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Fufang Muji granules (FMGs) are a prominent modern prescription Chinese patent formulation derived from the Muji decoction. Utilized in clinical practice for nearly four decades, FMGs have demonstrated efficacy in treating liver diseases. However, the precise mechanism of action remains unclear. This study investigates the hepatoprotective effects of FMGs against liver fibrosis in rats based on untargeted metabolomics and elucidates their underlying mechanisms. A comprehensive model of liver fibrosis was established with 30% CCl4 (2 mL/kg) injected intraperitoneally, and a fat and sugar diet combined with high temperatures and humidity. Rats were orally administered FMGs (3.12 g/kg/d) once daily for six weeks. FMG administration resulted in improved liver fibrosis and attenuated hepatic oxidative stress and apoptosis. Furthermore, FMGs inhibited hepatic stellate cell activation and modulated transforming growth factor β1/Smad signaling. Additionally, FMG treatment influenced the expression levels of interleukin-6, interleukin-1β, and tumour necrosis factor alpha in the injured liver. Metabolic pathways involving taurine and hypotaurine metabolism, as well as primary bile acid biosynthesis, were identified as mechanisms of action for FMGs. Immunohistochemistry, quantitative reverse transcription polymerase chain reaction (RT-qPCR), and quantitative analysis also revealed that FMGs regulated taurine and hypotaurine metabolism and bile acid metabolism. These findings provide a valuable understanding of the role of FMGs in liver fibrosis management.

To evaluate the thermal stability of composite polymer-modified asphalt, thermoplastic elastomer styrene-butadiene rubber (SBR)/polypropylene (PP) pellets were prepared using a hot-melt blending technique, with butyl rubber powder and waste polypropylene pellets as raw materials. The effects of different evaluation indexes on the thermal stability of SBR/PP-modified asphalt were investigated using a frequency scan test and a multi-stress creep recovery (MSCR) test, and the compatibility of SBR/PP particles with asphalt was studied using the Cole–Cole diagram and microstructure images. The tests show that, firstly, the performance grade (PG) classification of asphalt can be improved by adding an SBR/PP thermoplastic elastomer to enhance the adaptability of asphalt in high- and low-temperature environments, and the evaluation separation index can reflect the high-temperature storage stability of composite-modified asphalt more reasonably. Additionally, the larger the rubber-to-plastic ratio the worse the high-temperature thermal stability of composite-modified asphalt. Moreover, the addition of additives to the composite particles can promote the SBR/PP particles in the asphalt to be more uniformly dispersed, forming a more desirable microstructure and improving the thermal stability of composite-modified asphalt. Ultimately, the semicircular curve of the Cole–Cole diagram can reflect the compatibility characteristics of the two-phase structure of SBR/PP-modified asphalt, which can be used as an auxiliary index to evaluate the compatibility of polymer-modified asphalt.

Microbial degradation is a cost-effective and environmentally friendly method for removing microcystin-LR (MC-LR). However, the application of free bacteria has limitations due to low operational stability and difficulties in recovery. In a previous study, our group successfully isolated a highly efficient MC-LR-degrading bacterium, Sphingopyxis sp. YF1, from Taihu. To enhance its practical potential in addressing MC-LR-contaminated water pollution, a novel biological material named polyacrylonitrile-based carbon fiber @Sphingopyxis sp. YF1 (PAN-CF@YF1) was synthesized. The immobilization conditions of strain Sphingopyxis sp. YF1 on PAN-CF surfaces were optimized using Box–Behnken design and response surface methodology (RSM), which turned out to be an optimal pH of 7.6 for the culture medium, a ratio of 0.038 g of supporting materials per 100 mL of culture media, and an incubation time of 53.4 h. The resultant PAN-CF@YF1 showed a great degradation effect both for low and high concentrations of MC-LR and exhibited satisfactory cyclic stability (85.75% after six cycles). Moreover, the application of PAN-CF@YF1 in the bioreactors demonstrated effective and sustainable MC-LR removal, with a removal efficiency of 78.83% after three consecutive treatments. Therefore, PAN-CF@YF1 with high degradation activity, environmental compatibility, straightforward preparation, and recyclability shows significant application potential for the bioremediation of MC-LR-contaminated water bodies.

The effects of maternal dietary energy and arginine level on embryonic development and serum lipid metabolism were investigated in this study. A 2 × 3 factorial experiment was conducted with six treatments represented by 10 replicates of eight Arbor Acre broiler breeder hens each. Diets fed from 40 to 50 weeks of age were formulated to contain two digestible arginine levels (9.6 g/kg and 14.5 g/kg) and three metabolic energy levels (10.08 MJ ME/kg, 11.88 MJ ME/kg, and 13.68 MJ ME/kg). Artificial insemination was used, and eggs collected from 50 weeks of hens’ age were hatched. Embryonic growth, biochemical and endocrine indexes of embryonic serum and allantoic fluid were measured on different embryonic days (E). The results were as follows: Egg weight (E0, E11, E13) and embryonic weight (E12, E15) in the high-energy group (13.68 MJ ME/kg) were significantly decreased (p < 0.01), as were embryonic breast rate (E13, E15, E21), thigh rate (E13–E21) and liver rate (E15–E21). The reciprocal effects of arginine and energy were significant on breast rate (E11, E13, E17), thigh rate (E19, E21) and liver rate (E11, E19) of the embryo (p < 0.05). CHO (E13–E19), high-density lipoprotein (E13, E15, E21), low-density lipoprotein (E15, E19, E21), and blood glucose (E13) levels in embryonic serum decreased with the increase in maternal dietary energy level (p < 0.05), but triglyceride levels (E19, E21) showed the opposite result (p < 0.05). The levels of cholesterol and blood glucose in embryonic serum at E11 and urea nitrogen in allantoic fluid at E11–E15 were significantly decreased in the 14.5 g/kg arginine group (p < 0.01). With the increase in maternal dietary energy and arginine levels, embryonic serum nitric oxide synthases levels (E11, E15, E19) increased significantly (p < 0.01). The reciprocal effect of arginine and energy in maternal diets was significant on the embryonic serum high-density lipoprotein level at E21 (p < 0.05). Embryonic serum insulin levels at E13 were significantly elevated in the high-energy group (13.68 MJ ME/kg). The reciprocal effect of arginine and energy was significant on the embryonic serum growth hormone level (p < 0.01). Embryonic serum growth hormone levels were significantly reduced in the 14.5 g/kg arginine and 13.68 MJ/kg metabolic energy group (p < 0.01). In conclusion, maternal restricted feeding improved embryonic development and regulated lipid metabolism-related indices in embryonic serum. Maternal dietary addition of digestible arginine had a significant effect on lipid metabolism indices in embryos. There was a maternal effect of maternal dietary energy and arginine levels on embryo growth and development. The deposition of maternal nutrients affects the development of embryos.

The combinatorial complexity of the protein sequence space presents a significant challenge for recombination experiments targeting beneficial positions. To overcome these difficulties, a machine learning (ML) approach was employed, which was trained on a limited literature dataset and combined with iterative generation and experimental data implementation. The PyPEF method was utilized to identify existing variants and predict recombinant variants targeting the substrate channel of P450 CYP116B3. Through molecular dynamics simulations, eight multiple-substituted improved variants were successfully validated. Specifically, the RMSF of variant A86T/T91H/M108S/A109M/T111P was decreased from 3.06 Å (wild type) to 1.07 Å. Additionally, the average RMSF of the variant A86T/T91P/M108V/A109M/T111P decreased to 1.41 Å, compared to the wild type’s 1.53 Å. Of particular significance was the prediction that the variant A86T/T91H/M108G/A109M/T111P exhibited an activity approximately 15 times higher than that of the wild type. Furthermore, during the selection of the regression model, PLS and MLP regressions were compared. The effect of data size and data relevance on the two regression approaches has been summarized. The aforementioned conclusions provide evidence for the feasibility of the strategy that combines ML with experimental approaches. This integrated strategy proves effective in exploring potential variations within the protein sequence space. Furthermore, this method facilitates a deeper understanding of the substrate channel in P450 CYP116B3.

This paper proposes colaGAE, a self-supervised learning framework for graph-structured data. While graph autoencoders (GAEs) commonly use graph reconstruction as a pretext task, this simple approach often yields poor model performance. To address this issue, colaGAE employs mutual isomorphism as a pretext task for a continuous latent space sampling GAE (colaGAE). The central idea of mutual isomorphism is to sample from multiple views in the latent space and reconstruct the graph structure, with significant improvements in terms of the model’s training difficulty. To investigate whether continuous latent space sampling can enhance GAEs’ learning of graph representations, we provide both theoretical and empirical evidence for the benefits of this pretext task. Theoretically, we prove that mutual isomorphism can offer improvements with respect to the difficulty of model training, leading to better performance. Empirically, we conduct extensive experiments on eight benchmark datasets and achieve four state-of-the-art (SOTA) results; the average accuracy rate experiences a notable enhancement of 0.3%, demonstrating the superiority of colaGAE in node classification tasks.

Epoxy resin (EP), as a kind of dielectric polymer, exhibits the advantages of low-curing shrinkage, high-insulating properties, and good thermal/chemical stability, which is widely used in electronic and electrical industry. However, the complicated preparation process of EP has limited their practical applications for energy storage. In this manuscript, bisphenol F epoxy resin (EPF) was successfully fabricated into polymer films with a thickness of 10~15 μm by a facile hot−pressing method. It was found that the curing degree of EPF was significantly affected by changing the ratio of EP monomer/curing agent, which led to the improvement in breakdown strength and energy storage performance. In particular, a high discharged energy density (Ud) of 6.5 J·cm−3 and efficiency (η) of 86% under an electric field of 600 MV·m−1 were obtained for the EPF film with an EP monomer/curing agent ratio of 1:1.5 by hot pressing at 130 °C, which indicates that the hot−pressing method could be facilely employed to produce high−quality EP films with excellent energy storage performance for pulse power capacitors.

Due to the increasingly serious problem of offshore oil spills, research related to oil–water separation has attracted more and more attention. Here, we prepared a super-hydrophilic/underwater super-oleophobic membrane (hereinafter referred to as BTA) using poly-dopamine (PDA) to adhesive TiO2 nanoparticles on the surface of bacterial cellulose, coated with sodium alienate by vacuum-assisted filtration technique. This demonstrates its excellent underwater super-oleophobic property. Its contact angle is about 153°. Remarkably, BTA has 99% separation efficiency. More importantly, BTA still showed excellent anti-pollution property under ultraviolet light after 20 cycles. BTA has the advantages of low cost, environmentally friendliness and good anti-fouling performance. We believe it can play an important role in dealing with problems related to oily wastewater.

In recent years, with the development of batteries, ceramics, glass and other industries, the demand for lithium has increased rapidly. Due to the rich lithium resources in seawater and salt-lake brine, the question of how to selectively adsorb and separate lithium ions from such brine has attracted the attention and research of many scholars. The Li-ion sieve stands out from other methods thanks to its excellent special adsorption and separation performance. In this paper, mesoporous titanium dioxide and lithium hydroxide were prepared by hydrothermal reaction using bacterial cellulose as a biological template. After calcination at 600 °C, spinel lithium titanium oxide Li2TiO3 was formed. The precursor was eluted with HCl eluent to obtain H2TiO3. The lithium titanate were characterized by IR, SEM and X-ray diffraction. The adsorption properties of H2TiO3 were studied by adsorption pH, adsorption kinetics, adsorption isotherm and competitive adsorption. The results show that H2TiO3 has a single-layer chemical adsorption process, and has a good adsorption effect on lithium ions at pH 11.0, with a maximum adsorption capacity of 35.45 mg g−1. The lithium-ion sieve can selectively adsorb Li+, and its partition coefficient is 2242.548 mL g−1. It can be predicted that the lithium-ion sieve prepared by biological template will have broad application prospects.

Due to the advantages of flexible configuration, bistatic synthetic aperture radar (BiSAR) has the ability to effectively observe from various visual angles, such as forward view area and squint area, and has good anti-jamming characteristics. It can be applied to the surveillance of ship targets on the sea and is gradually gaining an increasing amount of attention. However, for ship targets with complex motions on the sea surface, such as maneuvering targets or ship targets under high sea conditions, the high-order Doppler frequency of the scattering points is always spatial variation (related to the spatial position of scattering points), which poses a considerable challenge for the imaging of maritime ship targets in BiSAR. To resolve this problem, a BiSAR maritime ship target imaging algorithm based on cubic phase time-scaled transformation is proposed in this paper. First, through pre-processing of echo such as Doppler prefiltering and keystone transform, the translation compensation of the BiSAR maritime ship target is completed, and the scattering point energy is corrected to within one range unit. Then, the azimuth signal is modeled as a multi-component cubic phase signal. Based on the proposed cubic phase time-scaled transformation, the Doppler centroid, frequency rate, and third-order frequency of scattering points are estimated. Eventually, the BiSAR imaging of maritime ship targets is realized. This algorithm has excellent noise immunity and low cross-terms. The simulation leads to the verification of the validity of the proposed algorithm.

The development of biosensors based on field-effect transistors (FETs) using atomically thick carbon nanotubes (CNTs) as a channel material has the potential to revolutionize the related field due to their small size, high sensitivity, label-free detection, and real-time monitoring capabilities. Despite extensive research efforts to improve the sensitivity, selectivity, and practicality of CNT FET-based biosensors, their commercialization has not yet been achieved due to the non-uniform and unstable device performance, difficulties in their fabrication, the immaturity of sensor packaging processes, and a lack of reliable modification methods. This review article focuses on the practical applications of CNT-based FET biosensors for the detection of ultra-low concentrations of biologically relevant molecules. We discuss the various factors that affect the sensors’ performance in terms of materials, device architecture, and sensor packaging, highlighting the need for a robust commercial process that prioritizes product performance. Additionally, we review recent advances in the application of CNT FET biosensors for the ultra-sensitive detection of various biomarkers. Finally, we examine the key obstacles that currently hinder the large-scale deployment of these biosensors, aiming to identify the challenges that must be addressed for the future industrialization of CNT FET sensors.

This study aimed to develop an integrated approach of deep eutectic solvent-based ultrasound-assisted extraction (DES–UAE) to simultaneously extract five major bioactive macamides from the roots of Lepidium meyenii Walp. Ten different DESs containing choline chloride and selected hydrogen-bond donors were prepared and evaluated based on the extracted macamide content determination using high-performance liquid chromatography (HPLC). Choline chloride/1,6-hexanediol in a 1:2 molar ratio with 20% water exhibited the most promising extraction efficiencies under the optimized parameters verified using single-factor optimization as well as Box–Behnken design. Using the optimized DES–UAE method, the extraction efficiencies of the five macamides were up to 40.3% higher compared to those using the most favorable organic solvent petroleum ether and were also superior to those of the other extraction methods, such as heating and combination of heating and stirring. Furthermore, using the macroporous resin HPD-100, the recoveries of the five target macamides from the DES extraction reached 85.62–92.25%. The 20 μg/mL group of the five macamide extracts showed superior neuroprotective activity against PC12 cell injury than that of the positive drug nimodipine. The macamide extracts also showed higher NO inhibition in LPS-stimulated RAW264.7 cells. Thus, the developed approach was a green and potential alternative that can be used to extract bioactive macamide constituents from L. meyenii in the pharmaceutical and food industries.

The low-earth-orbit synthetic aperture radar (SAR) can achieve enhanced remote-sensing capabilities by exploiting the large-scale and long-duration beam coverage of a geosynchronous (GEO) SAR illuminator. Different bistatic imaging modes can be implemented by the steering of an antenna beam onboard the LEO receiver, such as high-resolution sliding-spotlight mode. In this paper, the accurate focusing of GEO-LEO bistatic SAR (GEO-LEO BiSAR) in sliding-spotlight mode is investigated. First, the two major problems of the accurate bistatic range model, i.e., curved trajectory within long integration time and ‘stop-and-go’ assumption error, for sliding-spotlight GEO-LEO BiSAR are analyzed. Then, a novel bistatic range model based on equivalent circular orbit trajectory is proposed to accurately represent the range history of GEO-LEO BiSAR in sliding-spotlight mode. Based on the proposed range model, a frequency-domain imaging method is put forward. First, a modified two-step preprocessing method is implemented to remove the Doppler aliasing caused by azimuth variance of Doppler centroid and beam steering. Then, an azimuth trajectory scaling is formulated to remove the azimuth variance of motion parameters due to curved trajectory. A modified frequency-domain imaging method is derived to eliminate the 2-D spatial variance and achieve accurate focusing of the echo data. Finally, imaging results and analysis on both simulated data and real data from an equivalent BiSAR experiment validate the effectiveness of the proposed method.

Healthy diets promote immune functions and have been shown to reduce COVID-19 severity. In 2021, COVID-19 vaccines have become available to the general public. However, whether vaccination status could affect individual and populational health behaviors is unknown. This study aimed to investigate the impacts of vaccination status and confidence on dietary practices. An online survey was conducted in August 2021. We collected data on dietary intake, diversity and behaviors, vaccination status and confidence and socio-demographic characteristics. Among the 5107 responses received, a total of 4873 study participants were included in the final analysis. Most of our participants aged between 18 and 45 years and 82% of them were fully vaccinated against COVID-19. Household level dietary diversity was found to be higher among people who were fully vaccinated (β = 0.321, 95%CI: 0.024 to 0.618) or who were more confident in the protectiveness of the vaccine (β for tertile 3 comparing with lowest tertile = 0.544, 95%CI: 0.407, 0.682). Vaccination promoted the intake of seafood, but it was also positively associated with the consumption of sugar, preserved, fried and barbequed foods and reduced vegetable intake. Higher vaccination confidence was associated with increased consumption of seafood, bean, fruits and vegetables and reduced fat intake. Changes in dietary behaviors compared with early 2021 (when vaccination was not common) were observed and differed by vaccination status and confidence level. Conclusion: COVID-19 vaccination status and confidence had varied, and possibly negative, impacts on dietary intake and behaviors. Our results suggest that vaccination status and confidence might be significant influencing factors affecting people’s health behaviors and highlight that healthy eating should be consistently promoted to prevent poor dietary practices during global health crisis.

This study aimed to explore food and nutrition related concerns during the post-lockdown period and their impacts on food shopping, preparation, and eating behaviors. Design: A cross-sectional study was conducted through online questionnaire. We collected data on food and nutrition related concerns, socio-demographic characteristics, and changes in dietary behaviors. Participants: A total of 2267 responses were received from people living in 31 provinces across mainland China and 1994 participants were included in the final analysis. Analysis: Linear and multinomial logistic regression analyses were performed to evaluate the association among food and nutrition related concerns, socio-demographic factors, and dietary behaviors Results: About 56% of participants reported moderate to high levels of concerns related to food and nutrition. Contracting the virus when dining out or through contaminated foods were the top two concerns, followed by overnutrition. Higher levels of concerns were found among people who were older, overweight, or obese, having lower income and education, and living in urban areas, or whose family contained vulnerable individuals. Compared with the pre-COVID-19 period, people who were more concerned about food and nutrition were more likely to report changes in their food purchases and consumption; they were also more likely to eat from individual plates, using serving chopsticks, and separating plates and utensils for raw and cooked foods during the post COVID-19 lockdown period. Conclusion and Implication: Food and nutrition related concerns during the post-lockdown period were prevalent and associated with changes in dietary behaviors. Preventative policies and nutritional guidance should be developed to address these concerns in order to reduce inappropriate dietary behaviors amid public health crises.

Breast cancer is one of the most commonly diagnosed malignancies and the leading cause of cancer death in women worldwide. Although many factors associated with breast cancer have been identified, the definite etiology of breast cancer is still unclear. In addition, early diagnosis of breast cancer remains challenging. Exosomes are membrane-bound nanovesicles secreted by most types of cells and contain a series of biologically important molecules, such as lipids, proteins, and miRNAs, etc. Emerging evidence shows that exosomes can affect the status of cells by transmitting substances and messages among cells and are involved in various physiological and pathological processes. In breast cancer, exosomes play a significant role in breast tumorigenesis and progression through transfer miRNAs which can be potential biomarkers for early diagnosis of breast cancer. This review discusses the potential utility of exosomal miRNAs in breast cancer progression such as tumorigenesis, metastasis, immune regulation and drug resistance, and further in breast cancer diagnosis.

Nanofiber membranes were successfully prepared with crown ether (CE) functionalized graphene oxide (GO), chitosan (CS), and polyvinyl alcohol (PVA) by low-temperature thermally induced liquid–liquid phase separation. The physical and chemical properties and adsorption performance of nanofiber membrane were studied through SEM, FT-IR, XRD, and static adsorption experiments. The results show that the specific surface area of the nanofiber membrane is as high as 101.5 m2∙g−1. The results of static adsorption experiments show that the maximum adsorption capacity of the nanofiber membrane can reach 168.50 mg∙g−1 when the pH is 7.0. In the selective adsorption experiment, the nanofiber membrane showed high selectivity for Li+ in salt lake brine. After five cycles, the material still retains 88.31% of the adsorption capacity. Therefore, it is proved that the material has good regeneration ability.

The BeiDou navigation satellite system shows its potential for passive radar vessel target detection owing to its global-scale coverage. However, the restrained power budget from BeiDou satellite hampers the detection performance. To solve this limitation, this paper proposes a long-time optimized integration method to obtain an adequate signal-to-noise ratio (SNR). During the long observation time, the range migration, intricate Doppler migration, and noncoherence characteristic bring challenges to the integration processing. In this paper, first, the keystone transform is applied to correct the range walk. Then, considering the noncoherence of the entire echo, the hybrid integration strategy is adopted. To remove the Doppler migration and correct the residual range migration, the long-time integration is modeled as an optimization problem. Finally, the particle swarm optimization (PSO) algorithm is applied to solve the optimization problem, after which the target echo over the long observation time is well concentrated, providing a reliable detection performance for the BeiDou-based passive radar. Its effectiveness is shown by the simulated and experimental results.

Recalcitrant plastic waste has caused serious global ecological problems. There is an urgent need to develop environmentally friendly and efficient methods for degrading the highly stable carbon skeleton structure of plastics. To that end, we used a quantum mechanical calculation to thoroughly investigate the oxidative scission of the carbon-carbon (C–C) backbone in polyethylene (PE). Here, we studied the reaction path of C–C bond oxidation via hydroxyl radical in PE. The flexible force constants and fuzzy bond orders of the C–C bonds were calculated in the presence of one or more carbocations in the same PE carbon chain. By comparison, the strength of the C–C bond decreased when carbocation density increased. However, the higher the density of carbocations, the higher the total energy of the molecule and the more difficult it was to be generated. The results revealed that PE oxidized to alcohol and other products, such as carboxylic acid, aldehyde and ketone, etc. Moreover, the presence of carbocations was seen to promote the cleavage of C–C backbones in the absence of oxygen.

Following a diet rich in whole grains, vegetables, fruit, and beans may reduce cancer incidence and mortality. The aim of this study was to investigate the effect of Coping with Cancer in the Kitchen (CCK), an 8 week in-person program offering education, culinary demonstrations and food tasting, and psychosocial group support, compared to receiving CCK printed materials by mail on knowledge, confidence, and skills in implementing a plant-based diet. A total of 54 adult cancer survivors were randomly assigned to intervention (n = 26) and control groups (n = 27) with assessments at baseline, 9, and 15 weeks via self-administered survey. The response rate was 91% at 9 weeks and 58% at 15 weeks. The majority of our study participants were female breast cancer survivors (58%) who had overweight or obesity (65%). Compared with the control, there were significant (p < 0.05) increases in intervention participants’ knowledge about a plant-based diet at weeks 9 and 15, reductions in perceived barriers to eating more fruits and vegetables at week 9, and enhanced confidence and skills in preparing a plant-based diet at week 15. There was a significant reduction in processed meat intake but changes in other food groups and psychosocial measures were modest. Participation in CCK in person increased knowledge, skills, and confidence and reduced barriers to adopting a plant-based diet. Positive trends in intake of plant-based foods and quality of life warrant further investigation in larger-scale studies and diverse populations.

Coronavirus disease 2019 (COVID-19) has imposed enormous challenges on people’s lifestyles. People in China have gradually returned to normal life; however, in the protracted pandemic, people may still follow certain dietary behaviors to cope with COVID-19. This study was the second stage of a longitudinal nutritional survey conducted in post-lockdown China that was aimed at exploring post-lockdown dietary behaviors and their effects on dietary diversity. In line with the first stage of the survey, the current dietary behaviors used to cope with COVID-19 and ways of purchasing food were determined. In addition, changes in dietary behavior compared to the same period in 2019 and those behaviors recommended to ensure food safety were also investigated. The Household Dietary Diversity Score (HDDS) was used to assess dietary diversity; this was also used in the first stage of the survey. Linear regression was used to model the associations between the HDDS, participants’ characteristics, and dietary behaviors. The data of 1994 participants were included in the analysis. The overall mean HDDS was 9.2 ± 2.0. Compared to the same period in 2019, a substantial proportion of participants self-reported that they had recently decreased eating in restaurants (61.6%) and reduced intakes of seafood (53.1%), imported frozen food (57.1%), and raw food (60.5%), while 64.8% of participants reported increased cooking at home. People with an increased consumption of seafood (adjusted OR (95%CI) = 0.56 (0.07, 1.04)) and raw food (adjusted OR (95%CI) = 0.74 (0.27, 1.21)) had a significantly higher HDDS. Participants who changed their consumption of imported frozen food (both increased and decreased) had a higher HDDS (adjusted OR (95%CI) = 0.56 (0.07, 1.04) and 0.27 (0.09, 0.44), respectively). People who depended more on purchasing food online had a significantly higher HDDS (adjusted OR (95%CI) = 0.29 (0.02, 0.55)). Compared to the data from stage 1, the proportion of people choosing healthy products to cope with COVID-19 did not greatly change and those people had a higher HDDS (adjusted OR (95%CI) = 0.31 (0.19, 0.42)). Although this study found that the proportion of people who chose to use alcohol or vinegar to prevent COVID-19 had decreased substantially compared to during lockdown, there were still 5.3% and 9.8% who followed these irrational behaviors. Regarding the dietary behavior regarding food safety, except for cooking food fully, fewer than half of participants followed the recommended dietary behaviors, including individual food servings (44.2%), using serving chopsticks and spoons (44.8%), and preparing raw and cooked food separately (43.3%). People who followed these behaviors had a better dietary diversity. In conclusion, during the post-lockdown period, people still followed certain dietary behaviors to cope with COVID-19. While some dietary behaviors were adopted to help prevent infection, irrational dietary behaviors were still followed. These behaviors were associated with the dietary diversity in Chinese adults.

COVID-19, a Public Health Emergency of International Concern, has imposed enormous challenges on the health system, economy, and food supply and has substantially modified people’s lifestyles. This study aimed to (1) explore the dietary diversity during the lockdown time in China and (2) examine factors associated with dietary diversity including socio-economic characteristics, sources for food and food purchases, and specific dietary behaviors responding to COVID-19 and isolation. A cross-sectional questionnaire-based survey was conducted online in March 2020. Multi-stage sampling was used to recruit participants living in Hubei Province and other parts of China. Dietary diversity was assessed using the Household Dietary Diversity Score (HDDS) and clustering analysis was used to categorize people with different propensities of methods for purchasing or obtaining foods. Logistic regression was used to model the associations among HDDS, participants’ characteristics, approaches to purchase or obtain food, and behaviors adopted to cope with COVID-19. Results: A total of 1938 participants were included in the analysis. The overall mean HDDS was 9.7 ± 2.1, and the median (25th, 75th) was 10 (8, 12). There were relatively low consumptions of fish, legumes, and miscellaneous foods (e.g., processed food like snacks and beverages). After adjusting for age, family income, and geographic regions, people living in places where laboratory confirmed COVID-19 cases were above 500 (ORadjusted = 0.79, 95%CI 0.65, 0.96), or living in Hubei Province (ORadjusted = 0.60, 95%CI 0.39, 0.93) had a lower HDDS. During isolation time, the most common sources for food and food purchases were in-house storage and in person grocery shopping. More than half of the participants (55.9%) purchased food at least once via online ordering and delivery services. There was no significant difference in HDDS among people with distinct dependences on different ways to obtain or purchase food (i.e., dependence on in-person grocery shopping, dependence on both in-house storage and in-person grocery shopping, or dependence on online food purchasing). We also identified a total of 37.7% participants who consumed certain foods or nutritional supplements to cope with COVID-19, which included vitamin C, probiotics, other dietary supplements, alcohol, and vinegar. People who reported these specific dietary behaviors had a significantly higher HDDS (ORadjusted = 1.23, 95%CI 1.02, 1.45) than those who did not do so. This study revealed an overall good dietary diversity among the studied Chinese residents during the COVID-19 pandemic. However, we observed a lower dietary diversity among people living in areas with a high number of confirmed COVID-19 cases. Online ordering and delivery services were popular and could serve as a feasible method to obtain and purchase food, contributing to ensure diversified diets during the time of lockdown. Certain dietary behaviors associated with COVID-19 were also identified and had significant impacts on HDDS.

The pharmacokinetic (PK) properties of drug, which include drug absorption and excretion, play an important role in determining the in vivo pharmaceutical activity. However, current in vitro systems that model PK profiles are often limited by the in vivo-like concentration profile of a drug. Herein, we present a perfused and multi-layered microfluidic chip system to model the PK profile of anti-cancer drug 5-FU in vitro. The chip device contains two layers of culture channels sandwiched by a porous membrane, which allows for drug exposure and diffusion between the two channels. The integration of upper intestine cells (Caco-2) and bottom targeted cells within the device enables the generation of loading and clearance portions of a PK curve under peristaltic flow. Fluorescein as a test molecule was initially used to generate a concentration-time curve, investigating the effects of parameters of flow rate, administration time, and initial concentration on dynamic drug concentration profiles. Furthermore, anti-cancer drug 5-FU was performed to assess its pharmaceutical activity on target cells (human lung adenocarcinoma cells or human pulmonary alveolar epithelial cells) using different drug administration regimens. A dynamic, in vivo-like 5-FU exposure refers to PK profile regimen, led to generate a lower drug concentration (dynamically fluctuate from 0 to 1 μg/mL affected by absorption) compared to the constant exposure. Moreover, the PK profile regimen alleviates the drug-induced cytotoxicity on target cells. These results demonstrate the feasibility of determining the PK profiles using this microfluidic system with in vivo-like drug administration regimens. This established system may provide a powerful platform for the prediction of drug safety and effectiveness in the pharmaceutical research.

In bistatic forward-looking synthetic aperture radar (BFSAR) ground moving target detection (GMTD), the suppression of the strong and heterogeneous ground clutter is one of the most crucial and challenging issues. Due to the bistatic forward-looking mode and long observation time, Doppler ambiguity, range and Doppler cells migration and non-stationary characteristics will exist in clutter receives, which leads to severe performance degradation of the traditional method. Hence, this paper proposes a GMTD method based on joint clutter cancellation in echo-image domain for BFSAR to achieve effective GMTD in heterogeneous BFSAR clutter. First, the pre-filtering and keystone transform are applied to suppress Doppler ambiguity and correct range cell migration, respectively. Then, time-division space-time adaptive clutter cancellation is adopted to suppress clutter at the first time in the echo domain, which can eliminate the effect of the migration of Doppler cells. However, its performance will be severely degraded due to the strong non-stationary characteristic of BFSAR clutter. Finally, adaptive displaced phase center antenna is exploited to suppress the residual non-stationary BFSAR clutter in image domain. Experimental results have shown that the strong non-stationary clutter of BFSAR has been sufficiently suppressed by the proposed method and the SCNR provided is enough to detect a moving target well.

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

Bistatic Synthetic Aperture Radar (SAR) has attracted increasing attention in recent years due to its unique advantages, such as the ability of forward-looking imaging. In translational variant bistatic forward-looking SAR (TV-BFSAR), it is difficult to get a well focused image due to large range cell migration (RCM) and 2-D variation of both Doppler characteristics and RCM. In this paper, an extended azimuth nonlinear chirp scaling (NLCS) algorithm is proposed to deal with these problems. Firstly, Keystone Transform (KT) is introduced to remove the spatial-variant linear RCM, which is of great significance in TV-BFSAR. Secondly, a correction factor is multiplied to the signal in range frequency domain to compensate for the residual RCM. At last, a fourth-order filtering together with azimuth NLCS is performed in every range gate to equalize both the azimuth-variant Doppler centroid and frequency modulation rate based on the azimuth numerical fitting. The proposed method is verified by simulation and real data processing. Multiple targets are generated and focused by the method, of which the peak sidelobe ratio (PSLR) is around −13 dB and integrated sidelobe ratio (ISLR) is around −10 dB. The method is accurate and can achieve high-resolution focusing for TV-BFSAR data.

We investigated the effects of variety, planting density, and irrigation amount on grain yield, water-use efficiency (WUE), and evapotranspiration (ETc). The trial was conducted in Tong Liao, Inner Mongolia, from 2021 to 2022, with compact variety Dika159 (DK159) and conventional variety Zhengdan958 (ZD958) as the test materials. The planting density was set to 6.0 × 104 plants/ha (D1, local farmer planting density) and 9.0 × 104 plants/ha (D2), with five irrigation levels: 450 mm (W450, irrigation amount used by local farmers, CK); 360 mm (W360); 270 mm (W270); 180 mm (W180); and 90 mm (W90). The results indicate that the yield and WUE of variety DK159 increased by 7.48% and 5.00%, compared to ZD958, respectively. Increasing planting density enhanced yield by 13.32–15.57% in maize yield and 9.55–11.47% in WUE. Maize yield exhibited a trend of increasing linearly with the irrigation amount before reaching a plateau, reaching a maximum (16.62–17.39 t/ha) and high WUE (2.45–2.49 kg/m3) with DK159-D2-W270. The highest water consumption intensity occurred during the silking stage to the milk stage for different densities and varieties. The results indicate that selecting compact varieties, increasing planting density, and optimizing irrigation amount through integrated drip irrigation and water fertilizer can effectively improve maize yield and WUE.

The demand for oceanic resource exploration and development is increasing, and autonomous underwater vehicles (AUVs) have emerged as potential tools for ocean exploration. To meet specific operational requirements, AUVs are required to operate in close proximity to the seafloor. However, complex and changeable seafloor terrains have complex spatiotemporal characteristics, which produce unsteady hydrodynamic interference on AUVs, affecting their safety and stability. In order to investigate the hydrodynamic characteristics of AUVs in turbulent flow fields near seafloor terrains, this study selects a typical dune terrain. Based on the computational fluid dynamics (CFD) method, the flow field around an AUV near the seafloor is simulated, and the flow field is solved using the large eddy simulation (LES) method, calculating the AUV’s hydrodynamic instantaneous and average characteristics, as well as flow field characteristics at different inflow velocities and distances from the seafloor. The results indicate that when the AUV is situated within the turbulent flow field caused by the terrain, its drag, lift, and pitch moment performance present significant fluctuations. Variations in total resistance are primarily caused by variations in pressure resistance. Variations in lift and pitch moment are more sensitive to variations in the flow field structure. The AUV also affects the development of the turbulent flow field near the terrain. When the AUV is in close proximity to the seafloor, it hampers the development of vortices below it. These results will offer guidance for the maneuverability and control of AUVs in practical engineering applications.

Taking location-based service (LBS) as the research scenario and aiming at the limitation of visualizing LBS points of interest (POI) in conventional web maps, this article proposes a visualization method of LBS-POI based on tag cloud, which is called “LBS tag cloud”. In this method, the user location is taken as the layout center, and the name of the POI is converted into a text tag and then placed around the center. The tags’ size, color, and placement location are calculated based on other attributes of the POI. The calculation of placement location is at the core of the LBS tag cloud. Firstly, the tag’s initial placement position and layout priority are calculated based on polar coordinates, and the tags are placed in the initial placement position in the order of layout priority. Then, based on the force-directed model, a repulsive force is applied to the tag from the layout center to make it move to a position without overlapping with other tags. During the move, the quadtree partition of the text glyph is used to optimize the detection of overlaps between tags. Taking scenic spots as an example, the experimental results show that the LBS tag cloud can present the attributes and distribution of POIs completely and intuitively and can effectively represent the relationship between the POIs and user location, which is a new visualization form suitable for spatial cognition.

Autism spectrum disorder (ASD) is a congenital, lifelong neurodevelopmental disorder whose main symptom is impaired social communication and interaction. However, no drug can treat social deficits in patients with ASD, and treatments to alleviate social behavioral deficits are sorely needed. Here, we examined the effect of oral supplementation of maca (Lepidium meyenii) on social deficits of in utero-exposed valproic acid (VPA) mice, widely used as an ASD model. Although maca is widely consumed as a fertility enhancer and aphrodisiac, it possesses multiple beneficial activities. Additionally, it benefits learning and memory in experimental animal models. Therefore, the effect of maca supplementation on the social behavioral deficit of VPA mice was assessed using a social interaction test, a three-stage open field test, and a five-trial social memory test. The oral supplementation of maca attenuated social interaction behavior deficit and social memory impairment. The number of c-Fos-positive cells and the percentage of c-Fos-positive oxytocin neurons increased in supraoptic and paraventricular neurons of maca-treated VPA mice. These results reveal for the first time that maca is beneficial to social memory and that it restores social recognition impairments by augmenting the oxytocinergic neuronal pathways, which play an essential role in diverse social behaviors.

Pre-eclampsia (PE) is a serious pregnancy complication, and gut dysbiosis is an important cause of it. Puerariae lobatae Radix (PLR) is a medicine and food homologous species; however, its effect on PE is unclear. This study aimed to investigate the efficacy of PLR in alleviating PE and its mechanisms. We used an NG-nitro-L-arginine methyl ester (L-NAME)-induced PE mouse model to examine the efficacy of preventive and therapeutic PLR supplementation. The results showed that both PLR interventions alleviated hypertension and proteinuria, increased fetal and placental weights, and elevated the levels of VEGF and PlGF. Moreover, PLR protected the placenta from oxidative stress via activating the Nrf2/HO-1/NQO1 pathway and mitigated placental damage by increasing intestinal barrier markers (ZO-1, Occludin, and Claudin-1) expression and reducing lipopolysaccharide leakage. Notably, preventive PLR administration corrected gut dysbiosis in PE mice, as evidenced by the increased abundance and positive interactions of beneficial bacteria including Bifidobacterium, Blautia, and Turicibacter. Fecal microbiota transplantation confirmed that the gut microbiota partially mediated the beneficial effects of PLR on PE. Our findings revealed that modulating the gut microbiota is an effective strategy for the treatment of PE and highlighted that PLR might be used as an intestinal nutrient supplement in PE patients.

A well-designed loss function can effectively improve the characterization ability of network features without increasing the amount of calculation in the model inference stage, and has become the focus of attention in recent research. Given that the existing lightweight network adds a loss to the last layer, which severely attenuates the gradient during the backpropagation process, we propose a hierarchical polynomial kernel prototype loss function in this study. In this function, the addition of a polynomial kernel loss function to multiple stages of the deep neural network effectively enhances the efficiency of gradient return, and only adds multi-layer prototype loss functions in the training stage without increasing the calculation of the inference stage. In addition, the good non-linear expression ability of the polynomial kernel improves the characteristic expression performance of the network. Verification on multiple public datasets shows that the lightweight network trained with the proposed hierarchical polynomial kernel loss function has a higher accuracy than other loss functions.

Meta-learning aims to teach the machine how to learn. Embedding model-based meta-learning performs well in solving the few-shot problem. The methods use an embedding model, usually a convolutional neural network, to extract features from samples and use a classifier to measure the features extracted from a particular stage of the embedding model. However, the feature of the embedding model at the low stage contains richer visual information, while the feature at the high stage contains richer semantic information. Existing methods fail to consider the impact of the information carried by the features at different stages on the performance of the classifier. Therefore, we propose a meta-learning method based on adaptive feature fusion and weight optimization. The main innovations of the method are as follows: firstly, a feature fusion strategy is used to fuse the feature of each stage of the embedding model based on certain weights, effectively utilizing the information carried by different stage features. Secondly, the particle swarm optimization algorithm was used to optimize the weight of feature fusion, and determine each stage feature’s weight in the process of feature fusion. Compared to current mainstream baseline methods on multiple few-shot image recognition benchmarks, the method performs better.

A tightly coupled fluid-structure interaction (FSI) methodology is developed for aeroelasticity analysis in the time domain. The preconditioned Navier–Stokes equations for all Mach numbers are employed and the structural equations are tightly coupled with the fluid equations by discretizing their time derivative term in the same pseudo time-stepping method. A modified mesh deformation method based on reduced control points radial basis functions (RBF) is utilized, and a RBF based mapping algorithm is introduced for data exchange on the interaction interface. To evaluate the methodology, the flutter boundary and the limit cycle oscillation of Isogai wing and the flutter boundary of AGARD 445.6 wing are analyzed and validated.

Light-weight convolutional neural networks (CNNs) suffer limited feature representation capabilities due to low computational budgets, resulting in degradation in performance. To make CNNs more efficient, dynamic neural networks (DyNet) have been proposed to increase the complexity of the model by using the Squeeze-and-Excitation (SE) module to adaptively obtain the importance of each convolution kernel through the attention mechanism. However, the attention mechanism in the SE network (SENet) selects all channel information for calculations, which brings essential challenges: (a) interference caused by the internal redundant information; and (b) increasing number of network calculations. To address the above problems, this work proposes a dynamic convolutional network (termed as EAM-DyNet) to reduce the number of channels in feature maps by extracting only the useful spatial information. EAM-DyNet first uses the random channel reduction and channel grouping reduction methods to remove the redundancy in the information. As the downsampling of information can lead to the loss of useful information, it then applies an adaptive average pooling method to maintain the information integrity. Extensive experimental results on the baseline demonstrate that EAM-DyNet outperformed the existing approaches, thus it can achieve higher accuracy of the network test and less network parameters.

We describe a human nasal epithelial (HNE) organoid model derived directly from patient samples that is well-differentiated and recapitulates the airway epithelium, including the expression of cilia, mucins, tight junctions, the cystic fibrosis transmembrane conductance regulator (CFTR), and ionocytes. This model requires few cells compared to airway epithelial monolayer cultures, with multiple outcome measurements depending on the application. A novel feature of the model is the predictive capacity of lumen formation, a marker of baseline CFTR function that correlates with short-circuit current activation of CFTR in monolayers and discriminates the cystic fibrosis (CF) phenotype from non-CF. Our HNE organoid model is amenable to automated measurements of forskolin-induced swelling (FIS), which distinguishes levels of CFTR activity. While the apical side is not easily accessible, RNA- and DNA-based therapies intended for systemic administration could be evaluated in vitro, or it could be used as an ex vivo biomarker of successful repair of a mutant gene. In conclusion, this highly differentiated airway epithelial model could serve as a surrogate biomarker to assess correction of the mutant gene in CF or other diseases, recapitulating the phenotypic and genotypic diversity of the population.

To investigate the characteristics of the non-Darcian water flow through saturated clay and one-dimensional rheological consolidation behaviors of the soil in the Henan Province, we conducted constant-head permeability and one-dimensional rheological consolidation tests with one-way drainage using improved permeameter and oedometer tests, respectively. We then used Hansbo’s flow equation to classify the permeability test results and one-dimensional rheological consolidation equation combined with unified hardening (UH) constitutive model considering time effect was introduced to simulate the oedometer test results. The obtained results showed that the improved constant-head permeability test device was suitable for saturated clays, and that the UH constitutive model and Hansbo’s flow equation had good applications for the saturated clays investigated in this experiment.