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The inferred density of Enceladus' core, together with evidence of hydrothermal activity within the moon, suggests that the core is porous. Tidal dissipation in an unconsolidated core has been proposed as the main source of Enceladus' geological activity. However, the tidal response of its core has generally been modeled assuming it behaves viscoelastically rather than poroviscoelastically. In this work, we analyze the poroviscoelastic response to better constrain the distribution of tidal dissipation within Enceladus. A poroviscoelastic body has a different tidal response than a viscoelastic one; pressure within the pores alters the stress field and induces a Darcian porous flow. This flow represents an additional pathway for energy dissipation. Using Biot's theory of poroviscoelasticity, we develop a new framework to obtain the tidal response of a spherically symmetric, self-gravitating moon with porous layers and apply it to Enceladus. We show that the boundary conditions at the interface of the core and overlying ocean play a key role in the tidal response. The ocean hinders the development of a large-amplitude Darcian flow, making negligible the Darcian contribution to the dissipation budget. We therefore infer that Enceladus' core can be the source of its geological activity only if it has a low rigidity and a very low viscosity. A future mission to Enceladus could test this hypothesis by measuring the phase lags of tidally induced changes of gravitational potential and surface displacements.

Gastric mucosal samples were procured and underwent the sequencing of 16S ribosomal RNA (16S rRNA) via Illumina high-throughput sequencing technology to explore the impact of Helicobacter pylori (H. pylori) infection on the composition of gastric flora in chronic gastritis (CG) patients. In the results, the operational taxonomic unit (OTU) analysis revealed an overlap of 5706 OTUs shared between the two groups. The top 5 abundance ranking (TOP5) phyla comprised Bacteroidetes, Proteobacteria, Firmicutes, Actinobacteria, and Epsilonbacteraeota, while the TOP5 genus was Lachnospiraceae_NK4A136_group, Helicobacter, Bacteroides, Klebsiella, and Pseudomonas. In the metabolic pathways at the Kyoto Encyclopedia of Genes and Genomes (KEGG)_L3 level, conspicuous variations across seven functions were observed between the H. pylori-positive (HP_Pos) and H. pylori-negative (HP_Neg) groups. Subsequently, functional gene enrichment in KEGG pathways was further validated through animal experimentation. In contrast to the mice in the HP_Neg group, those infected with H. pylori manifested an infiltration of inflammatory cells, an augmentation in gastric acid secretion, and conspicuously elevated scores regarding gastric activity, along with heightened levels of malondialdehyde. In conclusion, CG patients infected with H. pylori displayed a disorder in gastric flora, furnishing a theoretical basis for the prophylaxis of H. pylori infection and its associated pathogenic ramifications.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

Nowadays, human activities intensified the combined pollution of fluoride and lead in acidic tea garden soil. The key to eliminating this combined pollution is to immobilize pollutants simultaneously, thus preventing their migration from tea garden soil to tea trees. In this paper, the natural product bayberry tannin was employed as raw material to fabricate functional materials (TF-Zr) for simultaneous adsorption of fluorine (F) and lead (Pb) in water and soil by the reactivity of tannin with Pb2+ and the affinity of Zr with F. SEM-Mapping, EDS, FT-IR, XPS were utilized to probe the immobilization mechanisms. The results showed that TF-Zr could simultaneously and efficiently adsorb F– and Pb2+ from water with the adsorption capacity of 5.02 mg/g (Pb) and 4.55 mg/g (F). The adsorption processes were both in accordance with the proposed secondary kinetic adsorption model. Besides, the presence of F– promoted the adsorption of Pb2+ by TF-Zr. The materials were applied into tea garden soil to explore its effect on the variation of F and Pb forms in the soil. It was found that the proportion of water-soluble fluorine, exchangeable fluorine and exchangeable lead in the tea garden soil decreased significantly, while the proportion of residual fluorine and lead increased evidently, illustrating TF-Zr possessed eximious fixation effect on the highly reactive fluorine and lead in the soil and facilitated their conversion to the more stable residue state. Therefore, TF-Zr can be used for the efficient and simultaneous immobilization of fluorine and lead in water and tea garden soil. [ABSTRACT FROM AUTHOR]

Ultrafast laser technology has moved from ultrafast to ultra-strong due to the development of chirped pulse amplification technology. Ultrafast laser technology, such as femtosecond lasers and picosecond lasers, has quickly become a flexible tool for processing brittle and hard materials and complex micro-components, which are widely used in and developed for medical, aerospace, semiconductor applications and so on. However, the mechanisms of the interaction between an ultrafast laser and brittle and hard materials are still unclear. Meanwhile, the ultrafast laser processing of these materials is still a challenge. Additionally, highly efficient and high-precision manufacturing using ultrafast lasers needs to be developed. This review is focused on the common challenges and current status of the ultrafast laser processing of brittle and hard materials, such as nickel-based superalloys, thermal barrier ceramics, diamond, silicon dioxide, and silicon carbide composites. Firstly, different materials are distinguished according to their bandgap width, thermal conductivity and other characteristics in order to reveal the absorption mechanism of the laser energy during the ultrafast laser processing of brittle and hard materials. Secondly, the mechanism of laser energy transfer and transformation is investigated by analyzing the interaction between the photons and the electrons and ions in laser-induced plasma, as well as the interaction with the continuum of the materials. Thirdly, the relationship between key parameters and ultrafast laser processing quality is discussed. Finally, the methods for achieving highly efficient and high-precision manufacturing of complex three-dimensional micro-components are explored in detail. [ABSTRACT FROM AUTHOR]

Abstract HgCdTe avalanche photodiodes promise various fascinating applications due to the outstanding capability of detecting weak signals or even single photon. However, the underlying transport mechanisms of diverse dark current components are still unresolved at high reverse bias, thus limiting the development of high-performance devices. Here, we establish an accurate model to demonstrate the competitive mechanism between band-to-band and avalanche dark currents in positive-intrinsic-negative structures. Based on the high consistency between the simulated and measured results, we find that both components jointly dominate overall dark current but with a larger avalanche current. This breaks the conventional cognition that band-to-band dark current contributes the majority. With the guidance, we reconstruct an optimized device and achieve gain 1876 (6153) and dark current 10−10 (10−9) A at bias −10 (−10.5) V, respectively. Comparisons of dark current and gain with reported single-element devices further confirm the outstanding performance of our device.

The objective of task allocation in unmanned systems is to complete tasks at minimal costs. However, the current algorithms employed for coordinating multiple unmanned systems in task allocation tasks frequently converge to local optima, thus impeding the identification of the best solutions. To address these challenges, this study builds upon the sheep flock optimization algorithm (SFOA) by preserving individuals eliminated during the iterative process within a prior knowledge set, which is continuously updated. During the reproduction phase of the algorithm, this prior knowledge is utilized to guide the generation of new individuals, preventing their rapid reconvergence to local optima. This approach aids in reducing the frequency at which the algorithm converges to local optima, continually steering the algorithm towards the global optimum and thereby enhancing the efficiency of task allocation. Finally, various task scenarios are presented to evaluate the performances of various algorithms. The results show that the algorithm proposed in this paper is more likely than other algorithms to escape from local optima and find the global optimum. [ABSTRACT FROM AUTHOR]

Abstract On 24 March 2021, an Mw 5.3 earthquake struck northwest Baicheng, located in the Kuqa fold‐and‐thrust belt (FTB), northwest China. In the current study, interferometric synthetic aperture radar (InSAR) data were used to investigate the associated fault rupture solution (dip, dip direction, and slip sense), to determine the geometry of the seismogenic structure; the high‐resolution images of the surface rupture were obtained using an unmanned aerial vehicle (UAV). This geometric model, along with the co‐seismic slip distribution from the InSAR data, and deformation characteristics of co‐seismic surface rupture revealed that: (a) it was a shallow event, the focal depth was 0.5–2 km, and the co‐seismic slip was distributed in the 0–7 km range with high dip angles (66°, 70°). (b) A 4‐km long surface rupture with obvious left‐lateral strike‐slip was distributed on the surface, and the maximum strike‐slip displacement and width were 0.79 and 0.7 m, respectively. This left‐lateral strike‐slip event indicates that the relative motion between the Tianshan and Tarim blocks is a continuous and diffuse deformation process. The study shows that, when evaluating the earthquake risk of the Kuqa FTB, we should consider both the front position of the fault outburst and the internal compressional salt‐related structures, which can also produce moderate to strong earthquakes.