Scientific elite revisited: Patterns of productivity, collaboration, authorship and impact

Throughout history, a relatively small number of individuals have made a profound and lasting impact on science and society. Despite long-standing, multi-disciplinary interests in understanding careers of elite scientists, there have been limited attempts for a quantitative, career-level analysis. Here, we leverage a comprehensive dataset we assembled, allowing us to trace the entire career histories of nearly all Nobel laureates in physics, chemistry, and physiology or medicine over the past century. We find that, although Nobel laureates were energetic producers from the outset, producing works that garner unusually high impact, their careers before winning the prize follow relatively similar patterns as ordinary scientists, being characterized by hot streaks and increasing reliance on collaborations. We also uncovered notable variations along their careers, often associated with the Nobel prize, including shifting coauthorship structure in the prize-winning work, and a significant but temporary dip in the impact of work they produce after winning the Nobel. Together, these results document quantitative patterns governing the careers of scientific elites, offering an empirical basis for a deeper understanding of the hallmarks of exceptional careers in science

Significant wave height forecasting based on the hybrid EMD-SVM method

1957-1962Prediction of significant wave height (SWH) is considered an effective method in marine engineering and prevention of marine disasters. Support vector machine (SVM) model has limitations in processing nonlinear and non-stationary SWH time series. Fortunately, empirical mode decomposition (EMD) can effectively deal with the complicated series. So, the SWH prediction method based on EMD and SVM is proposed by combining the advantages of both methods. A statistical analysis was carried out to compare the results of two models i.e., between the hybrid EMD-SVM and SVM. In addition, two models are used for forecasting SWH with 3, 6, 12 and 24 hours lead times, respectively. A high R value of different prediction times for the hybrid model. Results indicate that SWH prediction of the hybrid EMD-SVM model is superior to the SVM model

A sketch-and-project method for solving the matrix equation AXB = C

In this paper, based on an optimization problem, a sketch-and-project method for solving the linear matrix equation AXB = C is proposed. We provide a thorough convergence analysis for the new method and derive a lower bound on the convergence rate and some convergence conditions including the case that the coefficient matrix is rank deficient. By varying three parameters in the new method and convergence theorems, the new method recovers an array of well-known algorithms and their convergence results. Meanwhile, with the use of Gaussian sampling, we can obtain the Gaussian global randomized Kaczmarz (GaussGRK) method which shows some advantages in solving the matrix equation AXB = C. Finally, numerical experiments are given to illustrate the effectiveness of recovered methods.Comment: arXiv admin note: text overlap with arXiv:1506.03296, arXiv:1612.06013, arXiv:2204.13920 by other author

Covariance localization in the ensemble transform Kalman filter based on an augmented ensemble

With the increased density of available observation data, data assimilation has become an increasingly important tool in marine research. However, the success of the ensemble Kalman filter is highly dependent on the size of the ensemble. A small ensemble used in data assimilation could cause filter divergence, undersampling and spurious correlations. The primary method to alleviate these problems is localization. It can eliminate some spurious correlations and increase the rank of the forecast error covariance matrix. The ensemble transform Kalman filter has been widely used in various studies as a deterministic filter. Unfortunately, the covariance localization cannot be directly applied to ensemble transform Kalman filter. The new covariance localization needs to be presented to adapt the ensemble transform Kalman filter. Based on the method of expanded ensemble and eigenvalue decomposition, this study describes a variation of covariance localization that takes advantage of an unbiased covariance matrix from the expanded ensemble. Experiments described herein show that the new method outperforms the localization methods proposed by others when used in the ensemble transform Kalman filter. The new method yields an analysis estimate that is closer to the true state under different experimental conditions

Transport Model of Underground Sediment in Soils

Studies about sediment erosion were mainly concentrated on the river channel sediment, the terrestrial sediment, and the underground sediment. The transport process of underground sediment is studied in the paper. The concept of the flush potential sediment is founded. The transport equation with stable saturated seepage is set up, and the relations between the flush potential sediment and water sediment are discussed. Flushing of underground sediment begins with small particles, and large particles will be taken away later. The pore ratio of the soil increases gradually. The flow ultimately becomes direct water seepage, and the sediment concentration at the same position in the water decreases over time. The concentration of maximal flushing potential sediment decreases along the path. The underground sediment flushing model reflects the flushing mechanism of underground sediment

A Resonance Model for Spontaneous Cortical Activity

How human brain function emerges from structure has intrigued researchers for decades and numerous models have been put forward, yet none of them yields a close structure-function relation. Here we present a resonance model based on neuronal spike timing dependent plasticity (STDP) principle to describe the spontaneous cortical activity by incorporating the dynamic interactions between neuronal populations into a wave equation, which is able to accurately predict the resting brain functional connectivity (FC), including the resting-state networks. Besides, the proposed model provides strong theoretical and experimental evidences that the spontaneous dynamic coupling between brain regions fluctuates with a low frequency. Crucially, it is able to account for how the negative functional correlations emerge during resonance. We test the model with a large cohort of subjects (1038) from the Human Connectome Project (HCP) S1200 release in both time and frequency domain, which exhibits superior performance to existing eigen-decomposition models

Partial masquerading and background matching in two Asian box turtle species (<i>Cuora</i> spp.)

Animals living in heterogeneous natural environments adopt different camouflage strategies against different backgrounds, and behavioral adaptation is crucial for their survival. However, studies of camouflage strategies have not always quantified the effect of multiple strategies used together. In the present study, we used a human visual model to quantify similarities in color and shape between the carapace patterns of two Cuora species and their preferred habitats. Our results showed that the color of the middle stripe on the carapace of Cuora galbinifrons (Indochinese box turtle) was significantly similar to the color of their preferred substrates. Meanwhile, the middle stripe on the carapace of C. mouhotii (keeled box turtle) contrasted more with their preferred substrates, and the side stripe matched most closely with the environment. Furthermore, the carapace side stripe of C. galbinifrons and the carapace middle stripe of C. mouhotii highly contrasted with their preferred substrates. We quantified the similarity in shape between the high-contrast stripes of both Cuora species and leaves from their habitats. The carapace middle stripe of C. mouhotii was most similar in shape to leaves from the broad-leaves substrate, and the carapace side stripe of C. galbinifrons was the most similar in shape to leaves from the bamboo-leaves substrate. We determined that these species adopt partial masquerading when their entire carapace is exposed and partially match their background when they semi-cover themselves in leaf litter. To the best of our knowledge, this is the first study to demonstrate that partial masquerading and background matching improve the camouflage effect of Asian box turtles in their preferred habitats. This is a novel study focusing on the influence of the shape and color of individual carapace segments on reducing detectability and recognition.</p

Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generation

Generative Neural Radiance Fields (GNeRF) based 3D-aware GANs have demonstrated remarkable capabilities in generating high-quality images while maintaining strong 3D consistency. Notably, significant advancements have been made in the domain of face generation. However, most existing models prioritize view consistency over disentanglement, resulting in limited semantic/attribute control during generation. To address this limitation, we propose a conditional GNeRF model incorporating specific attribute labels as input to enhance the controllability and disentanglement abilities of 3D-aware generative models. Our approach builds upon a pre-trained 3D-aware face model, and we introduce a Training as Init and Optimizing for Tuning (TRIOT) method to train a conditional normalized flow module to enable the facial attribute editing, then optimize the latent vector to improve attribute-editing precision further. Our extensive experiments demonstrate that our model produces high-quality edits with superior view consistency while preserving non-target regions. Code is available at https://github.com/zhangqianhui/TT-GNeRF.Comment: 13 page

Surfactant Induced Reservoir Wettability Alteration: Recent Theoretical and Experimental Advances in Enhanced Oil Recovery

Reservoir wettability plays an important role in various oil recovery processes. The origin and evolution of reservoir wettability were critically reviewed to better understand the complexity of wettability due to interactions in crude oil-brine-rock system, with introduction of different wetting states and their influence on fluid distribution in pore spaces. The effect of wettability on oil recovery of waterflooding was then summarized from past and recent research to emphasize the importance of wettability in oil displacement by brine. The mechanism of wettability alteration by different surfactants in both carbonate and sandstone reservoirs was analyzed, concerning their distinct surface chemistry, and different interaction patterns of surfactants with components on rock surface. Other concerns such as the combined effect of wettability alteration and interfacial tension (IFT) reduction on the imbibition process was also taken into account. Generally, surfactant induced wettability alteration for enhanced oil recovery is still in the stage of laboratory investigation. The successful application of this technique relies on a comprehensive survey of target reservoir conditions, and could be expected especially in low permeability fractured reservoirs and forced imbibition process

Synthesis of Alkyl Substituted Dicyclohexano-18-crown-6 Homologues for Strontium Extraction in HNO3 Media

AbstractA series of dicyclohexano-18-crown-6 (DCH18C6) homologues containing different alkyl substituents were synthesized for a comparative study of the extraction ability towards strontium. The synthesis and the structure characterization of the intermediates and the products were detailed. The crown ether homologues were labeled as CX-DCH18C6 (X=3∼7), where the X represents the number of the carbon atoms in the alkyl substituents. The extraction ability of the CX-DCH18C6 samples towards strontium in solvent extraction system was investigated. The substituent effect of the samples was discussed, and the factors affecting the separation such as solvent, acidity and initial metal concentration were examined