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Fundamental understanding of the dynamic behaviors at the electrochemical interface is crucial for electrocatalyst design and optimization. Here, we revisit the oxygen reduction reaction mechanism on a series of transition metal (M = Fe, Co, Ni, Cu) single atom sites embedded in N-doped nanocarbon by ab initio molecular dynamics simulations with explicit solvation. We have identified the dissociative pathways and the thereby emerged solvated hydroxide species for all the proton-coupled electron transfer (PCET) steps at the electrochemical interface. Such hydroxide species can be dynamically confined in a “pseudo-adsorption” state at a few water layers away from the active site and respond to the redox event at the catalytic center in a coupled manner within timescale less than 1 ps. In the PCET steps, the proton species (in form of hydronium in neutral/acidic media or water in alkaline medium) can protonate the pseudo-adsorbed hydroxide without needing to travel to the direct catalyst surface. This, therefore, expands the reactive region beyond the direct catalyst surface, boosting the reaction kinetics via alleviating mass transfer limits. Our work implies that in catalysis the reaction species may not necessarily bind to the catalyst surface but be confined in an active region. The reaction region is commonly considered to be the direct catalyst surface. Here, the authors challenge this view and use molecular dynamics simulations to reveal a solvated hydroxide species dynamically confined in a pseudo-adsorption state at a few water layers away from the active site during oxygen reduction reaction on single atom electrocatalyst.

This study proposes an advanced elevator fault precursor prediction method integrating Variational Mode Decomposition (VMD), Bidirectional Long Short-Term Memory (BILSTM), and an Autoencoder with an Attention Mechanism (AEAM), collectively referred to as the VMD-BILSTM-AEAM algorithm. This model addresses the challenges of feature redundancy and noise interference in elevator operation data, improving the stability and accuracy of fault predictions. Using a dataset of elevator operation parameters, including current, voltage, and running speed, the model utilizes the Attribute Correlation Density Ranking (ACDR) method for feature selection and the TSO-optimized VMD for denoising, enhancing data quality. Cross-validation and statistical analyses, including confidence interval calculations, were employed to validate the robustness of the model. The results demonstrate that the VMD-BILSTM-AEAM algorithm achieves a mean True Positive Rate (TPR) of 0.919 with a 95% confidence interval of 0.915 to 0.924, a mean False Positive Rate (FPR) of 0.090 with a 95% confidence interval of 0.087 to 0.092, and a mean Area Under the Curve (AUC) of 0.919 with a 95% confidence interval of 0.915 to 0.923. These performance metrics indicate a significant improvement over traditional and other deep learning models, confirming the model’s superiority in predictive maintenance of elevators. The robust capability of the VMD-BILSTM-AEAM algorithm to accurately process and analyze time-series data, even in the presence of noise, highlights its potential for broader applications in predictive maintenance and fault detection across various domains.

Time-reversed evolution has substantial implications in physics, including applications in refocusing of classical waves or spins and fundamental studies such as quantum information scrambling. In quantum metrology, nonlinear interferometry based on time-reversal protocols supports entanglement-enhanced measurements without requiring low-noise detection. Despite the broad interest in this topic, it remains challenging to reverse the quantum dynamics of an interacting many-body system, which is typically realized by an (effective) sign flip of the system’s Hamiltonian. Here we present an approach that is broadly applicable to cyclic systems for implementing nonlinear interferometry without invoking time reversal. As time-reversed dynamics drives a system back to its starting point, we propose to accomplish the same by forcing the system to travel along a ‘closed loop’ instead of explicitly tracing back its antecedent path. Utilizing the quasiperiodic spin mixing dynamics in a three-mode 87 Rb atomic spinor condensate, we implement such a closed-loop nonlinear interferometer and achieve a metrological gain of 5.0 1 − 0.76 + 0.76 decibels over the classical limit for a total of 26,500 atoms. Our approach unlocks the potential of nonlinear interferometry by allowing the dynamics to penetrate into the deep nonlinear regime, which gives rise to highly entangled non-Gaussian states. Nonlinear interferometry based on time reversal enables entanglement-enhanced measurements without the need for low-noise detection. An alternative approach now exploits cyclic dynamics and shows performance beyond the standard quantum limit.

In soft coal bedding drilling hard into the problem of hole, based on the drilling of coal in the process of motion, from two aspects to improve the traditional drilling technology, selection of high power, large torque drill and selecting reasonable parameters of drilling tools and better way of powder, formed a “high power drill, shallow blade spiral drill pipe, wind pressure in the wind” of the construction process. The field application test was carried out in Xinxin Coal Mine of Yunnan Province, and the test results show that the average monthly footage of drilling rig is 8000 m/rig•month. The average depth is 137m, the primary pore formation rate reaches 90%. Compared with the original drilling technology, the new technology increases the average hole depth by 12%∼70%, the drilling efficiency by 30%∼46%, the extraction concentration by more than one time, and the single hole extraction amount by 33.6%. The drilling technology of soft outburst coal seam has improved the drilling efficiency and realized the full coverage of gas drainage in working face, which is worthy of reference and reference in soft coal seam mine.

The primary objective of water distribution systems (WDSs) is to ensure a high-quality water supply. Chlorine, commonly used as a primary disinfectant in WDSs, requires precise control of its concentration to safeguard public health. However, the complex network structure and its highly nonlinear dynamics inherent in a WDS pose significant challenges in chlorine management. This study proposes an optimization approach to tackle these challenges by leveraging different kinds of valves to distribute water flow within the network, thereby realizing both chlorine and pressure management. A simplified chlorine propagation model is introduced, based on which three optimization problems are formulated and solved to compute optimal management strategies. The first one is a nonlinear programming (NLP) which minimizes source dosing across the WDS by an optimal distribution of the water flow in the pipelines, leading to a lower bound for the chlorine management. The second one is a mixed-integer nonlinear programming (MINLP) problem to localize isolation valves (IVs) and achieve a realistic and practical solution. The third one extends the MINLP framework to integrate pressure reducing valves (PRVs), optimizing the placement of both IVs and PRVs to enable a multi-objective approach that minimizes chlorine dosing while regulating the system pressure. The results of a benchmark demonstrate that the integrated use of IVs and PRVs significantly enhances the performance of both chlorine concentration and pressure regulation, offering an efficient solution for WDS management.

For the full cross-sectional profile measurement of high-aspect-ratio micro-grooves, traditional measurement methods have blind measurement areas in the vertical sidewall and its intersection area with the bottom. This paper proposes a deflection-based scanning method that utilizes a large length-to-diameter ratio probe to achieve a full cross-sectional profile measurement of micro-grooves. Blind measurement areas were eliminated by a deflection-based scanning method. The complete groove profile was obtained by stitching the positive and reversal deflection-based measurement results. The optimal deflection angle of the probe was calculated by considering the profile-stitching setting and the principle of minimizing the probe deformation during the measurement process. A four-axis measurement system was established to measure high-aspect-ratio micro-grooves, which incorporated a force feedback mechanism to maintain a constant contact force during the measurement and an integrated error separation module to modify the measurement results. The measurement method and system were experimentally validated to achieve a full cross-sectional profile measurement of micro-grooves with a width of 50 μm and an aspect ratio of no less than 3. The standard deviation of the measurement results was 82 nm, and the expanded uncertainty was 108 nm.

The introduction of digital technologies in collective actions seems to have transformed the dynamics of movement organizing and enabled divergent forms of protest organizing. While some studies emphasize “organizationless” organizing in which traditional organizational forms—social movements organizations and formal-bureaucratic structures—have been pushed into the margins, other studies showcase how traditional forms have assumed alternative features, for example, connective leadership and organizations with fluid boundaries. While existing research correctly points out the evolving organizing dynamics and forms in digital activism, few studies have accounted for why digitally enabled protests take certain organizing forms over others among multiple modes of interaction between protesters and digital technologies. Using a case study of a protest campaign organized by Chinese American immigrants, this study illustrates why immigrant activists struggled to keep the campaign “organizationless” on WeChat, a China-based digital platform that afforded other forms of organizing over such an organizing mode. Building on the mechanism-based approach in social movement studies, the findings show that immigrant activists’ emotional–cognitive responses to the changing digital environments became the driving force behind the relational choices to maintain the protest “organizationless.” The study, therefore, may not only inform future studies to explore why certain structures of protest networks emerge and develop but also contribute to the mechanism-based approach by foregrounding emotional–cognitive mechanisms, which mediate environmental and relational mechanisms.

The radii and orbital periods of 4,000+ confirmed/candidate exoplanets have been precisely measured by the Kepler mission. The radii show a bimodal distribution, with two peaks corresponding to smaller planets (likely rocky) and larger intermediate-size planets, respectively. While only the masses of the planets orbiting the brightest stars can be determined by ground-based spectroscopic observations, these observations allow calculation of their average densities placing constraints on the bulk compositions and internal structures. However, an important question about the composition of planets ranging from 2 to 4 Earth radii (R⊕) still remains. They may either have a rocky core enveloped in a H₂–He gaseous envelope (gas dwarfs) or contain a significant amount of multicomponent, H₂O-dominated ices/fluids (water worlds). Planets in the mass range of 10–15 M⊕, if half-ice and half-rock by mass, have radii of 2.5 R⊕, which exactly match the second peak of the exoplanet radius bimodal distribution. Any planet in the 2- to 4-R⊕ range requires a gas envelope of at most a few mass percentage points, regardless of the core composition. To resolve the ambiguity of internal compositions, we use a growth model and conduct Monte Carlo simulations to demonstrate that many intermediate-size planets are “water worlds.”

The Cassini spacecraft spent 13 years orbiting Saturn; as it ran low on fuel, the trajectory was changed to sample regions it had not yet visited. A series of orbits close to the rings was followed by a Grand Finale orbit, which took the spacecraft through the gap between Saturn and its rings before the spacecraft was destroyed when it entered the planet's upper atmosphere. Six papers in this issue report results from these final phases of the Cassini mission. Dougherty et al. measured the magnetic field close to Saturn, which implies a complex multilayer dynamo process inside the planet. Roussos et al. detected an additional radiation belt trapped within the rings, sustained by the radioactive decay of free neutrons. Lamy et al. present plasma measurements taken as Cassini flew through regions emitting kilometric radiation, connected to the planet's aurorae. Hsu et al. determined the composition of large, solid dust particles falling from the rings into the planet, whereas Mitchell et al. investigated the smaller dust nanograins and show how they interact with the planet's upper atmosphere. Finally, Waite et al. identified molecules in the infalling material and directly measured the composition of Saturn's atmosphere. Science , this issue p. eaat5434 , p. eaat1962 , p. eaat2027 , p. eaat3185 , p. eaat2236 , p. eaat2382 During 2017, the Cassini fluxgate magnetometer made in situ measurements of Saturn’s magnetic field at distances ~2550 ± 1290 kilometers above the 1-bar surface during 22 highly inclined Grand Finale orbits. These observations refine the extreme axisymmetry of Saturn’s internal magnetic field and show displacement of the magnetic equator northward from the planet’s physical equator. Persistent small-scale magnetic structures, corresponding to high-degree (>3) axisymmetric magnetic moments, were observed. This suggests secondary shallow dynamo action in the semiconducting region of Saturn’s interior. Some high-degree magnetic moments could arise from strong high-latitude concentrations of magnetic flux within the planet’s deep dynamo. A strong field-aligned current (FAC) system is located between Saturn and the inner edge of its D-ring, with strength comparable to the high-latitude auroral FACs.

Phenazines are a large group of nitrogen-containing heterocycles, providing diverse chemical structures and various biological activities. Natural phenazines are mainly isolated from marine and terrestrial microorganisms. So far, more than 100 different natural compounds and over 6000 synthetic derivatives have been found and investigated. Many phenazines show great pharmacological activity in various fields, such as antimicrobial, antiparasitic, neuroprotective, insecticidal, anti-inflammatory and anticancer activity. Researchers continued to investigate these compounds and hope to develop them as medicines. Cimmino et al. published a significant review about anticancer activity of phenazines, containing articles from 2000 to 2011. Here, we mainly summarize articles from 2012 to 2021. According to sources of compounds, phenazines were categorized into natural phenazines and synthetic phenazine derivatives in this review. Their pharmacological activities, mechanisms of action, biosynthetic pathways and synthetic strategies were summarized. These may provide guidance for the investigation on phenazines in the future.