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To overcome the disadvantages of premature convergence and easy trapping into local optimum solutions, this paper proposes an improved particle swarm optimization algorithm (named NDWPSO algorithm) based on multiple hybrid strategies. Firstly, the elite opposition-based learning method is utilized to initialize the particle position matrix. Secondly, the dynamic inertial weight parameters are given to improve the global search speed in the early iterative phase. Thirdly, a new local optimal jump-out strategy is proposed to overcome the \"premature\" problem. Finally, the algorithm applies the spiral shrinkage search strategy from the whale optimization algorithm (WOA) and the Differential Evolution (DE) mutation strategy in the later iteration to accelerate the convergence speed. The NDWPSO is further compared with other 8 well-known nature-inspired algorithms (3 PSO variants and 5 other intelligent algorithms) on 23 benchmark test functions and three practical engineering problems. Simulation results prove that the NDWPSO algorithm obtains better results for all 49 sets of data than the other 3 PSO variants. Compared with 5 other intelligent algorithms, the NDWPSO obtains 69.2%, 84.6%, and 84.6% of the best results for the benchmark function ( f 1 - f 13 ) with 3 kinds of dimensional spaces (Dim = 30,50,100) and 80% of the best optimal solutions for 10 fixed-multimodal benchmark functions. Also, the best design solutions are obtained by NDWPSO for all 3 classical practical engineering problems.

The lithofacies play a pivotal role in studying development patterns, reservoir characteristics, and sweet spot predictions of shale oil. Lithofacies classification typically relies on core observations and conventional well logging analyses, whereas seismic attribute extraction is often employed in regions with sparse or absent wells. However, seismic attribute extraction entails considerable computation and time, and exclusive reliance on seismic attribute analysis can result in multiple interpretations. This paper emphasizes predicting shale oil lithofacies associations based on seismic reflection characteristics and sedimentary facies patterns which can can help avoid these issues. The lithofacies classification scheme has identified seven lithofacies and associations by means of core observations, testing data, and logging curve analysis of the Shahejie Formation in the Huanghekou Sag. Through well-seismic calibration, the seismic reflections and sedimentary patterns of different lithofacies associations were examined to formulate a seismic facies identification chart and propose six models. For areas without wells, based on the distribution of sedimentary facies and in combination with seismic reflection characteristics, identification and delineation are conducted on a planar scale to analyze the distribution features of lithofacies associations. The results of predicting the distribution of shale oil lithofacies associations in the Shahejie Formation indicate that the development pattern of lithofacies associations is basically consistent with that of sedimentary facies units. The primary models developed in the study area encompass delta, sublacustrine fan, and shore-shallow lake. The approach of identifying shale oil lithofacies associations based on seismic reflection and sedimentary backgrounds offers a novel means for discerning lithofacies and associations in sections devoid of cores and specialized well logging data.

Rice (Oryza sativa) is an important dietary source of both essential micronutrients and toxic trace elements for humans. The genetic basis underlying the variations in the mineral composition, the ionome, in rice remains largely unknown. Here, we describe a comprehensive study of the genetic architecture of the variation in the rice ionome performed using genome-wide association studies (GWAS) of the concentrations of 17 mineral elements in rice grain from a diverse panel of 529 accessions, each genotyped at ∼6.4 million single nucleotide polymorphism loci. We identified 72 loci associated with natural ionomic variations, 32 that are common across locations and 40 that are common within a single location. We identified candidate genes for 42 loci and provide evidence for the causal nature of three genes, the sodium transporter gene Os-HKT1;5 for sodium, Os-MOLYBDATE TRANSPORTER1;1 for molybdenum, and Grain number, plant height, and heading date7 for nitrogen. Comparison of GWAS data from rice versus Arabidopsis (Arabidopsis thaliana) also identified well-known as well as new candidates with potential for further characterization. Our study provides crucial insights into the genetic basis of ionomic variations in rice and serves as an important foundation for further studies on the genetic and molecular mechanisms controlling the rice ionome.

This study identified and detected the existence of major pollutants in northeast China. As an alpine region and an agricultural base, this region has representative significance in pollution research. We selected 56 samples from drinking water sources of typical villages and towns, focusing on the analysis of heavy metals and organic micropollutants in northeast China. The analysis results showed that Fe and Mn were the main metal elements exceeding the standard. The exceeding rates were 17.9% and 19.6%. Experiments showed that there were 19 kinds of pesticides, 6 kinds of OPEs, 2 kinds of PAEs, 22 kinds of PPCPs. The detection rate of these 49 kinds of organic micro-pollutants were 1.79~82.14%. The characteristics of organic pollution were extensive and varied. Many underground water samples had high level of micropollutants. The water quality parameters of drinking water sources in villages and towns showed close relation to local geological conditions and agricultural activities. Actions must be taken to control these parameters from the source of pollution.

This paper presents a distributed vibration control method using attachable absorbers for micro-vibration control of large space payload structures. The distributed vibration control system is modeled at three levels. The simplification of the attachable absorber model is discussed, and the single-channel ANC controller is extended to a multi-channel configuration. Based on the models, simulation analysis is conducted, revealing that the voltage–force output of the absorber in the low-frequency range can be simplified to a second-order system. During the distributed vibration control system simulation, a Simulink–GA hybrid optimization is applied to address the large number of converging parameters. The optimized parameters successfully control the vibration of all channels. Further analysis indicates that the coupling between control channels slightly reduces convergence speed but has no impact on the final control effect. Additionally, the control system can achieve the same results by independently tuning parameters for each channel. The experimental results, using absorber prototypes and a model with 12 sub-mirror structures, demonstrate that the method can control sub-mirror vibrations simultaneously, maintaining the flatness of the main mirror under disturbance, with a 90% reduction in vibration within 4 s. The coupling effect reduces the final convergence speed by approximately 10%, with a time difference of around 1 s.

Hyperspectral anomaly detection is used to recognize unusual patterns or anomalies in hyperspectral data. Currently, many spectral–spatial detection methods have been proposed with a cascaded manner; however, they often neglect the complementary characteristics between the spectral and spatial dimensions, which easily leads to yield high false alarm rate. To alleviate this issue, a spectral–spatial information fusion (SSIF) method is designed for hyperspectral anomaly detection. First, an isolation forest is exploited to obtain spectral anomaly map, in which the object-level feature is constructed with an entropy rate segmentation algorithm. Then, a local spatial saliency detection scheme is proposed to produce the spatial anomaly result. Finally, the spectral and spatial anomaly scores are integrated together followed by a domain transform recursive filtering to generate the final detection result. Experiments on five hyperspectral datasets covering ocean and airport scenes prove that the proposed SSIF produces superior detection results over other state-of-the-art detection techniques.

Background Protein lysine succinylation is an important post-translational modification and plays a critical regulatory role in almost every aspects of cell metabolism in both eukaryotes and prokaryotes. Common wheat is one of the major global cereal crops. However, to date, little is known about the functions of lysine succinylation in this plant. Here, we performed a global analysis of lysine succinylation in wheat and examined its overlap with lysine acetylation. Results In total, 330 lysine succinylated modification sites were identified in 173 proteins. Bioinformatics analysis showed that the modified proteins are distributed in multiple subcellular compartments and are involved in a wide variety of biological processes such as photosynthesis and the Calvin-Benson cycle, suggesting an important role for lysine succinylation in these processes. Five putative succinylation motifs were identified. A protein interaction network analysis revealed that diverse interactions are modulated by protein succinylation. Moreover, 21 succinyl-lysine sites were found to be acetylated at the same position, and 33 proteins were modified by both acetylation and succinylation, suggesting an extensive overlap between succinylation and acetylation in common wheat. Comparative analysis indicated that lysine succinylation is conserved between common wheat and Brachypodium distachyon . Conclusions These results suggest that lysine succinylation is involved in diverse biological processes, especially in photosynthesis and carbon fixation. This systematic analysis represents the first global analysis of lysine succinylation in common wheat and provides an important resource for exploring the physiological role of lysine succinylation in this cereal crop and likely in all plants.

Lysine acetylation is a major post-translational modification that plays an important regulatory role in almost every aspects in both eukaryotes and prokaryotes. Bacillus amyloliquefaciens , a Gram-positive bacterium, is very effective for the control of plant pathogens. However, very little is known about the function of lysine acetylation in this organism. Here, we conducted the first lysine acetylome in B. amyloliquefaciens through a combination of highly sensitive immune-affinity purification and high-resolution LC−MS/MS. Overall, we identified 3268 lysine acetylation sites in 1254 proteins, which account for 32.9% of the total proteins in this bacterium. Till date, this is the highest ratio of acetylated proteins that have been identified in bacteria. Acetylated proteins are associated with a variety of biological processes and a large fraction of these proteins are involved in metabolism. Interestingly, for the first time, we found that about 71.1% (27/38) and 78.6% (22/28) of all the proteins tightly related to the synthesis of three types of pepketides and five families of lipopeptides were acetylated, respectively. These findings suggest that lysine acetylation plays a critical role in the regulation of antibiotics biosynthesis. These data serves as an important resource for further elucidation of the physiological role of lysine acetylation in B. amyloliquefaciens .

Background Ganoderma lucidum , one of the best-known medicinal mushrooms in the world, produces more than 400 different bioactive compounds. However, the regulation of these bioactive compounds biosynthesis is still unclear. Lysine succinylation is a critical post-translational modification and has many important functions in all aspects of eukaryotic and prokaryotic cells. Although it has been studied for a long time, its function is still unclear in G. lucidum . In this study, a global investigation was carried out on the succinylome in G. lucidum . Results In total, 382 modified proteins which contain 742 lysine succinylated sites were obtained. The proteomics data are available through ProteomeXchange with the dataset accession number PXD013954. Bioinformatics analysis revealed that the succinylated proteins were distributed in various cellular biological processes and participated in a great variety of metabolic pathways including carbon metabolism and biosynthesis of secondary metabolites. Notably, a total of 47 enzymes associated with biosynthesis of triterpenoids and polysaccharides were found to be succinylated. Furthermore, two succinylated sites K90 and K106 were found in the conserved Fve region of immunomodulatory protein LZ8. These observations show that lysine succinylation plays an indispensable role in metabolic regulation of bioactive compounds in G. lucidum . Conclusions These findings indicate that lysine succinylation is related to many metabolic pathways, especially pharmacologically bioactive compounds metabolism. This study provides the first global investigation of lysine succinylation in G. lucidum and the succinylome dataset provided in this study serves as a resource to further explore the physiological roles of these modifications in secondary metabolism.