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In 1999, the Yellow River Basin (YRB) launched the Grain for Green Program (GGP), which has had a huge impact on the Yellow River Basin vegetation. Research regarding the causes of vegetation changes can provide beneficial information for the management and construction of the ecological environment in the Yellow River Basin. In this study, after reconstructing the relationship between vegetation and climate change under natural conditions, topographic factors were introduced to understand vegetation change in the Yellow River Basin before and after the initiation of the Grain for Green Program, and the contribution rates of the driving factors of change were analyzed. Results show that human activities have had a great impact on the vegetation cover in the Yellow River Basin. We found that after the start of the Grain for Green Program, the vegetation recovery rate was more than six times (slope = 0.0067) that before its start (slope = 0.0011); high NDVI levels moved to lower altitudes, while low NDVI levels moved to high altitudes; and most vegetation types turned to gentle slopes. Human activities and climate change are the dominant factors influencing vegetation coverage, and the contribution rate of human activities had reached 59.3% after 2000, with a tendency to gradually dominate.

Optogenetics, which uses visible light to control the cells genetically modified with light-gated ion channels, is a powerful tool for precise deconstruction of neural circuitry with neuron-subtype specificity. However, due to limited tissue penetration of visible light, invasive craniotomy and intracranial implantation of tethered optical fibers are usually required for in vivo optogenetic modulation. Here we report mechanoluminescent nanoparticles that can act as local light sources in the brain when triggered by brain-penetrant focused ultrasound (FUS) through intact scalp and skull. Mechanoluminescent nanoparticles can be delivered into the blood circulation via i.v. injection, recharged by 400-nm photoexcitation light in superficial blood vessels during circulation, and turned on by FUS to emit 470-nm light repetitively in the intact brain for optogenetic stimulation. Unlike the conventional “outside-in” approaches of optogenetics with fiber implantation, our method provides an “inside-out” approach to deliver nanoscopic light emitters via the intrinsic circulatory system and switch them on and off at any time and location of interest in the brain without extravasation through a minimally invasive ultrasound interface.

Conducting polymer hydrogels represent a unique class of materials that synergizes the advantageous features of hydrogels and organic conductors and have been used in many applications such as bioelectronics and energy storage devices. They are often synthesized by polymerizing conductive polymer monomer within a nonconducting hydrogel matrix, resulting in deterioration of their electrical properties. Here, we report a scalable and versatile synthesis of multifunctional polyaniline (PAni) hydrogel with excellent electronic conductivity and electrochemical properties. With high surface area and three-dimensional porous nanostructures, the PAni hydrogels demonstrated potential as high-performance supercapacitor electrodes with high specific capacitance (∼480 F·g ⁻¹), unprecedented rate capability, and cycling stability (∼83% capacitance retention after 10,000 cycles). The PAni hydrogels can also function as the active component of glucose oxidase sensors with fast response time (∼0.3 s) and superior sensitivity (∼16.7 μA·mM ⁻¹). The scalable synthesis and excellent electrode performance of the PAni hydrogel make it an attractive candidate for bioelectronics and future-generation energy storage electrodes.

Human skin relies on cutaneous receptors that output digital signals for tactile sensing in which the intensity of stimulation is converted to a series of voltage pulses. We present a power-efficient skin-inspired mechanoreceptor with a flexible organic transistor circuit that transduces pressure into digital frequency signals directly. The output frequency ranges between 0 and 200 hertz, with a sublinear response to increasing force stimuli that mimics slow-adapting skin mechanoreceptors. The output of the sensors was further used to stimulate optogenetically engineered mouse somatosensory neurons of mouse cortex in vitro, achieving stimulated pulses in accordance with pressure levels. This work represents a step toward the design and use of large-area organic electronic skins with neural-integrated touch feedback for replacement limbs.

The structural and functional complexity of multicellular biological systems, such as the brain, are beyond the reach of human design or assembly capabilities. Cells in living organisms may be recruited to construct synthetic materials or structures if treated as anatomically defined compartments for specific chemistry, harnessing biology for the assembly of complex functional structures. By integrating engineered-enzyme targeting and polymer chemistry, we genetically instructed specific living neurons to guide chemical synthesis of electrically functional (conductive or insulating) polymers at the plasma membrane. Electrophysiological and behavioral analyses confirmed that rationally designed, genetically targeted assembly of functional polymers not only preserved neuronal viability but also achieved remodeling of membrane properties and modulated cell type–specific behaviors in freely moving animals. This approach may enable the creation of diverse, complex, and functional structures and materials within living systems.

Evapotranspiration (ET) is a key link between atmospheric processes and land surface hydrological processes. With the impact of global warming and human activities, research on ET has become a hot topic. Supported by a total of 1,222 Chinese and English literatures from China National Knowledge Infrastructure and the Web of Science Core Collection from 2013 to 2022, this paper adopts the bibliometric visualization method to review the current research progress and future trend of ET with respect to the time of publication, countries, institutions, journals, and research hotspots. The results show that the number of related research articles is increasing rapidly and the journals with high citations are Journal of Hydrology, Agricultural and Forest Meteorology and Agricultural Water Management. The research hotspots have been focused on prototype observation, remote sensing inversion, mechanism equation, model simulation, spatial–temporal analysis, and attribution identification. In the future, there is an urgent need to integrate algorithms such as machine learning and artificial intelligence, to develop higher resolution remote sensing products, to improve the mechanism equations based on precise observations, and to clarify the impact of synergistic effects on ET among the driving factors.

Photoluminescence (PL) mechanisms of nontraditional luminogens (NTLs) have attracted great interest, and they are generally explained with intra/intermolecular through‐space conjugation (TSC) of nonconventional chromophores. Here a new concept of nonaromatic through‐bond conjugation (TBC) is proposed and it is proved that it plays an important role in the PL of NTLs. The PL behaviors of the three respective isomers of cyclohexanedione and gemdimethyl‐1,3‐cyclohexanedione were studied and correlated with their chemical and aggregate structures. These compounds show different fluorescence emissions as well as different concentration, excitation and solvent‐dependent emissions. The compounds which undergo keto‐enol tautomerism and hence with a conjugated ketone‐enol structure (i.e., nonaromatic TBC) show more red‐shifted emissions. TBC effect reduces the energy gaps and facilitates the formation of stronger TSC in the aggregate state. The compounds in the ketone‐enol form are also prone to occur excited state intra/intermolecular proton transfer (ESIPT). The cooperative effect of nonaromatic TBC and TSC determines the PL behaviors of NTLs. This work provides a novel understanding of the PL mechanisms of NTLs and is of great importance for directing the design and synthesis of novel NTLs. A novel concept of nonaromatic through‐bond conjugation (TBC) is proposed and it is proven to play an important role in the photoluminescence of nontraditional luminogens by studying the relationship between the photophysical properties of the isomers of cyclohexanedione and dimethyl‐1,3‐cyclohexanedione and their chemical structures, aggregate structures and interactions.

Narrowing the mechanical mismatch between tissue and implantable microelectronics is essential for reducing immune responses and for accommodating body movement. However, the design of implantable soft electronics (on the order of 10 kPa in modulus) remains a challenge because of the limited availability of suitable electronic materials. Here, we report electrically conductive hydrogel-based elastic microelectronics with Young’s modulus values in the kilopascal range. The system consists of a highly conductive soft hydrogel as a conductor and an elastic fluorinated photoresist as the passivation insulation layer. Owing to the high volumetric capacitance and the passivation layer of the hydrogel, electrode arrays of the thin-film hydrogel ‘elastronics’, 20 μm in feature size, show a significantly reduced interfacial impedance with tissue, a current-injection density that is ~30 times higher than that of platinum electrodes, and stable electrical performance under strain. We demonstrate the use of the soft elastronic arrays for localized low-voltage electrical stimulation of the sciatic nerve in live mice. Conductive and elastic hydrogel-based microelectronic arrays with high current-injection density and low interfacial impedance with tissue enable the localized low-voltage electrical stimulation of the sciatic nerve in live mice.

Flood risk assessment is an important tool for disaster warning and prevention. In this study, an integrated approach based on a D-number-improved analytic hierarchy process (D-AHP) and a self-organizing map (SOM) clustering algorithm are proposed for urban flooding risk assessment. The urban flood inundation model and geographic information system (GIS) technology were used to quantify the assessment indices of urban flood risk. The D-AHP approach was adopted to determine the weights of the indices, which effectively makes up for the shortcomings of the AHP in dealing with uncertain evaluation information (such as fuzzy and incomplete information). In addition, the SOM clustering algorithm was applied to determine the flood risk level. It is a data-driven approach that avoids the subjective determination of a flood risk classification threshold. The proposed approach for flood risk assessment was implemented in Zhengzhou, China. The flood risk was classified into five levels: highest risk, higher risk, medium risk, lower risk, and the lowest risk. The proportion of the highest risk areas was 9.86%; such areas were mainly distributed in the central and eastern parts of the Jinshui District, the eastern part of the Huiji District, and the northeastern part of the Guancheng District, where there were low terrain and serious waterlogging. The higher risk areas accounted for 24.26% of the study area, and were mainly distributed in the western and southern parts of the Jinshui District, the southern part of the Huiji District, the middle and eastern parts of the Zhongyuan District, the northeastern part of the Erqi District, and the northwestern part of the Guancheng District, which consisted of economically developed areas of dense population and buildings, matching well with historical flooding events. To verify the effectiveness of the proposed approach, traditional approaches for risk assessment were compared. The comparison indicated that the proposed approach is more reasonable and accurate than the traditional approaches. This study showed the potential of a novel approach to flood risk assessment. The results can provide a reference for urban flood management and disaster reduction in the study area.

With global climate change, cities face the challenge of increasing flood disaster caused by heavy rainfall, and the prediction and assessment of flood disaster risk is a crucial step towards risk mitigation and adaptation planning. In this study, a method combining Bayesian network (BN) model and geographic information system (GIS), which can capture the potential relationships between factors impacting flood disaster and has capacity of quantifying uncertainty and utilizing both data and knowledge-based sources, was proposed to assess flood disaster risk. The proposed methodology was applied in a case study to assess flood disaster risk and to diagnose the reason for flood disaster in Zhengzhou City, and the results were validated by comparing with actual situation. The results show that that the relative error of very-low, low, moderate, high and very-high risk predicted by the proposed model is 12.57%, 13.21%, 2.23%, 19.63% and 21.65%, respectively, which demonstrates the discriminative power of the established model. Based on the spatial distribution of different risk levels, it can be recognized that the flood disaster risk in Zhengzhou City is decreasing from the middle to the surroundings. The results provide some basis for the field control and management of urban flood disaster.