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Under the dual-carbon target, the popularization and application of building integrated photovoltaic (BIPV) and ground source heat pump systems have made active buildings a research hotspot in the field of architecture and energy. Aiming at this issue, based on the building energy consumption model of active buildings, an active building energy management system (EMS) control strategy based on multi-energy load collaborative optimization is proposed. Firstly, based on the thermal dynamic characteristics and building performance parameters of active buildings, the overall refined energy consumption model of active buildings is constructed. Secondly, based on the construction of BIPV, the ice storage air conditioning system, the ground source heat pump system, and the integrated demand response (IDR) model, a tiered carbon transaction cost model is introduced, and an energy management strategy that leverages the synergistic application of renewable and active technologies is proposed. This strategy aims to meet the comprehensive needs of active buildings in terms of economic benefits, comfort, and environmental protection. Finally, the strategy's effectiveness is demonstrated through a practical example. [ABSTRACT FROM AUTHOR]

Chiral cyclic β-amino alcohols are vital building blocks for the synthesis of numerous pharmaceuticals and bioactive molecules. Asymmetric ring-opening of cyclic meso-epoxides is a straightforward and appealing method for their synthesis. However, developing an environmentally friendly and cost-effective approach for this process remains elusive. Herein, the synthesis of enantiomerically pure cyclic β-amino alcohols through a fully biocatalytic asymmetric ring-opening of cyclic meso-epoxides is described. A novel amine transaminase (CepTA) from Capronia epimyces with comparable activity and excellent enantioselectivity toward small molecule cyclic α-hydroxy ketones was discovered and proved to be efficient on a wide range of substrates. Homology modelling, molecular docking, and molecular dynamics simulations were also performed to elucidate the highly efficient catalytic mechanisms of CepTA for small cyclic α-hydroxy ketones. The asymmetric ring-opening of cyclic meso-epoxides (4′j–k) was successfully achieved by using combined recombinant E. coli (SpEH-AnDDH-BsLDH) and E. coli (CepTA) resting cells, leading to the production of cyclic (1R,2R)-trans-β-amino alcohols (1′j–k) up to 81.8% conversions and >99% ee. This study marks the first instance of achieving fully biocatalytic asymmetric ring-opening of meso-epoxides to chiral cyclic β-amino alcohols, offering a novel pathway for the environmentally friendly synthesis of chiral cyclic β-amino alcohols from readily available, cost-effective meso-epoxides. [ABSTRACT FROM AUTHOR]

Summary In this paper, a new high‐step‐up DC‐DC converter without any coupled inductors or transformers is introduced. The structure of the introduced converter consists of two boost techniques, namely, switched inductor and switched capacitor, used simultaneously. The drawbacks of each technique are mitigated according to the proposed structure and the introduced control method. Therefore, the main contribution of the introduced converter is its ability to use boost techniques while avoiding high input current ripples and inrush currents in the path of semiconductor devices. Thus, there is no need for an auxiliary inductor. Additionally, the number of required components is low, and it benefits from a common ground, which are advantages of this converter in terms of economy and reliability. Another advantage is the high efficiency of the proposed converter in comparison with recent topologies, making it suitable for renewable energy applications such as photovoltaic (PV) systems and fuel cell applications. The proposed converter has been implemented in a laboratory to verify its performance. It operates at 94.51% efficiency with a 200 W output power, a 40 kHz switching frequency, a 40 V input voltage, and a 240 V output voltage. [ABSTRACT FROM AUTHOR]

Deserts are predicted to be one of the ecosystems most vulnerable to global climate change, with dramatic fluctuations of temperature and water, even over the span of a single day. These previous disturbances could influence the response of the soil microbiome and its functions to subsequent disturbances, which is known as legacy effect. However, how legacy effects shape the response of soil microbiome and its functions to environmental fluctuations (e.g. temperature and water availability) in desert ecosystems remains to be investigated.Here, we firstly exposed desert soils to drought, freezing or their combination, and then followed by a second disturbance, resulting in a temporally full factorial treatment.We found that environmental change legacies affected the response of soil multifunctionality, microbial abundance and richness to second drought and freezing, except for eukaryotic richness. Initial disturbances caused legacy effects on microbial composition and weakened their responses to later disturbances, and these effects were stronger for prokaryotes than eukaryotes. The attenuated response to later disturbances is largely due to that almost half of the taxa affected by the earlier disturbances were also affected by the second disturbances. The phylogenetic depth of these responses varied minimally among the types of disturbances but were more conserved for negative responses, indicating a result of historical adaptation. Moreover, the altered community composition was associated with functional changes in the disturbed soils.These findings will improve our understanding of the mechanisms underlying the legacy impacts of multiple environmental disturbances on desert microbial communities and strengthen our ability to develop management strategies for protection prior to disturbance events. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

BACKGROUND: Intestinal development and function are critical to maintaining sustained broiler growth. The present study aimed to evaluate the effects of coated sodium butyrate (CSB) and vitamin D3 (VD3) on the intestinal immunity, barrier, oxidative stress and microflora in early‐stage broilers. In total, 192 one‐day‐old broilers were assigned to a 2 × 2 factorial design including two dietary supplements at two different levels, in which the main effects were VD3 (3000 or 5000 IU kg−1) and CSB (0 or 1 g kg−1). RESULTS: The results showed that CSB supplementation increased ileal goblet cells (GCs) numbers, villus height and decreased crypt depth in broilers. CSB increased ileal proliferating cell nuclear antigen expression and high‐level VD3 decreased cluster of differentiation 3 expression. CSB reduced serum d‐lactate, endotoxin (ET), adrenocorticotropic hormone, corticosterone and malondialdehyde (MDA) concentrations and increased total antioxidant capacity (T‐AOC) level. Meanwhile, high‐level VD3 decreased serum ET concentration. Furthermore, CSB increased ileal T‐AOC, lysozyme (LYZ) and transforming growth factor (TGF)‐β and decreased MDA, whereas high‐level VD3 decreased ileal MDA and increased secretory immunoglobulin A. CSB up‐regulated ileal claudin1, superoxide dismutase 1, TGF‐β and LYZ mRNA expression and down‐regulated interleukin‐1β mRNA expression. CSB combined with high‐level VD3 increased ileal Faecalibaculum abundance. Spearman correlation analysis showed that Faecalibaculum was related to the immune and barrier function. CONCLUSION: Dietary supplementation with CSB and high‐level VD3 improved early gut health in broilers by promoting intestinal development, enhancing antioxidant capacity, strengthening barrier function and enhancing the favorable composition of the gut bacterial flora. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

[Display omitted] In the present study, the catalyst modified with alkaline oxide can enhance the selectivity to primary amines. However, the addition of alkaline oxide inevitably reduces catalytic activity. In this study, NiCo-NC@BaO-MFC catalyst derived from zeolitic imidazolate framework-67, Ba(CH 3 COO) 2 , and melamine formaldehyde (MF) resin was prepared and used for the hydrogenation of adiponitrile (ADN) to hexamethylene diamine (HDMA). The carbon layer obtained from the MF resin effectively prevents the interaction between barium (Ba) and the active center, thus improving target product selectivity without decreasing catalytic activity. The results of the density functional theory (DFT) calculation and characterization indicated that the effect of synergy between nickel (Ni) and cobalt (Co) bimetals induces an electron density growth on the Ni surface, bringing the d-band center toward the Fermi surface. Meanwhile, the high electron density of the active center compensates for the electron-deficient state of the carbon atom in –C N, thus improving the catalytic activity. Furthermore, it was found that the introduction of Ba promotes the formation of nucleophilic hydrogen anions, which facilitates the hydrogenation of 6-aminohexylimine (AHIM) to HDMA and inhibits the intramolecular condensation of AHIM, hence improving the selectivity to HDMA. The NiCo-NC@BaO-MFC catalyst gives 98.6 % ADN conversion and 97.2 % selectivity to HDMA in an alkali-free system. [ABSTRACT FROM AUTHOR]

BACKGROUND RESULTS CONCLUSION Rice vinegar is a popular cereal vinegar worldwide and is typically produced in an open environment, and the ecosystem of solid‐state fermentation is complicated and robust. The present study aimed to reveal the shaping force of the establishment of the ecosystem of Beijing rice vinegar, the core function microbiota and their correlation with critical environmental factors. [Correction added after first online publication on 29 May 2024; the word “worldwide” has been removed from the first sentence under the section Background.]The experimental findings revealed the changes in environmental factors, major metabolites and microbial patterns during Beijing rice vinegar fermentation were obtained. The major metabolites accumulated at the middle and late acetic acid fermentation (AAF) periods. Principal coordinates and t‐test analyses revealed the specific bacterial and fungal species at corresponding stages. Kosakonia, Methlobacterium, Sphingomonas, unidentified Rhizobiaceae, Pseudozyma and Saccharomycopsis dorminated during saccharification and alcohol fermentation and early AAF, whereas Lactococcus, Acetobacter, Rhodotorula and Kazachstania dominated the later AAF stages. Canonical correspondence analysis of environmental factors with core microbiota. Temperature and total acid were the most significant factors correlated with the SAF bacterial profile (Pediococcus, Weissella, Enterococcus and Kosakonia). Ethanol was the most significant factor between AAF1 and AAF3, and mainly affected Acetobacter and Lactobacillus. Conversely, ethanol was the most significant factor in the SAF, AAF1 and AAF3 fungi communities; typical microorganisms were Saccharomyces and Malassezia. Furthermore, the predicted phenotypes of bacteria and their response to environmental factors were evaluated.In conclusion, the present study has provided insights into the process regulation of spontaneous fermentation and distinguished the key driving forces in the microbiota of Beijing rice vinegar fermentation. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Environment-benign one-pot three-component cycloadditions of diazo compounds, nitrosoarenes and vinyl pyrimidines, or vinyl purines, or vinyl imidazoles, or vinyl triazoles or vinyl indole have been developed. This catalyst- and additive-free strategy could efficiently introduce the isoxazolidine skeleton into nucleoside analogues, oxazole molecules and indole derivatives to provide diverse classes of isoxazolidinyl pyrimidine nucleoside analogues, isoxazolidinyl purine nucleoside analogues, isoxazolidinyl imidazoles, isoxazolidinyl triazoles and isoxazolidinyl indole with moderate to good yields for most substrates. [ABSTRACT FROM AUTHOR]

Copy-move is a common image forgery operation, which copies and moves a block of an image from one position to another place. Image hashing refers to extracting a unique number sequence from the image by using various image features. In practical application, image hashing is used to replace the image itself, which effectively reduces the cost of image storage and computational complexity. In this paper, we propose a novel image hash extraction scheme: constructing image hashing by combining local feature based on Canny operator and global feature based on tensor. In addition, instead of using the traditional correlation coefficient or Hamming distance, a novel method is proposed to calculate the hash distances. A large number of experiments have proved that our image hashing can achieve a better balance between robustness and discrimination with a shorter hash length. What's more, we can directly locate the forgery areas from the hashing for copy-move forged images. [ABSTRACT FROM AUTHOR]

For the first time, we report novel aggregation-induced electrochemiluminescence (AIECL) of organic dots in aqueous media, with near-infrared II (NIR-II) luminescence peaked at 906 nm. Furthermore, a hybrid mechanism of ECL generation is revealed by various experiments in conjunction with theoretical calculations. This work opens a window for exploring efficient organic dye-based NIR-II AIECL emitters. [ABSTRACT FROM AUTHOR]

In the realm of abrasive flow machining (AFM), precise finishing and maintaining dimensional accuracy have remained challenging due to non-uniformities in the AFM process and complexities associated with the abrasive media's shear viscosity and wall slip behavior. By addressing these challenges, this study introduces a comprehensive framework, combining theoretical foundations, measurement techniques, and experimental setups. Utilizing capillary flow, a novel compensation strategy is incorporated within the Mooney method to counter entrance pressure drop effects. This enhanced capillary flow method emerges as a promising alternative to the conventional Cox–Merz empirical rule, enabling precise characterization of wall slip behavior and shear viscosity, particularly at elevated shear rates. The abrasive media exhibit a Navier nonlinear wall slip, as highlighted by the Mooney method. Rigorous verification of the proposed methodologies and models against supplemental experiments showcases a high degree of congruence between predicted and observed results, emphasizing their accuracy and broad application potential in AFM. This research illuminates the intricacies of the abrasive media's behavior, accentuating the need for meticulous characterization, and provides a robust foundation for genuine modeling and predictions in material removal within AFM. [ABSTRACT FROM AUTHOR]

Construction of white‐light emitters is of great importance in practical applications but is challenging for metal nanoclusters. Herein, arginine (Arg)‐mediated copper nanoclusters (Cu NCs) assemblies with white‐light emission (WLE) are reported for the first time. The multidentate ligand, Arg, not only effectively tailors the high stability and locally‐excited emission (LES) of aqueous phase Cu NCs, but also bridges 1‐naphthalenol methylcarbamate (NMC) to generate a blue emitter via through‐space interactions (TSIs), resulting in a stable mixed light. Density functional theory calculation and mass spectrum further confirm that Arg can allow for the formation of strong hydrogen‐bonds with the ligand 2,4‐diaminotoluene of Cu NCs, and formation of TSIs‐based complexes with NMC. More importantly, pure white‐light emission (WLE) with Commission Internationale de L'Eclairagecoordination (0.30, 0.31) is observed by regulating the ratio between Arg and the interfacial ligand of NMC. The findings not only provide a new perspective for the construction of WLE emitters via interface modification chemistry but also open a window to gain insight into the mechanism of interface engineering. [ABSTRACT FROM AUTHOR]

Multi-view representation learning aims to capture comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning to different views in a pairwise manner, which is still scalable: view-specific noise is not filtered in learning view-shared representations; the fake negative pairs, where the negative terms are actually within the same class as the positive, and the real negative pairs are coequally treated; evenly measuring the similarities between terms might interfere with optimization. Importantly, few works study the theoretical framework of generalized self-supervised multi-view learning, especially for more than two views. To this end, we rethink the existing multi-view learning paradigm from the perspective of information theory and then propose a novel information theoretical framework for generalized multi-view learning. Guided by it, we build a multi-view coding method with a three-tier progressive architecture, namely Information theory-guided heuristic Progressive Multi-view Coding (IPMC). In the distribution-tier , IPMC aligns the distribution between views to reduce view-specific noise. In the set-tier , IPMC constructs self-adjusted contrasting pools, which are adaptively modified by a view filter. Lastly, in the instance-tier , we adopt a designed unified loss to learn representations and reduce the gradient interference. Theoretically and empirically, we demonstrate the superiority of IPMC over state-of-the-art methods. [ABSTRACT FROM AUTHOR]

An event logic graph is a kind of knowledge mapping technology for knowledge inference and simulation analysis, which takes events as the core and portrays the hierarchical system and logical evolution pattern between events. In order to apply it to further improve the accuracy of related studies, such as pedestrian flow evacuation, simulation model optimization and risk prediction. In this paper, we use social network resources, media resources and journal database resources to build our corpus and adopt the explicit event relationship extraction method based on syntactic dependency and the implicit event relationship extraction method based on BERT+Bi-LSTM+Attention+Softmax for the characteristics of explicit event relationship and implicit event relationship, respectively. This paper constructs a pedestrian flow evacuation matter mapping for three typical scenarios and discusses its application path. It is found that once a sound knowledge base of logical reasoning and event logic graph is established, both research on optimization of pedestrian flow evacuation simulation models and research on identification and assessment of pedestrian flow evacuation safety risks will receive excellent support. [ABSTRACT FROM AUTHOR]

Space vector modulation (SVM) schemes with leakage current mitigation capability for current‐source inverters (CSIs) in transformerless photovoltaic (PV) systems have not been well explored yet. In this study, the advantage of a special SVM scheme, called active zero‐state SVM (AZS‐SVM), on suppressing high‐order harmonics in the common‐mode voltage (CMV) is revealed and theoretically analysed, since the high‐frequency components in the CMV have decisive impacts on the generated leakage current. A five‐segment sequence is proposed for AZS‐SVM applied for CSIs. Both simulation and experiments are conducted on a (2.5 kW/208 V/6.94 A) grid‐connected three‐phase CSI, which validates the effectiveness of the designed AZS‐SVM to mitigate the CMV high‐order harmonics when compared to that by conventional SVM under different operating conditions. [ABSTRACT FROM AUTHOR]

Nonspecific lipid transfer proteins (LTPs) are small, cysteine‐rich proteins that play numerous functional roles in plant growth and development, including cutin wax formation, pollen tube adhesion, cell expansion, seed development, germination, and adaptation to changing environmental conditions. LTPs contain eight conserved cysteine residues and a hydrophobic cavity that provides a wide variety of lipid‐binding specificities. As members of the pathogenesis‐related protein 14 family (PR14), many LTPs inhibit fungal or bacterial growth, and act as positive regulators in plant disease resistance. Over the past decade, these essential immunity‐related roles of LTPs in plant immune processes have been documented in a growing body of literature. In this review, we summarize the roles of LTPs in plant–pathogen interactions, emphasizing the underlying molecular mechanisms in plant immune responses and specific LTP functions. [ABSTRACT FROM AUTHOR]

With the widespread use of magneto-sensitive elements, magnetic shields are an important part of electronic equipment, ultra-sensitive atomic sensors, and in basic physics experiments. Particularly in Spin-exchange relaxation-free (SERF) co-magnetometers, the magnetic shield is an important component for maintaining the SERF state. However, the inherent noise of magnetic shield materials is an important factor limiting the measurement sensitivity and accuracy of SERF co-magnetometers. In this paper, both amorphous and nanocrystalline materials were designed and applied as the innermost magnetic shield of an SERF co-magnetometer. Magnetic noise characteristics of different amorphous and nanocrystalline materials used as the internal magnetic shielding layer of the magnetic shielding system were analyzed. In addition, the effects on magnetic noise due to adding aluminum to amorphous and nanocrystalline materials were studied. The experimental results show that compared with an amorphous material, a nanocrystalline material as the inner magnetic shield layer can effectively reduce the magnetic noise and improve the sensitivity and precision of the rotation measurement. Nanocrystalline material is very promising for inner shield composition in SERF co-magnetometers. Furthermore, its ultra-thin structure and low cost have significant application value in the miniaturization of SERF co-magnetometers. [ABSTRACT FROM AUTHOR]

Fluid mechanics is an important area where deep learning produces excellent results and can bring about scientific innovation because of its high dimensionality, significant nonlinearity, and ability to process an enormous amount of data. Deep learning technology is currently being used to study fluid mechanics, and its application potential is gradually being demonstrated. We propose a novel multi-resolution convolutional interaction network (MCIN), a hierarchical forecast framework based on a convolutional neural network. This structure can capture temporal dependencies at multiple temporal resolutions to enhance the forecasting performance of the original time series. The high-dimensional data of the flow around a cylinder are projected into a low-dimensional subspace using a variational autoencoder (VAE) as a nonlinear order-reduction technique. Then, the data of the subspace are used as the input to MCIN to forecast future velocity fields. The proposed MCIN is compared to non-intrusive reduced-order models based on dynamic mode decomposition and long short-term memory, combined with a VAE. The results demonstrate that MCIN has superior stability to other models in forecasting the evolution of complicated fluid flows and has the potential to forecast a greater number of future outcomes. [ABSTRACT FROM AUTHOR]

The hydrogen balloon is widely used for wind sensing by tracking it with optical theodolites. The traditional theodolite observation (single- and double-theodolite) methods assume that the balloon is a perfect tracer of the background wind and it rises with a constant speed during the whole observation period, but these assumptions may not hold well in complex wind circumstances. In this paper, an accurate wind field retrieval method based on multi-theodolite measurement is proposed. The extended Kalman filter algorithm is used to filter the angle data observed by the theodolites in order to accurately estimate the trajectory of the balloon, and the motion equation is used to correct the velocity difference between the background wind and the balloon. As a result, not only the horizontal velocity but also the vertical velocity can be accurately retrieved by this method. Numerical simulation and field experiments show that the multi-theodolite observation method excels the traditional single-theodolite method, and the velocity errors can be reduced by even more than 40% in comparison with the single-theodolite method for complex wind cases. Significanace Statement: In the meteorological community, hydrogen balloon tracking is a widely used wind retrieval method, but the accuracy is limited, especially under complex wind conditions. In this paper, a new method based on tracking the hydrogen balloon with multi-theodolite is proposed, which uses the extended Kalman filter and the motion equation to get an accurate estimation of the balloon's velocity and fix the inertia effect of balloon, respectively. Simulation and field experiment show that the new method can reduce the velocity error by more than 40% compared with the traditional method. [ABSTRACT FROM AUTHOR]

Near-infrared (NIR) aggregation induced-emission luminogens (AIEgens) circumvent the noisome aggregation-caused quenching (ACQ) effect in physiological milieu, thus holding high promise for real-time and sensitive imaging of biomarkers in vivo. β-Galactosidase (β-Gal) is a biomarker for primary ovarian carcinoma, but current AIEgens for β-Gal sensing display emissions in the visible region and have not been applied in vivo. We herein propose an NIR AIEgen QM-TPA-Gal and applied it for imaging β-Gal activity in vitro and in ovarian tumor model. After being internalized by ovarian cancer cells (e.g. , SKOV3), the hydrophilic nonfluorescent QM-TPA-Gal undergoes hydrolyzation by β-Gal to yield hydrophobic QM-TPA-OH , which subsequently aggregates into nanoparticles to turn NIR fluorescence "on" through the AIE mechanism. In vitro experimental results indicate that QM-TPA-Gal has a sensitive and selective response to β-Gal with a limit of detection (LOD) of 0.21 U/mL. Molecular docking simulation confirms that QM-TPA-Gal has a good binding ability with β-Gal to allow efficient hydrolysis. Furthermore, QM-TPA-Gal is successfully applied for β-Gal imaging in SKOV3 cell and SKOV3-bearing living mouse models. It is anticipated that QM-TPA-Gal could be applied for early diagnosis of ovarian cancers or other β-Gal-associated diseases in near future. • A near-infrared AIEgen QM-TPA-Gal was designed and synthesized for the first time. • QM-TPA-Gal presented highly sensitive and selective response to β-Gal in vitro, with a limit of detection (LOD) of 0.21 U/mL. • QM-TPA-Gal was successfully applied for β-Gal imaging in vivo with superior sensitivity, specificity, and biosafety. [ABSTRACT FROM AUTHOR]

In the spin-exchange relaxation-free (SERF) comagnetometer, the atomic polarization gradient caused by light absorption can cause significant but unexpected nuclear spin transverse relaxation, which affects the system's accuracy and sensitivity. This paper proposes the SERF comagnetometer configuration based on optical compensation to suppress polarization gradient in the vapor cell. The influence of polarization gradient on the system's magnetic field suppression ability is analyzed by the state-space method. In addition, the atomic polarization distribution simulation and the performance testing between the traditional SERF comagnetometer and the proposed configuration are conducted. Compared to traditional configuration, the polarization gradient relaxation of the proposed configuration is effectively suppressed by 62%, the magnetic field suppression ability of the system is improved by 51%, and the rotation sensitivity is increased by 25.4%. This work investigates the influence of polarization gradient on system characteristics and proposes a comagnetometer configuration to suppress polarization gradient, enhancing the system's magnetic field suppression ability and improving sensitivity. The demonstration of the polarization gradient suppression method is of significance for improving the performance of other inertial measurement devices such as nuclear magnetic resonance gyroscopes. [Display omitted] • A uniform atomic comagnetometer based on optical compensation is proposed. • The influence of polarization gradient on the system is analyzed. • The atomic spatial distribution model of the proposed configuration is established. • The polarization gradient relaxation is suppressed by 62%. • A rapid polarization confirmation method is proposed for performance comparison. [ABSTRACT FROM AUTHOR]

A series of intricate and dynamic physiological healing processes are involved in the healing of skin wounds. Herein, a multifunctional hydrogel is firstly designed and constructed by L -arginine-grafted O -carboxymethyl chitosan (CMCA), catechol-modified oxidized hyaluronic acid (DOHA), and dopamine nanoparticles (pDA-NPs). pDA-NPs were loaded in hydrogel for inherently powerful antimicrobial properties and could be as a cross-linking agent to construct hydrogels. Raffinose (Raf) was further incorporated to obtain CMCA-DOHA-pDA2@Raf hydrogel for its function of modulating epidermal differentiation. The hydrogel has good physicochemical properties and could promote cell proliferation and migration, which shows superior hemostatic capabilities in animal models of hemorrhage. The hydrogel significantly promoted wound healing on rat skin defect models by upregulating VEGF and CD31 and decreasing IL-6 and TNF-α, stimulating neovascularization and collagen deposition in epithelial structures. This multifunctional hydrogel implies the potential to be a dynamic wound dressing. • A unique physicochemical double cross-linked hydrogel was successfully prepared. • This multifunctional hydrogel displayed excellent adhesion, self-healing, antimicrobial and hemostatic properties. • The multifunctional hydrogels significantly promoted dynamic wound healing. [ABSTRACT FROM AUTHOR]

When engaging in end-to-end graph representation learning with Graph Neural Networks (GNNs), the intricate causal relationships and rules inherent in graph data pose a formidable challenge for the model in accurately capturing authentic data relationships. A proposed mitigating strategy involves the direct integration of rules or relationships corresponding to the graph data into the model. However, within the domain of graph representation learning, the inherent complexity of graph data obstructs the derivation of a comprehensive causal structure that encapsulates universal rules or relationships governing the entire dataset. Instead, only specialized diminutive causal structures, delineating specific causal relationships within constrained subsets of graph data, emerge as discernible. Motivated by empirical insights, it is observed that GNN models exhibit a tendency to converge towards such specialized causal structures during the training process. Consequently, we posit that the introduction of these specific causal structures is advantageous for the training of GNN models. Building upon this proposition, we introduce a novel method that enables GNN models to glean insights from these specialized diminutive causal structures, thereby enhancing overall performance. Our method specifically extracts causal knowledge from the model representation of these diminutive causal structures and incorporates interchange intervention to optimize the learning process. Theoretical analysis serves to corroborate the efficacy of our proposed method. Furthermore, empirical experiments consistently demonstrate significant performance improvements across diverse datasets. [Display omitted] • Discovered that introducing diminutive causal structures can enhance performance. • A novel method for introducing diminutive causal structures into GNN models. • Thorough theoretical analysis and substantiation regarding the studied problem. • Comprehensive validation of the proposed method through multiple experiments. [ABSTRACT FROM AUTHOR]

Conventional platooning control algorithms that improve traffic flow require complex computations and are not well-suited for real-time operations. Moreover, prior research has primarily concentrated on idealized settings, such as isolated intersections or corridors that solely consist of fully connected automated vehicles (CAVs), making it challenging to be applied to real-world traffic systems. To overcome these challenges, this paper aims to design an innovative learning framework based on arrival timing vectors (ATVs) and traffic signal synchronization for platooning control that can improve traffic throughput and reduce fuel consumption through four basic platoon maneuvers: split, acceleration, deceleration, and no-op. We integrate reinforcement learning (RL) with neural networks (NNs) to model non-linear relationships between inputs and outputs for a complex application. The utilization of ATVs as inputs in our proposed framework furnishes an agent with ample information to facilitate a better comprehension of the actions that need to be taken for particular states. Additionally, our proposed DRL-based platooning control collaborates with traffic signal synchronization across adjacent intersections to optimize traffic efficiency in a further step. Numerical experiments have been conducted on both corridor and network scenarios, demonstrating the positive effects of synchronization and DRL-based platooning control on average delay and fuel consumption. Various DRL-based methods have been compared to demonstrate the fast convergence and improved mobility of our proposed algorithm. Furthermore, our algorithm shows robust performance in mixed-traffic environments of CAV and human-driven vehicles. • A new DRL framework using deep learning to manipulate vehicle platoon behaviors. • The approach integrates platooning control with traffic signal synchronization. • A comparison shows the 2DSARSA algorithm outperforms other popular DRL methods. • Case studies showed DRL-based control reduce delay and fuel use in different networks. [ABSTRACT FROM AUTHOR]

N-glycosylation, an important post-translational modification of proteins in all eukaryotes, has been clearly shown to be involved in numerous diseases in mammalian systems. In contrast, little is known regarding the role of protein N-glycosylation in plant defensive responses to pathogen infection. We identified, for the first time, glycoproteins related to systemic acquired resistance (SAR) in an Arabidopsis thaliana model, using a glycoproteomics platform based on high-resolution mass spectrometry. 407 glycosylation sites corresponding to 378 glycopeptides and 273 unique glycoproteins were identified. 65 significantly changed glycoproteins with 80 N-glycosylation sites were detected in systemic leaves of SAR-induced plants, including numerous GDSL-like lipases, thioglucoside glucohydrolases, kinases, and glycosidases. Functional enrichment analysis revealed that significantly changed glycoproteins were involved mainly in N-glycan biosynthesis and degradation, phenylpropanoid biosynthesis, cutin and wax biosynthesis, and plant-pathogen interactions. Comparative analysis of glycoproteomics and proteomics data indicated that glycoproteomics analysis is an efficient method for screening proteins associated with SAR. The present findings clarify glycosylation status and sites of A. thaliana proteins, and will facilitate further research on roles of glycoproteins in SAR induction. [ABSTRACT FROM AUTHOR]

The uniform and linear wind models have been commonly used for wind field retrieval in meteorological community. However, the accuracy and robustness of the retrieval results can be quite unsatisfactory due to the mismatch between these models and the real wind distribution, especially under complex wind conditions. In this article, a nonlinear model based on high-order Taylor expansion is proposed to deal with this limitation, and the combination of ridge regression and decomposition-iteration process (denoted as Ridge-DI method) is further introduced to solve the model with high accuracy and robustness. A case study on simulation and field experiment shows that the proposed method with the third-order Taylor expansion can reduce the mean root-mean-square errors (RMSEs) of the retrieved velocities by more than 16.84% in comparison with traditional methods. [ABSTRACT FROM AUTHOR]

As an emergent picornavirus pathogenic to pigs, Senecavirus A (SVA) can replicate in pig kidneys and proliferates well in porcine kidney epithelial PK-15 cells. Here, tandem mass tags (TMT) labeling coupled with liquid chromatography–tandem mass spectrometry (LC-MS/MS) was used to analyze the proteome dynamic changes in PK-15 cells during SVA infection. In total, 314, 697 and 426 upregulated differentially expressed proteins (DEPs) and 131, 263 and 342 downregulated DEPs were identified at 12, 24 and 36 hpi, respectively. After ensuring reliability of the proteomic data by quantitative PCR and Western blot testing of five randomly selected DEPs, Mx1, eIF4E, G6PD, TOP1 and PGAM1, all the DEPs were subjected to multiple bioinformatics analyses, including GO, COG, KEGG and STRING. The results reveal that the DEPs were mainly involved in host innate and adaptive immune responses in the early and middle stages of SVA infection, while the DEPs mainly participated in various metabolic processes in the late stage of infection. Finally, we demonstrated that Mx1 protein exerts antiviral activity against SVA by interacting with VP1 and VP2 proteins dependent on its GTPase, oligomerization and interaction activities, while Mx1 interacts with VP3 only depending on its oligomerization activity. Collectively, our study provides valuable clues for further investigation of SVA pathogenesis. [ABSTRACT FROM AUTHOR]

Antibiotics usage is a double-edged sword among the production promotion and environmental aggravation of aquaculture system. In this study, the effects of sulfadiazine addition on algal-bacterial-based aquaponic (AA) system were thoroughly investigated. Results showed that sulfadiazine addition increased the nitrogen (N) and carbon (C) recovery of AA system by 1.3 times and 2.9 times, respectively. Meanwhile, the global warming potential was increased by 63% due to aggravated nitrous oxide (N2O) emission. This was mainly because sulfadiazine increased the abundance of nirS genes and decreased the abundance of nosZ genes, which subsequently led to higher N2O accumulation. Furthermore, resistance gene (sul-1, sul-2, and intI-1) abundance in the treatment group was an order higher than that of the control group, which would give rise to the environmental risk for agroecological system. Key Points: • Sulfadiazine addition increased NUE at expense of aggravated GHG emissions. • Sulfadiazine disrupted the balance between the abundance of nirS and nosZ genes. • Sulfadiazine addition increased the resistance gene abundance of AA system. [ABSTRACT FROM AUTHOR]

To study the behavior of square concrete-filled CFRP (carbon fiber polymer) steel tubular under bending-torsional load, nine square section concrete-filled CFRP steel tubular specimens are designed. The T-θ curve and failure mode of square concrete-filled CFRP steel tubular are studied under a bending-torsional load. Based on the test results, a finite element modeling method is proposed by using the finite element software ABAQUS, and the simulation results are compared with the experimental results. The results show that the simulation is in good agreement with the experimental results. On the basis of verifying the reliability of the model, the whole stress process and parameter analysis of the component are studied, and the calculation expression of bearing capacity of square concrete-filled CFRP steel tubular under bending-torsion load is proposed. The predicted specimen-bearing capacity of the proposed calculation expression of the bearing capacity of square concrete-filled CFRP steel tubular under bending-torsion load is basically consistent with the test results. [ABSTRACT FROM AUTHOR]

To protect the security of data outsourced to the cloud, the tampers detection and recovery for outsourced image have aroused the concern of people. A secure tampering detection and lossless recovery for medical images (MI) using permutation ordered binary (POB) number system is proposed. In the proposed scheme, the region of interest (ROI) of MI is first extracted, and then, ROI is divided into some no-overlapping blocks, and image encoding is conducted on these blocks based on the better compression performance of JPEG-LS for medical image. After that, the generated compression data by all the blocks are divided into high 4-bit and low 4-bit planes, and shuffling and combination are used to generate two plane images. Owing to the substantial redundancies space in the compressed data, the data of each plane are spread to the size of the original image. Lastly, authentication data of two bits is obtained for every pixel and inserted into the pixel itself within the each plane, and the corresponding 10-bit data is transformed into the POB value of 8-bit. Furthermore, encryption is implemented on the above image to produce two shares which can be outsourced to the cloud server. The users can detect tampered part and recover original image when they down load the shares from the cloud. Extensive experiments on some ordinary medical image and COVID-19 image datasets show that the proposed approach can locate the tampered parts within the MI, and the original MI can be recovered without any loss even if one of the shares are totally destroyed, or two shares are tampered at the ration not more than 50%. Some comparisons and analysis are given to show the better performance of the scheme. [ABSTRACT FROM AUTHOR]

Quantum Key Agreement (QKA) is an important branch of quantum cryptography, which uses the characteristics of quantum entanglement to ensure security of the key. The multi-party quantum key agreement requires all communicants to exert the same influence on the result of the protocol, and the key cannot be determined individually. Most of the MQKA protocols that have been proposed are based on a single particle or Bell state, where each particle corresponds to only one classical bit. This paper proposes a multi-party QKA protocol based on the GHZ-like state and χ+ state, which can realize that each particle corresponds to 1.5 classical bits. The security of the protocol is guaranteed by the uncertainty of the measurement results of entanglement swapping. The results show that the proposed multi-party QKA protocol is secure, fair, and efficient, which can be implemented with existing physical technology. In addition, it is simpler and less computational in the proposed MQKA protocol. [ABSTRACT FROM AUTHOR]

Ginkgo biloba extract (GBE) had several effects on the human body as one of the widely used phytopharmaceuticals, but it had no application in microbial enhancement in the environmental field. The study focused on the impact of GBE on denitrification specifically under neutral conditions. At the identified optimal addition ratio of 2% (v/v), the system exhibited a noteworthy increase in nitrate reduction rate (NRR) by 56.34%, elevating from 0.71 to 1.11 mg-N/(L·h). Moreover, the extraction of microbial extracellular polymeric substance (EPS) at this ratio revealed changes in the composition of EPS, the electron exchange capacity (EEC) was enhanced from 87.16 to 140.4 μmol/(g C), and the transfer impedance was reduced within the EPS. The flavin, fulvic acid (FA), and humic acid (HA) provided a π-electron conjugated structure for the denitrification system, enhancing extracellular electron transfer (EET) by stimulating carbon source metabolism. GBE also improved electron transfer system activity (ETSA) from 0.025 to 0.071 μL O 2 /(g·min·prot) and the content of NADH enhanced by 22.90% while significantly reducing the activation energy (E a) by 85.6% in the denitrification process. The synergy of improving both intracellular and extracellular electron transfer, along with the reduction of E a , notably amplified the initiation and reduction rates of the denitrification process. Additionally, GBE demonstrated suitability for denitrification across various pH levels, enhancing microbial resilience in alkaline conditions and promoting survival and proliferation. Overall, these findings open the door to potential applications of GBE as a natural additive in the environmental field to improve the efficiency of denitrification processes, which are essential for nitrogen removal in various environmental contexts. [Display omitted] • GBE enhances denitrification efficiency and reduces microbial mortality. • GBE mitigates systemic impedance thereby expedites electron transfer. • Quercetin plays pivotal roles in augmenting the denitrification process facilitated. • GBE substantially decreases the activation energy required for bioreactions. [ABSTRACT FROM AUTHOR]

Rationally designing high-efficient g-C 3 N 4 based photocatalysts still remains a big challenge. Herein, Ni 7 S 6 decorated K-doped g-C 3 N 4 /graphene oxide photocatalyst was synthesized. Interestingly, amorphous conductive carbon black and urea are simultaneously transferred to graphene oxide and K-doped g-C 3 N 4 , which achieves in-situ coupled K-g-C 3 N 4 /graphene oxide composite. The in-situ fabricated graphene oxide acts as a charge transfer substrate for the rapid photocarriers migration. Ni 7 S 6 forms Schottky heterojunction with K-g-C 3 N 4 photocatalyst, promoting photocarriers separation. The Ni 7 S 6 /K-g-C 3 N 4 /graphene oxide composite achieves a visible light hydrogen production rate of 487.59 μmol·g−1·h−1, which is about 7.5 times higher than that of K-g-C 3 N 4 (65.4 μmol·g−1·h−1). This work provides a novel strategy for preparing high-efficient g-C 3 N 4 based photocatalysts. [Display omitted] • Graphitic carbon nitride modified with graphene oxide and Ni 7 S 6 was prepared. • Graphitization and K-g-C 3 N 4 formation simultaneously took place forming tightly coupled interface. • Ni 7 S 6 with K-g-C 3 N 4 formed Schottky junction to inhibit the recombination of photocarriers. • The composite shows an excellent photocatalytic activity of 487.59 μmol·g−1·h−1 and enhanced stability. [ABSTRACT FROM AUTHOR]

Real-time driving distraction detection has garnered significant attention due to its potential to build various driving safety protections such as distraction warnings and driver assistance systems. Recent studies have focused on the development of neural networks for vision-based detection, though achieving a balance between performance and efficiency has proven challenging. In this paper, we propose a novel constrained attention (CA) mechanism for real-time driver distraction detection, which aims to achieve better performance meanwhile ensuring the computation efficiency. Specifically, we conduct some case studies by generating class activation maps to check the model attention, and three potential factors affecting performance are mined, which are ambiguous attention signal, excessive attention region, and similar attention between different classes. Two regularization terms are designed to optimize the three obstacles. Firstly, a concentrative regularization is introduced to limit the size of the attention region, meanwhile, pixels in the region have clear attention degrees. Secondly, an orthogonal regularization is proposed to optimize the attention of different classes to be discriminative. To further inspiring the model, we design an intersample constraint, which optimizes the attention of images with the same ground truth to be similar. Experiments are conducted on two driver distraction detection datasets, and the experimental results showed that our CA mechanism can bring significant performance improvement. More importantly, there will be no additional computational burden when the trained model is deployed in actual scenarios. Codes are released at https://github.com/gaohangcodes/CAN4DDD. [ABSTRACT FROM AUTHOR]

The importance of the uncertainty quantification in ship maneuverability prediction is expounded. An efficient method for the uncertainty quantification problem, the Non-Intrusive Polynomial Chaos (NIPC) method, is introduced. A 3-DOF MMG model is adopted to carry out simulations of 35° turning circle tests and 10°/10° zig-zag tests for a KCS container ship model. The effects of the uncertainty of the hull-related hydrodynamic derivatives in the MMG model on the maneuverability parameters, i.e., the advance, the tactical diameter, the initial turning time and the overshoot angles are analyzed quantitatively, and the sensitivities of these parameters to the hydrodynamic derivatives are determined. The results are compared with those obtained by the Monte Carlo (MC) method. It is shown that the NIPC method is much better than the MC method in terms of the convergence with respect to the number of samples, and the computation accuracy of the NIPC method is higher than that of the MC method under the same number of samples; the considered maneuverability parameters are most sensitive to the uncertainty of the yaw moment related hydrodynamic derivatives, and least sensitive to that of the longitudinal force related ones. The feasibility of the NIPC method in the uncertainty quantification of ship maneuverability prediction is proved, which provides a novel approach to analyze the influence of the accuracy of the hydrodynamic derivatives on ship maneuverability prediction. [ABSTRACT FROM AUTHOR]

Acrydite‐modified DNA is the most frequently used reagent to prepare DNA‐functionalized hydrogels. Herein, we show that unmodified penta‐adenine (A5) can reach up to 75 % conjugation efficiency in 8 h under a freezing polymerization condition in polyacrylamide hydrogels. DNA incorporation efficiency was reduced by forming duplex or other folded structures and by removing the freezing condition. By designing diblock DNA containing an A5 block, various functional DNA sequences were attached. Such hydrogels were designed for ultrasensitive DNA hybridization and Hg2+ detection, with detection limits of 50 pM and 10 nM, respectively, demonstrating the feasibility of using unmodified DNA to replace acrydite‐DNA. The same method worked for both gel nanoparticles and monoliths. This work revealed interesting reaction products by exploiting freezing and has provided a cost‐effective way to attach DNA to hydrogels. [ABSTRACT FROM AUTHOR]

Acrydite‐modified DNA is the most frequently used reagent to prepare DNA‐functionalized hydrogels. Herein, we show that unmodified penta‐adenine (A5) can reach up to 75 % conjugation efficiency in 8 h under a freezing polymerization condition in polyacrylamide hydrogels. DNA incorporation efficiency was reduced by forming duplex or other folded structures and by removing the freezing condition. By designing diblock DNA containing an A5 block, various functional DNA sequences were attached. Such hydrogels were designed for ultrasensitive DNA hybridization and Hg2+ detection, with detection limits of 50 pM and 10 nM, respectively, demonstrating the feasibility of using unmodified DNA to replace acrydite‐DNA. The same method worked for both gel nanoparticles and monoliths. This work revealed interesting reaction products by exploiting freezing and has provided a cost‐effective way to attach DNA to hydrogels. [ABSTRACT FROM AUTHOR]

Aims/Introduction: The molecular mechanisms of diabetic nephropathy (DN) are poorly identified. However, the advantage of an increasing amount on microarray data of diabetic nephropathy intrigued us to explore the mechanisms based on bioinformatics prediction for diabetic nephropathy. Materials and Methods: Bioinformatics analysis was conducted to screen the hub genes associated with diabetic nephropathy. The average human renal tubular epithelial cells were exposed to high glucose (HG) to generate an in vitro cell model. In addition, a mouse model of diabetic nephropathy was established using a high‐fat diet and streptozotocin injection. Finally, the shRNA targeting immunoglobulin heavy constant gamma 1 (IGHG1) was introduced in vitro and in vivo to illustrate its effect on downstream factors and on the development diabetic nephropathy. Results: Bioinformatics analysis revealed that IGHG1, TRIM11 (tripartite motif protein 11), and TonEBP are highly expressed in diabetic nephropathy. In vitro cell experiments demonstrated that IGHG1 positively regulates the expression of TRIM11 and TonEBP (tonicity‐responsive enhancer binding protein) in HK2 cells treated with high glucose. Furthermore, TRIM11 upregulates the expression of TonEBP through activation of the MEK/ERK (mitogen‐activated protein kinase/extracellular signal‐regulated kinase) signaling pathway in HK2 cells treated with high glucose. In vivo, animal experiments further confirmed that silencing IGHG1 could prevent the occurrence and development of diabetic nephropathy. Conclusion: The silencing of IGHG1 alleviated diabetic nephropathy by inhibiting the TRIM11/MEK/ERK axis and by downregulating TonEBP. [ABSTRACT FROM AUTHOR]

Background: Retinoids are promising agents in the treatment of different types of neoplasia including estrogen receptor-positive breast cancers, whereas refractoriness/low sensitivity is observed in triple-negative breast cancer (TNBC) subtype. However, the reason for these diverse retinoid-sensitivity remains elusive. Methods: Determinants of retinoid sensitivity were investigated using immunohistochemistry of primary patient samples, and identified retinoic acid receptor α (RARα) as a putative factor. The anti-tumor activity of hypo-phosphorylated RARα was investigated in TNBC cell models and a xenograft mouse model. Next, miRNA sequencing analysis was performed to identify the target miRNA of RARα, and luciferase reporter was used to confirm the direct target gene of miR-3074-5p. Results: We discovered that serine-77 residue of RARα was constantly phosphorylated, which correlated with TNBC's resistance to retinoids. Overexpression of a phosphorylation-defective mutant RARαS77A mimicked activated RARα and repressed TNBC cell progression both in vitro and in vivo, via activating cell cycle arrest, apoptosis, and cytotoxic autophagy, independent of RARα agonists. We further revealed that the anti-tumor action of RARαS77A was, at least in part, mediated by the up-regulation of miR-3074-5p, which directly targeted DHRS3, a reductase negatively associated with TNBC patient survival. Our results suggest that the inhibition of RARαS77 phosphorylation by either expressing RARαS77A or inhibiting RARα's phosphokinase CDK7, can bypass RA stimuli to transactivate tumor-suppressive miR-3074-5p and reduce oncogenic DHRS3, thus overcoming the RA-resistance of TNBC. Conclusion: The novel regulatory network, involving RARαS77 phosphorylation, miR-3074-5p, and DHRS3, emerges as a new target for TNBC treatment. [ABSTRACT FROM AUTHOR]

Acrydite‐modified DNA is the most frequently used reagent to prepare DNA‐functionalized hydrogels. Herein, we show that unmodified penta‐adenine (A5) can reach up to 75 % conjugation efficiency in 8 h under a freezing polymerization condition in polyacrylamide hydrogels. DNA incorporation efficiency was reduced by forming duplex or other folded structures and by removing the freezing condition. By designing diblock DNA containing an A5 block, various functional DNA sequences were attached. Such hydrogels were designed for ultrasensitive DNA hybridization and Hg2+ detection, with detection limits of 50 pM and 10 nM, respectively, demonstrating the feasibility of using unmodified DNA to replace acrydite‐DNA. The same method worked for both gel nanoparticles and monoliths. This work revealed interesting reaction products by exploiting freezing and has provided a cost‐effective way to attach DNA to hydrogels. [ABSTRACT FROM AUTHOR]

Abrasive flow machining (AFM) process, as a widely known technique for finishing internal surfaces of complex parts, can significantly improve the performance and reliability of components in numerous industries. Prediction of material removal rate (MRR) is a vital task in AFM process because it significantly affects the efficiency and cost-effectiveness of the process. In-depth studies about the influence of input parameters on material removal in AFM process, however, are limited. In this paper, the mechanism of material removal was investigated, and a MRR modelling was then established in which viscoelastic extrusion modelling with wall slip conditions was employed in AFM process. A novel fixture with gradient shear flow channel was designed. MRR obtained by simulations and experiment showed a reasonable agreement. Finally, parameters, including abrasive media pressure, velocity and shape geometry of flow channel, were identified as key factors affecting MRR in AFM process. Established computational fluid dynamics (CFD) analysis and MRR modelling can be a powerful tool to determine MRR in future AFM process. [Display omitted] • Viscoelastic MRR modelling was established based on mechanism of indentation and wall slip interactions. • Novel designed fixture formed various values of media pressure, velocity and shear rate in one single extrusion. • Experiments and simulation saw well a agreement in abrasive media extrusion profiles with an error of below 10 %. • Predicted MRR model and experiments both proved the most influential factor was pressure, followed by velocity and shear rate. [ABSTRACT FROM AUTHOR]

The demand for transporting coreactant to emitter and short lifetime of the radicals in electrochemiluminescence (ECL) emission inhibit greatly its application in cytosensing and microscopic imaging. Herein we designed a dual intramolecular electron transfer strategy and tertiary amine conjugated polymer dots (TEA‐Pdots) to develop a coreactant‐embedded ECL mechanism and microimaging system. The TEA‐Pdots could produce ECL emission at +1.2 V without need of coreactant in test solution. The superstructure and intramolecular electron transfer led to unprecedented ECL strength, which was 132 and 45 times stronger than those from the mixture of Pdots with TEA at equivalent and 62.5 times higher amounts, respectively. The ECL efficiency was even higher than that of typical [Ru(bpy)3]2+ system. Therefore, this strategy and coreactant‐embedded ECL system could be used for in situ ECL microimaging of membrane protein on single living cells without additional permeable treatment for transporting coreactant. The feasibility and validity were demonstrated by evaluating the specific protein expression on cell surface. This work opens new avenues for ECL applications in single cell analysis and dynamic study of biological events. [ABSTRACT FROM AUTHOR]

The demand for transporting coreactant to emitter and short lifetime of the radicals in electrochemiluminescence (ECL) emission inhibit greatly its application in cytosensing and microscopic imaging. Herein we designed a dual intramolecular electron transfer strategy and tertiary amine conjugated polymer dots (TEA‐Pdots) to develop a coreactant‐embedded ECL mechanism and microimaging system. The TEA‐Pdots could produce ECL emission at +1.2 V without need of coreactant in test solution. The superstructure and intramolecular electron transfer led to unprecedented ECL strength, which was 132 and 45 times stronger than those from the mixture of Pdots with TEA at equivalent and 62.5 times higher amounts, respectively. The ECL efficiency was even higher than that of typical [Ru(bpy)3]2+ system. Therefore, this strategy and coreactant‐embedded ECL system could be used for in situ ECL microimaging of membrane protein on single living cells without additional permeable treatment for transporting coreactant. The feasibility and validity were demonstrated by evaluating the specific protein expression on cell surface. This work opens new avenues for ECL applications in single cell analysis and dynamic study of biological events. [ABSTRACT FROM AUTHOR]

Model predictive control is an effective approach to achieve high performance on electric motor drives. In this study, a two‐vector based low‐complexity model predictive flux control (TVLC‐MPFC) is proposed and introduced for low power current‐source inverter (CSI)‐fed induction motor (IM) drive. In contrast to conventional two‐vector based model predictive flux control (TV‐MPFC), TVLC‐MPFC is a more simplified scheme with a lower calculation burden, which eliminates the requirement on the iteration procedures to obtain the results of the optimal current vector combination with optimal dwell time. Moreover, since TVLC‐MPFC avoids the possibility of selecting the wrong vector combination in some cases, which would happen with conventional TV‐MPFC, it presents better output performance than TV‐MPFC. The robustness of TVLC‐MPFC under parameter uncertainty is discussed as well. Experimental tests are carried out on a low power CSI‐fed IM drive (5 kW/208 V/14.3 A) and verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

A single crystal of potassium dihydrogen phosphate (KH 2 PO 4 , KDP), which possesses unique excellent non-linear electro-optical properties, is currently the only material suitable for electro-optic switches and high power laser-frequency conversion applications in laser-induced inertial confinement fusion. However, KDP crystals are difficult to produce because of their inherent softness, brittleness, and water-solubility, as well as their strong anisotropy and temperature sensitivity. Obtaining high-quality near-lossless KDP elements is an issue that should be solved urgently. In this study, an ultra-precision numerical control polishing method based on the water dissolution principle was introduced to achieve a controllable material removal. A small polishing tool was used to process a large KDP surface, and an accurate tool influence functions is required for deterministic fabrication of KDP surface. In order to quantify the influence of critical parameters (e.g. , polishing speed, polishing pressure, water content, and directions of revolution and rotation) on material removal rate distribution, a tool influence function model was established based on the Preston equation. The model was then modified based on experiments, and its accuracy was verified. This modified model lays the foundation for ultra-precision water dissolution polishing of large KDP crystals. A very smoothed surface with high surface accuracy (peak-to-valley value below 0.4 λ) and low surface roughness (Ra 1.598 nm) could indeed be obtained by using the model. This research is also applicable to the polishing of other water-soluble materials. • A modified TIF model is proposed to quantify the influence of critical parameters on material removal rate distribution. • Excellent correlations between the proposed TIF model and the experiments are obtained. • A very smoothed KDP surface with high surface accuracy and low surface roughness was obtained. [ABSTRACT FROM AUTHOR]

Aqueous zinc-ion batteries (AZIBs) have been getting lots of attention in the field of large scale energy storage owing to their low cost, large capacity and excellent safety. However, Zn anodes have serious dendritic growth and corrosion hydrogen evolution issues, which hinder their further application. Herein, a simple drop-coating technique was used to build a thin sulfate poly(ether ketone) (SPEEK) solid-electrolyte interphase (SEI) on the surface of the Zn anode to address these issues. The sulfonated group (−SO3−） in SPEEK can provide rich coordination sites for Zn2+, controlling the uniform deposition of Zn2+. Therefore, the polymer SEI can block electrolytes and homogenize the Zn2+ flux, resulting that the modified Zn (SPEEK@Zn) anode could effectively limit the formation of dendrites and side reactions. At a current density of 0.5 mA cm−2, SPEEK@Zn electrodes can maintain an ultra-long plating/stripping cycle life of 1000 h. Full batteries based on SPEEK@Zn have more superior cycle stability than the bare ones. This approach offers a straightforward and scalable remedy for high-performance Zn anode batteries. [ABSTRACT FROM AUTHOR]

In this paper, we study the global null controllability of nonlinear parabolic integro-differential equations arising in reactor dynamics with internal distributed control. Unlike the known results for nonlinear parabolic equations, controllability is analyzed in the frame of strong solutions. The result implies the nonlinear growth of the system with memory which is null controllable can be higher than that of classical parabolic equations. This phenomenon is caused by the memory effects. [ABSTRACT FROM AUTHOR]