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This study evaluates the application of supercritical carbon dioxide chelation extraction technology for treating heavy metal ions (Zn2+ and Cr3+) in drilling fluid waste. Through a combination of experimental and molecular dynamics simulation methods, the influence of extraction parameters (temperature, pressure, duration, and chelating agents) on the extraction efficiency are investigated. Findings show that increased duration and pressure significantly improve extraction efficiency, while temperature has a complex effect, initially increasing efficiency but plateauing and slightly decreasing at higher temperatures. The optimum extraction condition with pressure of 220 bar, temperature 348.15 K and an extraction duration of 70 min using ethylene diamine tetraacetic acid (EDTA) as the chelating agent has been determined. Importantly, molecular simulation analysis revealed that citric acid outperforms EDTA in terms of Zn2+ and Cr3+ aggregation by forming larger aggregates with greater numbers of molecules while reducing overall aggregate count. Furthermore, optimization of extraction pressure in the EDTA system shows potential benefits. These results suggest that supercritical carbon dioxide chelation extraction technology has strong potential for environmentally friendly and reliable waste management in the drilling industry. This study represents a significant step forward in developing sustainable solutions for heavy metal removal from drilling fluid waste.

The aim of this study is to optimize the extraction process of oat saponins (Os) and to evaluate their antioxidant potential. Single factor experiment, response surface optimization design, and orthogonal test were employed to optimize the process of ultrasonic-assisted extraction of Os, and the optimal extraction conditions were as followed: ethanol volume fraction of 80 %, material-solvent ratio of 1:14, ultrasonic power of 400 W, ultrasonic time of 25 min, extraction temperature of 60℃, extraction time of 180 min, and the extraction rate of Os was 0.317 %±0.105 %. Using the method, the crude extract of Os was prepared and its abilities of scavenging radicals in vitro and inhibiting protein oxidation in pork were determined, with ascorbic acid (Vc) as the control. Results revealed that the scavenging ability of Os against DPPH radical, hydroxyl radical (·OH) and superoxide anion (O2–) increased with the concentration of Os. Interestingly, the scavenging abilities of Os against DPPH and O2– were far lower than that of Vc, but its scavenging ability against ·OH was very close to that of Vc, reaching 84.59 % and 96.33 %, respectively. Furthermore, the experiments of pork storage and Fenton oxidation system showed that Os with 0.09–0.72 mg/mL could reduce the production of carbonyl (8.49 %-50.05 %) and the oxidation of total sulfhydryl (1.29 %-25.86 %), and effectively inhibit the oxidation of protein in pork by 7.82 %–22.53 %. The results of this study will provide a theoretical basis for the application of oat saponins as a natural anti-protein oxidant in meat processing and storage.

Summary: Due to the higher and more rapid consumption of carbohydrates by cancer cells compared to normal cells, carbohydrates can be effectively employed as a targeted therapeutic strategy for tumor treatment. Here, we present a protocol for synthesizing sequence-controlled glycooligomers using both solution-phase and solid-phase systems. We outline detailed procedures for evaluating the safety and tumor-targeting properties of the sequence-controlled glycooligomers in vivo.For complete details on the use and execution of this protocol, please refer to Chen et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Recombinant keratins possess strong hemostatic and wound healing properties but suffer from poor water solubility that restricts their bioactivities in biomedical applications. Herein, we report the rational design and synthesis of water‐soluble keratins using a simple methodology named the QTY code. In vitro biophysical analyses and molecular dynamic simulation demonstrated a 200‐fold increase in the water solubility of QTY variant keratins without apparent structural changes compared to native proteins. Homotypic self‐assembly was observed for the first time in recombinant keratins in an aqueous environment, without urea and after QTY modification. Cell and animal experiments showed the in situ gel‐forming capability of QTY variant keratins with superior hemostatic and wound healing activities at the wound sites compared to native recombinant keratins. Our work not only presented a simple and feasible pathway to produce large amounts of water‐soluble keratins using QTY modification but also validated the enhanced self‐assembly, hemostasis, and wound healing properties of these novel keratin species that may open up new venues for biomedical applications.

Music emotion recognition is becoming an important research direction due to its great significance for music information retrieval, music recommendation, and so on. In the task of music emotion recognition, the key to achieving accurate emotion recognition lies in how to extract the affect-salient features fully. In this paper, we propose an end-to-end spatial-temporal feature extraction method named FFA-BiGRU for music emotion classification. Taking the log Mel-spectrogram of music audio as the input, this method employs an attention-based convolutional residual module named FFA, which serves as a spatial feature learning module to obtain multi-scale spatial features. In the FFA module, three group architecture blocks extract multi-level spatial features, each of which consists of a stack of multiple channel-spatial attention-based residual blocks. Then, the output features from FFA are fed into the bidirectional gated recurrent units (BiGRU) module to capture the temporal features of music further. In order to make full use of the extracted spatial and temporal features, the output feature maps of FFA and those of the BiGRU are concatenated in the channel dimension. Finally, the concatenated features are passed through fully connected layers to predict the emotion classification results. The experimental results of the EMOPIA dataset show that the proposed model achieves better classification accuracy than the existing baselines. Meanwhile, the ablation experiments also demonstrate the effectiveness of each part of the proposed method.

In order to investigate the contact characteristics of the mechanical parts of the brewing robot with wine lees particles, it is essential to calibrate the parameters of the discrete elemental model of wine lees particles. This paper proposes a method based on tests of the angle of repose. The simulation test is conducted to establish a regression model and combined with physical tests to find optimization. The contact model used in simulation modeling is Hertz-Mindlin with Johnson-Kendall-Roberts. Not all discrete element model parameters of wine lees particles have a significant impact on the angle of repose, so screening through Plackett-Burman Design is performed. The results indicate that the restitution coefficient between wine lees particles and restitution coefficient between wine lees particle and steel plate have a significant impact on angle of repose. Additionally, another parameter that is difficult to obtain, namely surface energy (JKR), also plays a crucial role. The optimal value interval for these three parameters is determined by the steepest ascent test, and a linear regression model for angle of repose is built through Box-Behnken Design. The optimal values obtained are as follows: restitution coefficient between wine lees particles—0.603; restitution coefficient between wine lees particle and steel plate—0.595; JKR—0.083. Finally, in order to verify the accuracy of calibrated parameters, simulation verification tests are carried out which show that there is only a relative error rate at 0.18% between simulated angle of repose and actual angle of repose, indicating that accurate calibration parameters were achieved. This study can provide reference for selecting discrete element model parameters for wine lees particles in future research endeavors.

The objective of this paper is to discuss the influence of geometric parameters on the performance of the rotational hydrodynamic cavitation reactor (RHCR) using numerical method. The novel RHCR is implemented by modifying a centrifugal impeller into a new one using the annular slit constriction (ASC) with circumferentially distributed blind holes. The cavitation intensity and cavitation generation rate are selected to evaluate the cavitation performance, the head is used to assess conveying performance, and the entropy generation theory is used to evaluate the energy loss in the impeller. The effect of the axial width, radial length and radial position of the ASC on the cavitating flow of the RHCR is investigated by CFD method. The results indicate that three patterns of cavitation are induced in the RHCR, including separation cavitation, vortex cavitation and shear cavitation. The axial width, radial length and radial position of the ASC are the important geometric parameter that affect the performance of the RHCR. A small width is superior to a large width in terms of cavitation performance, although the conveying performance suffers as a result. The energy loss in the impeller initially increases and then decreases as the width decreases. Both a reduction in radial length and radial position leads to higher cavitation and conveying capacity, accompanying slight increase in energy loss. Compared to the original model, the RHCR with an axial width of 3 mm, a radial length of 17 mm, and a radial position of 0.541 achieves the highest performance.

Liver fibrosis is a fundamental pathological alteration observed in individuals with Wilson disease. Quercetin (Que) has shown potential in inhibiting fibrosis in various diseases. However, the precise mechanism by which Que alleviates liver fibrosis in Wilson disease remains unclear. The present study aimed to investigate the potential role of Que in liver fibrosis of Wilson disease using male Toxic Milk (TX) mice and Cu2+-induced hepatoblastoma cells (HepG2 cells). In TX mice, Analyses using Histopathology, Immunohistochemical staining, Enzyme-linked immunosorbent assay (ELISA), and Western blot, revealed that Que treatment facilitated the efflux of Cu2+ from the liver, improvement of liver function indicators and pathological damage of liver tissue, and significantly inhibited Hedghog (Hh) signaling pathway, leading to significant downregulation of key proteins and genes involved in this pathway, including Gli1, Ptch1, Smo, and Shh. Moreover, Que can reverse epithelial-mesenchymal transition (EMT), and we have also investigated key proteins and genes of EMT and the specific transcription factors controlling E-cadherin expression at the transcriptional level (Slug, Snail, ZEB-1, and Twist) and found that Que can regulatory their expression levels. In Cu2+-induced HepG2 cells, we using Hh Signaling pathway Inhibitor: GDC-0449, found blocking Hh Signaling pathway can reverse the EMT and consistent with in vivo results. Therefore, Que may have the potential to ameliorate liver fibrosis in Wilson disease and EMT by suppressing the Hh signaling pathway.

Soft starters are effective devices used to provide overload protection for motors from large mechanical shocks during the start-up period. However, existing soft starters require additional power supplies, sensors, and complex control elements that pose serious challenges to the integration, versatility, and operability of mechanical transmission system. Herein, we propose a newly soft starter based on the triboelectric nanogenerator (TENG) and electrorheological fluid (ERF) to realize a self-powered mechanical transmission system. Both ERF’s rheological characteristic and the baffle structure play a role in the torque of device. Driven by TENG, the soft starter with optimized baffle achieves a 715% growth in transmission torque compared to that of the device without baffle. And a smooth start is obtained with transmission speeds ranging from 0% to 100%. In application demonstration, this triboelectric soft starter (TSS) has the capacity to gain a smooth operation of the high-speed motor. In contrast, the direct start generates an overshoot, leading to a break in the conveyor belt. The TSS designed in this work with the advantages of self-powered, highly integrated, easy to operate, and low cost, provides a prospective strategy for broadening the application of TENG in mechanical transmission systems.

Exploring an appropriate immobilization approach to enhance catalytic activity and reusability of cellulase is of great importance to reduce the price of enzymes and promote the industrialization of cellulose-derived biochemicals. In this study, Fe3O4 magnetic nanoparticles (MNPs) were functionalized with meso-2,3-dimercaptosuccinic acid to introduce carboxyl groups on the surface (DMNPs). Then, melamine–glutaraldehyde dendrimer-like polymers were grafted on DMNPs to increase protein binding sites for the immobilization of processive endoglucanase EG5C-1. Moreover, this dendrimer-like structure was beneficial to protect the conformation of EG5C-1 and facilitate the interaction between substrate and active center. The loading capacity of the functionalized copolymers (MG-DMNPs) for EG5C-1 was about 195 mg/g, where more than 90% of the activity was recovered. Immobilized EG5C-1 exhibited improved thermal stability and increased tolerability over a broad pH range compared with the free one. Additionally, MG-DMNP/EG5C-1 biocomposite maintained approximately 80% of its initial hydrolysis productivity after five cycles of usage using filter paper as the substrate. Our results provided a promising approach for the functionalization of MNPs, enabling the immobilization of cellulases with a high loading capacity and excellent activity recovery.

Abstract The combination of super‐resolution microscopy and synthetic fluorescence probes has emerged as a universal tool to monitor dynamic biological events at the nanometer scale. However, the limited site‐specificity and fluorogenicity of synthetic fluorescent probes make it still difficult to realize long‐term super‐resolution imaging. Herein, we introduce a dynamic aggregation mediated SNAP‐tag fluorogenic probe, BGAN‐Aze, which can specifically bind to various SNAP‐tag fusion proteins with 41‐fold fluorescence enhancement. The equilibrium between the non‐fluorescent aggregate/dimer (A–D) and the fluorescent monomer (M) of BGAN‐Aze acts as an effective method to reduce the fluorescence background and endow BGAN‐Aze with the capability of conducting washing‐free super‐resolution imaging of various intracellular and extracellular proteins. Using this probe, we monitored multiple dynamic biological events, such as MMC, mitophagy, the fusion of nucleolus, and the growth and contact of filopodia. We expect that BGAN‐Aze will become a widely used SNAP‐tag for super‐resolution imaging of dynamic biological events and the A–D–M equilibrium can be a general strategy for designing fluorogenic probes.

It is an economical way to use the pile-supported embankment for the construction of the embankment over soft soil. The combined use of piles and reinforcement effectively reduces the differential settlement of the embankment surface. However, the previous analysis of embankment stress and settlement did not take into account the anisotropy in the embankment filler. In this paper, the UMAT subroutine is developed by using the material subroutine interface in ABAQUS 2016 finite element software. The anisotropy of soil cohesion and friction angle has been incorporated into the Mohr–Coulomb yield criterion so that it can consider the anisotropy of soil. The accuracy of the anisotropic yield criterion in this paper is verified by an ABAQUS source program and related engineering examples. It is found that the anisotropy value of soil cohesion is inversely proportional to the stress ratio on the pile–soil interface while being directly proportional to the tensile stress applied to the geogrid. The results show that the anisotropy of the friction angle decreases with the soil arching effect but increases by 23.1% with the tensile stress on the geogrid. The position of the settlement plane remains relatively constant at 2.3 m as the friction angle anisotropy coefficient increases. These research results provide valuable theoretical guidance for on-site construction design.

Cognitive impairment is a neurological manifestation of Wilson's disease (WD). Gandouling (GDL), a traditional Chinese medicine, protects against WD-related brain damage. However, the mechanisms underlying its protective effect have not been elucidated. Therefore, we explored the neuroprotective effects of GDL on cognitive abilities to understand the underlying molecular mechanisms using a toxic milk mouse model of WD. We employed the Morris water maze test and open field test to assess the effects of GDL on spatial memory, learning abilities and exploratory behavior in these mice. GDL treatment reduced the escape latency and increased the number of times mice crossed the platform to reach the target zone, indicative of alleviated WD-associated cognitive dysfunction. It also ameliorated the histopathological changes in the hippocampus via downregulation of IL-1β, IL-6, and TNF-α expression, reduced oxidative stress, and increased cell vigor. GDL treatment increased the protein and mRNA levels of Nrf2 and OH-1 protein while lowering p62, Beclin1, and LC3 expression in the hippocampus. Collectively, GDL improves cognitive dysfunction in mice with WD by regulating the Nrf2/p62 signaling pathway by reducing oxidative stress and autophagy. Based on its anti-inflammatory, antioxidant, and autophagy-inhibiting effects, we believe GDL is a promising therapy for WD-related cognitive dysfunction.

Building polygons plays an important role in urban management. Although leveraging deep learning techniques for building polygon extraction offers advantages, the models heavily rely on a large number of training samples to achieve good generalization performance. In scenarios with small training samples, the models struggle to effectively represent diverse building structures and handle the complexity introduced by the background. A common approach to enhance feature representation is fine-tuning a pre-trained model on a large dataset specific to the task. However, the fine-tuning process tends to overfit the model to the task area samples, leading to the loss of generalization knowledge from the large dataset. To address this challenge and enable the model to inherit the generalization knowledge from the large dataset while learning the characteristics of the task area samples, this paper proposes a knowledge distillation-based framework called Building Polygon Distillation Network (BPDNet). The teacher network of BPDNet is trained on a large building polygon dataset containing diverse building samples. The student network was trained on a small number of available samples from the target area to learn the characteristics of the task area samples. The teacher network provides guidance during the training of the student network, enabling it to learn under the supervision of generalization knowledge. Moreover, to improve the extraction of buildings against the backdrop of a complex urban context, characterized by fuzziness, irregularity, and connectivity issues, BPDNet employs the Dice Loss, which focuses attention on building boundaries. The experimental results demonstrated that BPDNet effectively addresses the problem of limited generalization by integrating the generalization knowledge from the large dataset with the characteristics of the task area samples. It accurately identifies building polygons with diverse structures and alleviates boundary fuzziness and connectivity issues.

Some trace elements in the human body, such as proteins and metabolites, are closely related to human health. Changes in the concentration of proteins can usually be used as indicators for the diagnosis of diseases. On the other side, some metabolites such as lactic acid and uric acid are closely related to human motor function. A large part of cancer markers are proteins, and their concentration changes in human serum and body fluid are usually closely related to cancer diagnosis, staging and prognosis. It has always been the goal of researchers to efficiently and sensitively detect the relevant trace elements in human body. Due to the characteristics of low energy, coherence and fingerprint, terahertz (THz) waves have been widely used in the detection of substances in recent years. Metasurface sensor is a new type of sensor with unique electromagnetic characteristics based on artificial design. The emergence of THz metasurface sensors provides a new technical means for the detection of trace elements proteins. Based on the above background, the research objects in this paper are three common protein cancer markers: carcinoembryonic antigen (CEA), neuron-specific enolase (NSE) and squamous epithelial cell carcinoma antigen (SCC), in order to study the detection performance of THz metasurface sensor and its improvement effect after modification. In the experiment, the cancer marker is dropped onto the surface of sensor, and the spectrum is detected by THz time-domain system (TDS), and the frequency shift is calculated by comparing with the resonance frequency of the blank sensor. Then the experiment was repeated by changing the concentration and class of the marker, and the sensitivity of sensors was calculated by fitting the relationship between the frequency shift and the concentration of markers. After that, two compounds (halloysite nanotube and Tungsten disulfide) were used to modify the metasurface sensor, and compared with the unmodified metasurface sensor. The experimental results show that for the detection of three markers, the metasurface sensor modified with HNT has significantly improved the detection sensitivity compared with the sensor modified with WS2 and blank sensor. This provides a new means for THz metasurface sensors in the detection of biomarkers, which is suitable for biomedicine, human health monitoring and other fields.

Ethyl-thioglycolate-modified Fe3O4@ZnS nanoparticles (Fe3O4@ZnS-SH) were successfully prepared using a simple chemical precipitation method. The introduction of ethyl thioglycolate better regulated the surface distribution of ZnS, which can act as a recognition group and can cause a considerable quenching of the fluorescence intensity of the magnetic fluorescent nanoprobe, Fe3O4@ZnS-SH. Benefiting from stable fluorescence emission, the magnetic fluorescent nanoprobe showed a highly selective fluorescent response to Ag+ in the range of 0–400 μM, with a low detection limit of 0.20 μM. The magnetic fluorescent nanoprobe was used to determine the content of Ag+ in real samples. A simple and environmentally friendly approach was proposed to simultaneously achieve the enrichment, detection, and separation of Ag+ and the magnetic fluorescent nanoprobe from an aqueous solution. These results may lead to a wider range of application prospects of Fe3O4 nanomaterials as base materials for fluorescence detection in the environment.

Silibinin and capsaicin both are natural product molecules with diverse biological activities. In this article, we investigated the anti-inflammatory effects of silibinin combined with capsaicin in lipopolysaccharide (LPS)-induced RAW264.7 cells. The results showed that silibinin combined with capsaicin strongly inhibited LPS-induced nitric oxide (NO), tumor necrosis factor-α (TNF-α), Interleukin-6 (IL-6), and COX-2. Moreover, silibinin combined with capsaicin potently inhibited nuclear factor-κB (NF-κB) and mitogen-activated protein kinase (MAPK) signaling pathways. The results of the present study indicate that silibinin combined with capsaicin effectively inhibits inflammation.

In order to investigate the cumulative deformation of the pile group in saturated clay under horizontal cyclic loading, a series of 1g model tests were conducted using the self-made loading equipment in this paper. Firstly, the loading equipment and testing procedure are introduced. Then, the cumulative deformation of the pile group, the dynamic response of the soil, and the bending moment of the pile shaft under horizontal cyclic loading are studied. Finally, the horizontal cyclic stiffness of the pile group is analyzed based on the experimental results. It can be found that the cumulative displacement, the rotation angle of the bearing platform, the pile shaft bending moment, and the pore water pressure can attain 90% of the peak values within the first 1000 cycles, and the growth rate slows down in subsequent loading cycles. Moreover, the bending moment of each pile increases with the burial depth and gradually decreases after the peak values. Notably, the horizontal cyclic stiffness of the pile group grows with the cycle loading times and decreases with the loading amplitude.

Image dehazing has always been one of the main areas of research in image processing. The traditional dark channel prior algorithm (DCP) has some shortcomings, such as incomplete fog removal and excessively dark images. In order to obtain haze-free images with high quality, a hybrid dark channel prior (HDCP) algorithm is proposed in this paper. HDCP first employs Retinex to remove the interference of the illumination component. The variant genetic algorithm (VGA) is then used to obtain the guidance image required by the guided filter to optimize the atmospheric transmittance. Finally, the modified dark channel prior algorithm is used to obtain the dehazed image. Compared with three other modified DCP algorithms, HDCP has the best subjective visual effects of haze removal and color fidelity. HDCP also shows superior objective indexes in the mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and information entropy (E) for different haze degrees.

This experiment evaluated antioxidant, anti-human breast cancer activities, and cytotoxicity effects of green synthesis of Au nanoparticles (AuNPs) containing Foeniculum Vulgare aqueous extract. Mixing Foeniculum Vulgare aqueous with Au chloride solution produced Au nanoparticles. The characteristics of Au nanoparticles determined using Fourier Transformed Infrared Spectroscopy (FT‐IR), Transmission Electron Microscopy (TEM), UV–Visible Spectroscopy (UV–Vis), and Field Emission Scanning Electron Microscopy (FE‐SEM). To check the cytotoxicity and anti-breast cancer effects of Au chloride, Foeniculum Vulgare aqueous extract, and AuNPs on common breast cancer cell lines i.e., ZR-75-30, T47D, and HCC1187 was used MTT assay. AuNPs showed no cytotoxicity and the most effective anti-breast cancer features compared to other items that were tested. They had no cytotoxic effects on normal cell line (HUVEC) and had very low cell viability, high anti-breast cancer activities dose-dependently against ZR-75-30, T47D, and HCC1187 cell lines. In the presence of butylated hydroxytoluene as the positive control, the DPPH test was used to evaluate the antioxidant features of Au chloride, Foeniculum Vulgare aqueous extract, and Au nanoparticles. AuNPs showed the best antioxidant properties compared to other items that were tested. Perhaps remarkable anti-human breast cancer activities of Au nanoparticles synthesized by Foeniculum Vulgare aqueous extract due to its antioxidant properties. After clinical trial and confirmation of results, this formulation can be used as an effective drug to treat breast cancer.

In order to develop a deep method for removing trace acetic acid from industrial solvents, a type of quaternary ammonium-salt-modified magnetic microspheres was developed as a potential nanoadsorbent for low-concentration acetic-acid-enhanced removal from DMAC aqueous solution. The ion-exchange magnetic microspheres (Fe3O4@SiO2@N(CH3)3+) have been prepared by a two-step sol-gel method with N-trimethoxysilylpropyl-N, N, N-trimethylammonium chloride as functional monomer, tetraethyl orthosilicate as a cross-linking agent, Fe3O4@SiO2 as a matrix. The nanocomposite is characterized by SEM, FI-IR, XRD, VSM, and XPS. Moreover, the optimization of adsorption experiments shows that the maximum adsorption capacity of nanoadsorbent is 7.25 mg/g at a concentration = 30 mg/L, adsorbent dosage = 10 mg, V = 10 mL, and room temperature. Furthermore, the saturated Fe3O4@SiO2@N(CH3)3+ achieved an efficient regeneration using a simple desorption method and demonstrated a good regeneration performance after five adsorption/desorption cycles. In addition, Fe3O4@SiO2@N(CH3)3+ was used to remove acetic acid in DMAC waste liquid; the adsorption effect is consistent with that of a nanoadsorbent of acetic acid in an aqueous solution. These results indicate that Fe3O4@SiO2@N(CH3)3+ can efficiently treat acetic acid that is difficult to remove from DMAC waste liquid.

Energy level interaction and electron concentration are crucial aspects that affect the response performance of quantum cascade detectors (QCDs). In this work, two different-structured array QCDs are prepared, and the detectivity reaches 109 cm·Hz1/2/W at room temperature. The overlap integral (OI) and oscillator strength (OS) between different energy levels under a series of applied biases are fitted and reveal the influence of energy level interaction on the response performance. The redistribution of electrons in the cascade structure at room temperatures is established. The coupled doped-well structure shows a higher electron concentration at room temperature, which represents a high absorption efficiency in the active region. Even better responsivity and detectivity are exhibited in the coupled doped-well QCD. These results offer a novel strategy to understand the mechanisms that affect response performance and expand the application range of QCDs for long-wave infrared (LWIR) detection.

Compared with natural enzymes, nanozymes based on carbonaceous nanomaterials are advantages due to high stability, good biocompatibility, and the possibility of multifunctionalities through materials engineering at an atomic level. Herein, we present a sensing platform using a nitrogen-doped graphene quantum dot (NGQD) as a highly efficient fluorescent peroxidase mimic, which enables a colorimetric/fluorescent dual-modality platform for detection of hydrogen peroxide (H2O2) and biomolecules (ascorbic acid-AA, acid phosphatase-ACP) with high sensitivity. NGQD is synthesized using a simple hydrothermal process, which has advantages of high production yield and potential for large-scale preparation. NGQD with uniform size (3.0 ± 0.6 nm) and a single-layer graphene structure exhibits bright and stable fluorescence. N-doping and ultrasmall size endow NGQD with high peroxidase-mimicking activity with an obviously reduced Michaelis–Menten constant (Km) in comparison with natural horseradish peroxidase. Taking advantages of both high nanozyme activity and unique fluorescence property of NGQD, a colorimetric and fluorescent dual-modality platform capable of detecting H2O2 and biomolecules (AA, ACP) with high sensitivity is developed as the proof-of-concept demonstration. Furthermore, the mechanisms underlying the nanozyme activity and biosensing are investigated.

Medical data is an important part of modern medicine. However, with the rapid increase in the amount of data, it has become hard to use this data effectively. The development of machine learning, such as feature engineering, enables researchers to capture and extract valuable information from medical data. Many deep learning methods are conducted to handle various subtasks of EHR from the view of information extraction and representation learning. This survey designs a taxonomy to summarize and introduce the existing deep learning-based methods on EHR, which could be divided into four types (Information Extraction, Representation Learning, Medical Prediction and Privacy Protection). Furthermore, we summarize the most recognized EHR datasets, MIMIC, eICU, PCORnet, Open NHS, NCBI-disease and i2b2/n2c2 NLP Research Data Sets, and introduce the labeling scheme of these datasets. Furthermore, we provide an overview of deep learning models in various EHR applications. Finally, we conclude the challenges that EHR tasks face and identify avenues of future deep EHR research.

As the effects of droughts on agriculture and industrial water availability intensify with climate change, developing suitable drought prevention and mitigation measures has become increasingly important. However, measuring drought conditions using different indices leads to disjointed drought management responses by ministries and agencies. Additionally, indices based on only one variable are insufficient to accurately assess drought conditions. Therefore, creating and adopting a OneMap drought index would be beneficial in the assessment of drought conditions and the implementation of appropriate measures. In this study, we used multivariate statistical modeling using Bayesian principal component analysis to develop a OneMap drought index that unifies existing measures of drought conditions, including meteorological, agricultural, and hydrological drought indices. After evaluating the accuracy of the corrected OneMap drought index based on the self-organizing migrating algorithm optimization technique, it was found that the applicability of the OneMap drought index and its ability to regenerate drought were excellent for ground and satellite data. Therefore, the authors recommend implementing step-by-step drought management action plans using the integrated index to generate drought forecasts and warnings, thus promoting concerted and effective responses of local governments and authorities.

The phonon Boltzmann transport equation combined with first-principles calculation has achieved great success in exploring the lattice thermal conductivity (κ) of various materials. However, the convergence of the predicted κ is a critical issue, leading to quite scattered results recorded in the literature, even for the same material. In this paper, we explore the origin for the convergence of thermal conductivity in two-dimensional (2D) materials. Two kinds of typical 2D materials, graphene and silicene, are studied, and the bulk silicon is also compared as a control system for a three-dimensional material. The effect of the cutoff radius (rc) in the third-order interatomic force constants on κ is studied for these three materials. It is found that that κ of these three materials exhibits diverse convergence behaviors with respect to rc, which coincides very well with the strength of hydrodynamic phonon transport. By further analyzing the phonon lifetime and scattering rates, we reveal that the dominance of the normal scattering process gives rise to the hydrodynamic phonon transport in both graphene and silicene, which results in long-range interaction and a large lifetime of low-frequency flexural acoustic phonons, while the same phenomenon is absent in bulk silicon. Our study highlights the importance of long-range interaction associated with hydrodynamic phonon transport in determining the thermal conductivity of 2D materials.

As deformation and defects are inevitable during the manufacture and service of graphene resonators, comprehensive molecular dynamic (MD) simulations are performed to investigate the vibrational properties of the defective single-layer graphene sheets (SLGSs) during tension. Perfect SLGSs, SLGSs with single vacancy, SLGSs with low-concentration vacancies, and SLGSs with high-concentration vacancies are considered, respectively. The frequencies of the perfect and defective SLGSs at different stretching stages are investigated in detail. The effects of different external forces are also taken into account to study the vibration properties of the defective SLGSs. Results show that the perfect and defective SLGSs both successively perform four stages, i.e., the elastic stage, the yield stage, the hardening stage, and the fracture stage during stretching, and the elastic properties of the SLGSs are insensitive to the vacancy defects, while the ultimate strain is noticeably reduced by the vacancies. The single vacancy has no effect on the vibration properties of SLGS, while the frequency decreases with the increasing vacancy concentration for SLGS at the elastic stage. The frequency of yielded SLGS with a certain vacancy concentration is almost constant even with a varying external force.

Here we report the design and preparation of an ultrastable Au nanocatalyst through a photo-deposition strategy at room temperature, in which Au nanoparticles were covered by an island-like dispersed Cr2O3 overlayer. The latter was induced by the excited electrons in the TiO2 conduction band transferred to the Au nanoparticle. The resulting titania-supported Au catalyst promoted by chromia is resistant to sintering and exhibits excellent activity and stability in the low-temperature CO oxidation reaction and air atmosphere.

Indocyanine green (ICG) was the first fluorescent dye approved by the United States Food and Drug Administration (FDA) for clinical use in humans and had been widely used in biological imaging for decades. However, there were few public reports on the synthesis method of ICG, and there were few studies on its fluorescence emission mechanism, which limited its chemical derivation and function expansion. In this paper, we provided a one-step condensation method for the synthesis of ICG with 92% yield. We also employed quantum chemical calculations of the frontier molecular orbitals to show that the luminescence of ICG was mainly derived from the polymethine conjugation system, and the naphthalenyl rings at both ends had little effect on the UV–vis absorption and fluorescence wavelengths.

In an attempt to find a potential application of cell culture harvesting, a novel method for the preparation of an upper critical solution temperature (UCST) thermosensitive hydrogel was studied. An electron accelerator was used as the electron beam (EB) radiation source, and acrylamide (AAm) was first grafted onto the pre-irradiated polypropylene (PP) sheet. Then, the grafting layer of poly (acrylamide-co-acrylonitrile) (P (AAm-co-AN)) was obtained by the partial dehydration of the acylamino group into the cyano group in the solution mixture of sulfoxide chloride (SOCl2) and dimethyl formamide (DMF). The effects of the absorbed dose, AAm concentration, reaction time, and temperature on the degree of grafting were studied, respectively. The effect of the SOCl2 concentration on the conversion degree of the cyano group from the acylamino group was studied, followed by the temperature of the UCST. The UCST properties of the grafted samples with P (AAm-co-AN) were studied by quartz crystal microbalance (QCM) and atomic force microscope (AFM), respectively. The cytotoxicities of the hydrogels against cells were verified by CCK-8 studies.

Soil shear strength is an important indicator of soil erosion sensitivity and the tillage performance of the cultivated layer. Measuring soil shear strength at a field scale is difficult, time-consuming, and costly. This study proposes a new method to predict soil shear strength parameters (cohesion and internal friction angle) by combining cone penetration test (CPT) data and soil properties. A portable CPT measuring device with two pressure sensors was designed to collect two CPT data in farmland, namely cone tip resistance, and cone side pressure. Direct shear tests were performed in the laboratory to determine the soil shear strength parameters for 83 CPT data collection points. Two easily available soil properties (water content and bulk density) were determined via the oven-drying method. Using the two CPT data and the two soil properties as predictors, three machine learning (ML) models were built for predicting soil cohesion and the internal friction angle, including backpropagation neural network (BPNN), partial least squares regression (PLSR), and support vector regression (SVR). The prediction performance of each model was evaluated using the coefficient of determination (R2), the root-mean-square error (RMSE), and the relative error (RE). The results suggested that among all the evaluated models, the BPNN model was the most suitable prediction model for soil cohesion, and the SVR model performed best in predicting soil internal friction angle. Thus, our findings provide a foundation for the convenient and low-cost measurement of soil shear strength parameters.

Due to the rapid development of micro/nano manufacturing techniques and the greater understanding in electrochemical principles and methods, micro/nano electrode array sensing has received much attention in recent years, especially in bioanalysis. This review aims to explore recent progress in innovative techniques for the construction of micro/nano electrode array sensor and the unique applications of various types of micro/nano electrode array sensors in biochemical analysis. Moreover, the new area of smart sensing benefited from miniaturization of portable micro/nano electrode array sensors as well as wearable intelligent devices are further discussed.

Self-assembling peptides can be used to design new materials for medical and biological applications. Here we synthesized and characterized two novel cyclic γ-peptides (γ-CPs) with hydrophobic inner surfaces. The NMR and FT-IR studies confirmed that the CPs could self-assemble into parallel stacking structures via intermolecular H-bonds and π-π interactions. The morphologies of the self-assembly CPs showed bundles of nanotubes via transmission electron microscopy (TEM); these nanotubes form water channels to transport water across the lipid membrane. The properties of blocking the transport of protons like natural water channels showed that the hydrophobic inner surfaces are important in artificial transmembrane water channel designs. These studies also showed that water transport was a function of pore size and length of the assemblies.

A new germanate garnet compound, Ce2CaMg2Ge3O12, was synthesized via flux crystal growth. Truncated spherical, reddish-orange single crystals with a typical size of 0.1–0.3 mm were grown out of a BaCl2-CaCl2 melt. The single crystals were characterized by single-crystal X-ray diffraction analysis, which revealed that it adopted a cubic garnet-type structure with a = 12.5487(3) Å in the space group Ia−3d. Its composition is best described as A3B2C3O12, where Ce/Ca, Mg, and Ge occupied the A, B, and C sites, respectively. A UV–vis absorption spectroscopy measurement on the germanate garnet revealed a clear absorption edge corresponding to a band gap of 2.21 eV (λ = 561 nm). First-principle calculations indicated that the valence band maximum was composed of Ce 4f bands, whereas the conduction band minimum mainly consisted of Ce 5d bands. These findings explain the observed absorption edge through the Ce 4f → 5d absorption. Photoluminescence emission spectra exhibited a very broad peak centered at 600 nm, corresponding to transition from the lowest energy d level to the 4f levels.

Curved surfaces can give plates a unique aesthetic effect and physical advantages in acoustics and optics. Assembling such curved plates can greatly improve the image of buildings and enrich their functions. It is thus not surprising to notice that their wide applications in designed or completed buildings in China have become a trend. Thus, this study offers a comprehensive summary of the application progress of curved plates in the architectural field from three aspects: image expression, acoustic characteristics, and optical characteristics. On this basis, future directions are proposed. The main findings or suggestions are as follows: (1) climate harshness has increased recently, and the safety of structures and materials and the coupling effect of the two must be fully considered when designing the shapes of curved surface buildings; (2) research on the mechanism and numerical calculation of curved diffuser systems with different sizes and curvatures needs to be further developed; and (3) experimental studies of various and complex curved plates and different conditions to explore their optimal reflectivity, transmittance, absorptivity, and other optical properties will be an important development direction.

This paper investigates the aeroelastic flutter and vibration reduction of functionally graded (FG) multilayer graphene nanoplatelets (GPLs) reinforced composite plates with piezoelectric patch subjected to supersonic flow. Activated by the control voltage, the piezoelectric patch can generate the active mass and active stiffness that can accordingly increase the base plate’s stiffness and mass. As a result, it changes the GPLs reinforced plate’s dynamic characteristics. The motion equation of the plate-piezoelectric system is derived through the Hamilton principle. Based on the modified Halpin–Tsai model, the effects of graphene nanoplatelets weight fraction and distribution pattern on the dynamic behaviors of the plate are numerically studied in detail. The result illustrates that adding a few amounts of grapheme nanoplatelets can effectually enhance the aeroelastic properties of the plates. Two kinds of control strategies, including the displacement and acceleration feedback control, are applied to suppress the occurrence of the flutter of the plate. It shows that the displacement and acceleration feedback control can improve the critical flutter Mach number of the plate by attaching active stiffness and active mass, respectively. Furthermore, the combined displacement and acceleration feedback control has a better control effect than that of considering only one of them.

Surface plasmon (SP) enhancement of photoluminescence (PL) from a green-emitting InGaN/GaN quantum well (QW) using nanoparticles (NPs) made of different metals and their combinations was investigated. The NPs were formed by annealing the metal films in N2 followed by rapid cooling. Four-fold enhancement in PL intensity was achieved using random metal NPs made of Cu on Mg (Cu-Mg) double metal film that was more than two folds of the enhancement observed by AgNPs. Reversing the order of metal film deposition (Mg on Cu) resulted in much lower PL intensity due to significantly different NPs size distribution as the given annealing conditions did not cause homogeneous alloying of the two metals. The results pave the way for the application of NPs of relatively low-cost unconventional metals and their combinations in the SP enhancement of LEDs.

In order to solve the problems of serious soil reflux and poor stability of ditch depth in the existing ditching organic fertilizer fertilization device in grey desert and loess orchards, rotary tillage theory and software simulation were used to conduct kinematic analysis of soil particles and ditching blade in the ditching process, and meanwhile, modeling and simulation are carried out for sand soil particles by using EDEM software, so as to determine the action mechanism of soil, blade and fairing in ditching process of grey desert and loess. The abstract on this basis, the quadratic orthogonal regression-rotation combination experiment was designed. The soil bin test was carried out by taking the cutter wheel speed, ditching depth and inclination of curved surface as the influencing factors, and the throwing distance and the stability of ditch depth as the test indexes. And it was concluded that the order of the influence of the operating parameters of the ditching device on the soil throwing distance is ditching depth > inclination of curved surface > cutter speed, and the order of the influence on the stability of the ditch depth is ditching depth > cutter speed > Inclination of curved surface. Finally, the optimized operating parameters of the ditching device are as follows: the cutter wheel speed is 119.61 r·min−1, the inclination of curved surface is 30.07°, the ditching depth is 35.52 mm, the soil throwing distance is 57.31, and the stability of ditch depth is 87.43. With these parameters as test objects, 10 groups of single factor tests were carried out to obtain that the soil throwing distance is 58.33, and the stability of ditch depth is 86.51, which were basically consistent with the expected results of the optimization test, and also in line with the relevant agronomic standards.