Effect of interstitial carbon on the evolution of early-stage irradiation damage in equi-atomic FeMnNiCoCr high-entropy alloys

Owing to their excellent radiation tolerance, some of the high-entropy alloys (HEAs) are considered as potential candidates for structural materials in extreme conditions. In order to shed light on the early-stage irradiation damage in HEAs, we performed positron annihilation spectroscopy on hydrogen implanted equiatomic FeMnNiCoCr and interstitial carbon-containing FeMnNiCoCr HEAs. We reveal primary damage as monovacancies in low dose irradiated HEAs. The enhancement of Frenkel pair recombination by C addition is observed in C-containing HEAs. In addition, the C interstitials suppress the vacancy cluster formation in high dose irradiated HEAs.Peer reviewe

Regulation of secondary growth by poplar BLADE-ON-PETIOLE genes in Arabidopsis

BLADE-ON-PETIOLE (BOP) genes are essential regulators of vegetative and reproductive development in land plants. First characterized in Arabidopsis thaliana (Arabidopsis), members of this clade function as transcriptional co-activators by recruiting TGACG-motif binding (TGA) basic leucine zipper (bZIP) transcription factors. Highly expressed at organ boundaries, these genes are also expressed in vascular tissue and contribute to lignin biosynthesis during secondary growth. How these genes function in trees, which undergo extensive secondary growth to produce wood, remains unclear. Here, we investigate the functional conservation of BOP orthologs in Populus trichocarpa (poplar), a widely-used model for tree development. Within the poplar genome, we identified two BOP-like genes, PtrBPL1 and PtrBPL2, with abundant transcripts in stems. To assess their functions, we used heterologous assays in Arabidopsis plants. The promoters of PtrBPL1 and PtrBPL2, fused with a β-glucuronidase (GUS) reporter gene showed activity at organ boundaries and in secondary xylem and phloem. When introduced into Arabidopsis plants, PtrBPL1 and PtrBPL2 complemented leaf and flower patterning defects in bop1 bop2 mutants. Notably, Arabidopsis plants overexpressing PtrBPL1 and PtrBPL2 showed defects in stem elongation and the lignification of secondary tissues in the hypocotyl and stem. Finally, PtrBPL1 and PtrBPL2 formed complexes with TGA bZIP proteins in yeast. Collectively, our findings suggest that PtrBPL1 and PtrBPL2 are orthologs of Arabidopsis BOP1 and BOP2, potentially contributing to secondary growth regulation in poplar trees. This work provides a foundation for functional studies in trees

Identification and characterization of regulatory genes associated with secondary wall formation in Populus and Arabidopsis thaliana

Transcript profiling has the potential to reveal transcriptional networks operating during development and provides expression data for genes of unknown function. Based on previous studies employing global transcription profiling of Arabidopsis thaliana inflorescence stem development and A. thaliana root cell type-specific expression, ten candidate transcription factor (TF) genes potentially associated with secondary wall formation and lignification were identified. Similar transcript profiling experiments had revealed gene expression patterns associated with secondary wall formation during secondary xylem formation in Populus species. I verified gene expression patterns of the poplar putative orthologs of the A. thaliana candidates, and the combination of the A. thaliana and poplar data identified a subset of conserved MYB and homeodomain TFs that behaved similarly in both plants. I analyzed the expression patterns of promoter-GUS fusions of all candidate genes in A. thaliana, most of which showed expression in xylem and cortex cells adjacent to interfascicular fibers in the stem, and in the root stele. T-DNA insertion mutants for most candidate genes were characterized, but only homeodomain transcription factor KNAT7 (At1g62990) T-DNA insertion mutants exhibited an obvious phenotype in inflorescence stems. The knat7 phenotype is characterized by irregular xylem (irx), interfascicular fibers with thicker cell walls, and defects in secreted seed mucilage. I also assayed for changes in gene expression in the knat7 background, and the results suggested that KNAT7 directly or indirectly regulates lignin biosynthesis genes. KNAT7 is known to interact with members of the Ovate Family Protein (OFP) transcription co-regulators. I confirmed the KNAT7-OFP1 and KNAT7-OFP4 interactions in planta, and showed that the interaction enhances KNAT7 transcriptional repression activity. Furthermore, an ofp4 mutant exhibits similar phenotypes as knat7, and the pleiotropic effect of OFP1 and OFP4 overexpression depends upon KNAT7 function. A knat7/ofp4 double mutant showed a very similar phenotype to the single mutants, supporting the hypothesis that the two proteins work in the same pathway. KNAT7 thus appears to form a functional complex with OFP proteins, and may directly or indirectly regulate lignin biosynthesis through interaction with OFP family members. These investigations provide new insights into the regulatory network(s) governing secondary wall biosynthesis in A. thaliana and poplar.Science, Faculty ofBotany, Department ofGraduat

Aspect-Aware Target Detection and Localization by Wireless Sensor Networks

This paper considers the active detection of a stealth target with aspect dependent reflection (e.g., submarine, aircraft, etc.) using wireless sensor networks (WSNs). When the target is detected, its localization is also of interest. Due to stringent bandwidth and energy constraints, sensor observations are quantized into few-bit data individually and then transmitted to a fusion center (FC), where a generalized likelihood ratio test (GLRT) detector is employed to achieve target detection and maximum likelihood estimation of the target location simultaneously. In this context, we first develop a GLRT detector using one-bit quantized data which is shown to outperform the typical counting rule and the detection scheme based on the scan statistic. We further propose a GLRT detector based on adaptive multi-bit quantization, where the sensor observations are more precisely quantized, and the quantized data can be efficiently transmitted to the FC. The Cramer-Rao lower bound (CRLB) of the estimate of target location is also derived for the GLRT detector. The simulation results show that the proposed GLRT detector with adaptive 2-bit quantization achieves much better performance than the GLRT based on one-bit quantization, at the cost of only a minor increase in communication overhead

The Impact of Artificial Afforestation on the Soil Microbial Community and Function in Desertified Areas of NW China

Afforestation is a widely used method of controlling desertification globally as it significantly impacts the soil quality, microbial community structure, and function. Investigating the effects of various artificial vegetation restoration models on soil microbial communities is crucial in understanding the mechanisms involved in combating desertification. However, research on this topic in arid, desertified regions is limited. In this study, we collected soil samples from two types of artificial forests (single species and mixed species) and bare desert soils in desertified areas of Northwest China to explore the impact of afforestation on soil nutrients, the microbial community composition, network relationships, and carbohydrate degradation abilities using metagenomic sequencing techniques. Our findings indicate that afforestation significantly enhances the soil moisture, total carbon, available phosphorus, and total nitrogen levels. The soil under mixed-species forests exhibited significantly higher levels of total carbon, total phosphorus, available phosphorus, and total nitrogen than that under single-species forests. Following afforestation, the populations of Pseudomonadota, Acidobacteriota, and Cyanobacteria increased significantly, whereas Actinomycetota decreased markedly. In single-species forests, Pseudomonadota and Bacillota were enriched, whereas Chloroflexota, Planctomycetota, and Acidobacteriota were more prevalent in mixed-species plantations. Afforestation increases the complexity and stability of microbial community networks. Afforestation enhances microbial metabolic activity, particularly increasing the abundance of carbon degradation functional genes in forest soils compared to bare desert soils. Mixed-species plantations outperform single-species forests in enhancing carbohydrate metabolism, amino acid metabolism, and the biodegradation and metabolism of xenobiotics. The abundance of functional genes associated with the degradation of starch, cellulose, hemicellulose, chitin, and pectin in mixed-species forests was significantly greater than in single-species plantations. Our study shows that mixed-species afforestation effectively improves the soil quality, enhances the stability of soil microbial communities, and bolsters the carbon cycle in arid regions prone to desertification. The reciprocal relationship between microorganisms and plants may serve as an intrinsic mechanism by which mixed-species afforestation more effectively controls desertification

Random Deep Belief Networks for Recognizing Emotions from Speech Signals

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition

Enhancement of vacancy diffusion by C and N interstitials in the equiatomic FeMnNiCoCr high entropy alloy

We present evidence of homogenization of atomic diffusion properties caused by C and N interstitials in an equiatomic single-phase high entropy alloy (FeMnNiCoCr). This phenomenon is manifested by an unexpected interstitial-induced reduction and narrowing of the directly experimentally determined migration barrier distribution of mono-vacancy defects introduced by particle irradiation. Our observation by positron annihilation spectroscopy is explained by state-of-the-art theoretical calculations that predict preferential localization of C/N interstitials in regions rich in Mn and Cr, leading to a narrowing and reduction of the mono-vacancy size distribution in the random alloy. This phenomenon is likely to have a significant impact on the mechanical behavior under irradiation, as the local variations in elemental motion have a profound effect on the solute strengthening in high entropy alloys. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of Acta Materialia Inc.Peer reviewe

Decentralized Truncated One-Sided Sequential Detection of a Noncooperative Moving Target

This letter considers the decentralized detection of a noncooperative moving target by employing a wireless sensor network. Suppose that, if present, the target moves along a direction with a constant velocity, and it emits an unknown signal experiencing distance-dependent attenuation that is periodically sampled by sensors. The sensor observations are quantized into one-bit data individually and then sequentially transmitted to a fusion center, which is in charge of making a global decision. We first derive the generalized Rao test statistic as a more computationally efficient alternative when compared to the typical generalized likelihood ratio test statistic. Then, we propose a truncated one-sided sequential (TOS) test rule by imposing a finite maximum stopping time (namely the deadline) on typical one-sided sequential tests. With a deadline slightly larger than the sample size of a benchmarked fixed-sample-size (FSS) test, the proposed TOS test rule provides the same detection performance and significantly accelerates the target-detection process on average, which is corroborated by simulation results