Differential responses of soil bacteria and fungi to altered precipitation in a meadow steppe

Soil microorganisms are essential participants in ecosystem processes, yet their composition, diversity, and function are affected by altered precipitation. The patterns and key processes driving the effects of changes in precipitation on soil bacterial and fungal communities remain unclear. To better understand how changes in precipitation may affect soil microorganisms, we conducted a three-year field precipitation manipulation experiment, with treatments ranging from 50% reduction to 50% increases in precipitation, in a meadow steppe located in northeast China. Our results demonstrated that the bacterial community was more sensitive to changes in precipitation than the fungal community. The fungal community was sensitive to inter-annual differences in precipitation, but not to the treatment-induced changes in precipitation. Increased annual precipitation shifted the dominance of the microbial community from bacteria to fungi. Over the precipitation range (200–280 mm) soil microbial biomass and diversity are maximal, below the long-term mean annual precipitation (430 mm) for this site. Soil water content, pH, and total phosphorus were the main factors related to the variance in soil microbial community diversity. Results show non-linear, time-dependent, and interacting responses of bacterial and fungal biomass and diversity to soil properties under gradients of altered precipitation magnitude in this semi-arid grassland

Piercing Through Highly Obscured and Compton-thick AGNs in the Chandra Deep Fields: I. X-ray Spectral and Long-term Variability Analyses

We present a detailed X-ray spectral analysis of 1152 AGNs selected in the Chandra Deep Fields (CDFs), in order to identify highly obscured AGNs ($N_{\rm H} > 10^{23}\ \rm cm^{-2}$). By fitting spectra with physical models, 436 (38%) sources with $L_{\rm X} > 10^{42}\ \rm erg\ s^{-1}$ are confirmed to be highly obscured, including 102 Compton-thick (CT) candidates. We propose a new hardness-ratio measure of the obscuration level which can be used to select highly obscured AGN candidates. The completeness and accuracy of applying this method to our AGNs are 88% and 80%, respectively. The observed logN-logS relation favors cosmic X-ray background models that predict moderate (i.e., between optimistic and pessimistic) CT number counts. 19% (6/31) of our highly obscured AGNs that have optical classifications are labeled as broad-line AGNs, suggesting that, at least for part of the AGN population, the heavy X-ray obscuration is largely a line-of-sight effect, i.e., some high-column-density clouds on various scales (but not necessarily a dust-enshrouded torus) along our sightline may obscure the compact X-ray emitter. After correcting for several observational biases, we obtain the intrinsic NH distribution and its evolution. The CT-to-highly-obscured fraction is roughly 52% and is consistent with no evident redshift evolution. We also perform long-term (~17 years in the observed frame) variability analyses for 31 sources with the largest number of counts available. Among them, 17 sources show flux variabilities: 31% (5/17) are caused by the change of NH, 53% (9/17) are caused by the intrinsic luminosity variability, 6% (1/17) are driven by both effects, and 2 are not classified due to large spectral fitting errors.Comment: 32 pages, 21 figures, 9 tables, accepted for publication in Ap

A survey and classification of software-defined storage systems

The exponential growth of digital information is imposing increasing scale and efficiency demands on modern storage infrastructures. As infrastructure complexity increases, so does the difficulty in ensuring quality of service, maintainability, and resource fairness, raising unprecedented performance, scalability, and programmability challenges. Software-Defined Storage (SDS) addresses these challenges by cleanly disentangling control and data flows, easing management, and improving control functionality of conventional storage systems. Despite its momentum in the research community, many aspects of the paradigm are still unclear, undefined, and unexplored, leading to misunderstandings that hamper the research and development of novel SDS technologies. In this article, we present an in-depth study of SDS systems, providing a thorough description and categorization of each plane of functionality. Further, we propose a taxonomy and classification of existing SDS solutions according to different criteria. Finally, we provide key insights about the paradigm and discuss potential future research directions for the field.This work was financed by the Portuguese funding agency FCT-Fundacao para a Ciencia e a Tecnologia through national funds, the PhD grant SFRH/BD/146059/2019, the project ThreatAdapt (FCT-FNR/0002/2018), the LASIGE Research Unit (UIDB/00408/2020), and cofunded by the FEDER, where applicable

AN INTEGRATED APPROACH TO STUDYING AND ENGINEERING BACTERIAL TYPE II POLYKETIDE CORE STRUCTURE BIOSYNTHESIS

Natural products including alkaloids, phenylpropanoids, polyketides, terpenoids and antibiotics provide abundant resources for drugs and drug leads. Type II polyketides (PK-IIs) are a large array of aromatic polyketides that have exhibited various bioactivities including anti-tumor, anti-cancer, anti-fungal and anti-bacteria. Based on the lengths of carbon chains and the cyclization patterns in their core structures, most bacterial PK-IIs have been classified into 6 typical classes: benzoisochromanequinone (BIQ), anthracycline (ANT), angucycline (ANG), tetracycline (TET), tetracenomycin (TCM) and pentangular (PEN). Bioengineering for diversification of PK-II core structures will generate libraries of bioactivities, which can serve the drug discovery in this family of compounds. However, although some typical PK-II core structures have been expressed, the general approach to producing different PK-II core structures had not been proposed. We validated the functional sequence of PactI promoter, tested different expression plasmid designs, and compared the production of compound in different culture media. These knowledge allowed us to develop a general approach to producing different PK-II core structures, that expressing non-redundant PK-II core structure biosynthetic pathways in a general way in the same host strain grown in the same culture medium. This approach not only improved our understanding to PK-II core structures and their biosynthetic pathways, but also provided a convenient way for generating the diverse-oriented libraries of PK-II molecules. We attempted the BIQ halogenation. On the other hand, the approach provided a bottom-up method to study functions of proteins involved in PK-II biosynthesis. We studied ActVI-ORFA, ActVI-ORF3, ActVA-ORF3 and Aln5 by expressing derived BIQ biosynthetic pathways. Crystallization and structure solutions were carried out for ActVI-ORFA and its two homologs. Our studies have provided clues to deducing their functions. Tests of a Aln5 homolog has revealed that the C3 reduction in BIQ biosynthesis can happen medium dependently in the absence of the C3 ketoreductase

Assessment and solutions for vulnerability of urban rail transit network based on complex network theory: A case study of Chongqing

As a typical complex network system, the operating environment of rail transit network (RTN) is complex and demanding. This study aims to accurate assess the weaknesses and vulnerability of RTN, which is crucial for ensuring its smooth operation. Taking Chongqing Rail Transit (CRT) as an example, this study developed a network topology model using the spatial L method and analyzed the network structure characteristics, along with the importance of key nodes under different indicators, based on complex network theory. Additionally, this study analyzed the geographical spatial distribution characteristics of nodes based on the topography and urban spatial structure of Chongqing. Then, this study classified the nodes in the RTN according to basic topological indicators, namely degree, betweenness centrality, network efficiency, and passenger flow volume (PFV). The results indicated six cluster of nodes, reflecting the variability in node vulnerability concerning overall influence (providing alternative paths, reducing path length), regional aggregation capacity, and transportation capacity. Finally, this study proposed targeted management strategies for different clusters of nodes and their respective geographical locations, providing necessary references for rational planning, safety protection, and sustainable construction of RTN

A Robust Distributed Multipoint Fiber Optic Gas Sensor System Based on AGC Amplifier Structure

A harsh environment-oriented distributed multipoint fiber optic gas sensor system realized by automatic gain control (AGC) technology is proposed. To improve the photoelectric signal reliability, the electronic variable gain can be modified in real time by an AGC closed-loop feedback structure to compensate for optical transmission loss which is caused by the fiber bend loss or other reasons. The deviation of the system based on AGC structure is below 4.02% when photoelectric signal decays due to fiber bending loss for bending radius of 5 mm, which is 20 times lower than the ordinary differential system. In addition, the AGC circuit with the same electric parameters can keep the baseline intensity of signals in different channels of the distributed multipoint sensor system at the same level. This avoids repetitive calibrations and streamlines the installation process

Construction of “small-intelligent” focused mutagenesis libraries using well-designed combinatorial degenerate primers

Site-saturation mutagenesis is a powerful tool for protein optimization due to its efficiency and simplicity. A degenerate codon NNN or NNS (K) is often used to encode the 20 standard amino acids, but this will produce redundant codons and cause uneven distribution of amino acids in the constructed library. Here we present a novel “small-intelligent” strategy to construct mutagenesis libraries that have a minimal gene library size without inherent amino acid biases, stop codons, or rare codons of Escherichia coli by coupling well-designed combinatorial degenerate primers with suitable PCR-based mutagenesis methods. The designed primer mixture contains exactly one codon per amino acid and thus allows the construction of small-intelligent mutagenesis libraries with one gene per protein. In addition, the software tool DC-Analyzer was developed to assist in primer design according to the user-defined randomization scheme for library construction. This small-intelligent strategy was successfully applied to the randomization of halohydrin dehalogenases with one or two randomized sites. With the help of DC-Analyzer, the strategy was proven to be as simple as NNS randomization and could serve as a general tool to efficiently randomize target genes at positions of interest