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Abstract Mimicking the human eye’s ability to autonomously adapt to diverse and mixed illumination conditions remains a fundamental challenge in artificial vision systems. Although substantial progress has been made in materials and device engineering, current adaptive vision architectures still depend heavily on complex circuitry or algorithms and are typically restricted to uniform illumination owing to the strong intensity-dependence of photosensitivity. Here, this work presents a highly adaptive TiO₂/PEDOT:PSS photomemristor that leverages the tunable conductivity of PEDOT:PSS together with the optoelectronic response of TiO₂. The photothermal effect dynamically modulates the water absorption/desorption equilibrium in PEDOT:PSS, enabling reversible suppression or enhancement of photosensitivity under bright or dim illumination, respectively. By combining with artificial neural networks (ANNs), the artificial vision system based on TiO₂/PEDOT:PSS photomemristor arrays achieves a high accuracy of 91.3% in image recognition under mixed-light conditions—without the need for complex circuitry or algorithms. This work may establish a new approach for designing autonomous, efficient, and high-performance neuromorphic vision systems to advance the development of autonomous driving and humanoid robots. 

In situ monitoring of sweat glucose during exercise can provide a real-time and continuous assessment of blood glucose dynamics. However, the relatively poor correlation between sweat and blood glucose concentrations during exercise makes it challenging for blood glucose management (BGM) during exercise therapy for diabetes, along with training for athletes and fitness enthusiasts. This work presents a flexible wireless sweat glucose and pH sensing platform integrated with a pH-based correlation model to accurately predict the continuous changes in blood glucose. The pH-based correlation model calibrates enzyme activity changes in glucose oxidase and accounts for the effects of sweat dilution and filtering during paracellular transport of glucose from interstitial fluid and plasma to sweat during exercise. The correlation model has been validated in both healthy individuals and diabetic patients, revealing distinct blood glucose dynamic patterns between the two cohorts. The observed different glucose fluctuations after the intake of various nutritive foods further facilitate the management of diabetes and allow for the identification of hypo-/hyperglycemic risks during training or fitness exercise. The exercise-based device platform combines continuous blood glucose monitoring with diabetes management through effective treatment evaluation and can also provide early prevention for the at-risk population and reduce or even reverse diabetes. 

ABSTRACT Eastern boundary upwelling currents are some of the most biologically productive and diverse regions in the world's oceans. Driven by equatorward winds and Ekman transport, surface waters are transported offshore and replaced by cold, nutrient‐rich deep waters that seed extensive phytoplankton blooms. Studying phytoplankton community succession and physiological acclimation during the initial stages of upwelling is critical to building a comprehensive understanding of phytoplankton responses to upwelling in these important regions. Additionally, factors like lateral transport, seed population dynamics and physiological and molecular shifts are conducive to shaping the community assemblage and primary productivity. This study examines how phytoplankton gene expression and resulting physiology change between early and later phases of upwelling. By incorporating metatranscriptomic analyses and stable isotope incubations to measure nutrient uptake kinetics into our assessment of early and later upwelling stages, we observed variability in phytoplankton assemblages and differential gene expression of phytoplankton that were de‐coupled from their physiology. We show that the gene expression response to a fresh upwelling event precedes their physiological response. Ultimately, understanding how phytoplankton change through the course of an upwelling event is critical to assessing their importance to regional biological rate processes, trophic systems and resulting biogeochemistry. 

Abstract The concentration of dopamine (DA) and tyrosine (Tyr) reflects the condition of patients with Parkinson's disease, whereas moderate paracetamol (PA) can help relieve their pain. Therefore, real‐time measurements of these bioanalytes have important clinical implications for patients with Parkinson's disease. However, previous sensors suffer from either limited sensitivity or complex fabrication and integration processes. This work introduces a simple and cost‐effective method to prepare high‐quality, flexible titanium dioxide (TiO₂) thin films with highly reactive (001)‐facets. The as‐fabricated TiO₂film supported by a carbon cloth electrode (i.e., TiO₂–CC) allows excellent electrochemical specificity and sensitivity to DA (1.390 µA µM⁻¹ cm⁻²), Tyr (0.126 µA µM⁻¹ cm⁻²), and PA (0.0841 µA µM⁻¹ cm⁻²). More importantly, accurate DA concentration in varied pH conditions can be obtained by decoupling them within a single differential pulse voltammetry measurement without additional sensing units. The TiO₂–CC electrochemical sensor can be integrated into a smart diaper to detect the trace amount of DA or an integrated skin‐interfaced patch with microfluidic sampling and wireless transmission units for real‐time detection of the sweat Try and PA concentration. The wearable sensor based on TiO₂–CC prepared by facile manufacturing methods holds great potential in the daily health monitoring and care of patients with neurological disorders. 

Abstract While most models agree that the Atlantic meridional overturning circulation (AMOC) becomes weaker under greenhouse gas emission and is likely to weaken over the twenty-first century, they disagree on the projected magnitudes of AMOC weakening. In this work, CMIP6 models with stronger climatological AMOC are shown to project stronger AMOC weakening in both 1% ramping CO 2 and abrupt CO 2 quadrupling simulations. A physical interpretation of this result is developed. For models with stronger mean state AMOC, stratification in the upper Labrador Sea is weaker, allowing for stronger mixing of the surface buoyancy flux. In response to CO 2 increase, surface warming is mixed to the deeper Labrador Sea in models with stronger upper-ocean mixing. This subsurface warming and corresponding density decrease drives AMOC weakening through advection from the Labrador Sea to the subtropics via the deep western boundary current. Time series analysis shows that most CMIP6 models agree that the decrease in subsurface Labrador Sea density leads AMOC weakening in the subtropics by several years. Also, idealized experiments conducted in an ocean-only model show that the subsurface warming over 500–1500 m in the Labrador Sea leads to stronger AMOC weakening several years later, while the warming that is too shallow (<500 m) or too deep (>1500 m) in the Labrador Sea causes little AMOC weakening. These results suggest that a better representation of mean state AMOC is necessary for narrowing the intermodel uncertainty of AMOC weakening to greenhouse gas emission and its corresponding impacts on future warming projections. 

A comprehensive understanding of phonon transport is essential to develop effective solutions for heat dissipation. Gallium nitride (GaN), a representative of third-generation power semiconductors, has been extensively studied regarding its thermodynamics and lattice dynamics. However, the temperature-dependent phonon properties, especially the anharmonicity at high temperatures, are poorly understood. Here, by combining inelastic neutron scattering (INS) experiments and calculations including the temperature effect based on machine learning potentials, we report the high-order phonon anharmonicity in GaN over a wide temperature range. Our calculations agree well with the experimental phonon dispersion, density of states and entropy, underlining the significance of anharmonicity of GaN at elevated temperatures. Moreover, considering the four-phonon processes, the calculated thermal conductivity is suppressed by 20%, and the anisotropy is also reduced gradually with increasing temperature. Such behavior arises mainly from the large four-phonon scattering channels between 20 and 30 meV, where the critical scattering rule for the three-phonon process is largely restricted at high temperatures. Our study highlights the importance of high-order phonon anharmonicity for thermal transport in GaN and provides a theoretical reference for thermal management in other related semiconductors. 

Abstract General movements (GMs) have been widely used for the early clinical evaluation of infant brain development, allowing immediate evaluation of potential development disorders and timely rehabilitation. The infants’ general movements can be captured digitally, but the lack of quantitative assessment and well‐trained clinical pediatricians presents an obstacle for many years to achieve wider deployment, especially in low‐resource settings. There is a high potential to explore wearable sensors for movement analysis due to outstanding privacy, low cost, and easy‐to‐use features. This work presents a sparse sensor network with soft wireless IMU devices (SWDs) for automatic early evaluation of general movements in infants. The sparse network consisting of only five sensor nodes (SWDs) with robust mechanical properties and excellent biocompatibility continuously and stably captures full‐body motion data. The proof‐of‐the‐concept clinical testing with 23 infants showcases outstanding performance in recognizing neonatal activities, confirming the reliability of the system. Taken together with a tiny machine learning algorithm, the system can automatically identify risky infants based on the GMs, with an accuracy of up to 100% (99.9%). The wearable sparse sensor network with an artificial intelligence‐based algorithm facilitates intelligent evaluation of infant brain development and early diagnosis of development disorders.