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One of the earliest and most intensively studied problems in quantum optics is the interaction of a two-level system (an atom) with a single photon. This simple system provides a rich platform for exploring exotic light-matter interactions and the emergence of more complex phenomena such as superradiance, which is a cooperative effect that emerges when the density of atoms is increased and coupling between them is enhanced. Going beyond the light-matter system, Li et al. observed analogous cooperative effects for coupled magnetic systems. The results suggest that ideas in quantum optics could be carried over and used to control and predict exotic phases in condensed matter systems. Science , this issue p. 794 Cooperatively enhanced coupling, similar to that of light-matter interactions, is generalized to a coupled spin system. The interaction of N two-level atoms with a single-mode light field is an extensively studied many-body problem in quantum optics, first analyzed by Dicke in the context of superradiance. A characteristic of such systems is the cooperative enhancement of the coupling strength by a factor of N . In this study, we extended this cooperatively enhanced coupling to a solid-state system, demonstrating that it also occurs in a magnetic solid in the form of matter-matter interaction. Specifically, the exchange interaction of N paramagnetic erbium(III) (Er 3+ ) spins with an iron(III) (Fe 3+ ) magnon field in erbium orthoferrite (ErFeO 3 ) exhibits a vacuum Rabi splitting whose magnitude is proportional to N . Our results provide a route for understanding, controlling, and predicting novel phases of condensed matter using concepts and tools available in quantum optics.

BackgroundMechanical thrombectomy (MT) is the primary treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO). However, the likelihood of futile recanalization (FR) at 90 days post-MT remains high.MethodsThis study included 534 AIS patients with anterior circulation LVO who underwent MT, with the primary outcome being FR. The derivation cohort consisted of 445 patients (June 2018–June 2023), while the temporal validation cohort had 89 patients (July 2023–June 2024). The derivation cohort was split into 70% training and 30% internal validation sets. Eleven machine learning (ML) models were trained, tested, and compared, and the best-performing model was selected for optimization and temporal validation. SHapley Additive exPlanations (SHAP) were used for model interpretation.ResultsThe CatBoost model showed the best discriminative ability among the 11 ML models. After feature selection and dimensionality reduction, a final explainable CatBoost model with 12 features was established, accurately predicting FR in both internal (area under the curve (AUC)=0.915) and temporal (AUC=0.930) validations. The model has been deployed as a web application for clinical use.ConclusionWe developed a ML prediction model with 12 key features that demonstrates excellent performance in predicting FR. The deployment of this model as a web application offers a promising tool for clinicians to assess FR risk, potentially enhancing patient selection and improving personalized stroke care.

As the architecture of logic devices is evolving towards gate-all-around (GAA) structure, research efforts on advanced transistors are increasingly desired. In order to rapidly perform accurate compact modeling for these ultra-scaled transistors with the capability to cover dimensional variations, neural networks are considered. In this paper, a compact model generation methodology based on artificial neural network (ANN) is developed for GAA nanosheet FETs (NSFETs) at advanced technology nodes. The DC and AC characteristics of GAA NSFETs with various physical gate lengths (Lg), nanosheet widths (Wsh) and thicknesses (Tsh), as well as different gate voltages (Vgs) and drain voltages (Vds) are obtained through TCAD simulations. Subsequently, a high-precision ANN model architecture is evaluated. A systematical study on the impacts of ANN size, activation function, learning rate, and epoch (the times of complete pass through the entire training dataset) on the accuracy of ANN models is conducted, and a shallow neural network configuration for generating optimal ANN models is proposed. The results clearly show that the optimized ANN model can reproduce the DC and AC characteristics of NSFETs very accurately with a fitting error (MSE) of 0.01.

Mycoplasma pneumoniae pneumonia (MPP) is a common disorder that invades predominantly the school-aged children and adolescents globally. Given its nonspecific clinical manifestations at the initial stage and the significance of early identification of severe cases for clinical management, it highlights the necessity of diagnostic confirmation through laboratory testing. Recent advances in metabolomics have demonstrated significant potential in elucidating the pathogenic mechanisms of MPP. It enables an analysis of metabolic alterations in biological samples, thus providing a comprehensive understanding of disease-associated perturbations in metabolic networks, and offering novel insights into its etiology. Simultaneously, metabolomics can facilitate the discovery of potential biomarkers, thereby serving as valuable tools for early diagnosis and disease progression evaluation.

BackgroundIn this randomized controlled trial we aim to validate the efficacy and safety of a hydrogel vascular closure device (VCD) for hemostasis after transfemoral intervention.MethodsBetween January and August 2023, 212 patients were enrolled, including 202 in a non-inferiority randomized controlled trial (1:1 hydrogel vs ExoSeal; prespecified margin −10%) and 10 in a hydrogel-only observational arm (8 F). The primary endpoint was device success rate and secondary endpoints including hemostasis time and procedural blood loss.ResultsAmong 102 hydrogel and 100 ExoSeal recipients, hydrogel had non-inferior success rates (99.02% vs 94.00%; 95% CI −0.27% to 11.74%). Hydrogel achieved significantly faster hemostasis (1.99 vs 3.14 min, P<0.001) and reduced blood loss (0.83 mL vs 8.93 mL, P<0.001). No major access site complications were observed in either group. No secondary complications occurred in patients in the experimental group and secondary complications occurred in one patient in the control group (P=0.497). The supplementary cohort of 10 patients supported the efficacy and safety of hydrogel VCD.ConclusionsHydrogel VCD shows non-inferior efficacy to ExoSeal for transfemoral cerebrovascular interventions, with superior hemostatic speed and reduced blood loss while maintaining comparable safety.Trial registration numberChiCTR2300068029 (https://www.chictr.org.cn/showproj.html?proj=178962)

Reactions between a boninitic or basaltic magma and harzburgite at shallow mantle depths are thought to be closely related to the formation of podiform chromitites, but little experimental data is available on these reactions. In this study, a series of experiments were conducted at 1.5 GPa and 1 000–1 400 °C to investigate the interactions between boninitic magma and harzburgite in homogenous mixed systems with varied bulk concentrations of water (∼0.7 wt.%–10 wt.%) and Cr2O3 (∼0.2 wt.%–4 wt.%). In the experimental charges, chromite grains can be observed coexisting with orthopyroxene, clinopyroxene±olivine, and quenched melt in the Cr-bearing systems. The bulk concentration of Cr2O3 in the starting material has a slight effect on compositional changes in the chromites generated. However, the Cr# (Cr#=100×Cr/(Cr+Al)) and Mg# (Mg#=100×Mg/(Mg+Fe)) values for the chromites exhibit positive and negative correlations, respectively, with the bulk H2O concentrations. At 1 100 °C, chromite Cr# values range from ∼33–35 to ∼58–65, and chromite Mg# values range from ∼70–73 to ∼55–58 when bulk H2O contents in the starting material are increased from ∼0.7 wt.% to ∼10 wt.%. The experimentally produced chromites have compositions (as expressed by Cr#, Mg#, and NiO and MnO contents) similar to natural chromites from low-Cr# chromitite bodies. We suggest that the interactions between boninitic magmas with varied H2O contents and harzburgite in a shallow mantle wedge could be a possible mechanism that forms the low-Cr# chromitites found in ophiolites. We emphasize here that H2O may play an important role in the compositional evolutions of natural chromitites.

This study aimed to prepare a new lightweight ultra-high-voltage insulator core filler composite, which can solve the problem of bulkiness. In this study, rigid polyurethane foam pellets with different densities are used as lightweight fillers and polyurethane resins to compound lightweight composite materials. On accounting for working conditions, the density, insulation, heat resistance, water absorption and mechanical properties are tested. The compressive properties of composites are determined by a foam skeleton and a process. Among three kinds of composites, in which the composites with the best comprehensive performance are materials filled with pellets to a density of 0.15g·cm−3. The density, surface resistance, volume resistance, leakage current, initial decomposition temperature, water absorption, force, rupture displacement and limiting oxygen index (LOI) of composites are 0.665 g·cm−3, 1.17 × 1014 Ω, 9.68 × 1014 Ω·cm, 0.079 mA, 208 °C, 0.047%, 2262 N, 2.54 mm, and 23.3%, respectively. The ultra-high-voltage insulator core filler in this study can reduce the weight of the solid core insulator crossarm for Ultra-High Voltage (UHV) by 50–75%.

A promising clinical trial utilizing gold-silica core-shell nanostructures coated with polyethylene glycol (PEG) has been reported for near-infrared (NIR) photothermal therapy (PTT) of prostate cancer. The next critical step for PTT is the visualization of therapeutically relevant nanoshell (NS) concentrations at the tumor site. Here we report the synthesis of PEGylated Gd₂O₃-mesoporous silica/gold core/shell NSs (Gd₂O₃-MS NSs) with NIR photothermal properties that also supply sufficient MRI contrast to be visualized at therapeutic doses (≥10⁸ NSs per milliliter). The nanoparticles have r₁ relaxivities more than three times larger than those of conventional T₁ contrast agents, requiring less concentration of Gd3+ to observe an equivalent signal enhancement in T₁-weighted MR images. Furthermore, Gd₂O₃-MS NS nanoparticles have r₂ relaxivities comparable to those of existing T₂ contrast agents, observed in agarose phantoms. This highly unusual combination of simultaneous T₁ and T₂ contrast allows for MRI enhancement through different approaches. As a rudimentary example, we demonstrate T₁/T₂ ratio MR images with sixfold contrast signal enhancement relative to its T₁ MRI and induced temperature increases of 20 to 55 °C under clinical illumination conditions. These nanoparticles facilitate MRI-guided PTT while providing real-time temperature feedback through thermal MRI mapping.

Fast and reliable inverse design has long been a sought-after goal in the field of nanophotonics, particularly in light of the rapid advancements in computational science and numerical tools. In this work, we present a novel approach for topology optimization involving a GPU-accelerated Discrete Dipole Approximation (DDA) algorithm, seamlessly integrated with other cutting-edge techniques to enhance its accuracy, speed, and robustness. Utilizing this sophisticated computational framework, we have designed a range of highly efficient nanostructures and conducted an in-depth exploration of the underlying physics. The first and second parts provide a comprehensive description of the algorithm's implementation and performance. The third section showcases several nanostructures designed using the proposed algorithm, elucidating the associated physics and demonstrating the effectiveness of our approach in addressing contemporary challenges in nanophotonic device engineering.

A promising clinical trial utilizing gold-silica core-shell nanostructures coated with polyethylene glycol (PEG) has been reported for near-infrared (NIR) photothermal therapy (PTT) of prostate cancer. The next critical step for PTT is the visualization of therapeutically relevant nanoshell (NS) concentrations at the tumor site. Here we report the synthesis of PEGylated Gd 2 O 3 -mesoporous silica/gold core/shell NSs (Gd 2 O 3 -MS NSs) with NIR photothermal properties that also supply sufficient MRI contrast to be visualized at therapeutic doses (≥10 8 NSs per milliliter). The nanoparticles have r 1 relaxivities more than three times larger than those of conventional T 1 contrast agents, requiring less concentration of Gd 3+ to observe an equivalent signal enhancement in T 1 -weighted MR images. Furthermore, Gd 2 O 3 -MS NS nanoparticles have r 2 relaxivities comparable to those of existing T 2 contrast agents, observed in agarose phantoms. This highly unusual combination of simultaneous T 1 and T 2 contrast allows for MRI enhancement through different approaches. As a rudimentary example, we demonstrate T 1 / T 2 ratio MR images with sixfold contrast signal enhancement relative to its T 1 MRI and induced temperature increases of 20 to 55 °C under clinical illumination conditions. These nanoparticles facilitate MRI-guided PTT while providing real-time temperature feedback through thermal MRI mapping.