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The precipitation of magnesium oxide (MgO) from the Earth's core has been proposed as a potential energy source to power the geodynamo prior to the inner core solidification. Yet, the stable phase and exact amount of MgO exsolution remain elusive. Here we utilize an iterative learning scheme to develop a unified deep learning interatomic potential for the Mg‐Fe‐O system valid over a wide pressure‐temperature range. This potential enables direct, large‐scale simulations of MgO exsolution processes at the Earth's core‐mantle boundary. Our results suggest that Mg exsolve in the form of crystalline Fe‐poor ferropericlase as opposed to a liquid MgO component presumed previously. The solubility of Mg in the core is limited, and the present‐day core is nearly Mg‐free. The resulting exsolution rate is small yet nonnegligible, suggesting that MgO exsolution may provide a potentially important energy source, although it alone may be difficult to drive an early geodynamo. Plain Language Summary The paleomagnetic records suggest that the Earth's magnetic field dates back to at least 3.4 billion years ago. Yet, the energy source of this early geodynamo is still puzzling. One popular hypothesis is that buoyant magnesium oxide may exsolve out of the Earth's core as the core cools, releasing gravitational potential energy to drive the core convection and power the early geodynamo. However, the amount of MgO exsolved is uncertain due to experimental and computational challenges. Here, for the first time, we directly simulate the MgO exsolution processes using large‐scale molecular dynamics simulations, made possible by interatomic potentials built upon machine learning methods. The results show that MgO exsolve as a component of a crystalline ferropericlase, in contrast to early studies which generally assume that MgO exsolve as a component of silicate melts. We find that MgO solubility in the core is low. The exsolution rate is small and MgO alone may be insufficient to sustain a long‐lasting magnetic field at the Earth's surface in its early history. Key Points A machine learning potential of ab initio quality is developed for the Mg‐Fe‐O system Mg exsolve in the form of crystalline Fe‐poor ferropericlase with a small exsolution rate assuming only Mg and O are present in the core MgO exsolution may serve as an important source of buoyant flux to drive the early geodynamo

Concatenation and communication between chemically distinct chemical reaction networks (CRNs) is an essential principle in biology for controlling dynamics of hierarchical structures. Here, to provide a model system for such biological systems, we demonstrate autonomous lifecycles of DNA nanotubes (DNTs) by two concatenated CRNs using different thermodynamic principles: (1) ATP-powered ligation/restriction of DNA components and (2) input strand-mediated DNA strand displacement (DSD) using energy gains provided in DNA toeholds. This allows to achieve hierarchical non-equilibrium systems by concurrent ATP-powered ligation-induced DSD for activating DNT self-assembly and restriction-induced backward DSD reactions for triggering DNT degradation. We introduce indirect and direct activation of DNT self-assemblies, and orthogonal molecular recognition allows ATP-fueled self-sorting of transient multicomponent DNTs. Coupling ATP dissipation to DNA nanostructures via programmable DSD is a generic concept which should be widely applicable to organize other DNA nanostructures, and enable the design of automatons and life-like systems of higher structural complexity. Integration and communication of distinct chemical reaction networks is a biological strategy for controlling dynamics of hierarchical structures. Here, the authors report ATP-fuelled autonomous DNA nanotube assembly regulated by DNA strand displacement reactions, which are induced and controlled by an upstream enzyme reaction network of concurrent ATP-mediated ligation and restriction of DNA components.

Biological systems organize multiple hierarchical structures in parallel, and create dynamic assemblies and functions by energy dissipation. In contrast, emerging artificial non-equilibrium self-assembling systems have remained relatively simplistic concerning hierarchical design, and non-equilibrium multi-component systems are uncharted territory. Here we report a modular DNA toolbox allowing to program transient non-equilibrium multicomponent systems across hierarchical length scales by introducing chemically fueled molecular recognition orchestrated by reaction networks of concurrent ATP-powered ligation and cleavage of freely programmable DNA building blocks. Going across hierarchical levels, we demonstrate transient side-chain functionalized nucleic acid polymers, and further introduce the concept of transient cooperative multivalency as a key to bridge length scales to pioneer fuel-driven encapsulation, self-assembly of colloids, and non-equilibrium transient narcissistic colloidal self-sorting on a systems level. The fully programmable and functionalizable DNA components pave the way to design chemically fueled 4D (3 space, 1 time) molecular multicomponent systems and autonomous materials. There is interest in creating life-like behaviours in synthetic multicomponent systems. Here, the authors report on a modular DNA toolbox able to create transient, dynamic structures using ATP-driven molecular recognition in which multiple systems can run in parallel and across hierarchies.

With the change of social economic system and the rapid growth of agricultural economy in China, the amount of agricultural energy consumption and carbon dioxide emissions has increased dramatically. Based on the estimation of agricultural carbon dioxide emissions from 1991 to 2018 in China, this paper uses EKC model to analyze economic growth and agricultural carbon dioxide emissions. The Kaya method is used to decompose the factors affecting agricultural carbon dioxide emissions. The experimental results show that there is a co-integration relationship between economic growth and the total intensity of agricultural carbon emissions, and between economic growth and the intensity of carbon emissions caused by five types of carbon sources: fertilizer, pesticide, agricultural film, agricultural diesel oil and tillage. Economic growth is the main driving factor of agricultural carbon dioxide emissions. In addition, technological progress has a strong role in promoting carbon emission reduction, but it has a certain randomness. However, the impact of energy consumption structure and population size on carbon emissions is not obvious.

As global attention to sustainable development intensifies, environmental, social, and governance (ESG) factors have become crucial for firms in managing stakeholder relationships and risks. However, the heterogeneous impact of different dimensions of ESG performance on idiosyncratic risk (IR) remains unclear. Drawing upon the stakeholder theory, this study investigates the differing impacts of separate E, S, and G performance on IR, as well as the contingency role of political ties. Using a dataset of 2436 Chinese listed firms from 2011 to 2019, the empirical results indicate that S and G performance significantly mitigate IR, and these linear negative relationships are enhanced by political ties. Surprisingly, the linear effect of E performance on IR is not significant, but the post-hoc analysis reveals an inverted U-shaped relationship between E performance and IR. More importantly, this curvilinear linkage is steeper for firms with political ties. Moreover, the heterogeneity analysis indicates that firms with the chief executive officer (CEO) duality make the effects of E, S, and G performance on IR insignificant. This study extends the growing literature on ESG and risk management, guiding firms to develop differentiated ESG investment strategies and offering actionable insights for firms to better benefit from their ESG performance.

Sarcopenia is a progressive and widespread skeletal muscle disease that is related to an increased possibility of adverse consequences such as falls, fractures, physical disabilities and death, and its risk increases with age. With the deepening of the understanding of sarcopenia, the disease has become a major clinical disease of the elderly and a key challenge of healthy ageing. However, the exact molecular mechanism of this disease is still unclear, and the selection of treatment strategies and the evaluation of its effect are not the same. Most importantly, the early symptoms of this disease are not obvious and are easy to ignore. In addition, the clinical manifestations of each patient are not exactly the same, which makes it difficult to effectively study the progression of sarcopenia. Therefore, it is necessary to develop and use animal models to understand the pathophysiology of sarcopenia and develop therapeutic strategies. This paper reviews the mouse models that can be used in the study of sarcopenia, including ageing models, genetically engineered models, hindlimb suspension models, chemical induction models, denervation models, and immobilization models; analyses their advantages and disadvantages and application scope; and finally summarizes the evaluation of sarcopenia in mouse models.

Acute lung injury (ALI) is a complication of severe acute pancreatitis (SAP). Sitagliptin (SIT) is a DPP4 inhibitor that exerts anti-inflammatory and antioxidant effects; however, its mechanism of action in SAP-ALI remains unclear. In this study, we investigated the effects of SIT on SAP-ALI and the specific pathways involved in SAP-induced lung inflammation, including oxidative stress, autophagy, and p62–Kelch-like ECH-associated protein 1 (Keap1)–NF-E2-related factor 2 (Nrf2) signalling pathways. Nrf2 knockout (Nrf2 −/− ) and wild-type (WT) mice were pre-treated with SIT (100 mg/kg), followed by caerulein and lipopolysaccharide (LPS) administration to induce pancreatic and lung injury. BEAS-2B cells were transfected with siRNA-Nrf2 and treated with LPS, and the changes in inflammation, reactive oxygen species (ROS) levels, and autophagy were measured. SIT reduced histological damage, oedema, and myeloperoxidase activity in the lung, decreased the expression of pro-inflammatory cytokines, and inhibited excessive autophagy and ROS production via the activation of the p62–Keap1–Nrf2 signalling pathway and promotion of the nuclear translocation of Nrf2. In Nrf2-knockout mice, the anti-inflammatory effect of SIT was reduced, resulting in ROS accumulation and excessive autophagy. In BEAS-2B cells, LPS induced ROS production and activated autophagy, further enhanced by Nrf2 knockdown. This study demonstrates that SIT reduces SAP-ALI-associated oxidative stress and excessive autophagy through the p62–Keap1–Nrf2 signalling pathway and nuclear translocation of Nrf2, suggesting its therapeutic potential in SAP-ALI.

Thermal conductivity plays a pivotal role in understanding the dynamics and evolution of Earth's interior. The Earth's lower mantle is dominated by MgSiO3 polymorphs which may incorporate trace amounts of water. However, the thermal conductivity of MgSiO3‐H2O binary system remains poorly understood. Here, we calculate the thermal conductivity of water‐free and water‐bearing bridgmanite, post‐perovskite, and MgSiO3 melt, using a combination of Green‐Kubo method with molecular dynamics simulations based on a machine learning potential of ab initio quality. The thermal conductivities of water‐free bridgmanite and post‐perovskite overall agree well with previous theoretical and experimental studies. The presence of water mildly reduces the thermal conductivity of the host minerals, significantly weakens the temperature dependence of the thermal conductivity, and reduces the thermal anisotropy of post‐perovskite. Overall, water reduces the thermal conductivity difference between bridgmanite and post‐perovskite, and thus may attenuate lateral heterogeneities of the core‐mantle boundary heat flux. Plain Language Summary MgSiO3 is a major component of the Earth and water may dissolve into it. Even a small amount of water may affect the thermal conductivity of minerals and influence the heat transport in the Earth's interior, which is essential for the dynamics and evolution of our planet. However, the effect of water on the thermal conductivity of MgSiO3 remains largely unknown. In this study, we use computer simulations based on machine learning methods to investigate the thermal conductivity of MgSiO3‐H2O system. We find that adding water reduces the thermal conductivity of MgSiO3 mineral, makes the thermal conductivity less dependent on temperature, and also diminishes the differences in heat conduction in various directions. Our results suggest that the presence of water may reduce the increase in heat flow that is expected when MgSiO3 changes its structure at extreme depths and exerts influences on geological processes in the deep mantle. Key Points Thermal conductivity of MgSiO3‐H2O system is calculated using Green‐Kubo method with machine learning potentials Water weakens the temperature dependence and the anisotropy of thermal conductivity of minerals Water reduces the thermal conductivity enhancement effect due to the phase transition from bridgmanite to post‐perovskite

Earned value management (EVM) is widely used when monitoring and estimating operations related to construction projects. As the scope and complexity of construction projects expand, traditional EVM is sometimes ineffective and even results in conclusions that are contrary to the actual situation. Additionally, the estimate produced by EVM is a deterministic value that does not account for the uncertainty of activities involved in a construction project. This study proposes an estimation approach that combines an improved EVM, critical path method (CPM), program evaluation and review technique (PERT), and Monte Carlo simulation (MCS). The contribution is threefold. Firstly, a path-based schedule measurement approach is described using network diagrams and CPM to capture the logical relationships among activities. Secondly, the resource input categorizes activities to improve the accuracy of the duration and cost estimates. The remaining duration and cost will be estimated based on the execution performance of the activities in the same category. Thirdly, PERT and MCS approaches are used to reveal the uncertainty of estimates upon completion by replacing a deterministic value with a possible completion range. An experimental research study was used to apply the proposed approach. The result displayed that the commercial expansion project faced serious schedule delays and cost overruns. Based on the result, the project manager should focus highly on activities J, H, and G (in order of priority) and take corrective actions. In conclusion, the proposed approach demonstrates good performance when identifying deviations, estimating precise results, and determining the importance (priority) of activities that need to be controlled.

Magma oceans were once ubiquitous in the early solar system, setting up the initial conditions for different evolutionary paths of planetary bodies. In particular, the redox conditions of magma oceans may have profound influence on the redox state of subsequently formed mantles and the overlying atmospheres. The relevant redox buffering reactions, however, remain poorly constrained. Using first-principles simulations combined with thermodynamic modeling, we show that magma oceans of Earth, Mars, and the Moon are likely characterized with a vertical gradient in oxygen fugacity with deeper magma oceans invoking more oxidizing surface conditions. This redox zonation may be the major cause for the Earth’s upper mantle being more oxidized than Mars’ and the Moon’s. These contrasting redox profiles also suggest that Earth’s early atmosphere was dominated by CO 2 and H 2 O, in contrast to those enriched in H 2 O and H 2 for Mars, and H 2 and CO for the Moon. Applying first-principles molecular dynamic simulations and thermodynamic modelling, the authors suggest a vertical oxygen fugacity gradient in magma oceans of Earth, Mars, and the Moon. Consequently, the study proposes larger planets like Earth to have stronger oxidized upper mantles than smaller bodies such as Mars or the Moon.