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The common presence of glycidyl esters (GEs) in refined vegetable oils has been a concern for food safety. The present study aimed to investigate the inhibitory effects of three carotenoids derived from Haematococcus pluvialismicroalga on GE formation in both rice oil and a chemical model during heating. The addition of astaxanthin (AS), lutein (LU), and β-carotene (CA) at 0.6 mg/g in rice oil can reduce GE formation by 65.0%, 57.1%, and 57.5%, respectively, which are significantly higher than those achieved by common antioxidants such as l-ascorbyl palmitate (39.0%), α-tocopherol (18.5%), tert-butyl hydroquinone (42.7%), and quercetin (26.2%). UPLC-Q-TOF-MS/MS analysis showed that two new compounds, that is, propylene glycol monoester and diester of palmitic acid, were formed in the CA-added chemical model, which provided direct experimental evidence for the inhibition of antioxidants including AS, LU, and CA against GE formation not only by indirect antioxidative action but also by direct radical reactions to competitively prevent the formation of cyclic acyloxonium intermediates. Furthermore, it was interestingly found that only AS could react with the GEs. The adduct of AS with GEs, astaxanthin-3-O-propanetriol esters, was preliminarily identified using Q-TOF-MS/MS in the heated AS-GE model, suggesting that reacting with GEs might represent another distinct mechanism of AS to eliminate GEs.

We report 1 kV vertical P-i-N power diodes (PNDs) based on ultra-wide bandgap high-Al-composition (HAC) Al0.47Ga0.53N heterostructures grown on sapphire substrates by metal organic chemical vapor deposition (MOCVD). A p-type AlGaN layer with linearly graded Al composition is inserted between the p-type Al0.47Ga0.53N and p-GaN layer to leverage the polarization-enhanced p-doping effect and alleviate the fast strain relaxation during the growth of p-GaN on lattice mismatched HAC p-AlGaN layer. The vertical HAC AlGaN PNDs exhibit a low ideality factor of 2.3, a high on/off ratio (ION/I $_{\text {OFF}}\text {)}$ of $\sim 10^{{9}}$ and a remarkable reverse breakdown voltage of 1032 V, which is significantly enhanced compared to the reported AlGaN-based vertical PNDs. These results provide compelling evidence and significant potential of utilizing ultra-wide bandgap AlGaN material in the fabrication of high-voltage and high-power vertical devices.

This paper reports a strong robustness MEMS QMG with the parallel coupled structure design, for the first time. The motions of the four masses of the gyroscope in the drive and sense directions are coupled and connected through different rings to achieve the parallel coupled effect. We demonstrated that the parallel coupled QMG has stronger robustness by numerical analysis, FEA and experiments. We study the kinematic equations of the parallel coupled QMG and compare it with the serial coupled QMG to analyze the effect of the difference in stiffness matrices and damping mismatch on the gyroscope performance and carry out numerical analyses under the conditions of stiffness mismatch and external vibration, and the results show that the parallel coupled QMG has stronger stiffness robustness and vibration robustness. We applied accelerations of different magnitudes and directions to the parallel and serial QMG to simulate the external loads, and the results show that the bandwidth of the parallel QMG is almost unaffected by the acceleration. We fabricated the parallel coupled QMG prototype using the SOG process, and designed circuits to test the performance. The results indicate that the gyroscope is sensitive to small input angles with $\mathrm {0.0603 ^{\circ }/s/\surd Hz}$ ARW and 0.0135∘/s BI at 162 Hz frequency mismatch and $30~^{\circ }$ C temperature compensation. Moreover, the frequency and quality factor of the parallel QMG are little affected by temperature and the bandwidth remains almost constant with good temperature robustness. These results indicate that the parallel structure has the potential to deliver better performance. [2024-0021]

Due to their programmable stimuli-responsiveness, excellent biocompatibility, and water-rich and soft structures similar to biological tissues, smart DNA hydrogels hold great promise for biosensing and biomedical applications. However, most DNA hydrogels developed to date are composed of randomly oriented and isotropic polymer networks, and the resulting slow response to biotargets and lack of anisotropic properties similar to those of biological tissues have limited their extensive applications. Herein, anisotropic DNA hydrogels consisting of unidirectional void channels internally oriented up to macroscopic length scales were constructed by a directional cryopolymerization method, as exemplified by a DNA-incorporated covalently cross-linked DNA cryogel and a DNA duplex structure noncovalently cross-linked DNA cryogel. Results showed that the formation of unidirectional channels significantly improved the responsiveness of the gel matrix to biomacromolecular substances and further endowed the DNA cryogels with anisotropic properties, including anisotropic mechanical properties, anisotropic swelling/shrinking behaviors, and anisotropic responsiveness to specific biotargets. Moreover, the abundant oriented and long macroporous channels in the gel matrix facilitated the migration of cells, and through the introduction of aptamer structures and thermosensitive polymers, an anisotropic DNA cryogel-based platform was further constructed to achieve the highly efficient capture and release of specific cells. These anisotropic DNA hydrogels may provide new opportunities for the development of anisotropic separation and biosensing systems.

•Infection with drug-resistant bacteria decreased IMI and MEM PK/PD target attainment.•IMI concentration was associated with the ICU stay.•MEM concentration was not associated with ICU stay but associated with effectiveness.•Elevated doses of IMI and MEM should be given to patients with drug-resistant bacteria infection.

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Environmental remediation based on persulfate (i.e., peroxomonosulfate (PMS) and peroxydisulfate (PDS))-activation-enabled radical and non-radical oxidation has captured growing interest due to the strong oxidation power, long life of reactive oxygen species, and wide pH adaptability. While metal-based catalysts suffer from environmental problems (e.g., metal ion leaching), metal-free carbocatalysts become the focus of current activities for establishing environmentally benign and efficient carbocatalyst-driven PMS/PDS-based advanced oxidation processes (AOPs). However, the complex structure and nonstoichiometry of carbocatalysts cause the decoding of their active sites and associated pathways in activating persulfates and degrading pollutants to be challenging. Moreover, the ambiguous active sites and structure–activity–performance relationships, as well as the inability to differentiate the oxidation capabilities based on different reaction pathways, present an enormous obstacle to designing and fabricating highly active and durable carbocatalysts for PMS/PDS-based AOPs. Hereby, this paper makes an effort to unravel the catalytic sites of carbocatalysts and their associated pathways in PMS/PDS-based AOPs. Apart from various non-doped active sites, we summarize the diverse active sites induced by single-doping, dual-doping, and tri-doping carbon substrates with different kinds of heteroatoms. Meanwhile, the relationships between these active sites and associated pathways in PMS/PDS-based AOPs are simultaneously analyzed before presenting the challenges and future perspectives.

Multihop question answering (QA) over knowledge graph (KG) poses significant challenges in the context of industrial processes, due to the intricate semantics of natural language queries and the obscure relationships among triples in the KG. This article presents a multihop fault diagnosis (FD) QA framework based on KG reasoning and decision, called KG-MQA. It consists of three modules: 1) the embedding module is designed to learn representations of queried questions and encode entities and relationships within the input FD KG; 2) the KG reasoning module is proposed to learn to reason candidate answers based on query entities and context; and 3) the answer decision module is applied to obtain final answer by leveraging the attention mechanism to compute the attention scores between the input question and candidate answers. Extensive experiments have been conducted on the dataset from a hot rolling line, and our KG-MQA achieves an average accuracy of 95.7%, surpassing other state-of-the-art models. Ablation studies demonstrate the efficiency of KG-MQA in helping users obtain equipment fault-related information from massive data through the professional knowledge structure. It facilitates reasoning during data queries to efficiently provide multiple rounds of QA for equipment FD in hot rolling lines.

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Water injection and oil production often lead to significant surface deformations in oilfields. Such geological hazards are substantial potential threats to both the oilfield and its surrounding infrastructure. Liaohe oilfield is China’s largest production base for heavy and high-viscosity oil. It has a long history of surface deformation in its core production area near the Bohai Bay. Multitemporal synthetic aperture radar interferometry (MT-InSAR) offers long-term monitoring capabilities and has previously been used to monitor deformations in Liaohe oilfield. However, quantitative analysis of deformation-driving factors is less common in previous studies, and investigations are limited to data up until 2021. Continuous monitoring and analysis of deformation patterns and influencing factors in this region are of crucial practical importance. In this study, we acquired the latest long-term deformation data and the driving factors in Liaohe oilfield via MT-InSAR. For the first time, a quantitative analysis of deformation-driving factors was performed, and the ultra-long-term (from 1958 to 2023) deformation data with respect to Liaohe oilfield were collected and analyzed to interpret the deformation characteristics, variation tendency, and influencing factors. We employed 217 Sentinel-1A/B SAR images from 2019 to 2023 to calculate the deformation rates and cumulative deformations in this area. The results revealed three subsidence funnels and one uplift area, with deformation rates ranging from [−152, 41] mm/year and [−182, 51] mm/year (negative values indicating subsidence and positive values indicating uplift) for the ascending and descending datasets, respectively. Principal component analysis (PCA) was applied to the cumulative deformation sequence for extracting the primary components. The PCA results, groundwater data, and precipitation data were utilized for a quantitative analysis of primary deformation-driving factors. The analysis results indicate that the surface deformations exhibit a strongly linear trend mainly due to oilfield exploitation, coupled with slight variations related to precipitation and groundwater extraction. By integrating historical deformation information with the monitored results, the development process of the surface deformation was investigated and divided into six stages. This process was related to the oil energy demand, extraction techniques, and reservoir compaction phases. This study contributes to understanding the spatiotemporal evolution of surface deformation in the Liaohe oilfield and the driving factors, and it provides valuable insights for similar research in other oilfields.

There is increasing interest in developing quinoa products due to their unique nutritional value. Starch and protein are the primary components in quinoa, and the interaction between them affects the quality of quinoa products. This study extracted the starch and protein from quinoa and simulated the thermal processing of quinoa to investigate the effects of starch on the solubility and structure of quinoa protein isolates during heat treatment. The structure of quinoa protein isolates was characterized by fluorescence spectroscopy, Fourier transform infrared spectroscopy, laser particle size analysis, and scanning electron microscopy. The results showed that starch decreased protein solubility, and the maximum solubility was obtained after heating for 5 min. After starch addition during heat treatment, the surface charge distribution of protein changed, the degree of protein aggregation increased, the particle size of proteins increased, the thermal stability increased, and the β-sheet ratio of the proteins increased, suggesting that the protein structure is more ordered, which is the structural foundation of protein solubility decreasing. The research about the interaction between starch and protein and the effects on the solubility of protein could provide a reference for quinoa products processing.

Women with heart failure with reduced ejection fraction (HFrEF) receive less guideline-recommended therapy and experience worse quality of life than men.

Cuttings particles of different sizes in the drilling fluid are the leading cause of wear at the casing and drill pipe joints, and diamond-like carbon (DLC) films have excellent research potential in reducing tool wear due to their ultra-low friction coefficient and high wear resistance. In this paper, a corresponding molecular dynamics model was developed using LAMMPS to investigate the effect of silica particles of different particle sizes on the friction and wear mechanisms of Fe/DLC friction pairs at the microscale. The results show that small cuttings particles in a dry environment are more likely to cause interface wear between the casing and drill pipe joint, while in a water environment, the opposite is true. The main reason is that small particles in a dry environment have smaller contact areas and greater indentation depth, leading to greater wear at the friction interface. The movement of water molecules in the water environment will promote the composite movement of large particles, thereby exacerbating the wear of the interface. Moreover, the relevant research results at the micro-scale indicate that DLC films can effectively reduce wear, which provides theoretical support for its application in drill pipe joints.

In this paper, the frictional behaviors of Fe–Cr alloys in the lubricating effect of oil-based lubricant are investigated through reactive molecular dynamics. It is shown that the oil-based lubricant achieves ultralow friction through hydrodynamic lubrication by linear alpha olefin (C8H16) and passivation of the friction pairs by hydrogen gas (H2) and free H atoms generated by the friction chemistry. Moreover, there is a critical value for the transition of the crystal structure of Fe–Cr alloy from body-centered cubic (Bcc) to amorphous structure (Other), leading to a dramatic change in friction. Meanwhile, a sliding interface consisting of a large number of amorphous structures is formed near the rigid layer, which keeps the friction force stable.

Pulsed electric field (PEF) treatment is currently a hot spot in food science research. The improvement and regulation of protein structure and physicochemical properties after PEF treatment are a new development in its processing technology. This study aimed to clarify the effects of moderate‐intensity PEF treatment on the structure and physicochemical properties of foxtail millet (Setaria italica) prolamin and its action rules. PEF treatment changed the spatial conformation of millet prolamin, increased its hydrophobicity and solubility in alcohol solution, but did not change the subunit composition distribution. It also promoted the increase in soluble aggregates, resulting in an increase in protein particle size. The α‐helix content of the protein decreased, the β‐sheet content increased, the number of disulfide bonds increased, and the protein structure became more orderly after treatment. The results showed that the structure and physicochemical properties of millet prolamin significantly changed after the moderate‐intensity PEF treatment. The increased hydrophobicity of prolamin makes it a strong future candidate in medicinal excipients, food packaging materials, and biodegradable polymers.

The Chinese economy upheld a frail recovery in 2022 under the triple superposition of contraction of demand, disruption in supply, and weakening expectations, aggravated by unanticipated adverse shocks in the midst of global turmoil. Over the year, rising income uncertainty set off by the pandemic shock continued depressing household consumption and housing demand. Trade also saw slowing growth, along with consumption and investment, with sluggish residential investment awaiting policy stimulus to take force. Unemployment rate remained high, and was much higher for youth engendered by severe structural imbalances in the labor market. Local government debt burden worsened while revenue shrinking, only to exacerbate the local fiscal financial risk. It fared better on the price side. While growth in producer price index kept falling, consumer price index maintained steady growth. Renminbi depreciated against USD through fluctuations with larger swings, but the exchange rate remained in a manageable band. The Institute for Advanced Research‐China Macroeconomic Model projects the baseline growth rate in real gross domestic product to be 5.4% in 2023. We have also used the model to conduct alternative scenario analyses and policy simulations to assess the impacts of potential downside risks or favorable situations. Our findings call for a focus on economic construction with deepening reform and opening up more comprehensively and initiatively. Only by doing so can China spur market vitality, strengthen business confidence, and forge competitive advantages.

Whether a graphitization mechanism can control the low-friction behavior of DLC films is still controversial. In this paper, we establish the molecular dynamics model of the DLC film with graphene (DLC-GR-DLC) by LAMMPS and study the influence of the graphitization mechanism on the friction and wear behavior of the DLC film. The friction force of the DLC-GR-DLC model in the running-in stage is significantly smaller than that of the DLC film and then gradually increases to the same size as that of the DLC film. Further analysis indicates that the graphitization mechanism could indeed reduce the shear stress of the friction interface when graphene remains intact. However, the curling and breaking of the graphene structure will lead to an increase in shear force at the friction interface.

Ensartinib (X-396) is a second-generation anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitor (TKI) indicated for the treatment of ALK-positive patients with locally advanced or metastatic non–small cell lung cancer. Although in vitro experiments and molecular docking suggested its potential as a cytochrome P450 inhibitor, no further investigation or clinical trials have been conducted to assess its drug–drug interaction (DDI) risk. In this study, we conducted a series of in vitro experiments to elucidate the inhibition mechanism of ensartinib. Furthermore, a physiologically-based pharmacokinetic (PBPK) model was developed based on in vitro, in silico, and in vivo parameters, verified using clinical data, and applied to predict the clinical DDI mediated by ensartinib. The in vitro incubation experiments suggested that ensartinib exhibited strong time-dependent inhibition. Simulation results from the PBPK model indicated a significant increase in the exposure of CYP3A substrates in the presence of ensartinib, with the maximal plasma concentration and area under the plasma concentration-time curve increasing up to 12-fold and 29-fold for sensitive substrates. Based on these findings, it is evident that co-administration of ensartinib and CYP3A substrates requires careful regulatory consideration.SIGNIFICANCE STATEMENTEnsartinib was found to be a strong time-dependent inhibitor of CYP3A for the first time based on in vitro experiments, but there was no research conducted to estimate the risk of drug–drug interaction (DDI) of ensartinib in clinic. Therefore, the first ensartinib physiologically based pharmacokinetic model was developed and applied to predict various untested scenarios. The simulation result indicated that the exposure of CYP3A substrate increased significantly and urged the further clinical DDI study.:

Ionospheric phase delay is a critical error source in time series interferometric synthetic aperture radar (TS-InSAR) for the purpose of monitoring ground surface deformation with SAR data obtained from low-frequency radar systems. Recently, the range split-spectrum interferometry (RSSI) method has been employed to estimate and rectify ionospheric errors in TS-InSAR. However, the performance of the RSSI method is largely restricted by the significant linear scale factors resulting from the current small SAR bandwidth. In this study, we propose a reformulating RSSI (Re-RSSI)-based method for correcting the ionospheric error in TS-InSAR by optimizing the linear scale factors, with the aim of improving the accuracy of TS-InSAR measurements. We evaluate the Re-RSSI method using 121 ALOS-1 PALSAR images that cover two distinct regions: the low-latitude Lazufre volcano region and the high-latitude Anaktuvuk River tundra fire region. Our results demonstrate that the Re-RSSI method can effectively remove time series ionospheric errors at both test sites, where we detected ionospheric delays of approximately 2.5 cm/year (yr) and 2.0 cm/yr, respectively. Using Global Navigation Satellite System (GNSS) measurements as ground truth, we achieved an 86.59% improvement rate in the root-mean-square error (RMSE) with the Re-RSSI method, which is significantly higher than the 66.40% improvement rate achieved with the traditional RSSI method.

The increased power demand incurred by electric vehicles (EVs) has imposed new challenges on the distribution network. One significant responsibility of the distribution network operator (DNO) is to design and expand the distribution network periodically to accommodate the ever-increasing demand. The previous researches mainly use relaxation techniques to enhance the problem tractability, which would involve additional binary variables and incur computation burden to the optimization problem, or even worse, may lead to an intractable problem. This paper develops a mixed-integer non-linear programming (MINLP) model considering various network constraints for the distribution network expansion planning under a high penetration level of EVs. The stochastic characteristics of demands are addressed through set of scenarios. A distributed biased min-consensus algorithm based approach is proposed to solve the MINLP model. Finally, comparison tests are conducted on three different scales of distribution networks to validate the effectiveness of the proposed approach. Simulation results demonstrate that the computation time of the proposed approach is reduced by 42.46% on average for different systems compared with that of the traditional shortest path algorithm based approach.

To more fully assess the far-reaching effects of fossil fuel combustion on humanity, it is necessary to gain an in-depth understanding of the full impact of fossil fuels on human health and lifetime potential. However, current knowledge of the long-term consequences of fossil fuel use on health damage in early life, such as human capital impacts in adulthood, is still insufficient. This paper aims to summarize the current evidence on the health effects of fossil fuel-driven air pollution and climate change on children and the consequent effect on human capital stemming from these early health damages. Evidence indicates that climate change and air pollution not only deteriorate children's health but also affect the entire human capital in their adulthood and can be deeply affected through damaged early-life health. Fossil fuel combustion can significantly impact the lifelong health and human capital for generations. We call for a more holistic assessment of the full range of impacts borne by children, including direct damages to children's health, losses of human capital, and associated economic costs. Cross-disciplinary collaboration is vital to facilitate research on such assessments, thereby enriching our understanding of the multifaceted impact of fossil fuel combustion on the early life and its long-term implications on human capital and economic potential.

A detection method of carbofuran (CBF) in water samples was reported using deep eutectic solvent (DES)-based dispersive liquid–liquid microextraction (DLLME) combined with digital image colorimetry (DIC), which was environmentally friendly, solvent-saving, rapid, and convenient. Under alkaline conditions, the green and multifunctional extractant DESs dissociated into linalool and heptanoic acid, and CBF was hydrolyzed to 2,3-dihydro-2,2-dimethyl-7-benzofuranol and further coupled with fast blue BB salt to form an azo derivative. Heptanoic acid led to the dispersion of linalool to extract the orange-red azo derivative; DIC was used for quantitative analysis using a smartphone with its associated ease of data-acquisition. This experiment optimized the types, molar ratios, and volumes of DESs and the amounts of sodium carbonate and sodium chloride. Under optimal conditions, the limits of detection (LOD) and quantitation (LOQ) were 0.024–0.032 mg L−1and 0.081–0.108 mg L−1, respectively. The extraction recoveries in real samples (tap, pond, and river water) were 92.4–101.0% with a relative standard deviation below 4.6%. This method has successfully analyzed CBF in different water samples and shows prospects for the monitoring and control of CBF residues in other environmental samples.

AbstractFrom the perspective of spatial interaction, the impact of the modern service industry’s agglomeration on today’s increasingly connected cities is worth studying. This study uses a spatial econometric model to test the development trends and factors influencing the modern service industry’s agglomeration in the Yangtze River Delta city group. The results show that the industry has the highest agglomeration in leasing and business and the lowest in education. The overall concentration of the industry is generally low, implying a more fragmented distribution. Moreover, the agglomeration has a significant positive spatial correlation with economic development, knowledge intensity, and city size. However, it has a negative correlation with information technology level and transportation infrastructure, inconsistent with existing research. This study argues that the development of the information technology level and transportation infrastructure in a city could lead to the ‘virtual agglomeration’ of the modern service industry and gradual decentralisation in geographical distribution. This is a new paradox that city groups may face when improving their infrastructure and developing modern services. This study uses the spatial interaction perspective to propose policy recommendations for promoting the modern service industry’s agglomeration and coordinated regional development.

With the popularization of social media, the way of information transmission has changed, and the prediction of information popularity based on social media platforms has attracted extensive attention. Feature fusion-based media popularity prediction methods focus on the multi-modal features of social media, which aim at exploring the key factors affecting media popularity. Meanwhile, the methods make up for the deficiency in feature utilization of traditional methods based on information propagation processes. In this paper, we review feature fusion-based media popularity prediction methods from the perspective of feature extraction and predictive model construction. Before that, we analyze the influencing factors of media popularity to provide intuitive understanding. We further argue about the advantages and disadvantages of existing methods and datasets to highlight the future directions. Finally, we discuss the applications of popularity prediction. To the best of our knowledge, this is the first survey reporting feature fusion-based media popularity prediction methods.

12 μm thick rolled copper foil is the thinnest rolled copper foil that can be stably produced at present, which can be used for the production of high-end Flexible Printed Circuit (FPC) boards. With the miniaturized and multi-functional of various electronic components in the age of 5th Generation (5G) communication, higher requirements have been put forward for the etching performance of rolled copper foil. The microstructure of 12 μm thick rolled copper foil was obtained through thermal treatment at 180 °C for different times, and then the relationship between microstructure and etching performance was systematically studied. The research results show that the etching performance of rolled copper foil improves with the increasing of annealing time. But the etching performance of copper foil annealed for 10 min is better than that annealed for 30 min. Due to the low energy of Low Angle Grain Boundaries (LAGBs), the etching performance of copper foil gradually becomes better with the decreasing of LAGBs proportion. The etching performance of copper foil improves with the decreasing of work-hardening and dislocation density. The lower proportion of {001} crystal planes is the key reason for higher etching rate. The etching performance of copper foil is better with higher Random High Angle Grain Boundaries Network (RHGBN). The amount of grain boundaries decreases with the increasing of grain size, resulting in the decreasing of etching performance. In addition, it is found that the release of residual compressive stress on copper foil surface can also obviously improve the etching performance.