Search Results (2,305)

Feed efficiency is a key economic trait that affects the cost of production in broiler farming. Reducing broiler feed costs contributes to reducing excessive feed consumption and increasing the productivity of broiler breeding. Therefore, identifying genetic regions associated with feed efficiency is crucial for broiler breeding. In this study, we performed genome-wide association (GWAS) analyses of feed conversion ratio (FCR) and residual feed intake (RFI) traits for four growth cycles (72–81, 81–89, 89–113, and 113–120 days of age) using 55K single-nucleotide microarray genotypic data of 4493 Wenchang chickens from two generations. In the single-trait GWAS, a total of 59 SNPs were identified, and 36 genes were annotated within the ±50 kb regions surrounding candidate loci (including ABCC6, CLDN10, DGKB, EXT2, FOXO1, IFT140, JAG2, among others. These candidate loci explained 1.4–7.0% of the phenotypic variance explained, and applying a filtering criterion that required a deleteriousness score greater than 8, one locus-Gallus gallus chromosome (GGA) 5:3550350 (chCADD score = 12.51524) was located within intron 3 of ANOX3. In the FCR and RFI traits in the longitudinal GWAS (LONG-GWAS) model, 80 SNPs and 191 SNPs were identified, respectively, and a total of 43 genes and 121 genes were annotated. A total of 33 candidate loci were screened by combining the locus deleteriousness scores, and 25 candidate genes were annotated within the upper and lower 50 kb ranges. Through KEGG signaling pathway analysis, it was found that the candidate genes were highly enriched mainly in autophagy, mitochondrial phagocytosis, and other pathways. In conclusion, the SNPs and potential genes identified in this study will be helpful for chicken breeding and provide fundamental data for the genetic basis of chicken feed efficiency-related traits. Full article

Chaotic systems, characterized by extreme sensitivity to initial conditions and complex dynamical behaviors, exhibit significant potential for applications in various fields. Effective control of chaotic system synchronization is particularly crucial in sensor-related applications. This paper proposes a preset-time fuzzy zeroing neural network (PTCFZNN) model based on Takagi–Sugeno fuzzy control to achieve chaotic synchronization in aperiodic parameter exciting chaotic systems. The designed PTCFZNN model accurately handles the complex dynamic variations inherent in chaotic systems, overcoming the challenges posed by aperiodic parameter excitation to achieve synchronization. Additionally, field-programmable gate array (FPGA) verification experiments successfully implemented the PTCFZNN-based chaotic system synchronization control on hardware platforms, confirming its feasibility for practical engineering applications. Furthermore, experimental studies on chaos-masking communication applications of the PTCFZNN-based chaotic system synchronization further validate its effectiveness in enhancing communication confidentiality and anti-jamming capability, highlighting its important application value for securing sensor data transmission. Full article

Golden pompano (Trachinotus ovatus) is an economically important fish species along China’s southern coast. However, infections by Cryptocaryon irritans severely constrain the healthy and sustainable development of the aquaculture industry. To investigate the genetic basis of resistance to this parasite in golden pompano, this study employed transcriptomic and metabolomic analyses to compare differences between susceptible (ES) and resistant (RS) groups following C. irritans challenge. Transcriptome analysis identified 2031 differentially expressed genes (DEGs) between EST and RST groups, comprising 1004 up-regulated and 1027 down-regulated genes. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed that these DEGs were primarily enriched in lipid metabolism and amino acid metabolism pathways. Untargeted metabolomics detected 461 significantly differentially abundant metabolites (295 up-regulated, 166 down-regulated), confirming pronounced metabolic differences between ES and RS groups, particularly in lipid and amino acid metabolism. Further, KEGG enrichment highlighted steroid hormone biosynthesis, α-linolenic acid metabolism, and arachidonic acid metabolism as the most significantly altered pathways upon infection. This integrated transcriptomic and metabolomic study reveals substantial differences in gene expression and metabolite profiles between susceptible and resistant golden pompano in response to C. irritans. These changes predominantly involve lipid metabolism and amino acid metabolism, suggesting that these processes are critical in determining host resistance/susceptibility. Full article

To address urban flooding challenges exacerbated by climate change and urbanization, this study develops an integrated assessment framework combining the analytic hierarchy process (AHP), entropy weight method, and cloud model to quantify urban flood resilience. Resilience is deconstructed into resistance, adaptability, and recovery and evaluated through 24 indicators spanning water resources, socio-economic systems, and ecological systems. Subjective (AHP) and objective (entropy) weights are optimized via minimum information entropy, with the cloud model enabling qualitative–quantitative resilience mapping. Analyzing 2014–2024 data from 27 Chinese sponge city pilots, the results show resilience improved from “poor to average” to “good to average”, with a 2.89% annual growth rate. Megacities like Beijing and Shanghai excel in resistance and recovery due to infrastructure and economic strengths, while cities like Sanya enhance resilience via ecological restoration. Key drivers include water allocation (27.38%), economic system (18.41%), and social system (17.94%), with critical indicators being population density, secondary industry GDP ratio, and sewage treatment rate. Recommendations emphasize upgrading rainwater storage, intelligent monitoring networks, and resilience-oriented planning. The model offers a scientific foundation for urban disaster risk management, supporting sustainable development. This approach enables systematic improvements in adaptive capacity and recovery potential, providing actionable insights for global flood-resilient urban planning. Full article

Overpressure systems in the Qingshankou Formation of the Gulong Sag have a significant impact on unconventional shale oil accumulation, but their distribution and genesis are unknown. This study uses a comparative analysis of three primary pressure prediction methods—the equivalent depth method, the Eaton method, and the Bowers method—to investigate the genetic mechanisms of overpressure and their controlling factors. The study clarifies the link between overpressure and hydrocarbon distribution. The key findings are as follows. (1) The Eaton method is identified as the best approach for estimating current formation pore pressure. The Qingshankou Formation exhibits mild overpressure development, with a maximum pressure coefficient of 1.44. (2) Hydrocarbon-generating overpressure, driven by source rock maturation, is confirmed as the dominant mechanism through integrated acoustic velocity–density cross plots and logging analysis. (3) Tectonic-sedimentary factors, such as burial depth, source rock thickness, sand-mud ratio, and faults, collectively control the spatial variability of overpressure. (4) The distribution of the Gulong shale oil and the Fuyu tight oil is influenced by overpressure, with the northwestern part of the sag and the adjacent sand bodies being the respectively favorable areas. These results lay the groundwork for accurately reconstructing paleopressure and better understanding the hydrocarbon accumulation potential of shale oil and Fuyu tight oil. They also provide guidance on the exploration and development of unconventional resources. Full article

As a crucial aspect of epigenetic research, DNA methylation is fundamental to genomic stability, gene transcription regulation, and chromatin remodeling. Rice is a staple food source for roughly half of the world’s population. Therefore, optimizing rice yield and stress tolerance is vital for global food security. With the continuous advancement of DNA methylation detection technologies, studies have shown that DNA methylation regulates various rice growth and development processes, including root differentiation and grain development, through the dynamic equilibrium of de novo methylation, maintenance methylation, and demethylation. Furthermore, DNA methylation is crucial in the plant’s response to environmental stressors like high or low temperature, drought and salinity. The patterns of DNA methylation modifications are also closely linked to rice domestication and heterosis formation. Therefore, a comprehensive investigation of the DNA methylation regulatory network holds significant theoretical value for rice genetic improvement and molecular breeding. This review offers a systematic analysis of the molecular mechanisms and detection technologies of DNA methylation, as well as its regulatory roles in rice growth and development, stress responses, and other biological processes, aiming to provide a theoretical foundation for rice genetic improvement research. Full article

NIN-like proteins (NLPs) are conserved, plant-specific transcription factors that play crucial roles in the nitrate signaling response, plant growth and development, and abiotic stress responses. However, their functions have not been explored in sweet potato. In this study, we identified 7 NLPs in cultivated hexaploid sweet potato (Ipomoea batatas, 2n = 6x = 90), 9 NLPs in the diploid relative Ipomoea trifida (2n = 2x = 30), and 12 NLPs in Ipomoea triloba (2n = 2x = 30) via genome structure analysis and phylogenetic characterization, respectively. The protein physiological properties, chromosome localization, phylogenetic relationships, syntenic analysis maps, gene structure, promoter cis-acting regulatory elements, and protein interaction networks were systematically investigated to explore the possible roles of homologous NLPs in the nitrate signaling response, growth and development, and abiotic stress responses in sweet potato. The expression profiles of the identified NLPs in different tissues and treatments revealed tissue specificity and various expression patterns in sweet potato and its two diploid relatives, supporting differences in the evolutionary trajectories of the hexaploid sweet potato. These results are a critical first step in understanding the functions of sweet potato NLPs and offer more candidate genes for improving nitrogen use efficiency and increasing yield in cultivated sweet potato. Full article

The issue of working face stability in shield tunnels crossing inclined layered soil is addressed by a modified version of the Mohr–Coulomb strength criterion. This model considers spatial nonhomogeneity and anisotropy of the soil layer, and enables a 3D tunnel stability analysis. It derives the energy equation using virtual work, finds the ultimate support stress at the working face, and solves for its optimal upper bound using an algorithm. This research examined the impact of soil nonhomogeneity, anisotropy, and reduced tensile strength parameters on the stability of tunnel working faces. The results demonstrate the validity of the model, as the findings are consistent with existing research when only tensile strength is considered. The ultimate support force decreases with the nonhomogeneous coefficient and increases with the nonhomogeneously directional angle. The ultimate support force decreases first, and then increases with the soil layer’s inclined angle. Soil layers between 10° and 30° have the lowest ultimate support force. This ultimate support force gets stronger with an increasing anisotropic coefficient. Case studies show that using a method that accounts for soil tensile strength to calculate tunnel working face support force results in a relative error of only 1.92%, improving tunnel stability assessment accuracy. Full article

Water injection development represents the predominant development method for enhancing oil recovery (EOR) efficiency and achieving the balanced utilization of oil reservoirs. In light of the current situation of oilfield water injection technology, a comprehensive overview of the evolution of full-scale water injection technology is given, with particular emphasis on the influence of geological factors, technological advancements, and existing challenges. The principal issues currently encountered include an unequal distribution of layers, the complexity of subdivision, casing deformation, and damage to deep well equipment, which collectively impede the effective implementation of subdivision water injection development technology. The novelty of the research lies in the current development status of full-scale injection wells, which is not only reflected in the depth-scale, but also in the operational difficulty-scale. A thorough exploration of subdivision water injection development technologies has been conducted, and the applicability and limitations of these technologies in diverse reservoir conditions have been evaluated. The proposal is for intelligent injection technology to be adopted for medium–shallow heterogeneous wells, and for ball-pitching plugging profile control technology to be adopted for deep/horizontal/special condition wells. A comparative analysis was conducted to evaluate the characteristics, application scenarios, advantages, and disadvantages of intelligent injection technologies, demonstrating its intelligence, automation, and precision in the practical application. In regard to the ball-pitching plugging profile control technology, the design and performance of the plugging ball, the plugging mechanism, and the application effect were elucidated. Based on the existing challenges in the realm of water injection development, the research prospects for full-scale subdivision water injection development technologies were proposed, and the importance of interdisciplinary cooperation and the integration of artificial intelligence technology were also emphasized. This research would provide a technical foundation for increasing oil displacement efficiency, markedly augmenting EOR, and would also be imperative for improving the economic benefits and alleviating the global oil resource tension. Full article

Accurate and real-time environmental perception is essential for the safe and efficient execution of deep-sea mining operations. Semantic segmentation of forward-looking sonar (FLS) images plays a pivotal role in enabling environmental awareness for deep-sea mining vehicles (DSMVs), but remains challenging due to strong acoustic noise, blurred object boundaries, and long-range semantic dependencies. To address these issues, this study proposes DSM-Seg, a novel hybrid segmentation architecture combining Convolutional Neural Networks (CNNs) and Receptance Weighted Key-Value (RWKV) modeling. The architecture integrates a Physical Prior-Based Semantic Guidance Module (PSGM), which utilizes sonar-specific physical priors to produce high-confidence semantic guidance maps, thereby enhancing the delineation of target boundaries. In addition, a RWKV-Based Global Fusion with Semantic Constraints (RGFSC) module is introduced to suppress cross-regional interference in long-range dependency modeling and achieve the effective fusion of local and global semantic information. Extensive experiments on both a self-collected seabed terrain dataset and a public marine debris dataset demonstrate that DSM-Seg significantly improves segmentation accuracy under complex conditions while satisfying real-time performance requirements. These results highlight the potential of the proposed method to support intelligent environmental perception in DSMV applications. Full article

The seismic bearing capacity of water-saturated composite foundations adjacent to slopes is critical for engineering safety, yet it is significantly influenced by complex factors such as earthquakes and heavy rainfall. This paper establishes a failure mechanism model that involves both reinforced and non-reinforced zones, comprehensively considering the synergistic effects of seismic force, pore water pressure and group pile replacement rate, and thus addressing the issue that existing models struggle to account for the coupling effects of multiple factors. Based on the principle of virtual work, a general solution for ultimate bearing capacity is derived, and the optimal solution is obtained using the MATLAB R2023a exhaustive method. Findings reveal that pile group support substantially enhances bearing capacity: the improvement becomes more pronounced with higher soil strength parameters (φ, c) and replacement ratios. When the seismic acceleration coefficient increases from 0 to 0.3, the bearing capacity of the unreinforced foundation decreases by approximately 61.6% (from 134.71 kPa to 51.83 kPa), while group pile support can increase the bearing capacity by 433.2%. Notably, when soil strength is inherently high, the marginal benefit of pile group reinforcement diminishes. A case study in Fuzhou validates through numerical simulation that pile groups improve foundation stability by altering energy dissipation distribution, with the discrepancy between theoretical calculations and simulation results within 10%. The research results can directly guide the design of saturated composite foundations near slopes in earthquake-prone areas (such as Fujian and Guangdong) and enhance the seismic safety reserve by optimizing the replacement rate of group piles (recommended to be 0.2~0.3). Full article

Seed rope direct seeding technology is a precision seeding method that can accurately mix and arrange multiple varieties based on specific grain spacing and quantity, making it suitable for precision breeding and variety comparison studies. As seed ropes serve as the crucial seed encapsulation material in seed rope direct seeding, this study employed a multi-faceted approach to investigate the dynamic degradation of nonwoven fabric and paper material seed ropes under diverse environmental conditions as well as their adhesion properties with Ultisols, Oxisols, and the Substrate in this seeding technique. Firstly, the degradation dynamics were systematically analyzed using image-based surface area detection, breaking force measurement, and organic carbon content analysis. Secondly, the process of seed rope laying was simulated by modeling the sliding friction and adhesion forces during the detachment of soil slurry. The laying motion was simulated considering both sliding friction (during the uniform-speed interaction between the seed rope and soil slurry) and adhesion (during upward detachment), providing crucial reference values for optimizing the rope-breaking mechanism in field applications. The study yielded several significant findings: In natural environments, Wood pulp paper seed rope degrades significantly faster than nonwoven fabric, with a degradation cycle of only 5.68 days in winter (approximately 34% of the degradation cycle of nonwoven fabric) and 4.70 days in summer (approximately 78% of the degradation cycle of nonwoven fabric). The main effect of seed viability on the degradation rate of seed tapes was not statistically significant. The degradation of Wood pulp paper seed rope was relatively predictable in indoor settings but exhibited notable fluctuations outdoors. The peak friction occurred at 35% soil moisture content, with values of 1.22 N for Wood pulp paper seed rope and 2.08 N for nonwoven fabric when interacting with Oxisols; nonwoven ropes demonstrated stronger adhesion than Wood pulp paper seed rope in the Substrate (at moisture contents of 25–30% and 40–45%) and Oxisols (at 35–45% moisture). In Ultisols, nonwoven fabric only showed superior adhesion compared to Wood pulp paper seed rope at 35–45% moisture, while Wood pulp paper seed rope exhibited better adhesion in other moisture ranges. Full article

Fish reproduction requires suitable salinity and temperature, as well as sufficient energy. This study investigated temperature and salinity effects on ovarian development of Lateolabrax maculatus and energy metabolism differences between reproduction and growth. Two salinities (4‰ and 30‰) and temperatures (18 ± 1 °C and 30 ± 1 °C) formed four treatments: SWNT (30‰, 30 ± 1 °C), SWLT (30‰, 18 ± 1 °C), FWLT (4‰, 18 ± 1 °C), and FWNT (4‰, 30 ± 1 °C). GSI and sex hormones (FSH, LH, E2, and 17α,20β-DHP) were measured. Transcriptome analysis explored how temperature and salinity regulate ovarian development in L. maculatus, while integrated transcriptomic and targeted energy metabolomic analyses revealed energy metabolism differences between ovary and muscle during this process. The results showed that low salinity (4‰) and low temperature (18 ± 1 °C) synergistically promoted ovarian development in the FWLT group, as indicated by a significant increase in GSI and elevated levels of key sex hormones (FSH, LH, E2, and 17α,20β-DHP). Transcriptome analysis showed that low temperature activated pathways involved in steroidogenesis, oocyte maturation, and meiosis, and genes such as ADCY6, PRKACB, CPEB4, FZD7-A, and CCND2 were significantly upregulated. Salinity changes mainly affected amino acid metabolism, cholesterol metabolism, and the insulin signaling pathway. Genes such as PCSK9 and CKM may regulate ovarian development by regulating hormone synthesis and energy metabolism. Comprehensive transcriptome and metabolome analyses show that glycolysis is downregulated and oxidative phosphorylation is upregulated in the ovary, suggesting that ovarian oogenesis tends to be energized by aerobic metabolism. The TCA cycle may be used more for providing biosynthetic precursors and facilitating the transport of substrates between the mitochondrion and the cytoplasm rather than just as a source of ATP. Muscle tissue relies primarily on glycolysis for rapid energy production and may redistribute energy to the gonads, prioritizing the energy needs of the ovaries and contributing to the dynamic balance between reproduction and growth. This study provides insights into the molecular mechanisms of how environmental factors regulate fish reproduction, providing a theoretical basis and potential molecular targets for the regulation of reproduction and optimization of aquaculture environments. Full article

Plume poppy (Macleaya cordata), an important member of the Papaveraceae family, is a substantial source of benzylisoquinoline alkaloids (BIAs) such as sanguinarine and chelerythrine. These compounds possess significant therapeutic potential, including anti-inflammatory, anticancer, and antimicrobial activities, along with various industrial applications. However, the yield of these compounds in native plants are minimal and highly variable due to certain ecological factors. Recent advances in transgenic technologies have opened a new avenue for enhancing the biosynthesis of BIAs and optimizing their delivery in plume poppy. This review consolidates recent strategies in gene editing and metabolic modulations aimed at improving alkaloid biosynthesis in plume poppy. It uniquely connects these tools with industrial and therapeutic demands, offering a roadmap for enhanced BIA production. The current review also provides new insights into the overcoming the current limitations, offering potential solutions for stable, high-yield production of BIAs in plume poppy for their therapeutic use. Full article