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To reveal the diagenetic sequence of reservoir rocks in the central part of the deep depression basin, the Wuerhe Formation in Junggar Basin was taken as an example to conduct the detailed studies on its sedimentary facies, diagenetic sequence, and the micropore structure evolution rules based on the comprehensive data from a super deep exploration well C-6 (approximately 7,000 m in depth). First, an arid environment fan delta sedimentary model of the Wuerhe Formation was established, and its sedimentary evolution law was clarified as a gradual transition from a fan delta front to a fan delta plain during the water-regression process until the lake dried up. Then, the diagenesis types and evolution sequence of the Wuerhe Formation, and the influence degrees of the compaction, cementation, and dissolution on the rock formation process were clarified. Finally, the diagenesis and pore evolution model was established, and the greatest impact factors of the late reservoir densification were clarified. Based on this research, the diagenesis and pore evolution processes of the deep rocks in the studied deep central sag were ultimately revealed to provide useful guidance for the deeply buried oil and gas reservoir exploration.

The nonlinear optical properties of silicon have great potentials for developing all-optical switches and modulators, etc. Strategies based on all dielectric silicon photonic crystals and resonators have been proposed to design the nanophotonic devices with high nonlinearity. Nevertheless, the lack of compatible configuration with the mature CMOS technology may hinder the practical applications of the all dielectric devices. In this work, we proposed a metal–silicon hybrid metasurface to generate strong third harmonic signals from an amorphous silicon (α-Si) film. By integrating the α-Si film into a gold plasmonic nanocavity and controlling the periods of the gold meta-atoms, the efficiency of the THG process is expected to be greatly boosted. Compared to the planar α-Si film, the THG signal is enhanced by a factor of ∼370. The presented results in this work may open new routes for developing various silicon photonic devices with high optical nonlinearity.

In crop breeding, genomic selection (GS) serves as a powerful tool for predicting unknown phenotypes by using genome-wide markers, aimed at enhancing genetic gain for quantitative traits. However, in practical applications of GS, predictions are not always made within populations or for individuals that are genetically similar to the training population. Therefore, exploring possibilities and effective strategies for across-population prediction becomes an attractive avenue for applying GS technology in breeding practices. In this study, we used an existing maize population of 5820 hybrids as the training population to predict another population of 523 maize hybrids using the GBLUP and BayesB models. We evaluated the impact of optimizing the training population based on the genetic relationship between the training and breeding populations on the accuracy of across-population predictions. The results showed that the prediction accuracy improved to some extent with varying training population sizes. However, the optimal size of the training population differed for various traits. Additionally, we proposed a population structure-based across-population genomic prediction (PSAPGP) strategy, which integrates population structure as a fixed effect in the GS models. Principal component analysis, clustering, and Q-matrix analysis were used to assess the population structure. Notably, when the Q-matrix was used, the across-population prediction exhibited the best performance, with improvements ranging from 8 to 11% for ear weight, ear grain weight and plant height. This is a promising strategy for reducing phenotyping costs and enhancing maize hybrid breeding efficiency. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) has emerged as an effective technology to accelerate crop hybrid breeding by enabling early selection prior to phenotype collection. Genomic best linear unbiased prediction (GBLUP) is a robust method that has been routinely used in GS breeding programs. However, GBLUP assumes that markers contribute equally to the total genetic variance, which may not be the case. In this study, we developed a novel GS method called GA-GBLUP that leverages the genetic algorithm (GA) to select markers related to the target trait. We defined four fitness functions for optimization, including AIC, BIC, R2, and HAT, to improve the predictability and bin adjacent markers based on the principle of linkage disequilibrium to reduce model dimension. The results demonstrate that the GA-GBLUP model, equipped with R2 and HAT fitness function, produces much higher predictability than GBLUP for most traits in rice and maize datasets, particularly for traits with low heritability. Moreover, we have developed a user-friendly R package, GAGBLUP, for GS, and the package is freely available on CRAN (https://CRAN.R-project.org/package=GAGBLUP). [ABSTRACT FROM AUTHOR]

Leaf angle (LA) is closely related to plant architecture, photosynthesis and density tolerance in maize. In the current study, we used a recombinant inbred line population constructed by two maize-inbred lines to detect quantitative trait loci (QTLs) controlling LA. Based on the average LA in three environments, 13 QTLs were detected, with the logarithm of odds ranging from 2.7 to 7.21, and the phenotypic variation explained by a single QTL ranged from 3.93% to 12.64%. A stable QTL, qLA2-3, on chromosome 2 was detected and was considered to be the major QTL controlling the LA. On the basis of verifying the genetic effect of qLA2-3, a fine map was used to narrow the candidate interval, and finally, the target segment was located at a physical distance of approximately 338.46 kb (B73 RefGen_v4 version), containing 16 genes. Re-sequencing and transcriptome results revealed that five candidate genes may be involved in the regulation of LA. The results enrich the information for molecular marker-assisted selection of maize LA and provide genetic resources for the breeding of dense planting varieties. [ABSTRACT FROM AUTHOR]

In linear optical processes, compact and effective wavefront shaping techniques have been developed with the artificially engineered materials and devices in the past decades. Recently, wavefront shaping of light at newly generated frequencies was also demonstrated using nonlinear photonic crystals and metasurfaces. However, the nonlinear wave-shaping devices with both high nonlinear optical efficiency and high wave shaping efficiency are difficult to realize. To circumvent this constraint, we propose the idea of metasurface decorated optical crystal to take the best aspects of both traditional nonlinear crystals and photonic metasurfaces. In the proof-of-concept experiment, we show that a silicon nitride metasurface decorated quartz crystal can be used for the wavefront shaping of the second harmonic waves generated in quartz. With this crystal-metasurface hybrid platform, the nonlinear vortex beam generation and nonlinear holography were successfully demonstrated. The proposed methodology may have important applications in nonlinear structured light generation, super-resolution imaging, and optical information processing, etc.

The Cassegrain telescope, made of a concave primary mirror and a convex secondary mirror, is widely utilized for modern astronomical observation. However, the existence of curved mirrors inevitably results in bulky configurations. Here, we propose a new design of the miniaturized Cassegrain telescope by replacing the curved mirrors with planar reflective metasurfaces. The focusing and imaging properties of the Cassegrain metasurface telescopes are experimentally verified for circularly polarized incident light at near infrared wavelengths. The concept of the metasurface telescopes can be employed for applications in telescopes working at infrared, Terahertz, and microwave and even radio frequencies.

In the investigation of stratigraphic reservoirs, a significant discrepancy frequently exists between the delineation of the formation pinch-out line as traced using the characteristics of seismic wave reflections and the actual location of the formation pinch-out line. This has been the main problem restricting further hydrocarbon exploration and development. In this study, Hala'alate Mountain on the northwestern margin of the Junggar Basin is taken as an example for carrying out the study of stratigraphic reservoirs by integrating logging, drilling, and 3D seismic data. On the one hand, in studies based on the identification of formation pinch-out points using seismic data, the identification error of reservoir pinch-out lines is reduced by the improved included angle extrapolation method by utilizing the half energy attribute. On the other hand, the Poisson's ratio curve is reconstructed using acoustic curves and oil-gas sensitive logging, then the reservoir oil-bearing facies zone is predicted using Poisson's ratio post-stack genetic inversion to comprehensively analyze the controlling factors of stratigraphic reservoirs. The study area mainly features structural lithologic reservoirs, structural stratigraphic reservoirs and stratigraphic overlaps that pinch out reservoirs. The boundary of a stratigraphic reservoir is affected by the dip angle of the unconformity surface, the formation dip angle, and other factors. The improved included angle extrapolation method improves the identification accuracy of stratigraphic overlap pinch-out reservoirs. The reservoir distribution then is calculated according to Poisson's ratio inversion, improving the prediction accuracy for the reservoir. This method improves the predictive effect for stratigraphic reservoirs and provides a new idea for the exploration and development of similar reservoirs. [ABSTRACT FROM AUTHOR]

Drought stress is seriously affecting the growth and production of crops, especially when agricultural irrigation still remains quantitatively restricted in some arid and semi-arid areas. The identification of drought-tolerant genes is important for improving the adaptability of maize under stress. Here, we found that a new member of the actin-depolymerizing factor (ADF) family; the ZmADF5 gene was tightly linked with a consensus drought-tolerant quantitative trait locus, and the significantly associated signals were detected through genome wide association analysis. ZmADF5 expression could be induced by osmotic stress and the application of exogenous abscisic acid. Its overexpression in Arabidopsis and maize helped plants to keep a higher survival rate after water-deficit stress, which reduced the stomatal aperture and the water-loss rate, as well as improved clearance of reactive oxygen species. Moreover, seventeen differentially expressed genes were identified as regulated by both drought stress and ZmADF5, four of which were involved in the ABA-dependent drought stress response. ZmADF5-overexpressing plants were also identified as sensitive to ABA during the seed germination and seedling stages. These results suggested that ZmADF5 played an important role in the response to drought stress. [ABSTRACT FROM AUTHOR]