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Action recognition from video data forms a cornerstone with wide-ranging applications. Single-view action recognition faces limitations due to its reliance on a single viewpoint. In contrast, multi-view approaches capture complementary information from various viewpoints for improved accuracy. Recently, event cameras have emerged as innovative bio-inspired sensors, leading to advancements in event-based action recognition. However, existing works predominantly focus on single-view scenarios, leaving a gap in multi-view event data exploitation, particularly in challenges like information deficit and semantic misalignment. To bridge this gap, we introduce HyperMV, a multi-view event-based action recognition framework. HyperMV converts discrete event data into frame-like representations and extracts view-related features using a shared convolutional network. By treating segments as vertices and constructing hyperedges using rule-based and KNN-based strategies, a multi-view hypergraph neural network that captures relationships across viewpoint and temporal features is established. The vertex attention hypergraph propagation is also introduced for enhanced feature fusion. To prompt research in this area, we present the largest multi-view event-based action dataset $\mathbf{THU}^{\mathbf{MV-EACT}}\mathbf{-50}$THUMV-EACT-50, comprising 50 actions from 6 viewpoints, which surpasses existing datasets by over tenfold. Experimental results show that HyperMV significantly outperforms baselines in both cross-subject and cross-view scenarios, and also exceeds the state-of-the-arts in frame-based multi-view action recognition.

3,3,3-trifluoropropene (R1243zf), which has good environmental and cycling characteristics, is a very promising fourth generation new working fluid. However, it is flammable, so studying its combustion characteristics and how to suppress its flammability are of great significance. Firstly, the flammability limits of three binary mixtures composed of a combustible substance (R1243zf) and three flame retardants (R245fa, R1216, and R13I1) were experimentally studied. The results showed that as the proportion of flame retardants increased, the lower flammability limit of the mixture increased, while the upper flammability limit decreased except for R245fa. The critical suppression ratios of R245fa, R1216, and R13I1 on R1243zf were 4, 0.538, and 0.538, respectively. Then, the improved group contribution method was used to predict the minimum inhibitory concentration of R1243zf, with an error of only 4.57 % compared to the experimental values. Finally, the influence of variable ambient temperature (25–100℃) on the flammability of R1243zf was studied, and the calculated adiabatic flame temperature method was used to predict the flammability limit at different temperatures. The error between the predicted values and the experimental values is only 1.7 %. The relevant results are of great significance for the safe application of R1243zf and new binary mixed working fluids.

Selenomethionine (SeMet) is an important nutrient, but its role in milk synthesis and the GPCR related to SeMet sensing is still largely unknown. Here, we determined the dose-dependent role of SeMet on milk protein and fat synthesis and proliferation of mammary epithelial cells (MECs), and we also uncovered the GPCR-mediating SeMet function. At 24 h postdelivery, lactating mother mice were fed a maintenance diet supplemented with 0, 5, 10, 20, 40, and 80 mg/kg SeMet, and the feeding process lasted for 18 days. The 10 mg/kg group had the best increase in milk production, weight gain of offspring mice, and mammary gland weight and acinar size, whereas a higher concentration of SeMet gradually decreased the weight gain of the offspring mice and showed toxic effects. Transcriptome sequencing was performed to find the differentially expressed genes (DEGs) between the mammary gland tissues of mother mice in the 10 mg/kg SeMet treatment group and the control group. A total of 258 DEGs were screened out, including 82 highly expressed genes including GPR37 and 176 lowly expressed genes. SeMet increased milk protein and fat synthesis in HC11 cells and cell proliferation, mTOR and S6K1 phosphorylation, and expression of GPR37 in a dose-dependent manner. GPR37 knockdown decreased milk protein and fat synthesis in HC11 cells and cell proliferation and blocked SeMet stimulation on mTOR and S6K1 phosphorylation. Taken together, our data demonstrate that SeMet can promote milk protein and fat synthesis and proliferation of MECs and functions through the GPR37-mTOR-S6K1 signaling pathway.

The rheological properties of the styrene–butadiene–styrene modified asphalt (SBSMA) binder have not been thoroughly investigated yet. In this study, SBSMA binders with various SBS contents and base asphalt types were prepared and analysed. Fluorescence microscopy, temperature sweeping, and multiple stress creep recovery (MSCR) tests were conducted to analyse the phase structure and rheological behaviour of SBSMA. The results indicate that the special rheological behaviour of a decreasing phase angle value in SBSMA as the temperature increases is a result of the gradual dominance of the network structure over SBSMA’s rheological behaviour. Results from MSCR tests indicate that with the increase in stress levels, the elasticity of the network structure gradually diminishes, signifying a significant stress sensitivity in the network structure. Consequently, due to the stress sensitivity of the network structure, traditional rheological indicators measured at low stress levels (such as phase angle, elastic recovery rate) may overestimate the elasticity of SBSMA at high temperatures (40–80°C).

The photoelectric effect is not truly instantaneous but exhibits attosecond delays that can reveal complex molecular dynamics1–7. Sub-femtosecond-duration light pulses provide the requisite tools to resolve the dynamics of photoionization8–12. Accordingly, the past decade has produced a large volume of work on photoionization delays following single-photon absorption of an extreme ultraviolet photon. However, the measurement of time-resolved core-level photoionization remained out of reach. The required X-ray photon energies needed for core-level photoionization were not available with attosecond tabletop sources. Here we report measurements of the X-ray photoemission delay of core-level electrons, with unexpectedly large delays, ranging up to 700 as in NO near the oxygen K-shell threshold. These measurements exploit attosecond soft X-ray pulses from a free-electron laser to scan across the entire region near the K-shell threshold. Furthermore, we find that the delay spectrum is richly modulated, suggesting several contributions, including transient trapping of the photoelectron owing to shape resonances, collisions with the Auger–Meitner electron that is emitted in the rapid non-radiative relaxation of the molecule and multi-electron scattering effects. The results demonstrate how X-ray attosecond experiments, supported by comprehensive theoretical modelling, can unravel the complex correlated dynamics of core-level photoionization.

Infections caused by intracellular bacterial pathogens are difficult to treat since most antibiotics have low cell permeability and undergo rapid degradation within cells. The rapid development and dissemination of antimicrobial–resistant strains have exacerbated this dilemma. With the increasing knowledge of host–pathogen interactions, especially bacterial strategies for survival and proliferation within host cells, host-directed therapy (HDT) has attracted increased interest and has emerged as a promising anti-infection method for treating intracellular infection. Herein, we applied a cell-based screening approach to a US Food and Drug Administration (FDA)-approved drug library to identify compounds that can inhibit the intracellular replication of SalmonellaTyphimurium (S.Typhimurium). This screening allowed us to identify the antidiarrheal agent loperamide (LPD) as a potent inhibitor of S.Typhimurium intracellular proliferation. LPD treatment of infected cells markedly promoted the host autophagic response and lysosomal activity. A mechanistic study revealed that the increase in host autophagy and elimination of intracellular bacteria were dependent on the high expression of glycoprotein nonmetastatic melanoma protein B (GPNMB) induced by LPD. In addition, LPD treatment effectively protected against S.Typhimurium infection in Galleria mellonellaand mouse models. Thus, our study suggested that LPD may be useful for the treatment of diseases caused by intracellular bacterial pathogens. Moreover, LPD may serve as a promising lead compound for the development of anti-infection drugs based on the HDT strategy.

This article presents a multiport power electronic transformer (PET) based on a three-phase four-arm full-bridge modular multilevel converter (MMC), which is suitable for the hybrid ac–dc distribution grid because it can provide four ports, including medium-voltage ac and dc ports, low voltage dc and ac ports. Compared with the conventional MMC-based PET, which adopts three-phase six arms MMC with full-bridge submodules (FBSMs), the proposed PET uses three-phase four arms MMC with FBSMs, which can reduce the number of submodules. Meanwhile, the modulation index can be increased and the dc-bus voltage utilization can be improved. In addition, the concentrated capacitor on the medium-voltage dc port is eliminated in the proposed PET, so high transient discharging current from the concentrated capacitor can be avoided under the dc-bus short-circuit condition. The operating principle, applied control strategy and PWM scheme are presented in detail. The proposed PET is investigated and simulated in a hybrid 10 kV ac/±10 kV dc distribution grid. A scale down experimental test is also performed. Simulation and experimental results confirm the feasibility and validity of the proposed PET and control method.

ABSTRACTThe Pan-Eurasian Experiment Modelling Platform (PEEX-MP) is one of the key blocks of the PEEX Research Programme. The PEEX MP has more than 30 models and is directed towards seamless environmental prediction. The main focus area is the Arctic-boreal regions and China. The models used in PEEX-MP cover several main components of the Earth’s system, such as the atmosphere, hydrosphere, pedosphere and biosphere, and resolve the physical-chemical-biological processes at different spatial and temporal scales and resolutions. This paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system, online integrated, forward/inverse, and socioeconomical modelling, and other approaches with a particular focus on applications in the PEEX geographical domain. The employed high-performance computing facilities, capabilities, and PEEX dataflow for modelling results are described. Several virtual research platforms (PEEX-View, Virtual Research Environment, Web-based Atlas) for handling PEEX modelling and observational results are introduced. The overall approach allows us to understand better physical-chemical-biological processes, Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks, impact, consequences, etc. for population, environment and climate in the PEEX domain. This work was also one of the last projects of Prof. Sergej Zilitinkevich, who passed away on 15 February 2021. Since the finalization took time, the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

Cancer metastasis and invasion are closely related to tumor cell immunosuppression and intracellular hypoxia. Activation of immunogenicity and intracellular oxygenation are effective strategies for cancer treatment. In this study, multifunctional nanomicelle hyaluronic acid and cinnamaldehyde is self-assembled into nanomicelles (HPCNPs) were constructed for immunotherapy and tumor cell oxygenation. The Schiff base was constructed of HPCNPs with pyropheophorbide a–Cu (PPa–Cu). HPCNPs are concentrated in tumor sites under the guidance of CD44 proteins, and under the stimulation of tumor environment (weakly acidic), the Schiff base is destroyed to release free PPa. HPCNPs with photodynamic therapeutic functions and chemokinetic therapeutic functions produce a large number of reactive oxygen species (1O2and •OH) under exogenous (laser) and endogenous (H2O2) stimulations, causing cell damage, and then inducing immunogenic cell death (ICD). ICD markers (CRT and ATP) and immunoactivity markers (IL-2 and CD8) were characterized by immunofluorescence. Downregulation of Arg1 protein proved that the tumor microenvironment changed from immunosuppressive type (M2) to antitumor type (M1). The oxidation of glutathione by HPCNP cascades to amplify the concentration of reactive oxygen species. In situ oxygenation by HPCNPs based on a Fenton-like reaction improves the intracellular oxygen level. In vitro and in vivo experiments demonstrated that HPCNPs combined with an immune checkpoint blocker (a-PD-L1) effectively ablated primary tumors, effectively inhibited the growth of distal tumors, and increased the oxygen level in tumor cells.

Real-time dynamic imaging of immunoactivation-related cytokines is crucial for evaluating the efficacy of immune checkpoint blockade therapy and optimizing the treatment regimen. We introduce herein a spatiotemporally controlled nanodevice that allows in situphotoactivated imaging of interferon-gamma (IFN-γ) secretion from T cells in vitroand in vivo. The nanodevice is constructed by rational engineering of an aptamer-embedded, UV-cleavable PC-DNA probe and further integration with upconversion nanoparticles- and CRISPR-Cas12a-enhanced fluorescence systems. Using human peripheral blood mononuclear cells (PBMC)-engrafted mouse models, this nanodevice allows for the quantitative imaging of endogenous IFN-γ and its intratumoral dynamics responding to antiprogrammed cell death receptor 1 (anti-PD-1) therapy. This study thus provides a toolbox for boosting the sensitivity and precision of cytokine imaging during immune checkpoint blockade therapy, enlightening research toward imaging-guided tumor therapy.

Bacterial outer membrane vesicles (OMVs) have shown great potential in cancer immunotherapy. The isolation of OMVs from complex media with high purity and high bioactivity is the prerequisite of therapeutic applications, which remains highly challenging. Herein, we report a smart DNA hydrogel for the efficient isolation of OMVs from bacterial culture medium, which is further applied for localized cancer immunotherapy. The DNA hydrogel is constructed through the cross-linking of two ultralong DNA chains generated via rolling circle amplification (RCA). One chain contains polyvalent GN6 aptamer for the specific capture of OMVs, and the other contains polyvalent programmed death-1 (PD-1) aptamer for the blocking of PD-1 immune checkpoint on the surface of T lymphocytes. The OMVs capsulated by DNA hydrogel maintain high immunostimulatory bioactivity. In the mouse model of melanoma, this OMVs-containing DNA hydrogel shows a remarkable tumor inhibition rate of ∼95%. This smart DNA hydrogel represents a promising biomedical platform for the efficient isolation of bacterial-derived OMVs, and provides a powerful strategy for cancer immunotherapy.

The EAT-Lancet Commission has proposed a reference diet aiming to promote human health and environmental sustainability. Socioeconomic disadvantage and poor diet are well-known risk factors for dementia; however, whether the effect of this reference diet on dementia varies by socioeconomic status has not been investigated. The dietary habits of 190,893 participants from UK-Biobank were assessed; the association of EAT-Lancet diet with incident dementia across socioeconomic status was determined by Cox models. One thousand seven hundred twenty-eight dementia cases were identified during a median of 12.24 years follow-up. An inverse association between adherence to EAT-Lancet diet and all-cause dementia (high vs. low; hazard ratio [HR], 95% confidence interval [CI]: 0.82, 0.72–0.94) or late-onset dementia (high vs. low; HR, 95% CI: 0.78, 0.68–0.91) was observed only in individuals with high socioeconomic status. On the contrary, no protective effects of EAT-Lancet diet on early-onset dementia were observed, regardless of the socioeconomic status. Our findings indicated that adherence to an environment-friendly diet helps attenuate risk of dementia only in individuals with high socioeconomic level.

Electrochemical carbon dioxide reduction reaction (CO2RR) into multi-carbon (C2+) products with higher energy density and wider applicability is a promising route for CO2utilization. However, the selectivity and yield of C2+products remain challenging owing to the involvement of multiple electron transfer and the competing reaction, i.e., the hydrogen evolution reaction (HER). Here, we review recent progress in Cu-based electrocatalysts for CO2RR to C2+products. First, possible reaction pathways for CO2RR to C2+products are discussed, focusing on the mechanism of C–C bond formation. Then, strategies of Cu-based electrocatalysts for CO2RR into C2+products are summarized, the key of which is the modulation in C–C coupling of intermediates, leading to different product selectivities. In addition, the progress in in situtechniques for the elucidation of the mechanism is underlined, which is conducive to the precise design of efficient electrocatalysts. The outlooks along with current challenges are finally proposed for the future development of C2+-oriented CO2RR systems.

Terrestrial vegetation is a crucial component of the Earth system, and its changes not only represent one of the most distinct aspects of climate change but also exert significant feedback within the climate system by exchanging energy, moisture, and carbon dioxide. To quantitatively and mechanistically study climate-vegetation feedback, numerical vegetation models have been developed on the theory of ecophysiological constraints on plant functional types. The models eventually can simulate vegetation distribution and succession across different spatial and temporal scales, and associated terrestrial carbon cycle processes by categorizing vegetation into biomes according different plant functional types and their associated environmental factors. Here we review the developing history of vegetation models and provide recent advances and future directions. Before 21st century, static vegetation models, as developed statistical models, can only simulate equilibrated characteristics of vegetation distribution. In last several decades, Dynamic Global Vegetation Models (DGVMs) have been developed to simulate instantaneous responses of vegetation to climate change and associated dynamics, and can be coupled with Earth system models to investigate interactions among atmosphere, ocean, and land. DGVMs are also widely applied to investigate the dynamics accounting for changes in the geographic distribution patterns of land surface vegetation at different spatial and temporal scales and to assess the impacts of terrestrial carbon and water fluxes and land use changes. We suggest that future vegetation modeling could integrate with machine learning, and explore vegetation transient response and feedback as well as impacts of process hierarchies and human activities on climate and ecosystem.

A hybrid computing system employing the superconductor central processing unit and semiconductor memory is a prospective strategy to boost speed and power performance. Aiming to convert coded signals at room temperature to single-flux-quantum (SFQ) logic signals in a cryogenic environment, this article presents two types of CMOS-to-SFQ interface circuits for return-to-zero (RZ) and nonreturn-to-zero (NRZ) coded signals transformation. One can double the data rate (DDR) of bipolar RZ signals, and the other can decode unipolar and polar NRZ signals. In the simulation using parameters of the SIMIT Nb03 process, both the interface circuits have up to 20 GHz sampling frequency, more than ±30% bias current margin, and tolerance toward 20 dB SNR white noise. The DDR interface circuit can generate SFQ pulses at both edges of 1.4–2.6 mA bipolar RZ signal, and the decoding interface circuit can interpret 0.2–0.6 mA unipolar and polar NRZ signal into SFQ pulses. The test circuits have been fabricated under the SIMIT Nb03 6 kA/cm2 process. In low-frequency measurement, the DDR interface circuit can convert 1.4–2.4 mA bipolar RZ signal, and the decoding interface circuit can convert 0.25–0.5 mA unipolar and polar NRZ signal with more than ±30% bias current margin. In high-frequency measurement, the DDR interface circuit shows an ability to convert a 3.33 GHz input signal.

Synergistically modulating electron distribution between metal nodes in metal–organic frameworks (MOFs) is an effective strategy to improve the electrocatalytic performance of MOFs. Herein, a special bimetallic MOF composite (Al0.35/Ru0.15-TCPP-CNTs) was constructed by introducing highly dispersed Ru and Al co-existing in the MOF metal clusters and combining them with conductive carboxylic multi-walled carbon nanotubes (CNTs). Notably, the catalyst exhibited excellent hydrogen evolution reaction (HER) performance, with an overpotential of as low as 32 mV at a current density of 10 mA cm−2in acidic media, comparable to commercial Pt/C. Experimental results and density functional theory (DFT) calculations proved that a reasonable proportion of Al/Ru bimetallic clusters in MOFs and the loaded CNTs induced charge redistribution and cooperative electronic coupling, which not only optimized the adsorption energy of H intermediates (ΔGH*) and produced a possible hydrogen spillover effect, but also increased the specific surface area and facilitated electron/mass transfer. This work may provide an improved method and research idea for the study of MOF electrocatalysts at the atomic level.

In this article, a vision-based prescribed performance control is proposed for an unmanned aerial vehicle (UAV) subject to actuator saturation to track an uncooperative target. It is supposed that states cannot be measured directly, and are estimated by a on-board camera. The proposed controller is designed within a backstepping framework, where an error transforming function and Barrier Lyapunov Function are applied, and a robust adaptive controller is designed to deal with initial conditions violating the prescribed performance. It is proven that, with the proposed controller, the tracking error converges into the prescribed performance boundary before the finite preset time.

Electrocatalytic nitrate reduction reaction is considered as a promising and sustainable method for ammonia synthesis. However, the selectivity and yield rate of ammonia are limited by the competitive hydrogen evolution reaction and the complex eight-electron transfer process. Herein, we developed a (FeCoNiCu)Ox/CeO2polymetallic oxide electrocatalyst for effective nitrate reduction to ammonia. The synergistic effects among the multiple elements in the electrocatalyst were clearly elucidated by comprehensive experiments. Specifically, Cu acted as the active site for reducing nitrate to nitrite, and Co facilitated the subsequent reduction of nitrite to ammonia, while Fe and Ni promoted water dissociation to provide protons. Furthermore, the incorporation of CeO2increased the active surface area of (FeCoNiCu)Ox, resulting in an improved ammonia yield rate to meet industrial demands. Consequently, the (FeCoNiCu)Ox/CeO2electrocatalyst achieved an ammonia current density of 382 mA cm−2and a high ammonia yield rate of 30.3 mg h−1cm−2with a long-term stability. This work offers valuable insights for the future design of highly efficient multi-element electrocatalysts.

Nitrous oxide (N2O) is a long-lived greenhouse gas that mainly originates from agricultural soils. More and more studies have explored the sources, influencing factors and effective mitigation measures of N2O in recent decades. However, the hierarchy of factors influencing N2O emissions from agricultural soils at the global scale remains unclear. In this study, we carry out correlation and structural equation modeling analysis on a global N2O emission dataset to explore the hierarchy of influencing factors affecting N2O emissions from the nitrogen (N) and non-N fertilized upland farming systems, in terms of climatic factors, soil properties, and agricultural practices. Our results show that the average N2O emission intensity in the N fertilized soils (17.83 g N ha−1d−1) was significantly greater than that in the non-N fertilized soils (5.34 g N ha−1d−1) (p< 0.001). Climate factors and agricultural practices are the most important influencing factors on N2O emission in non-N and N fertilized upland soils, respectively. For different climatic zones, without fertilizer, the primary influence factors on soil N2O emissions are soil physical properties in subtropical monsoon zone, whereas climatic factors are key in the temperate zones. With fertilizer, the primary influence factors for subtropical monsoon and temperate continental zones are soil physical properties, while agricultural measures are the main factors in the temperate monsoon zone. Deploying enhanced agricultural practices, such as reduced N fertilizer rate combined with the addition of nitrification and urease inhibitors can potentially mitigate N2O emissions by more than 60% in upland farming systems.

The parallel connection of silicon carbide (SiC)-mosfet modules can effectively increase the rated current of modules, however, the related current imbalance issue will affect the performance of the system. To solve this problem, this article proposes a hybrid current balancing method for multiple paralleled SiC-mosfet half-bridge modules, which can balance the transient current and steady-state current of the modules, simultaneously. First, the operating principles of the current balancing circuit are analyzed, and multiple toroidal magnetic cores with additional windings and dc current compensator are utilized to suppress the transient imbalance currents. Then, a novel current detection circuit is introduced to capture the steady-state imbalance current of the modules. Based on the obtained unbalanced currents, the steady-state currents of the modules are finally balanced by using a closed-loop active pulse width modulation (PWM) edge regulation method. The proposed hybrid current balancing method does not require high-bandwidth high-precision current sensors and introduces negligible reactive power to the system. It can be easily extended to more paralleled modules and employed in dc–dc converters. The effectiveness of the proposed method is experimentally verified by a prototype with three paralleled 1200 V/120 A SiC-mosfet half-bridge modules. The results show that with the proposed method, both the transient current and steady-state current are well balanced.

Pump–probe experiments with subfemtosecond resolution are the key to understanding electronic dynamics in quantum systems. Here we demonstrate the generation and control of subfemtosecond pulse pairs from a two-colour X-ray free-electron laser. By measuring the delay between the two pulses with an angular streaking diagnostic, we characterize the group velocity of the X-ray free-electron laser and show control of the pulse delay down to 270 as. We confirm the application of this technique to a pump–probe measurement in core-ionized para-aminophenol. These results reveal the ability to perform pump–probe experiments with subfemtosecond resolution and atomic site specificity.

To realize multiparameter simultaneous sensing measurement and eliminate cross-sensitivity, we cascade three micro-tapered long-period fiber grating (TLPG) sensors and analyze the transmission characteristics and sensing capabilities of cascaded micro-TLPGs (CTLPGs) in detail. Based on the modulation of the resonant wavelength of the sensor by the change of the surrounding environment, the synchronous real-time detection of refractive index (RI), temperature, and liquid level is realized. The CTLPG sensor not only inherits the advantages of TLPG sensors and reduces the influence of cross-sensitivity when measuring multiparameters but also improves the sensitivity and accuracy of the sensor. The experimental results show that the maximum RI sensitivity is 693 nm/RIU, the maximum temperature sensitivity is −93 pm/°C, and the maximum liquid-level sensitivity is 12 nm/mm. The sensor has a simple structure, low manufacturing cost, high sensitivity, and potential applications in monitoring ocean temperature, salinity, and depth.

Intense attosecond X-ray pulses are key for ultrafast nonlinear spectroscopy and diffractive imaging. Here we demonstrate the generation of terawatt-scale isolated attosecond pulses with a two-stage cascaded X-ray free-electron laser. These pulses have a median energy in excess of 100 μJ in the soft X-ray region. The temporal profile is characterized with an angular streaking measurement, revealing a maximum peak power of 1.1 TW. Our data show an increase in the average peak power of attosecond X-ray pulses by one order of magnitude over previous reported results and provide strong evidence of soliton-like superradiant behaviour in the X-ray regime.

The electrochemical conversion of lignin for the production of high-value aromatic compounds holds immense potential. However, the process of depolymerizing lignin faces significant challenges due to its intricate structure, particularly the existence of C–C bonds, resulting in low conversion and product yields. In this work, we report the successful synthesis of a molecular palladium catalyst and its inaugural application in the electrochemical conversion of lignin model compounds. This catalyst with well-defined coordination structure demonstrates exceptional efficacy and achieves a remarkable 99% conversion rate for the lignin model compound 2-phenoxy-1-phenylethanol with a yield of 32% of the benzaldehyde product while valuable hydrogen is produced at the electrode under ambient conditions. Furthermore, employing radical trapping and EPR test point that the tBuO radical was the key to inducing C–C cleavage for high conversion and enabled a comprehensive elucidation of the possible reaction pathways involving radical/radical cross-coupling. Based on this study, we believe that molecular catalysts will open a new chapter in the electrocatalytic conversion of lignin.

Recent years have witnessed remarkable achievements in video-based action recognition. Apart from traditional frame-based cameras, event cameras are bio-inspired vision sensors that only record pixel-wise brightness changes rather than the brightness value. However, little effort has been made in event-based action recognition, and large-scale public datasets are also nearly unavailable. In this paper, we propose an event-based action recognition framework called EV-ACT. The Learnable Multi-Fused Representation (LMFR) is first proposed to integrate multiple event information in a learnable manner. The LMFR with dual temporal granularity is fed into the event-based slow-fast network for the fusion of appearance and motion features. A spatial-temporal attention mechanism is introduced to further enhance the learning capability of action recognition. To prompt research in this direction, we have collected the largest event-based action recognition benchmark named THUE-ACT-50 and the accompanying THUE-ACT-50-CHL dataset under challenging environments, including a total of over 12,830 recordings from 50 action categories, which is over 4 times the size of the previous largest dataset. Experimental results show that our proposed framework could achieve improvements of over 14.5%, 7.6%, 11.2%, and 7.4% compared to previous works on four benchmarks. We have also deployed our proposed EV-ACT framework on a mobile platform to validate its practicality and efficiency.

This article presents a wireless high-voltage power supply (WHPS) that leverages MHz wireless power transfer (WPT) technology with the double-sided LCC compensation topology, achieving high-voltage, high-isolation, high-efficiency, and high-power-density performance. The design utilizes magnetic resonant WPT for primary and secondary side isolation and incorporates multiple receiving coils on the secondary side. Rectifying each coil separately generates multiple direct current (dc) voltages, which are connected in series to produce high voltage output. To attain high power density, stacking of receiving coils and integration of compensation inductors are implemented. However, due to the close proximity of these components, strong coupling results in both mutual inductance and parasitic capacitance. A compensation parameter design method is proposed to decouple mutual inductance and ensure resonant and voltage equalization across each stage. The spatial structures of the coils and inductors are also specifically designed to mitigate the impact of parasitic capacitance, enabling the system's resonant frequency to be elevated to MHz levels. Finally, an 800 W/1.875 MHz WHPS prototype was design and fabricated. Experimental results show that the prototype is capable of converting a 150 V input into a 10 kV output, while maintaining a dc–dc efficiency exceeding 90% across a wide range of load conditions, from 6% to 100%. Moreover, the developed prototype demonstrates a power density of 3.66 kW/L (60 W/in3) and an electrical insulation performance surpassing 35 kV ac.

Gallium oxide (Ga2O3) phototransistors with low dark current and high ON-OFF ratio have been attracting considerable attention for UV-C light detection applications. However, the joint influence of photoconduction and gating on their photoresponse behaviors makes the photodetection mechanism experimentally ambiguous. Herein, a theoretical study on Ga2O3 phototransistors is performed with technology computer-aided design (TCAD) Silvaco software to reveal the role of gate bias and external UV-C light illumination on their electrical characteristics. The analyses on the transfer curves before and after 250-nm light illumination figure out that the responsivity increases and then decreases with the gate bias, and the gate bias required to achieve the maximum responsivity increases with Ga2O3 thickness. Interestingly, under weak light irradiation, the current density of Ga2O3 phototransistors is found to be obviously enhanced by the gate bias owing to the effective separation of photo-generated electron-hole pairs. However, this gating effect is weakened upon strong UV-C light illumination. Our theoretical work clarifies the synergism and competition relationships between photoconduction and gating effects and offers a reference for the design of high-performance Ga2O3 phototransistors.

The precise control of the artificially induced reactions inside living cells is emerging as an effective strategy for the regulation of cell functions. Nevertheless, the manipulation of the assembly of exogenous molecules into artificial architectures in response to intracellular-specific signals remains a grand challenge. Herein, we achieve the precise self-assembly of deoxyribonucleic acid (DNA) network inside cancer cells, specifically responding to telomerase, and realize effective mitochondrial interference and the consequent regulation of cellular behaviors. Two functional DNA modules were designed: a mitochondria-targeting branched DNA and a telomerase-responsive linear DNA. Upon uptake by cancer cells, the telomerase primer in linear DNA responded to telomerase, and a strand displacement reaction was triggered by the reverse transcription of telomerase, thus releasing a linker DNA from the linear DNA. The linker DNA afterward hybridized with the branched DNA to form a DNA network on mitochondria. The DNA network interfered with the function of mitochondria, realizing the apoptosis of cancer cells. This system was further administered in a nude mouse tumor model, showing remarkable suppression of tumor growth. We envision that the telomerase-mediated intracellular self-assembly of the DNA network provides a promising route for cancer therapy.

Due to its use of renewable energy and environmental friendliness, the electrochemical nitrogen reduction process (eNRR) has become a promising substitute for the manufacturing of ammonia. Despite extensive exploration of eNRR catalysts, an optimal catalyst has not been reported to date. Therefore, it is imperative to develop rational catalysts to enhance NH3synthesis efficiency. In order to offer suggestions for catalyst design, recent developments in electrocatalysts for eNRR are summarized in this paper. Firstly, the eNRR mechanism is briefly introduced. Secondly, the design strategies of eNRR catalysts were summarized in terms of morphology, structure, vacancies, doping, synergistic effect, heterojunction and single atom. Subsequently, the application of in situ mass spectrometry, in situ infrared, in situ XAS and in situ Raman to the NRR reaction is discussed. The importance of the density-functional theory (DFT) method for the study of reaction energy barriers and catalyst electron-orbital distributions during eNRR catalysis is discussed. Finally, this review presents the potential challenges and future perspectives of eNRR.