experimental verification of a Cluster AZ phage’s life cycle, we show that phage Powerpuff is a true temperate phage. It forms stable lysogens that exhibit immunity to superinfection by related phages, despite lacking identifiable repressors typically required for lysogenic maintenance and superinfection immunity. The ability of phage Powerpuff to undergo and maintain lysogeny suggests that other closely related phages may be temperate as well. Our findings provide additional evidence of significant shared phage genomic content spanning multiple actinobacterial host genera and demonstrate the continued need for verification and characterization of life cycles in newly isolated phages.

Reliability assessment of autonomous vehicles based on the safety control structure

The recent social trends and accelerated technological progress culminated in the development of autonomous vehicles (AVs). Reliability assessment for AV systems is in high demand before its market launch. In safety-critical systems (SCSs) such as AV systems, the reliability concept should be broadened to consider more safety-related issues. In this paper, reliability is defined as the probability that the system performs satisfactorily for a given period of time under stated conditions. This paper proposes a reliability assessment framework of AV, consisting of three main stages: (i) modeling the safety control structure through the Systems-Theoretic Accident Model and Processes (STAMP); (ii) mapping the control structure and functional relationships to a directed acyclic graph (DAG); and (iii) construct a Bayesian network (BN) on DAG to assess the system reliability. The fully automated (level 5) vehicle system is shown as a numeric example to illustrate how this suggested framework works. A brief discussion on involving human factors in systems to analyze lower levels of automated vehicles is also included, demonstrating the need for further research on real case studies.

Geometric parameters optimization of a two-dimensional phoxonic crystal with dual forbidden band characteristics

In this paper, a novel phoxonic crystal (PxC) structure composed of silicon, with optimal dual phononic band gap (PNBG) and photonic band gap (PTBG), is presented. Using the finite element analysis method, both the transmission characteristics and dispersion relation of PNBG and PTBG are calculated, and the existence of dual BGs is demonstrated by the means of the analysis of transmission for the PxC structure. The influences of structural parameters on the dual forbidden band characteristics are further explored, the sensitive structure parameters can be determined: the width of elastic beams, the length of square silicon, and the length of square hole. Using the orthogonal test, 25 experimental runs based on 3-factor and 5-level experiment are performed to finish the numerical experimental design and analysis. Four functional relationships can be acquired between the three sensitive parameters and dual BGs. Finally, the unified objective function method is employed to perform the construction of the single objective optimization model for the purpose of obtaining the optimal dual BGs and the corresponding optimal parameter combinations of the PxC structure. Such scheme can be used as the potential optimization way, which may find wide application in the development and design of PxCs.

Seasonal variability in carbon:234thorium ratios of suspended and sinking particles in coastal Antarctic waters: Field data and modeling synthesis

238U-234Th disequilibrium is a powerful tool for investigating particle cycling and carbon export associated with the ocean's biological carbon pump. However, the interpretation of this method is complicated by multiple processes that can modify carbon:thorium ratios over small spatial scales. We investigated seasonal variability in the thorium and carbon cycles at a coastal site in the Western Antarctic Peninsula. Throughout the ice-free summer season, we quantified carbon and 234Th vertical flux, total water column 234Th, particulate 234Th, and the C:234Th ratios of sinking material and bulk suspended material. Simultaneous identification and separation of fecal pellets from sinking material showed that fecal pellets (primarily from krill) contributed 56% of carbon flux and that as a result of lower C:234Th ratios than suspended particles, these fecal pellets were primary drivers of variability in the C:234Th ratios of sinking material. Bulk suspended particles had highly variable C:234Th ratios and were consistently elevated in the euphotic zone relative to deeper waters. The fraction of 234Th adsorbed onto particles was positively correlated with chlorophyll and particulate organic carbon (POC) concentrations. The C:234Th ratios of suspended particles were positively correlated with POC, although during the spring diatom bloom C:234Th ratios were lower than would have been predicted based on POC concentrations alone. We hypothesize that diatom production of transparent exopolymers may have led to enhanced rates of thorium adsorption during the bloom, thus decreasing the C:234Th ratios. We used a Bayesian model selection approach to develop and parameterize mechanistic models to simulate thorium sorption dynamics. The best model incorporated one slowly-sinking POC pool and rapidly-sinking fecal pellets, with second-order sorption kinetics. The model accurately simulated temporal patterns in the C:234Th ratios of sinking and suspended particles and the fraction of 234Th adsorbed to particles. However, it slightly over-estimated C:234Th ratios during the spring (diatom-dominated) bloom and underestimated C:234Th ratios during the fall (mixed-assemblage) bloom. Optimized model parameters for thorium sorption and desorption were 0.0047 +/- 0.0002 m3 mmol C-1 d-1 and 0.017 +/- 0.008 d-1, respectively. Our results highlight the important role that specific taxa can play in modifying the C:234Th ratio of sinking and suspended particles and provide guidance for future studies that use 234Th measurements to investigate the functional relationships driving the efficiency of the biological pump.

Frictional Behaviour of the Microstructural Surfaces Created by Cylindrical Grinding Processes

Cylindrical surface grinding can create defined textural patterns on a component with high quantity. This paper presents an experimental investigation of the frictional behaviours of ground cylindrical microstructural surfaces under a well lubrication condition. It shows that the coefficient of friction (COF) of microstructural surface is influenced by different workload and rotation speed. The results reveal that conventional surface roughness parameters do not present the influence of surface microstructure on friction performance well. However, the paper presents an interesting discovery that the friction behaviour of microstructural surfaces created by grinding could be controlled by combining dressing and grinding conditions. Such a discovery provides a logic way to reduce surface friction for energy efficiency applications. A few functional relationships have been established to illustrate the influence of microstructural features on friction. It was found that the ground microstructural surface could improve friction performance up to 20% compared to the smoother surfaces without defined surface textural patterns.

Transcriptome Profiling Based on Larvae at Different Time Points After Hatching Provides a Core Set of Gene Resource for Understanding the Metabolic Mechanisms of the Brood-Care Behavior in Octopus ocellatus

The metabolic processes of organisms are very complex. Each process is crucial and affects the growth, development, and reproduction of organisms. Metabolism-related mechanisms in Octopus ocellatus behaviors have not been widely studied. Brood-care is a common behavior in most organisms, which can improve the survival rate and constitution of larvae. Octopus ocellatus carried out this behavior, but it was rarely noticed by researchers before. In our study, 3,486 differentially expressed genes (DEGs) were identified based on transcriptome analysis of O. ocellatus. We identify metabolism-related DEGs using GO and KEGG enrichment analyses. Then, we construct protein–protein interaction networks to search the functional relationships between metabolism-related DEGs. Finally, we identified 10 hub genes related to multiple gene functions or involved in multiple signal pathways and verified them using quantitative real-time polymerase chain reaction (qRT-PCR). Protein–protein interaction networks were first used to study the effects of brood-care behavior on metabolism in the process of growing of O. ocellatus larvae, and the results provide us valuable genetic resources for understanding the metabolic processes of invertebrate larvae. The data lay a foundation for further study the brood-care behavior and metabolic mechanisms of invertebrates.

Fungal xenosiderophores from mycobiota and diet promote Salmonella colonization of the inflamed gut

The fungal gut microbiota (mycobiota) has been implicated in diseases that disturb gut homeostasis. However, little is known about functional relationships between bacteria and fungi in the gut during infectious colitis. We investigated the role of fungal metabolites during infection with the intestinal pathogen Salmonella enterica serovar Typhimurium. We found that in the gut lumen, both the mycobiota and fungi present in the diet can be a source of siderophores, small molecules that scavenge iron from the host. The ability to use fungal siderophores, such as ferrichrome and coprogen, conferred a competitive growth advantage to Salmonella strains expressing the fungal siderophore receptors FhuA or FhuE in vitro and in a mouse model. Our study highlights the role of inter-kingdom cross-feeding between fungi and Salmonella, and elucidates a new function for the gut mycobiota, revealing the importance of these under-studied members of the gut ecosystem during bacterial infection.

An Econometric Model for the Analysis of the Influence of the Refurbishment Costs on Housing Prices

With reference to the Italian context, the present research intends to analyze the functional relationships between the unit cost of restructuring and the selling prices in the residential segment. The analysis has been contextualized to the three clusters (Northern Italy, Central Italy, Southern Italy and Islands) in which the Italian territory is commonly divided. The case study concerns 965 residential units sold in the first half of 2019 and located in the 103 provincial capitals. The implemented econometric technique is a data-driven method that employs a genetic algorithm and allows the identification of the most influencing factors among the explanatory variables considered. For each cluster, a model has been selected in order to study the influence of unit cost of restructuring on housing prices.

Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data

Background Constructing gene coexpression networks is a powerful approach for analyzing high-throughput gene expression data towards module identification, gene function prediction, and disease-gene prioritization. While optimal workflows for constructing coexpression networks, including good choices for data pre-processing, normalization, and network transformation, have been developed for microarray-based expression data, such well-tested choices do not exist for RNA-seq data. Almost all studies that compare data processing and normalization methods for RNA-seq focus on the end goal of determining differential gene expression. Results Here, we present a comprehensive benchmarking and analysis of 36 different workflows, each with a unique set of normalization and network transformation methods, for constructing coexpression networks from RNA-seq datasets. We test these workflows on both large, homogenous datasets and small, heterogeneous datasets from various labs. We analyze the workflows in terms of aggregate performance, individual method choices, and the impact of multiple dataset experimental factors. Our results demonstrate that between-sample normalization has the biggest impact, with counts adjusted by size factors producing networks that most accurately recapitulate known tissue-naive and tissue-aware gene functional relationships. Conclusions Based on this work, we provide concrete recommendations on robust procedures for building an accurate coexpression network from an RNA-seq dataset. In addition, researchers can examine all the results in great detail at https://krishnanlab.github.io/RNAseq_coexpression to make appropriate choices for coexpression analysis based on the experimental factors of their RNA-seq dataset.