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It remains a challenge to produce soft robots that can mimic the responsive adaptability of living organisms. Rather than fabricating soft robots from bulk hydrogels,hydrogels are integrated into the interfacial assembly of aqueous two‐phase systems to generate ultra‐soft and elastic all‐aqueous aquabots that exhibit responsive adaptability, that can shrink on demand and have electrically conductive functions. The adaptive functions of the aquabots provide a new platform to develop minimally invasive surgical devices, targeted drug delivery systems, and flexible electronic sensors and actuators. [ABSTRACT FROM AUTHOR]

The advance of printed electronics is significantly bolstered by the development of liquid‐state electronics that overcome the inherent limitations in flexibility and reconfigurability of solid‐state electronics. By integrating the biocompatibility and conductivity of sulfonated polyaniline (S‐PANI) and phytic acid (PA) with the reconfigurability of structured liquids, highly conductive all‐liquid threads are developed. The dense packing and overlap of PA/S‐PANI complexes at an oil/water interface promotes in‐plane electron transport, and standard four‐point probe measurements of PA/S‐PANI interfacial assemblies demonstrate enhanced electrical properties. Notably, the rapid jetting of the ink phase into the matrix phase allows for liquid threads to be printed, enabling the fabrication of large‐scale, conductive pathways between two electrodes and liquid circuits. Upon mechanical cleavage of the liquid wires, circuits can be broken, but will easily self‐repair using an electric field, making this motif useful in the design of switches as well as restoring conductive pathways in series or in parallel. The demonstrated flexibility and reconfigurability these PA/S‐PANI wires possess hold significant promise for their practical use in the design of flexible and adaptive bioelectronics that can be repaired on demand, signifying a transformative step in the evolution of liquid electronic materials. [ABSTRACT FROM AUTHOR]

Li‐O2 batteries, known for their impressive theoretical specific energy, face significant practical challenges, including slow kinetics, voltage hysteresis, and reduced cycle life. In this study, a novel approach is introduced utilizing a bimetallic metal‐organic framework known as Fe‐UiO‐66 as a multifunctional photocatalyst to enhance the oxygen‐related reactions in photo‐assisted Li‐O2 batteries. In contrast to UiO‐66, Fe‐UiO‐66 exhibits an extended response to visible light, as confirmed through UV–vis and photoluminescence spectra. Electron paramagnetic resonance analysis provides further validation of the pivotal role played by O2− radicals in the electrochemical processes. Additionally, computations are employed to elucidate the distinct function of Fe centers and the underlying reaction mechanisms. Li‐O2 batteries with Fe‐UiO‐66 cathodes have a reduced charge/discharge voltage difference of 0.14 V under illumination and operate stably for 500 cycles. This work encourages MOF‐based photocathode development for Li‐O2 batteries. [ABSTRACT FROM AUTHOR]

Straw has been commonly incorporated into soil to increase soil organic carbon (SOC) content. However, the response and mechanism of organic carbon transformation following the addition of different forms of straw to saline soil to have not been fully evaluated. Thus, in our study, chopped wheat straw, granular wheat straw and wheat straw biochar were used as exogenous organic amendments. The carbon‐to‐nitrogen ratio of each form of straw was adjusted to 25:1. Under the same amount of carbon input, the three forms of straw were added to saline soil for a one‐year incubation experiment. The research focused on studying the changes in SOC transformation, enzyme activity, and microbial community structure. At the end of incubation, both granular and biochar straw treatments had significantly increased SOC relative to the unamended control, with extent of SOC increase greater in the biochar straw treatment. The biochar straw treatment also had significantly higher dissolved organic carbon than the other treatments at end of the incubation. The enzyme activity of β‐cellobiohyrolase (CBH) was the highest in the granular straw treatment, which was increased by 71.9% compared with the chopped straw treatment (p < 0.05). The cumulative carbon mineralization amount (Cum C) in the granular straw treatment was the highest, which was increased by 757.4% and 21.3% compared with the biochar straw and chopped straw treatments, respectively (p < 0.05). The Mantel test analysis further revealed significant correlations between soil bacterial community and SOC content in soils treated with different straw incorporation forms, as well as between fungal community and extracellular enzyme activities. We assumed that a possible reason for the high SOC mineralization amount in the granular straw treatment was changing the structure of the Bacteroidota in the bacterial phylum and Blastocladiomycota in the fungal phylum. Based on these findings, it is believed that adding biochar can increase the SOC content, but its utilization by microorganisms is limited. However, applying granular straw will not have a negative impact on its use as a microbial carbon source, thereby promoting carbon transformation. Therefore, in future research aimed at enhancing soil fertility in saline soil regions, the adoption of granular straw as an agricultural practice is recommended and should be promoted. [ABSTRACT FROM AUTHOR]

Plant Carbonic anhydrases (Cas) have been shown to be stress‐responsive enzymes that may play a role in adapting to adverse conditions. Cotton is a significant economic crop in China, with upland cotton (Gossypium hirsutum) being the most widely cultivated species. We conducted genome‐wide identification of the βCA gene in six cotton species and preliminary analysis of the βCA gene in upland cotton. In total, 73 βCA genes from six cotton species were identified, with phylogenetic analysis dividing them into five subgroups. GHβCA proteins were predominantly localized in the chloroplast and cytoplasm. The genes exhibited conserved motifs, with motifs 1, 2, and 3 being prominent. GHβCA genes were unevenly distributed across chromosomes and were associated with stress‐responsive cis‐regulatory elements, including those responding to light, MeJA, salicylic acid, abscisic acid, cell cycle regulation, and defence/stress. Expression analysis indicated that GHβCA6, GHβCA7, GHβCA10, GHβCA15, and GHβCA16 were highly expressed under various abiotic stress conditions, whereas GHβCA3, GHβCA9, GHβCA10, and GHβCA18 had higher expression patterns under Verticillium dahliae infection at different time intervals. In Gossypium thurberi, GthβCA1, GthβCA2, and GthβCA4 showed elevated expression across stress conditions and tissues. Silencing GHβCA10 through VIGS increased Verticillium wilt severity and reduced lignin deposition compared to non‐silenced plants. GHβCA10 is crucial for cotton's defense against Verticillium dahliae. Further research is needed to understand the underlying mechanisms and develop strategies to enhance resistance against Verticillium wilt. [ABSTRACT FROM AUTHOR]

In an electrocatalytic process, the cognition of the active phase in a catalyst has been regarded as one of the most vital issues, which not only boosts the fundamental understanding of the reaction procedure but also guides the engineering and design for further promising catalysts. Here, based on the oxygen evolution reaction (OER), the stepwise evolution of the dominant active phase is demonstrated in the LaNiO3 (LNO) catalyst once the single‐crystal thin film is decorated by LNO nanoparticles. It is found that the OER performance can be dramatically improved by this decoration, and the catalytic current density at 1.65 V can be enhanced by ≈1000% via ≈109 cm−2 nanoparticle adhesion after extracting the contribution of surface enlargement. Most importantly, a transition of the active phase from LNO to NiOOH via surface reconstruction with the density of LNO nanoparticles is demonstrated. Several mechanisms in terms of this active phase transition are discussed involving lattice orientation‐induced change of the surface energy profile, the lattice oxygen participation, and the A/B‐site ions leaching during OER cycles. This study suggests that the active phases in transition metal‐based OER catalysts can transform with morphology, which should be corresponding to distinct engineering strategies. [ABSTRACT FROM AUTHOR]

Due to high computational costs and memory requirements, it is necessary to use coarse grids for least‐squares reverse time migration when processing large‐scale field data. According to the dispersion relation, strong numerical dispersion will occur in least‐squares reverse time migration images when the migration velocity of the shallow strata is low, reducing the resolution of the migration results. To overcome this shortcoming, we propose new least‐squares reverse time migration implementation method with a modified flux‐corrected transport technique. This algorithm involves two main steps: obtain an appropriate calibration parameter for flux‐corrected transport through forward modelling and perform least‐squares reverse time migration using flux‐corrected transport. We remove the non‐linear processing from conventional flux‐corrected transport algorithm often used in computational fluid dynamics based on the assumption that the seismic wavefield is relatively continuous and smooth without strong ripples, which makes it possible to apply flux‐corrected transport to least‐squares reverse time migration without increasing too much computation complexity. To suppress the numerical dispersion more effectively, the diffusion fluxes along the diagonal direction are added to flux‐corrected transport. Numerical tests on synthetic data and field data illustrate that compared to the conventional least‐squares reverse time migration method, the proposed method produces images with fewer migration artefacts, more accurate amplitudes and faster convergence speed on the coarse grids. [ABSTRACT FROM AUTHOR]

Lysine succinylation (Ksucc) regulates various metabolic processes, participates in vital life processes, and is involved in the occurrence and development of numerous diseases. Accurate recognition of succinylation sites can reveal underlying functional mechanisms and pathogenesis. However, most remain undetected. Moreover, a deep learning architecture focusing on generic and species‐specific predictions is still lacking. Thus, we proposed a deep learning‐based framework named Deep‐Ksucc, combining a dense convolutional network and ordered‐neuron long short‐term memory in parallel, which took the cascading characteristics of sequence information and physicochemical properties as the input. The results of the generic and species‐specific predictions indicated that Deep‐Ksucc can identify sequence patterns of different organisms and recognize plenty of succinylation sites. The case study showed that Deep‐Ksucc can serve as a reliable tool for biology verification and computer‐aided recognition of succinylation sites. [ABSTRACT FROM AUTHOR]