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Abstract Although long-read sequencing enables the generation of complete genomes for unculturable microbes, its high cost limits the widespread adoption of long-read sequencing in large-scale metagenomic studies. An alternative method is to assemble short-reads with long-range connectivity, which can be a cost-effective way to generate high-quality microbial genomes. Here, we develop Pangaea, a bioinformatic approach designed to enhance metagenome assembly using short-reads with long-range connectivity. Pangaea leverages connectivity derived from physical barcodes of linked-reads or virtual barcodes by aligning short-reads to long-reads. Pangaea utilizes a deep learning-based read binning algorithm to assemble co-barcoded reads exhibiting similar sequence contexts and abundances, thereby improving the assembly of high- and medium-abundance microbial genomes. Pangaea also leverages a multi-thresholding algorithm strategy to refine assembly for low-abundance microbes. We benchmark Pangaea on linked-reads and a combination of short- and long-reads from simulation data, mock communities and human gut metagenomes. Pangaea achieves significantly higher contig continuity as well as more near-complete metagenome-assembled genomes (NCMAGs) than the existing assemblers. Pangaea also generates three complete and circular NCMAGs on the human gut microbiomes.

Abstract Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and clustering analysis, and visualization based on VCF formatted SNPs. We implemented five Kinship estimation methods and three clustering methods for its users to choose from. Moreover, unlike other PCA tools, VCF2PCACluster possesses a clustering function based on PCA result, which enabling users to automatically and clearly know about population structure. We demonstrated the same accuracy but a higher performance of this tool in performing PCA analysis on tens of millions of SNPs compared to another popular PLINK2 software, especially in peak memory usage that is independent of the number of SNPs in VCF2PCACluster.

Abstract With the rapid development of multimedia technology and the massive accumulation of user data, a huge amount of data is rapidly generated and shared over the network, while the problems of inappropriate data access and abuse persist. Reversible data hiding in encrypted images (RDHEI) is a privacy-preserving method that embeds protected data in an encrypted domain and accurately extracts the embedded data without affecting the original content. However, the amount of embedded data has been one of the major limitations in the performance and application of RDHEI. Currently, the main approaches to improve the capacity of RDHEI are either to increase the overall capacity or to reduce the length of the auxiliary information. In this paper, we propose a novel RDHEI scheme based on multi-prediction and adaptive Huffman encoding. To increase the overall capacity, we propose a multi-prediction, called MED+GAP predictor, to generate the label map data of non-reference pixels prior to image encryption. Then, an adaptive Huffman coding is designed to compress the generated labels in order to reduce the embedding length of the auxiliary information used for the extraction and recovery. Experiments show that the proposed method with MED+GAP predictor and adaptive Huffman coding improves 0.052 bpp, 0.023 bpp, and 0.047 bpp on average over the other state-of-the-art methods on the BOSSBase, BOWS-2, and UCID datasets, respectively, while maintaining security and reversibility.

The direct tensile mechanical properties of highly thermally damaged rock under high strain rate loads are a key basic mechanical problem that must be solved for the stability and effective control of surrounding rock stability in the combustion control area of an underground coal gasification project. In this paper, a two-dimensional equivalent grain-based model (GBM) unit and Split Hopkinson Tension Bar (SHTB) numerical model for thermally damaged coal-measures sandstone were constructed using particle flow code (PFC). The comparison with the experimental results shows that the numerical method can accurately describe the dynamic direct tensile behavior of thermally damaged sandstone. The following conclusions are drawn: The dynamic tensile strength of thermally damaged sandstone shows a significant strain rate-strengthening effect. With the increase in thermal damage temperature, the dynamic tensile strength of sandstone increases first and then decreases. The generation and development of hot cracks in a high-temperature environment is the fundamental reason for the change in macroscopic mechanical properties. The dynamic tensile failure process of thermally damaged sandstone can be divided into four stages: the dynamic damage initiation, the dynamic damage development, the damage crack penetration, and the sample dynamic fracture. With the increase in impact velocity, the initial kinetic energy, elastic strain energy, dissipated energy, and elastic strain energy ratio in the failure process of thermally damaged sandstone gradually increase. In contrast, the dissipated energy ratio gradually decreases. As the heat treatment temperature increases, the elastic strain energy and the ratio of elastic strain energy increase first and then decrease.

Abstract Sipuncula is a class of exocoelomic unsegmented animals whose evolutionary relationships are unresolved. The peanut worm Sipunculus nudus is a globally distributed, economically important species belonging to the class Sipuncula. Herein, we present the first high-quality chromosome-level assembly of S. nudus based on HiFi reads and high-resolution chromosome conformation capture (Hi-C) data. The assembled genome was 1,427 Mb, with a contig N50 length of 29.46 Mb and scaffold N50 length of 80.87 Mb. Approximately 97.91% of the genome sequence was anchored to 17 chromosomes. A BUSCO assessment showed that 97.7% of the expectedly conserved genes were present in the genome assembly. The genome was composed of 47.91% repetitive sequences, and 28,749 protein-coding genes were predicted. A phylogenetic tree demonstrated that Sipuncula belongs to Annelida and diverged from the common ancestor of Polychaeta. The high-quality chromosome-level genome of S. nudus will serve as a valuable reference for studies of the genetic diversity and evolution of Lophotrochozoa.

Tree peony (Paeonia ostii) has the largest chromosome of any sequenced plants to date. Here, the authors assemble its genome and reveal the association of a list of candidate genes with fatty acid biosynthesis and the possible contribution of transposon and histone expansion to maintain the giga-chromosomes.

In response to Boschma’s concern that the implications of relatedness- and unrelatedness-based diversification strategies lack empirical evidence at disaggregated levels and in the context of the Global South, this study generates a unique dataset at the city level and explores how these smart specialization strategies (S3) may explain digital industry innovations within a specific regional innovation system, i.e., the Yangtze River Delta, China. The findings reveal that both relatedness density and knowledge complexity play a positive role in explaining digital industry innovations. However, the relationship between relatedness and knowledge complexity and its interactive effects on innovation performance are less straightforward. In our study, we found that efficient cooperation between relatedness and complexity can only be achieved if the level of government intervention is moderate. Therefore, the discussion of S3 focuses on more than the dichotomous argument between relatedness and unrelatedness. Many socio-economic factors also impact the effectiveness of these theoretical components within different innovation systems, which are largely overlooked by present studies.

We explore whether there are value preferences of creative workers in addition to tolerance and how these value preferences vary among different occupation categories and countries. We use a dataset of 1968 and 1076 observations in China and the U.S., respectively, from the World Values Survey dataset (2017–2020, wave 7) (WVS 7), with a Structure Equation Modelling (SEM) and Multinomial Logit Model (MLM) at the micro level. The findings reveal that (1) the Chinese sample is more likely to have a balanced preference of tolerance towards migrants, religions, and homosexuality, while the American sample’s preference of tolerance is much more likely to be interpreted as accepting homosexuality only; (2) the American sample also shows preferences towards responsibility, technology, work style, and political actions, while a preference for happiness and political actions is identified in the Chinese sample; and (3) with a higher level of creativity, the difference regarding understanding of tolerance is more likely to be highlighted between China and the U.S. This study provides a quite unconventional perspective for understanding the composition of preferences and, to a certain extent, reconciles the inconsistency between the theoretical advocacy of building up a selected milieu and the reality of creative workers’ blended value mix.

The demand for object pose estimation is steadily increasing, and deep learning has propelled the advancement of this field. However, the majority of research endeavors face challenges in their applicability to industrial production. This is primarily due to the high cost of annotating 3D data, which places higher demands on the generalization capabilities of neural network models. Additionally, existing methods struggle to handle the abundance of textureless objects commonly found in industrial settings. Finally, there is a strong demand for real-time processing capabilities in industrial production processes. Therefore, in this study, we introduced a dual-channel Siamese framework to address these challenges in industrial applications. The architecture employs a Siamese structure for template matching, enabling it to learn the matching capability between the templates constructed from high-fidelity simulated data and real-world scenes. This capacity satisfies the requirements for generalization to unseen objects. Building upon this, we utilized two feature extraction channels to separately process RGB and depth information, addressing the limited feature issue associated with textureless objects. Through our experiments, we demonstrated that this architecture effectively estimates the three-dimensional pose of objects, achieving a 6.0% to 10.9% improvement compared to the state-of-the-art methods, while exhibiting robust generalization and real-time processing capabilities.

Human gut microbiota is associated with human health and disease, and is known to have the second-largest genome in the human body. The microbiota genome is important for their functions and metabolites; however, accurate genomic access to the microbiota of the human gut is hindered due to the difficulty of cultivating and the shortcomings of sequencing technology. Therefore, we applied the stLFR library construction method to assemble the microbiota genomes and demonstrated that assembly property outperformed standard metagenome sequencing. Using the assembled genomes as references, SNP, INDEL, and HGT gene analyses were performed. The results demonstrated significant differences in the number of SNPs and INDELs among different individuals. The individual displayed a unique species variation spectrum, and the similarity of strains within individuals decreased over time. In addition, the coverage depth analysis of the stLFR method shows that a sequencing depth of 60X is sufficient for SNP calling. HGT analysis revealed that the genes involved in replication, recombination and repair, mobilome prophages, and transposons were the most transferred genes among different bacterial species in individuals. A preliminary framework for human gut microbiome studies was established using the stLFR library construction method.

Male sterility is a valuable trait for watermelon breeding, as watermelon hybrids exhibit obvious heterosis. However, the underlying regulatory mechanism is still largely unknown, especially regarding the related non-coding genes. In the present study, approximately 1035 differentially expressed genes (DEGs), as well as 80 DE-lncRNAs and 10 DE-miRNAs, were identified, with the overwhelming majority down-regulated in male-sterile floral buds. Enrichment analyses revealed that the general phenylpropanoid pathway as well as its related metabolisms was predicted to be altered in a mutant compared to its fertile progenitor. Meanwhile, the conserved genetic pathway DYT1-TDF1-AMS-MS188-MS1, as well as the causal gene ClAMT1 for the male-sterile mutant Se18, was substantially disrupted during male reproductive development. In addition, some targets of the key regulators AMS and MS188 in tapetum development were also down-regulated at a transcriptional level, such as ABCG26 (Cla004479), ACOS5 (Cla022956), CYP703A2 (Cla021151), PKSA (Cla021099), and TKPR1 (Cla002563). Considering lncRNAs may act as functional endogenous target mimics of miRNAs, competitive endogenous RNA networks were subsequently constructed, with the most complex one containing three DE-miRNAs, two DE-lncRNAs, and 21 DEGs. Collectively, these findings not only contribute to a better understanding of genetic regulatory networks underlying male sterility in watermelon, but also provide valuable candidates for future research.

Aiming at the problems that the existing compressive sensing-based meaningful image encryption algorithms have low visual security of the encrypted images and poor quality of the reconstructed images, a 2-dimensional compressive sensing-based (2DCS) meaningful image encryption algorithm was proposed.Firstly, a chaotic pseudo-random sequence generation method associated with plaintext was designed, and the global random permutation and grayscale transformation operations were used for pre-encryption to improve the decrypted image quality.The generated pre-encrypted image was used as the input for 2DCS, and the secret image was generated after the compression encryption and quantization operations.Secondly, the relationship between the hidden and the modified data was considered, and an adaptive embedding method was adopted to modify the carrier coefficient values to improve the visual security of meaningful encrypted image.Finally, the 2-dimensional projection gradient reconstruction method was adopted to decompress and decrypt to obtain the decrypted image.The experimental results show that, compared with the existing algorithms, the proposed algorithm not only improves the visual security of encrypted image and the quality of reconstructed image, but also can resist noise and cropping attacks.

Metasurfaces that can realize the polarization manipulation of electromagnetic waves on the sub-wavelength scale have become an emerging research field. Here, a novel strategy of combining the metasurface and Fresnel zone plate to form a metasurface zone plate is proposed to realize the conversion from nearly arbitrary polarizations to a fixed polarization. Specifically, when one polarized wave is incident on adjacent ring zones constructed by different types of meta-atoms, the transmitted waves generated by odd-numbered and even-numbered ring zones converge at the same focus and superimpose to generate a fixed polarized wave. As function demonstrations, we have designed two types of metasurface zone plates: one is a focused linear polarizer, and the other can convert nearly arbitrary polarized waves into focused circularly polarized waves. The simulated and measured results are consistent with theoretical expectations, suggesting that the proposed concept is flexible and feasible. Our work provides an alternative platform for polarization manipulation and may vigorously promote the development of polarization photonic devices.

Laminated glass is extensively used in automotive windshields, making it crucial to have a comprehensive understanding of its fracture mechanism to ensure driver and pedestrian safety in various windshield impact scenarios. Current research on the cohesive zone model of glass impact failure has encountered challenges related to accuracy and computational efficiency. This paper addresses these issues by utilizing the finite element software LS-DYNA, which integrates a cohesive zone model and thick shell (Tshell) elements to simulate and analyze the impact failure process of laminated glass. The combination of Tshell and cohesive elements was validated using a DCB example. Subsequently, the proposed method was applied to simulate the impact damage on an automobile’s front windshield, providing valuable insights from the obtained results. Finally, the influence of curvature, the number of layers, and the thickness ratio of each layer were investigated, leading to some valuable conclusions. Firstly, an increase in the thickness of the upper glass layer correlates with a decrease in the peak acceleration of the dummy-head model due to the ductility of PVB material. Secondly, when a curvature exists, the arched configuration of the windshield promotes higher resistance against impact, consequently leading to increased peak acceleration.

Watermelon is a crucial horticultural crop worldwide but its genetic base has become extremely narrow owing to long-term cultivation. Induced mutagenesis can create a range of variations with distinctive agricultural characteristics. To broaden the genetic diversity of watermelon, we established a mutagenesis library containing over 4000 M1 seeds from an inbred line ‘M08’, which was irradiated by 350 Gy of 60Co γ-rays for 3 h. The rates of germination, emergence, and survival of the M1 seeds were reduced by 5.88%, 18.66%, and 41.96%, respectively. After phenotypic screening, 20 and 10 types of morphological changes were observed in the M1 and M2 generations, with approximately 10.57% and 14.17% mutation frequencies, respectively. Six mutants with desirable horticultural alterations were selected for additional presentation, including the leaf color mutant C1-NO.1, the yellow peel mutant C1-NO.2, the pericarp thickening mutant C1-NO.3, the pericarp thinning mutant C1-NO.4, the seedless mutant C1-NO.5, and the C2-No.1 mutant with normal female flowers and malformed male flowers. Moreover, the three mutants M1-3, M2-1, and M1-5 were identified from our EMS-induced M2 library, exhibiting the fusiform fruit, the dark green peel, and the yellow leaves, respectively. Compared to the wild type (WT), the photosynthetic pigments and parameters were negatively impacted in the yellow-leaf mutant M1-5. For example, the total chlorophyll was 1.22 and 2.22 mg/g in the young and mature leaves of M1-5, respectively, which were significantly lower than those in the WT (2.58 and 2.90 mg/g, respectively). Notably, some mutagenesis phenotypes could be stably inherited, including traits such as yellow leaf color, fusiform fruit shape, and thickening and thinning pericarp. Taken together, these results indicate that these two mutant libraries serve as essential resources to discover new phenotypic germplasms, thereby facilitating the genetic breeding and functional gene exploration in watermelon.

If a metalens integrates the circular polarization (CP) conversion function, the focusing lens together with circular-polarizing lens (CPL) in traditional cameras may be replaced by a metalens. However, in terahertz (THz) band, the reported metalenses still do not obtain the perfect and strict single-handed CP, because they were constructed via Pancharatnam-Berry phase so that CP conversion contained both left-handed CP (LCP) and right-handed CP (RCP) components. In this paper, a silicon based THz metalens is constructed using dynamic phase to obtain single-handed CP conversion. Also, we can rotate the whole metalens at a certain angle to control the conversion of multi-polarization states, which can simply manipulate the focusing for incident linear polarization (LP) THz wave in three polarization conversion states, including LP without conversion, LCP and RCP. Moreover, the polarization conversion behavior is reversible, that is, the THz metalens can convert not only the LP into arbitrary single-handed CP, but also the LCP and RCP into two perpendicular LP, respectively. The metalens is expected to be used in advanced THz camera, as a great candidate for traditional CPL and focusing lens group, and also shows potential application in polarization imaging with discriminating LCP and RCP.

The effect of landscape patterns and environmental factors on the population structure and genetic diversity of organisms is well-documented. However, this effect is still unclear in the case of Mymaridae parasitoids. Despite recent advances in machine learning methods for landscape genetics, ensemble learning still needs further investigation. Here, we evaluated the performance of different boosting algorithms and analyzed the effects of landscape and environmental factors on the genetic variations in the tea green leafhopper parasitoid Stethynium empoasca (Hymenoptera: Mymaridae). The S. empoasca populations showed a distinct pattern of isolation by distance. The minimum temperature of the coldest month, annual precipitation, the coverage of evergreen/deciduous needleleaf trees per 1 km2, and the minimum precipitation of the warmest quarter were identified as the dominant factors affecting the genetic divergence of S. empoasca populations. Notably, compared to previous machine learning studies, our model showed an unprecedented accuracy (r = 0.87) for the prediction of genetic differentiation. These findings not only demonstrated how the landscape shaped S. empoasca genetics but also provided an essential basis for developing conservation strategies for this biocontrol agent. In a broader sense, this study demonstrated the importance and efficiency of ensemble learning in landscape genetics.

Abstract Emerging evidence indicates an association between gut microbiome and arthritis diseases including gout. However, how and which gut bacteria affect host urate degradation and inflammation in gout remains unclear. Here we performed a metagenome analysis on 307 fecal samples from 102 gout patients and 86 healthy controls. Gout metagenomes significantly differed from those of healthy controls. The relative abundances of Prevotella, Fusobacterium, and Bacteroides were increased in gout, whereas those of Enterobacteriaceae and butyrate-producing species were decreased. Functionally, gout patients had greater abundances for genes in fructose, mannose metabolism and lipid A biosynthesis, and lower for genes in urate degradation and short chain fatty acid production. A three-pronged association between metagenomic species, functions and clinical parameters revealed that decreased abundances of species in Enterobacteriaceae were associated with reduced amino acid metabolism and environmental sensing, which together contribute to increased serum uric acid and C-reactive protein levels in gout. A random forest classifier based on three gut microbial genes showed high predictivity for gout in both discovery and validation cohorts (0.91 and 0.80 accuracy), with high specificity in the context of other chronic disorders. Longitudinal analysis showed that uric-acid-lowering and anti-inflammatory drugs partially restored gut microbiota after 24-week treatment. Comparative analysis with obesity, type 2 diabetes, ankylosing spondylitis and rheumatoid arthritis indicated that gout metagenomes were more similar to those of autoimmune than metabolic diseases. Our results suggest that gut dysbiosis was associated with dysregulated host urate degradation and systemic inflammation and may be used as non-invasive diagnostic markers for gout.

Cai and colleagues sequence and annotate the genome of the yellowstripe goby at the chromosome level. Combining genome and transcriptome data, they infer key metabolic pathways for high lipid accumulation in the liver of this fish.

The diamondback moth, Plutella xylostella is a cosmopolitan agricultural pest. By analyzing 532 genomes from 114 populations around the world, the authors find evidence supporting a South American origin of this moth, and look for signatures of positive selection.

Over the last three decades, accurate modeling and forecasting of electricity prices has become a key issue in competitive electricity markets. As electricity price series usually exhibit several complex features, such as high volatility, seasonality, calendar effect, non-stationarity, non-linearity and mean reversion, price forecasting is not a trivial task. However, participants of electricity market need price forecast to make decisions in their daily activity in the market, such as trading, risk management or future planning. In this study we consider linear and nonlinear models for one-day-ahead forecast of electricity prices using components estimation techniques. This approach requires to filter out the structural, deterministic components from the original time series and to model the residual component by means of some stochastic process. The final forecast is obtained by combining the predictions of both these components. In this work, linear and non-linear models are applied to both, deterministic and stochastic, components. In the case of stochastic component, AutoRegressive, Nonparametric AutoRegressive, Functional AutoRegressive, and Nonparametric Functional AutoRegressive have been considered. Furthermore, two naïve benchmarks are applied directly to the price time series and their results are compared with our proposed models. An application of the proposed methodology is presented for the Italian electricity market (IPEX). Our analysis suggests that, in terms of Mean Absolute Error, Mean Absolute Percentage Error, and Pearson correlation coefficient, best results are obtained when deterministic component is estimated by using parametric approach. Further, Functional AutoRegressive model performs relatively better than the rest while Nonparametric AutoRegressive is highly competitive.

To study the high quality processes, time-between-events (TBE) control charts have several advantages over the ordinary control charts. However, the existing TBE charts are based on the exponential distribution, which limit the application of these charts to monitor rare events. Therefore, to generalize existing exponential TBE charts, recently two new TBE charts assuming Weibull and generalized exponential distributions for the inter-arrival times of the renewal process, have been proposed in the literature. The main aim of this study is to present a detailed comparison of these charts. We use the expected quadratic loss (EQL), relative average run length (RARL), continuous rank probability score (CRPS) and closeness measure to assess the performance of the Weibull and the generalized exponential charts. We also discuss four real data examples in this article.

Motivation has been recognized as a vital component in successfully learning a second or foreign language. However, research on language learners’ motivation in a study abroad context requires more attention in an era in which international mobility is becoming a new normal. This study investigated 217 Chinese overseas university students’ L2 motivation during their one-year postgraduate study in the United Kingdom. by examining a range of motivational variables in relation to their motivated English language learning behaviors. Integrating results from both questionnaires and interviews from nine participating students, the study revealed that international posture showed the strongest positive power, followed by the ideal L2 self, in explaining the learners’ willingness to communicate, frequency of communication, and intended learning effort. Additionally, instrumentality and parental encouragement exerted prominent promotional influence in shaping their intended learning effort. However, the ought-to L2 self-displayed a significant negative impact on their L2 learning in this study abroad context, and the role of attitudes toward L2 speakers/community and culture was not evident in this case. The findings shed light on a more comprehensive understanding of L2 motivation in a study abroad context, and offer insightful implications for English as a Foreign Language education in cultivating language learners’ motivation to prepare for study abroad.

Methionine aminopeptidases (MetAPs) catalyze the cleavage of the N-terminal initiator methionine (iMet) in new peptide chains and arylamides, which is essential for protein and peptide synthesis. MetAP is differentially expressed in two diamondback moth (DBM; Plutella xylostella) strains: the G88 susceptible strain and the Cry1S1000 strain, which are resistant to the Bt toxin Cry1Ac, implicating that MetAP expression might be associated with Bt resistance. In this study, we identified and cloned a MetAP gene from DBMs, named PxMetAP1, which has a CDS of 1140 bp and encodes a 379 amino acid protein. The relative expression of PxMetAP1 was found to be ~2.2-fold lower in the Cry1S1000 strain compared to that in the G88 strain. PxMetAP1 presents a stage- and tissue-specific expression pattern, with higher levels in the eggs, adults, integument, and fatbody of DBMs. The linkage between PxMetAP1 and Cry1Ac resistance is verified by genetic linkage analysis. The knockout of PxMetAP1 in G88 by CRISPR/Cas9 leads to a ~5.6-fold decrease in sensitivity to the Cry1Ac toxin, further supporting the association between the PxMetAP1 gene and Bt tolerance. Our research sheds light on the role of MetAP genes in the development of Bt tolerance in P. xylostella and enriches the knowledge for the management of such a cosmopolitan pest.

The CRISPR/Cas9 system is an efficient tool for reverse genetics validation, and the application of this system in the cell lines provides a new perspective on target gene analysis for the development of biotechnology tools. However, in the cell lines of diamondback moth, Plutella xylostella, the integrity of the CRISPR/Cas9 system and the utilization of this cell lines still need to be improved to ensure the application of the system. Here, we stabilize the transfection efficiency of the P. xylostella cell lines at different passages at about 60% by trying different transfection reagents and adjusting the transfection method. For Cas9 expression in the CRIPSPR/Cas9 system, we identified a strong endogenous promoter: the 217–2 promoter. The dual-luciferase and EGFP reporter assay demonstrated that it has a driving efficiency close to that of the IE1 promoter. We constructed pB-Cas9-Neo plasmid and pU6-sgRNA plasmid for CRISPR/Cas9 system and subsequent cell screening. The feasibility of the CRISPR/Cas9 system in P. xylostella cell lines was verified by knocking out endogenous and exogenous genes. Finally, we generated a transgenic Cas9 cell line of P. xylostella that would benefit future exploitation, such as knock-in and multi-threaded editing. Our works provides the validity of the CRISPR/Cas9 system in the P. xylostella cell lines and lays the foundation for further genetic and molecular studies on insects, particularly favoring gene function analysis.

Recently, generating visually secure cipher images by compressive sensing (CS) techniques has drawn much attention among researchers. However, most of these algorithms generate cipher images based on direct bit substitution and the underlying relationship between the hidden and modified data is not considered, which reduces the visual security of cipher images. In addition, performing CS on plain images directly is inefficient, and CS decryption quality is not high enough. Thus, we design a novel cryptosystem by introducing vector quantization (VQ) into CS-based encryption based on a 3D fractional Lorenz chaotic system. In our work, CS compresses only the sparser error matrix generated from the plain and VQ images in the secret generation phase, which improves CS compression performance and the quality of decrypted images. In addition, a smooth function is used in the embedding phase to find the underlying relationship and determine relatively suitable modifiable values for the carrier image. All the secret streams are produced by updating the initial values and control parameters from the fractional chaotic system, and then utilized in CS, diffusion, and embedding. Simulation results demonstrate the effectiveness of the proposed method.

A control chart named as the hybrid double exponentially weighted moving average (HDEWMA) to monitor the mean of Weibull distribution in the presence of type-I censored data is proposed in this study. In particular, the focus of this study is to use the conditional median (CM) for the imputation of censored observations. The control chart performance is assessed by the average run length (ARL). A comparison between CM-DEWMA control chart and CM-based HDEWMA control chart is also presented in this article. Assuming different shift sizes and censoring rates, it is observed that the proposed control chart outperforms the CM-DEWMA chart. The effect of estimation, particularly the scale parameter estimation, on ARL is also a part of this study. Finally, a practical example is provided to understand the application and to investigate the performance of the proposal in practical scenarios.

Abstract Background Pear (Pyrus) is a globally grown fruit, with thousands of cultivars in five domesticated species and dozens of wild species. However, little is known about the evolutionary history of these pear species and what has contributed to the distinct phenotypic traits between Asian pears and European pears. Results We report the genome resequencing of 113 pear accessions from worldwide collections, representing both cultivated and wild pear species. Based on 18,302,883 identified SNPs, we conduct phylogenetics, population structure, gene flow, and selective sweep analyses. Furthermore, we propose a model for the divergence, dissemination, and independent domestication of Asian and European pears in which pear, after originating in southwest China and then being disseminated throughout central Asia, has eventually spread to western Asia, and then on to Europe. We find evidence for rapid evolution and balancing selection for S-RNase genes that have contributed to the maintenance of self-incompatibility, thus promoting outcrossing and accounting for pear genome diversity across the Eurasian continent. In addition, separate selective sweep signatures between Asian pears and European pears, combined with co-localized QTLs and differentially expressed genes, underline distinct phenotypic fruit traits, including flesh texture, sugar, acidity, aroma, and stone cells. Conclusions This study provides further clarification of the evolutionary history of pear along with independent domestication of Asian and European pears. Furthermore, it provides substantive and valuable genomic resources that will significantly advance pear improvement and molecular breeding efforts.

Several models have been proposed to explain the emergence of sex chromosomes. Here, through comparative genomics and mutant analysis, Harkess et al. show that linked but separate genes on the Y chromosome are responsible for sex determination in Asparagus, supporting a two-gene model for sex chromosome evolution.

Low availability of phosphorus (P) in calcareous soils is a major problem for sustainable improvement in cereals crops yield. A higher amount of calcium in soils precipitates the P, thus making it immobile in soil. Inoculation of arbuscular mycorrhizal fungi (AMF) and phosphate solubilizing bacteria (PSB) could be helpful in the sustainable management of immobile P in soil. However, their combined use in releasing P from rock phosphate (RP) in alkaline calcareous soils have been little investigated. In this regard, two successive field experiments were conducted to assess the interactive inoculation potential of AMF and PSB strain Bacillus sp. PIS7 with RP on the yield and P uptake of maize (Zea mays L.) and wheat (Triticum aestivum L.) crops in alkaline calcareous soil. The first field experiment was conducted in a complete randomized block design with 10 treatments and three replications by inoculating maize seeds with AMF and Bacillus sp. PIS7 inoculum alone and in combination with RP. Their performance was compared with single super phosphate (SSP) inorganic fertilizer. Afterward, the residual effects of inoculated AMF and Bacillus sp. PIS7 were investigated on wheat as a subsequent crop. Maize and wheat yield parameters, P uptake, AMF root colonization, and PSB population was measured. The results of both trials indicated the beneficial effects of AMF and Bacillus sp. PIS7 with RP in increasing the plants grain yield and P uptake until the second season after inoculation, as compared to controls. Likewise, maize and wheat roots colonization, PSB population density, and post-harvest soil properties were also improved by the combined inoculation of AMF and Bacillus sp. PIS7 with RP. It is concluded that PSB solubilizes the unavailable forms of P in combination with RP fertilizers in soil, and AMF ultimately transfers it to plants for growth promotion. Moreover, the combined inoculation of AMF and PSB with ground RP had more potential to improve maize-wheat yields and P uptake comparable to those obtained by using expensive phosphatic fertilizers in P deficient calcareous pH soils.

In calcareous soil, the significant portion of applied phosphorus (P) fertilizers is adsorbed on the calcite surface and becomes unavailable to plants. Addition of organic amendments with chemical fertilizers can be helpful in releasing the absorbed nutrients from these surfaces. To check out this problem, a field experiment was conducted for two years to determine the effect of P fertilizers and humic acid (HA) in enhancing P availability in soil and their ultimate effect on growth, yield and P uptake of wheat in calcareous soils. The experiment was comprised of five levels of P (0, 45, 67.5, 90 and 112.5 kg P2O5 ha−1) as a single superphosphate (SSP) and 2 levels of locally produced humic acid (with and without HA) arranged in a two factorial randomized complete block design (RCBD) with three replications. Wheat plant height, spike length, number of grains per spike, 1000-grain weight, grain, straw and biological yield were significantly improved by the addition of HA with SSP. Very often, the performance of 67.5 kg P2O5 ha−1 with HA were either similar or better than 90 or even 112.5 kg P2O5 ha−1 applied without HA. Post-harvest soil organic matter, AB-DTPA extractable and water-soluble P, plant P concentration and its uptake were also significantly improved by the addition of HA with SSP compared to sole SSP application. It was evident that P efficiency could be increased with HA addition and it has the potential to improve crop yield and plants P uptake in calcareous soils.

Global warming promotes soil calcification and salinization processes. As a result, soil phosphorus (P) is becoming deficient in arid and semiarid areas throughout the world. In this pot study, we evaluated the potential of phosphate-solubilizing bacteria (PSB) for enhancing the growth and P uptake in maize under varying levels of lime (4.8%, 10%, 15% and 20%) and additional P supplements (farmyard manure, poultry manure, single super phosphate and rock phosphate) added at the rate of 45 mg P2O5 kg−1. Inoculation and application of P as organic manures (Poultry and farm yard manures) improved maize growth and P uptake compared to the control and soils with P applied from mineral sources. Liming adversely affected crop growth, but the use of PSB and organic manure significantly neutralized this harmful effect. Mineral P sources combined with PSB were as effective as the organic sources alone. Furthermore, while single supper phosphate showed better results than Rock phosphate, the latter performed comparably upon PSB inoculation. Thus, PSB plus P application as organic manures is an eco-friendly option to improve crop growth and P nutrition in a calcareous soil under changing climate.

The histogram watermark, which performs watermark embedding by slightly modifying the histogram of the original image, has been a hot research topic in information hiding technology due to the superiority of its pixel modification during the watermark embedding process, which is independent of the pixel position. This property makes the histogram-based watermark strong resistant to geometric attacks, such as cropping attack, crossed attack, rotation attack, etc. In this paper, we propose a large capacity histogram-based robust watermarking algorithm based on three consecutive bins for the first time. In our scheme, we divide the shape of three consecutive bins into eight cases. According to these cases, we embed Information Number 0, 1, 2, 3, 4, 5, 6, or 7, respectively. The embedded information capacity reaches one bit per bin (bpb), and the amount of embedded information is equal to 200% of the previous existing algorithms. Experimental results show that the new algorithm not only has a large capacity of embedding information, but also has strong robustness to geometric attacks, as well as common image processing operations.

The large yellow croaker Larimichthys crocea (L. crocea) is one of the most economically important marine fish in China and East Asian countries. It also exhibits peculiar behavioral and physiological characteristics, especially sensitive to various environmental stresses, such as hypoxia and air exposure. These traits may render L. crocea a good model for investigating the response mechanisms to environmental stress. To understand the molecular and genetic mechanisms underlying the adaptation and response of L. crocea to environmental stress, we sequenced and assembled the genome of L. crocea using a bacterial artificial chromosome and whole-genome shotgun hierarchical strategy. The final genome assembly was 679 Mb, with a contig N50 of 63.11 kb and a scaffold N50 of 1.03 Mb, containing 25,401 protein-coding genes. Gene families underlying adaptive behaviours, such as vision-related crystallins, olfactory receptors, and auditory sense-related genes, were significantly expanded in the genome of L. crocea relative to those of other vertebrates. Transcriptome analyses of the hypoxia-exposed L. crocea brain revealed new aspects of neuro-endocrine-immune/metabolism regulatory networks that may help the fish to avoid cerebral inflammatory injury and maintain energy balance under hypoxia. Proteomics data demonstrate that skin mucus of the air-exposed L. crocea had a complex composition, with an unexpectedly high number of proteins (3,209), suggesting its multiple protective mechanisms involved in antioxidant functions, oxygen transport, immune defence, and osmotic and ionic regulation. Our results reveal the molecular and genetic basis of fish adaptation and response to hypoxia and air exposure. The data generated by this study will provide valuable resources for the genetic improvement of stress resistance and yield potential in L. crocea.

Heparanase promotes tumor invasion and metastasis in several malignancies including breast cancer. However, the roles and regulation mechanisms of heparanase during breast cancer progression are still not fully understood. The aim of this study is to determine the differential regulation of heparanase gene expression in specific stages of breast cancer by DNA methylation. We detected levels of heparanase expression and DNA methylation patterns of its promoter in breast cancer cell lines (MCF-7 and MDA-MB-435) and clinical tissues, respectively. It has been observed that heparanase is highly expressed in the invasive MDA-MB-435 cells with low methylation modification in the heparanase promoter. In contrast, lower expression of heparanase in MCF-7 cells is accompanied by higher methylation in the promoter. Treatment of MCF-7 cells with 5-aza-2'-deoxycytidine (5-aza-dC), a potent demethylating agent, results in induction of heparanase expression and higher invasion potential in vitro and leads to an advantage of tumor formation in vivo. In 54 tissue samples, cancer samples at late stages (stage IV) showed the highest heparanase expression accomplished by little DNA methylation. On the contrary, methylation prevalence is highest in normal tissue and inversely correlated with heparanase expression. A significant correlation between DNA methylation and clinical stage was demonstrated (p = 0.012). Collectively, these results demonstrate that DNA methylation play the regulation role in heparanase gene in different stages of breast cancer and present a direct effect on tumor progression.

Depression is a serious and potentially life-threatening mental disorder with unknown etiology. Emerging evidence shows that brain-derived neurotrophic factor (BDNF) and microRNAs (miRNAs) play critical roles in the etiology of depression. Here this study was aimed to identify and characterize the roles of BDNF and its putative regulatory miRNAs in depression. First, we identified that miR-182 may be a putative miRNA that regulates BDNF levels by bioinformatic studies, and characterized the effects of miR-182 on the BDNF levels using cell-based studies, side by side with miR-132 (a known miRNA that regulates BDNF expression). We showed that treatment of miR-132 and miR-182 respectively decreased the BDNF protein levels in a human neuronal cell model, supporting the regulatory roles of miR-132 and miR-182 on the BDNF expression. Furthermore, we explored the roles of miR-132 and miR-182 on the BDNF levels in depression using human subjects by assessing their serum levels. Compared with the healthy controls, patients with depression showed lower serum BDNF levels (via the enzyme-linked immunosorbent assays) and higher serum miR-132 and miR-182 levels (via the real-time PCR). Finally, the Pearson's (or Spearman's) correlation coefficient was calculated to study whether there was a relationship among the Self-Rating Depression Scale score, the serum BDNF levels, and serum BDNF-related miRNA levels. Our results revealed that there was a significant negative correlation between the SDS scores and the serum BDNF levels, and a positive correlation between the SDS scores and miR-132 levels. In addition, we found a reverse relationship between the serum BDNF levels and the miR-132/miR-182 levels in depression. Collectively, we provided evidence supporting that miR-182 is a putative BDNF-regulatory miRNA, and suggested that the serum BDNF and its related miRNAs may be utilized as important biomarkers in the diagnosis or as therapeutic targets of depression.