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【Objective】Undersea optical cable plays a leading role in international communication. In the planning of undersea optical cable communication system, several groups of possible schemes are often determined according to experience. The scheme with relatively better transmission performance and investment cost is then selected. However, with the development of communication equipment and communication technology, the number of optional modulation formats and optical fibers keeps are increasing. The number of alternative schemes is too large to quickly determine the optimal scheme. Therefore, it is necessary to establish a cost optimization model of undersea optical cable communication system to solve the cost optimal scheme.【Methods】Aiming at the problem of system planning and configuration in the undersea optical cable communication system, a cost optimization model considering the parameters of transmission performance, transmission capacity and supply voltage is established by taking the span length, optical fiber type, number of optical fiber pairs, repeater output power, modulation format and number of practical channels as the variables. The cascaded-lexicographic method is used to solve the cost optimization model.【Results】The results show that the difference between the planning results of the proposed optimization algorithm and full traversal algorithm are no more than 0.34%. However, the number of operations of the optimization algorithm proposed in this paper is far less than that of the full traversal algorithm, with only 1/100 of that of the full traversal algorithm. Secondly, the number of operations of the cascade genelexicography method is less affected by the range of variables than that of the total traversal method. Finally, by comparing the optimal cost of the undersea cable communication system under different span length, it is found that the planning results have no regularity.【Conclusion】The variables always influence each other. The optimal cost design of the system cannot be obtained according to experience, so it needs to establish a model. The algorithm used in this paper is not only accurate, but also uses fewer operation times.

Summary: Grain chalkiness is an undesirable trait that negatively regulates grain yield and quality in rice. However, the regulatory mechanism underlying chalkiness is complex and remains unclear. We identified a positive regulator of white‐belly rate (WBR). The WBR7 gene encodes sucrose synthase 3 (SUS3). A weak functional allele of WBR7 is beneficial in increasing grain yield and quality. During the domestication of indica rice, a functional G/A variation in the coding region of WBR7 resulted in an E541K amino acid substitution in the GT‐4 glycosyltransferase domain, leading to a significant decrease in decomposition activity of WBR7A (allele in cultivar Jin23B) compared with WBR7G (allele in cultivar Beilu130). The NIL(J23B) and knockout line NIL(BL130)KO exhibited lower WBR7 decomposition activity than that of NIL(BL130) and NIL(J23B)COM, resulting in less sucrose decomposition and metabolism in the conducting organs. This caused more sucrose transportation to the endosperm, enhancing the synthesis of storage components in the endosperm and leading to decreased WBR. More sucrose was also transported to the anthers, providing sufficient substrate and energy supply for pollen maturation and germination, ultimately leading to an increase rate of seed setting and increased grain yield. Our findings elucidate a mechanism for enhancing rice yield and quality by modulating sucrose metabolism and allocation, and provides a valuable allele for improved rice quality. [ABSTRACT FROM AUTHOR]

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters.

In the aerospace sector, the development of lightweight aircraft heavily relies on the utilization of advanced aluminum–lithium alloys as primary structural materials. This study introduces an investigation aimed at optimizing the composition of an Al-2.32Li-1.44Cu-2.78Mg-0.3Ag-0.3Mn-0.1Zr alloy. The optimization process involves the selection of alloying elements through the application of machine learning techniques, with a focus on expected improvements in the specific modulus of these alloys. Expanding upon the optimization of the benchmark alloy's components, a more generalized modulus prediction model for Al–Li alloys was formulated. This model was then employed to evaluate the anticipated specific modulus of alloys within a virtual search space, encompassing substitutional elements. The study proceeded to validate six Al–Li alloys with a notably high potential for achieving an improved specific modulus. The results revealed that an alloy incorporating 0.96 wt.% of Ga as a substitutional element exhibited the most favorable microstructure. This alloy demonstrated optimal tensile strength (523 MPa) and specific modulus (31.531 GPa/(g·cm−3)), closely resembling that of the benchmark alloy. This research offers valuable insights into the application of compositional optimization to enhance the mechanical properties of Al–Li alloys. It emphasizes the significance of selecting alloying elements based on considerations such as their solid solubility thresholds and the expected enhancement of the specific modulus in Al–Li alloys. [ABSTRACT FROM AUTHOR]