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Gestation length (GL) is a critical indicator of reproductive performance in sows and is closely associated with other reproductive traits, such as total number born (TNB) and number born alive (NBA). Despite its importance, the genetic mechanisms underlying GL and its impact on reproductive traits remain poorly understood. In this study, we investigated the relationship between GL and reproductive traits using 7013 farrowing records and conducted an imputed whole-genome sequence-based genome-wide association study (GWAS) for GL in first-parity sows, involving 3005 French Large White sows. Our findings revealed that the heritability of GL ranged from 0.22 to 0.26. Both excessively short and long GLs were associated with negative impacts on TNB, NBA, and other reproductive traits. A total of 64 SNPs exceeded the significance threshold, leading to the identification of two novel quantitative trait loci (QTLs) on chromosome 5 (QTL-1: 15.29–15.39 Mb and QTL-2: 12.86–12.94 Mb) and three promising candidate genes: TROAP, RFX4, and ADCY6. Gene ontology and KEGG pathway enrichment analyses revealed that these candidate genes are enriched in key biological processes, including ovarian steroidogenesis, the GnRH signaling pathway, and the regulation of cAMP biosynthesis, all of which are crucial for gestation and pregnancy maintenance. These findings improve our understanding of the genetic architecture of GL in sows and offer valuable genetic markers for enhancing reproductive efficiency in breeding programs.

This study evaluated the effects of ultrasound-assisted slightly acidic electrolyzed water (SAEW) treatment on duck breast meat storage quality. The impact of different treatments—ultrasound combined with SAEW, SAEW alone, ultrasound combined with water, and water-alone treatment—on the freshness, texture, protein oxidation, and microbiological diversity of the meat was assessed under vacuum packaging at 4 °C. The results demonstrated that the ultrasound–SAEW combination significantly slowed pH decline, inhibited total volatile basic nitrogen (TVB-N) formation, and preserved the redness (a*) and texture of duck breast meat. Additionally, carbonyl and total sulfhydryl measurements indicated that the combined treatment delayed protein oxidation. 16S rDNA analysis showed that combined treatment reduced the microbial abundance, particularly Pseudomonas and Candida. After 9 days of storage, the total viable count (TVC) of the treated duck breast meat remained within the GB 16869—2005 microbial contamination threshold for fresh meat (5.56 log10 CFU/g). These findings highlight the effectiveness of ultrasound-assisted SAEW in extending the shelf life and maintaining the quality of duck breast meat.

To improve the detection accuracy of the drone-based oriented vehicle object detection network and establish high-accuracy vehicle trajectory datasets, we present a freeway on-ramp vehicle (FRVehicle) detection dataset with oriented bounding box annotations for vehicles in freeway on-ramp scenes from drone videos. Based on this dataset, we analyzed the dimension and angle distribution patterns of road vehicle object oriented bounding boxes and designed an Asymmetric Selective Kernel Network. This algorithm dynamically adjusts the receptive field of the backbone network’s feature extraction to accommodate the detection requirements for vehicles of different sizes. Additionally, we estimate vehicle heights with high-precision object detection results, further enhancing the accuracy of the vehicle trajectory. Comparative experimental results demonstrate that the proposed Asymmetric Selective Kernel Network achieved varying degrees of improvement in detection accuracy on both the FRVehicle dataset and DroneVehicle dataset compared to the symmetric selective kernel network in most scenarios, validating the effectiveness of the method.

The aim of this study was to investigate the possible effects of phosphorylation and ubiquitination on the degradation of myofibrillar proteins in mutton with different tenderness. The longissimus thoracis lumborum muscles were chosen and divided into tender and tough groups (n = 9), and then stored at 4 °C for 1 h, 12 h, 1 d, 3 d, and 5 d postmortem. Shear force, pH, myofibril fragmentation index, AMPK activity, E3 ubiquitin ligase abundance, protein phosphorylation, and the ubiquitination levels of muscle samples were measured. The results demonstrated that the meat of samples in the tender group had a higher degradation of desmin and a lower phosphorylation level of desmin at 1 d compared with the tough group. The ubiquitination level of desmin, AMPK activity, and E3 ubiquitin ligase abundance in the tender group were noticeably higher than those in the tough group at 12 h. There was a negative correlation between the shear force and desmin degradation. The desmin degradation was negatively correlated with desmin phosphorylation and ubiquitination levels. The phosphorylation level of desmin was positively correlated with its ubiquitination. In summary, this study suggests that AMPK and E3 ubiquitin ligase concurrently play significant roles in regulating meat tenderness by regulating phosphorylation and ubiquitination in meat postmortem.

This paper investigates the stability issues of the Unmanned Surface Vehicle (USV)–Unmanned Underwater Vehicle (ROV) system induced by cable loads under real marine conditions and high-speed operation. This study focuses on the dynamic coupling characteristics of cable forces affecting the unmanned platform and outlines the variation patterns of these forces under different operational scenarios. By developing the dynamic models of the USV, UC, and UUV, a comprehensive system model for the unmanned marine platform is constructed. The accuracy of the cable model is validated through experimental results, and the coupling interference effects of the cable during collaborative operations are systematically analyzed from multiple perspectives. Additionally, the cable tension and force behaviors under high-speed cruising conditions are thoroughly examined. The results provide a solid foundation for the development of cable load prediction models for collaborative marine unmanned platforms, and offer both theoretical and numerical insights for dynamic control strategies based on cable force adjustments.

Phosphorus (P) is an essential nutrient for rice growth, and the presence of phosphate-solubilizing bacteria (PSB) is an effective means to increase soil P content. However, the direct application of PSB may have minimal significance due to their low survival in soil. Biochar serves as a carrier that enhances microbial survival, and its porous structure and surface characteristics ensure the adsorption of Bacillus megaterium. Inoculating rice husk biochar-immobilized with Bacillus megaterium (BMB) resulted in dissolved inorganic and organic P levels of 39.55 and 31.97 mL L−1, respectively. Subsequently, rice pot experiments were conducted to investigate the response of soil microbial P mobilization and P uptake in rice to fertilizer inputs. The organic fertilizer (OF) combined with BMB treatment (MOF) showed the highest soil available phosphorus (AP) at 38 days, with a value of 7.83 mg kg−1, as well as increased the pqqC abundance while decreasing the abundance of phoD bacterial communities compared with the control. Furthermore, the bioavailable P reservoir (H2O–Pi and NaHCO3–Pi) in soil was greatly increased through the fertilizer input and microbial turnover, with the highest H2O–Pi (3.66 mg kg−1) in OF treatment and the highest NaHCO3–Pi (52.65 mg kg−1) in MOF treatment. Additionally, carbon utilization analysis was applied using the commercial Biolog system, revealing that the MOF treatment significantly increased the utilization of carbohydrates, polymers, and amino acid carbon sources. Moreover, compared to the control, MOF treatment significantly increased the shoot (0.469%) and root P (0.516%) content while promoting root development and thereby supporting rice growth. Our study demonstrates that the MOF treatment displayed higher P levels in both soil and rice plants, providing a theoretical basis for further understanding the role of biochar-based bacterial agents in rice P management.

Biofilms can enhance industrial fermentation efficiency by increasing cell density, stability, and metabolic activity and have been successfully applied to the continuous production of many small-molecule chemicals. However, the continuous production of proteins by biofilms has been less studied. This study used secretory human epidermal growth factor (hEGF) as a representative product to evaluate and optimize biofilm-based continuous protein production. First, by deleting the protease and overexpressing eight key genes involved in protein secretion in Saccharomyces cerevisiae, the yield of hEGF was improved by 82.6% from 77.4 to 141.3 mg/L in shake flasks. Subsequently, the flocculation genes FLO11 and ALS3 were introduced to facilitate the establishment of a biofilm-based continuous immobilization fermentation model. The optimal strain SIC-ALS3-PDI1 produced 583.8 mg/L of hEGF, with a productivity of 4.9 mg/L/h during traditional free-cell fermentation, while it produced an average of 300.0 mg/L of hEGF in 10 continuous batches of biofilm-based fermentation, with a productivity of 6.3 mg/L/h. Although the hEGF production in biofilms was lower than that in free-cell fermentation, biofilm fermentation demonstrated greater productivity, with the advantage of not requiring seed culture for each batch of fermentation. This study provided a valuable reference for the biofilm-based production of other peptides.

Few studies are concerned with the effect of the conjugat protein on the bioactivities of the abalone gonad polysaccharide (AGP). In this study, a series of treatments, including raw material (female and male) defatting, extraction temperature (25–121 °C), proteolysis, ultrafiltration, and ethanol precipitation, was conducted to investigate the role of the conjugate protein on AGP anticoagulant activity. All AGP extracts significantly prolonged activated partial thromboplastin time (APTT) and thrombin time (TT). The strongest was observed in the female AGPs prepared at 50 and 121 °C. The most active is located at 30–300 kDa by ultrafiltration. After being exposed to neutral protease, quick shortening of APTT and TT was found in all AGPs. Further ethanol precipitating of found the longest APTT in the sediment, which contains most polysaccharides and proteins. Defatting lowered the activity of female AGP but increased that of males. Proteolysis also significantly weakened the clotting factor inhibition effect of the 50 °C female AGP, but heating seemed not affect the effect. Five fractions were obtained after the 50 °C female AGP was subjected to ion exchange column. Fraction V, with the highest protein and medium polysaccharide content, showed the strongest anticoagulant effect and was also much higher than AGSP, which was obtained by multi-step proteolysis. The findings supported positive effect of the conjugate protein in AGP anticoagulant activity.

This paper investigates the dynamical behavior of a discrete fractional-order modified Leslie–Gower model with a Michaelis–Menten-type harvesting mechanism and a Holling-II functional response. We analyze the existence and stability of the nonnegative equilibrium points. For the interior equilibrium points, we study the conditions for period-doubling and Neimark–Sacker bifurcations using the center manifold theorem and bifurcation theory. To control the chaos arising from these bifurcations, two chaos control strategies are proposed. Numerical simulations are performed to validate the theoretical results. The findings provide valuable insights into the sustainable management and conservation of ecological systems.

Shock wave boundary/layer interactions (SWBLIs) are critical in high-speed aerodynamic flows, particularly within supersonic regimes, where unsteady dynamics can induce structural fatigue and degrade vehicle performance. Conventional measurement techniques, such as pressure-sensitive paint (PSP), face limitations in frequency response, calibration complexity, and intrusive instrumentation. Similarly, MEMS-based sensors, like Kulite® sensors, present challenges in terms of intrusiveness, cost, and integration complexity. This study presents a flexible, lightweight polyvinylidene fluoride (PVDF) piezoelectric sensor array designed for high-resolution wall-pressure measurements in SWBLI research. The primary objective is to optimize low-frequency pressure fluctuation detection, addressing SWBLI’s need for accurate, real-time measurements of low-frequency unsteadiness. Fabricated using a double-sided screen-printing technique, this sensor array is low-cost, flexible, and provides stable, high-sensitivity data. Finite Element Method (FEM) simulations indicate that the sensor structure also has potential for high-frequency responses, behaving as a high-pass filter with minimal signal attenuation up to 300 kHz, although the current study’s experimental testing is focused on low-frequency calibration and validation. A custom low-frequency sound pressure setup was used to calibrate the PVDF sensor array, ensuring uniform pressure distribution across sensor elements. Wind tunnel tests at Mach 2 verified the PVDF sensor’s ability to capture pressure fluctuations and unsteady behaviors consistent with those recorded by Kulite sensors. The findings suggest that PVDF sensors are promising alternatives for capturing low-frequency disturbances and intricate flow structures in advanced aerodynamic research, with high-frequency performance to be further explored in future work.

Arabinofuranosyl nucleotide analogue (arabinoside) and the derived compounds, a family of nucleoside analogues, exhibit diverse, typically biological activities and are widely used as antibacterial, antiviral, anti-inflammatory, and antitumor drugs in both clinical and preclinical trials. Despite their long and rich history in medicinal chemistry, the biosynthesis of arabinoside has only been sporadically designed and studied and has remained a challenging task. In this study, an in vitro synthetic enzymatic biosystem was designed and constructed for the production of arabinoside from low-cost nucleoside, based on a phosphorolysis -isomerization-dephosphorylation enzymatic cascade conversion routes. The enzymatic system achieves the biosynthesis of arabinoside by isomerizing the ribose part of nucleoside to arabinose. The reaction conditions affecting the yield of arabinoside were investigated and optimized, including meticulous enzyme selection, key enzyme dosage, the concentration of orthophosphate, and reaction time. Under the optimized conditions, we achieved the production of 0.12 mM of arabinofuranosylguanine from 0.5 mM of guanosine, representing 24% of the theoretical yield. Furthermore, this biosystem also demonstrated the capability to produce other arabinosides, such as vidarabine, spongouridine, and hypoxanthine arabinofuranoside from corresponding nucleosides. Overall, our biosynthesis approach provides a pathway for the biosynthesis of arabinoside.

Food public opinion is characterized by its low ignition point, high diffusibility, persistence, and strong negativity, which significantly impact food safety and consumer trust. This paper introduces the Food Public Opinion Prevention and Control (FPOPC) model driven by deep learning and personalized recommendation algorithms, rigorously tested and analyzed through experimentation. Initially, based on an analysis of food public opinion development, a comprehensive FPOPC framework addressing all stages of food public opinion was established. Subsequently, a sentiment prediction model for food news based on user comments was developed using a Stacked Autoencoder (SAE), enabling predictions about consumer sentiments toward food news. The sentiment values of the food news were then quantified, and improvements were made in allocating Pearson correlation coefficient weights, leading to the design of a collaborative filtering-based personalized food news recommendation mechanism. Furthermore, an enhanced Bloom filter integrated with HDFS technology devised a rapid recommendation mechanism for food public opinion. Finally, the designed FPOPC model and its associated mechanisms were validated through experimental verification and simulation analysis. The results demonstrate that the FPOPC model can accurately predict and control the development of food public opinion and the entire food supply chain, providing regulatory agencies with effective tools for managing food public sentiment.

To investigate the function of the gene penF in the pentostatin and vidarabine (Ara-A) biosynthetic gene cluster in Streptomyces antibioticus NRRL 3238, PenF was recombinantly expressed and characterized. Enzymatic characterization of the enzyme demonstrated that PenF exhibited metal-dependent nucleoside 5ʹ-monophosphatase activity, showing a substrate preference for arabinose nucleoside 5ʹ-monophosphate over 2ʹ-deoxyribonucleoside 5ʹ-monophosphate and ribonucleoside 5ʹ-monophosphate. Metal ions such as Mg2+ and Mn2+ significantly enhanced enzyme activity, whereas Zn2+, Cu2+, and Ca2+ inhibited it. For vidarabine 5′-monophosphate, the Km and kcat values were determined to be 71.5 μM and 33.9 min−1, respectively. The kcat/Km value was 474.1 mM−1·min−1 for vidarabine 5-monophosphate and was 68-fold higher than that for 2′-deoxyadenosine 5′-monophosphate. Comparative sequence alignment and structural studies suggested that residues outside the primary substrate-binding site are responsible for this substrate specificity. In conclusion, PenF’s activity toward vidarabine 5ʹ-monophosphate likely plays a role in the dephosphorylation of precursors during Ara-A biosynthesis.

This study investigates the tracking of underwater cables using autonomous underwater vehicles (AUVs) equipped with side-scan sonar (SSS). AUV motion stability is crucial for effective SSS imaging, which is essential for continuous cable tracking. Traditional methods that derive AUV guidance rates directly from measured cable states often cause unnecessary jitter when imaging, complicating accurate detection. To address this, we propose a non-myopic receding-horizon optimization (RHO) strategy designed to maximize cable imaging quality while considering AUV maneuvering constraints. This strategy identifies the optimal heading decision sequence over a future horizon, ensuring stable and efficient cable tracking. We also employ a long short-term memory (LSTM) network to predict future cable states, further minimizing AUV motion instability during abrupt path changes. Given the computational limitations of AUVs, we have developed an efficient decision-making framework that can execute resource-intensive algorithms in real time. Finally, the robustness and effectiveness of the proposed algorithm were validated through comparative experiments. The results demonstrate that the proposed method outperforms existing methods in key metrics such as cable-tracking accuracy and AUV motion stability. This ensures that the AUV can acquire high-quality acoustic images of the submarine cable in an optimal state, enhancing the continuity and reliability of cable-tracking tasks.

Understanding the aerodynamic performance of scaled-down models is vital for providing crucial insights into wind energy optimization. In this study, the aerodynamic performance of a scaled-down model (12%) was investigated. This validates the findings of the unsteady aerodynamic experiment (UAE) test sequence H. UAE tests provide information on the configuration and conditions of wind tunnel testing to measure the pressure coefficient distribution on the blade surface and the aerodynamic performance of the wind turbine. The computational simulations used shear stress transport and kinetic energy (SST K-Omega) and transitional shear stress transport (SST) turbulence models, with wind speeds ranging from 5 m/s to 25 m/s for the National Renewable Energy Laboratory (NREL) Phase VI and 4 m/s to 14 m/s for the 12% scaled-down model. The aerodynamic performance of both cases was assessed at representative wind speeds of 7 m/s for low, 10 m/s for medium, and 20 m/s for high flow speeds for NREL Phase VI and 7 m/s for low, 9 m/s medium, and 12 m/s for the scaled-down model. The results of the SST K-Omega and transitional SST models were aligned with experimental test measurement data at low wind speeds. However, the SST K-Omega torque values exhibited a slight deviation. The transitional SST and SST K-Omega models yielded aerodynamic properties that were comparable to those of the 12% scaled-down model. The torque values obtained from the simulation for the full-scale NREL Phase VI and the scaled-down model were 1686.5 Nm and 0.8349 Nm, respectively. Both turbulence models reliably predicted torque and pressure coefficient values that were consistent with the experimental data, considering specific flow regimes. The pressure coefficient was maximum at the leading edge of the wind turbine blade on the windward side and minimum on the leeward side. For the 12% scaled-down model, the flow simulation results bordering the low-pressure region of the blade varied slightly.

This study reviews the applications of big data (BD) and blockchain technology in modern food testing and explores their impact on educational reform. The first part highlights the critical role of BD in ensuring food safety across the supply chain, discussing various data collection methods, such as national and international food safety databases, while addressing the challenges related to data storage and real-time information retrieval. Additionally, blockchain technology has been explored for its ability to enhance transparency, traceability, and security in the food-testing process by creating immutable records of testing data, ensuring data integrity, and reducing the risk of tampering or fraud. The second part focuses on the influence of BD and blockchain on educational reform, particularly within food science curricula. BD enables data-driven curriculum design, supporting personalized learning and more effective educational outcomes, while blockchain ensures transparency in course management and credentials. This study advocates integrating these technologies into curriculum reform to enhance both the efficiency and quality of education.

Given the critical role of true triaxial strength assessment in underground rock and soil engineering design and construction, this study explores sandstone true triaxial strength using data-driven machine learning approaches. Fourteen distinct sandstone true triaxial test datasets were collected from the existing literature and randomly divided into training (70%) and testing (30%) sets. A Multilayer Perceptron (MLP) model was developed with uniaxial compressive strength (UCS, σc), intermediate principal stress (σ2), and minimum principal stress (σ3) as inputs and maximum principal stress (σ1) at failure as the output. The model was optimized using the Harris hawks optimization (HHO) algorithm to fine-tune hyperparameters. By adjusting the model structure and activation function characteristics, the final model was made continuously differentiable, enhancing its potential for numerical analysis applications. Four HHO-MLP models with different activation functions were trained and validated on the training set. Based on the comparison of prediction accuracy and meridian plane analysis, an HHO-MLP model with high predictive accuracy and meridional behavior consistent with theoretical trends was selected. Compared to five traditional strength criteria (Drucker–Prager, Hoek–Brown, Mogi–Coulomb, modified Lade, and modified Weibols–Cook), the optimized HHO-MLP model demonstrated superior predictive performance on both training and testing datasets. It successfully captured the complete strength variation in principal stress space, showing smooth and continuous failure envelopes on the meridian and deviatoric planes. These results underscore the model’s ability to generalize across different stress conditions, highlighting its potential as a powerful tool for predicting the true triaxial strength of sandstone in geotechnical engineering applications.

Arabinoside and derived nucleoside analogs, a family of nucleoside analogs, exhibit diverse typically biological activities and are widely used as antibacterial, antiviral, anti-inflammatory, antitumor, and other drugs in clinical and preclinical trials. Although with a long and rich history in the field of medicinal chemistry, the biosynthesis of arabinoside has only been sporadically designed and studied, and it remains a challenge. Here, we constructed an in vitro multi-enzymatic cascade for the biosynthesis of arabinosides. This artificial biosystem was systematically optimized, involving an exquisite pathway design, NADP+ regeneration, meticulous enzyme selection, optimization of the key enzyme dosage, and the concentration of inorganic phosphate. Under the optimized conditions, we achieved 0.37 mM of vidarabine from 5 mM of sucrose and 2 mM of adenine, representing 18.7% of the theoretical yield. Furthermore, this biosystem also has the capability to produce other arabinosides, such as spongouridine, arabinofuranosylguanine, hypoxanthine arabinofuranoside, fludarabine, and 2-methoxyadenine arabinofuranoside, from sucrose, and corresponding nucleobase by introducing different nucleoside phosphorylases. Overall, our biosynthesis approach provides a pathway for the biosynthesis of arabinose-derived nucleoside analogs, offering potential applications in the pharmaceutical industry.

Recent Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) protocols increasingly focus on scalability and security to meet the growing demand for Distributed Ledger Technology (DLT) applications across various domains. Current BFT consensus algorithms typically require a single leader node to receive and validate votes from the majority process and broadcast the results, a design challenging to scale in large systems. We propose a fast-response consensus algorithm based on improvements to HotStuff, aimed at enhancing transaction ordering speed and overall performance of distributed systems, even in the presence of faulty copies. The algorithm introduces an optimistic response assumption, employs a message aggregation tree to collect and validate votes, and uses a dynamically adjusted threshold mechanism to reduce communication delay and improve message delivery reliability. Additionally, a dynamic channel mechanism and an asynchronous leader multi-round mechanism are introduced to address multiple points of failure in the message aggregation tree structure, minimizing dependence on a single leader. This adaptation can be flexibly applied to real-world system conditions to improve performance and responsiveness. We conduct experimental evaluations to verify the algorithm’s effectiveness and superiority. Compared to the traditional HotStuff algorithm, the improved algorithm demonstrates higher efficiency and faster response times in handling faulty copies and transaction ordering.

Objective: The aim of this study was to optimize the formulation of a C60-modified self-microemulsifying drug delivery system loaded with triptolide (C60-SMEDDS/TP) and evaluate the cytoprotective effect of the C60-SMEDDS/TP on normal human cells. Results: The C60-SMEDDS/TP exhibited rapid emulsification, an optimal particle size distribution of 50 ± 0.19 nm (PDI 0.211 ± 0.049), and a near-neutral zeta potential of −1.60 mV. The release kinetics of TP from the C60-SMEDDS/TP exhibited a sustained release profile and followed pseudo-first-order release kinetics. Cellular proliferation and apoptosis analysis indicated that the C60-SMEDDS/TP (with a mass ratio of TP: DSPE-PEG-C60 = 1:10) exhibited lower toxicity towards L02 and GES-1 cells. This was demonstrated by a higher IC50 (40.88 nM on L02 cells and 17.22 nM on GES-1 cells) compared to free TP (21.3 nM and 11.1 nM), and a lower apoptosis rate (20.8% on L02 cells and 26.3% on GES-1 cells, respectively) compared to free TP (50.5% and 47.0%) at a concentration of 50 nM. In comparison to the free TP group, L02 cells and GES-1 cells exposed to the C60-SMEDDS/TP exhibited a significant decrease in intracellular ROS and an increase in mitochondrial membrane potential (ΔψM). On the other hand, the C60-SMEDDS/TP demonstrated a similar inhibitory effect on BEL-7402 cells (IC50 = 28.9 nM) and HepG2 cells (IC50 = 107.6 nM), comparable to that of the free TP (27.2 nM and 90.4 nM). The C60-SMEDDS/TP group also exhibited a similar intracellular level of ROS and mitochondrial membrane potential compared to the SMEDDS/TP and free TP groups. Method: Fullerenol-Grafted Distearoyl Phosphatidylethanolamine-Polyethylene Glycol (DSPE-PEG-C60) was synthesized and applied in the self-microemulsifying drug delivery system. The C60-SMEDDS/TP was formulated using Cremophor EL, medium-chain triglycerides (MCT), PEG-400, and DSPE-PEG-C60, and loaded with triptolide (TP). The toxicity and bioactivity of the C60-SMEDDS/TP were assessed using normal human liver cell lines (L02 cells), normal human gastric mucosal epithelial cell lines (GES-1 cells), and liver cancer cell lines (BEL-7402 cells and HepG2 cells). The production of reactive oxygen species (ROS) after the C60-SMEDDS/TP treatment was assessed using 2′,7′-dichlorofluorescein diacetate (DCFDA) staining. The alterations in mitochondrial membrane potential (ΔψM) were assessed by measuring JC-1 fluorescence. Conclusions: The cytoprotection provided by the C60-SMEDDS/TP favored normal cells (L02 and GES-1) over tumor cells (BEL-7402 and HepG2 cells) in vitro. This suggests a promising approach for the safe and effective treatment of TP.

3D digital-image correlation (3D-DIC) is a non-contact optical technique for full-field shape, displacement, and deformation measurement. Given the high experimental hardware costs associated with 3D-DIC, the development of high-fidelity 3D-DIC simulations holds significant value. However, existing research on 3D-DIC simulation was mainly carried out through the generation of random speckle images. This study innovatively proposes a complete 3D-DIC simulation method involving optical simulation and mechanical simulation and integrating 3D-DIC, virtual stereo vision, and image super-resolution reconstruction technology. Virtual stereo vision can reduce hardware costs and eliminate camera-synchronization errors. Image super-resolution reconstruction can compensate for the decrease in precision caused by image-resolution loss. An array of software tools such as ANSYS SPEOS 2024R1, ZEMAX 2024R1, MECHANICAL 2024R1, and MULTIDIC v1.1.0 are used to implement this simulation. Measurement systems based on stereo vision and virtual stereo vision were built and tested for use in 3D-DIC. The results of the simulation experiment show that when the synchronization error of the basic stereo-vision system (BSS) is within 10−3 time steps, the reconstruction error is within 0.005 mm and the accuracy of the virtual stereo-vision system is between the BSS’s synchronization error of 10−7 and 10−6 time steps. In addition, after image super-resolution reconstruction technology is applied, the reconstruction error will be reduced to within 0.002 mm. The simulation method proposed in this study can provide a novel research path for existing researchers in the field while also offering the opportunity for researchers without access to costly hardware to participate in related research.

Whole crop corn silage (WCCS) been an important source of roughage for confined ruminants. However, at the silage feed-out phase, the rise in temperature and relative humidity under aerobic conditions breeds the production of undesirable microorganisms, such as yeast and mold. In order to investigate the conservation characteristics and aerobic stability underlying the effects of additives in whole crop corn silage (WCCS), whole crop corn (WCC) at the milk-ripe stage was ensiled with Lentilactobacillus (L.) buchneri (LB) and different proportions of Artemisia argyi (AA) for 90 days (d) at room temperature, respectively, and aerobic exposure after 90 d fermentation was also conducted. The study found that AA as an additive improved the fermentation quality and enhanced aerobic stability of WCCS, for which the addition of 60% AA increased the lactic acid fermentation rate, with the lactic acid concentration at the end of aerobic exposure significantly higher than in all other treatment groups, at 98.21 g/kg DM (p < 0.01), which decreased the relative abundance of none wanted microorganisms and reduced the content of fungal toxins (p < 0.05). After 90 d of fermentation, LB also increased the organic acids and reduced the pH compared with control, thereby improving fermentation quality. Furthermore, we also discovered that the relative abundance of Candida within the 60% AA was the highest. Candida have the ability to convert WSC into organic acids and lower pH, thus improving the quality of silage. Particularly, 60% AA could improve the fermentation quality and aerobic stability of silage through the biosynthetic pathways of phenylalanine, tyrosine and tryptophan, as well as by participation in the hydrolysis of glycoside hydrolases (GHs). Unexpectedly, the addition of AA was found to reduce the relative abundance of antibiotic resistance genes. WCC, ensiled with 60% AA, exhibited excellent fermentation quality and aerobic stability, providing a theoretical basis for understanding the mechanisms of AA which improve the quality of WCCS during the aeration phase.

cAMP-dependent protein kinase (PKA) activity regulates protein phosphorylation, with Na+ playing a crucial role in PKA activity. The aim of this study was to investigate the effects of different Na+ concentrations on PKA activity and protein phosphorylation level in postmortem muscle. The study consisted of two experiments: (1) NaCl of 0, 20, 100, 200 and 400 mM was added to a muscle homogenate incubation model to analyze the effect of Na+ concentration on PKA activity, and (2) the same concentrations were added to pure PKA in vitro incubation models at 4 °C to verify the effect of Na+ on PKA activity. The PKA activity of the muscle homogenate model increased with storage time in groups with different Na+ concentrations. High concentrations of Na+ inhibited sarcoplasmic protein phosphorylation. The PKA activity at 24 h of storage and the sarcoplasmic protein phosphorylation level at 12 h of storage in the group with 200 mM Na+ was lower than that of the other groups. After 1 h incubation, the PKA activity of samples in the 200 mM Na+ group was inhibited and lower than that in the other Na+ groups in the in vitro incubation model. These results suggest that the Na+ concentration at 200 mM could better inhibit PKA activity. This study provided valuable insights for enhancing curing efficiency and improving meat quality.

Human epidermal growth factor (hEGF) holds significant importance in the fields of medicine and cosmetics. Therefore, it becomes imperative to develop a highly efficient fermentation system for hEGF production. In this study, a stable hEGF-secreting expression strain was created by integrating the hEGF gene into the genome of Escherichia coli (E. coli) BL21, and an immobilized fermentation system was developed based on biofilm to facilitate continuous hEGF production. After optimization of fermentation conditions and gene dosage, the production of hEGF was increased from 13.9 mg/L to 52.4 mg/L in free-cell fermentation. Moreover, genetic modifications targeting dgcC, csgD, bcsA, and bcsB proved to enhance biofilm formation. When the bcsB was overexpressed in BL21-hEGF-C5, the biofilm-forming ability was enhanced by 91.1% and the production of hEGF was increased by 28% in biofilm-immobilized continuous fermentation. In conclusion, this study successfully confirms the feasibility of continuous hEGF production through the biofilm system of E. coli, providing valuable insights for the development of other proteins in the field of continuous biomanufacturing.

Theanine, polyphenols, and caffeine not only affect the flavor of tea, but also play an important role in human health benefits. However, the specific regulatory mechanism of Se NMs on fat-reducing components is still unclear. In this study, the synthesis of fat-reducing components in Fuding Dabai (FDDB) tea was investigated. The results indicated that the 100-bud weight, theanine, EGCG, total catechin, and caffeine contents of tea buds were optimally promoted by 10 mg·L−1 Se NMs in the range of 24.3%, 36.2%, 53.9%, 67.1%, and 30.9%, respectively. Mechanically, Se NMs promoted photosynthesis in tea plants, increased the soluble sugar content in tea leaves (30.3%), and provided energy for the metabolic processes, including the TCA cycle, pyruvate metabolism, amino acid metabolism, and the glutamine/glutamic acid cycle, ultimately increasing the content of amino acids and antioxidant substances (catechins) in tea buds; the relative expressions of key genes for catechin synthesis, CsPAL, CsC4H, CsCHI, CsDFR, CsANS, CsANR, CsLAR, and UGGT, were significantly upregulated by 45.1–619.1%. The expressions of theanine synthesis genes CsTs, CsGs, and CsGOGAT were upregulated by 138.8–693.7%. Moreover, Se NMs promoted more sucrose transfer to the roots, with the upregulations of CsSUT1, CsSUT2, CsSUT3, and CsSWEET1a by 125.8–560.5%. Correspondingly, Se NMs enriched the beneficial rhizosphere microbiota (Roseiarcus, Acidothermus, Acidibacter, Conexicter, and Pedosphaeraceae), enhancing the absorption and utilization of ammonium nitrogen by tea plants, contributing to the accumulation of theanine. This study provides compelling evidence supporting the application of Se NMs in promoting the lipid-reducing components of tea by enhancing its nitrogen metabolism.

Conducting precise evaluations and predictions of the environmental conditions for plant growth in green spaces is crucial for ensuring their health and sustainability. Yet, assessing the health of urban greenery and the plant growth environment represents a significant and complex challenge within the fields of urban planning and environmental management. This complexity arises from two main challenges: the limitations in acquiring high-density, high-precision data, and the difficulties traditional methods face in capturing and modeling the complex nonlinear relationships between environmental factors and plant growth. In light of the superior spatial interpolation capabilities of CEDGAN (conditional encoder–decoder generative adversarial neural network), notwithstanding its comparative lack of robustness across different subjects, and the excellent ability of FCNN (fully connected neural network) to fit multiple nonlinear equation models, we have developed two models based on these network structures. One model performs high-precision spatial attribute interpolation for urban green spaces, and the other predicts and evaluates the environmental conditions for plant growth within these areas. Our research has demonstrated that, following training with various samples, the CEDGAN network exhibits satisfactory performance in interpolating soil pH values, with an average pixel error below 0.03. This accuracy in predicting both spatial distribution and feature aspects improves with the increase in sample size and the number of controlled sampling points, offering an advanced method for high-precision spatial attribute interpolation in the planning and routine management of urban green spaces. Similarly, FCNN has shown commendable performance in predicting and evaluating plant growth environments, with prediction errors generally less than 0.1. Comparing different network structures, models with fewer hidden layers and nodes yielded superior training outcomes.

To determine whether sarcoplasmic proteins affected water migration in myofibrils during air-drying, with protein denaturation as an indicator of sarcoplasmic protein changes, the extent of sarcoplasmic protein changes in lamb during air-drying was first studied. The results showed that sarcoplasmic protein’s thermal stability decreased and secondary structure changed, indicating sarcoplasmic protein denatured in lamb during air-drying (35 °C, 60% RH, 3 m/s wind speed). Subsequently, the effect of sarcoplasmic protein solutions, dried at different times and rates, on myofibril protein–water interaction was studied in vitro. Two sets of sarcoplasmic protein solutions were dried for 0, 3, 6, and 9 h in a drying oven, resulting in different degrees of change. These two sets with higher or lower drying rates were achieved by controlling the contact area between sarcoplasmic protein solution and air. These dried sarcoplasmic protein solutions were then mixed with extracted myofibril and incubated for 2 h. The results showed a significant increase in T21 relaxation time of the incubation system when sarcoplasmic protein solution was dried at 35 °C for 3 h. This indicated that myofibrillar protein–water interaction was weakened, facilitating water migration from the inside to the outside of myofibrils. The denaturation degree of sarcoplasmic proteins was slowed by a higher drying rate, thereby alleviating the increase in the amount of immobile water within myofibrils when dried for 6 h. In conclusion, the properties of sarcoplasmic proteins were influenced by both drying rate and time, thereby influencing the water migration within myofibrils during air-drying.

The purpose of this paper is to review the research progress in the realization of the organic–inorganic hybrid thin-film packaging of flexible organic electroluminescent devices using the PEALD (plasma-enhanced atomic layer deposition) and MLD (molecular layer deposition) techniques. Firstly, the importance and application prospect of organic electroluminescent devices in the field of flexible electronics are introduced. Subsequently, the principles, characteristics and applications of PEALD and MLD technologies in device packaging are described in detail. Then, the methods and process optimization strategies for the preparation of organic–inorganic hybrid thin-film encapsulation layers using PEALD and MLD technologies are reviewed. Further, the research results on the encapsulation effect, stability and reliability of organic–inorganic hybrid thin-film encapsulation layers in flexible organic electroluminescent devices are discussed. Finally, the current research progress is summarized, and the future research directions and development trends are prospected.

Basalt fiber-reinforced pea gravel concrete (BFRPGC) has remarkable potential for use as the retrofitting covers for masonry walls. However, a quantitative understanding of the mechanical properties of the BFRPGC material is still a perceived gap in the current literature. In this study, the role of basalt fibers in pea gravel concrete was evaluated by a comprehensive experimental investigation involving compressive strength tests and splitting tensile tests. Fiber length and volume fraction were selected as the key parameters. Two fiber lengths of 6 mm and 12 mm were considered, while the volume fraction corresponding to each of the fiber lengths was increased from 0.3% to 0.8%, with a step of 0.1%. The measured strengths were not simply proportional to the fiber volume fraction. The reason behind this phenomenon, i.e., the coupling effect of the bridging role of basalt fibers on concrete microcracks and the fiber agglomeration in concrete, was analyzed. The best performance of the BFRPGC material was achieved by incorporating 12-millimeter-length fibers with a volume fraction of 0.4%. Compared to that of the reference pea gravel concrete, a significant increase of up to 44.5% in compressive strength was recorded in this case. Furthermore, the failure mechanism of basalt fibers in pea gravel concrete was disclosed via the scanning electron microscope observations. In addition, the uniaxial compressive stress–strain model of the BFRPGC material was established.

Fermentation of dietary fiber (DF) is beneficial for gut health, but its prebiotic effects are often impeded in the distal large intestine because of the fast degradation of fermentable substrates. One way to enhance the prebiotic effect of DF is to deliver fibers to the lower parts of the gut, which can be achieved by mixing different kinds of fiber. Therefore, in the present study, an ileum-cannulated pig model was employed to investigate the fermentation influence in the large intestine by infusing resistant starch solely (RS, fast fermentable fiber) and mixing with other fibers (xylan or cellulose). Twenty-four ileum-cannulated growing pigs were divided into four groups: one control group receiving saline ileal infusions and three experimental groups infused with RS, RS with xylan, or RS with cellulose. Fecal and plasma samples were analyzed for gut microbiota composition, short-chain fatty acids (SCFAs), and blood biochemistry. Results indicated no significant differences between the RS and control group for the microbiome and SCFA concentration (p > 0.05). However, RS combined with fibers, particularly xylan, resulted in enhanced and prolonged fermentation, marked by an increase in Blautia and higher lactate and acetate production (p < 0.05). In contrast, RS with cellulose infusion enriched bacterial diversity in feces (p < 0.05). Blood biochemistry parameters showed no significant differences across groups (p > 0.05), though a trend of increased glucose levels was noted in the treatment groups (p < 0.1). Overall, RS alone had a limited impact on the distal hindgut microbiota due to rapid fermentation in the proximal gut, whereas combining RS with other fibers notably improved gut microecology by extending the fermentation process.

We analyzed metagenome data of feces from sows at different physiological periods reared on large-scale farms in Anhui Province, China, to provide a better understanding of the microbial diversity of the sow intestinal microbiome and the structure of antibiotic-resistance genes (ARGs) and virulence genes it carries. Species annotation of the metagenome showed that in the porcine intestinal microbiome, bacteria were dominant, representing >97% of the microorganisms at each physiological period. Firmicutes and Proteobacteria dominated the bacterial community. In the porcine gut microbiome, the viral component accounted for an average of 0.65%, and the species annotation results indicated that most viruses were phages. In addition, we analyzed the microbiome for ARGs and virulence genes. Multidrug-like, MLS-like, and tetracycline-like ARGs were most abundant in all samples. Evaluation of the resistance mechanisms indicated that antibiotic inactivation was the main mechanism of action in the samples. It is noteworthy that there was a significant positive correlation between ARGs and the total microbiome. Moreover, comparative analysis with the Virulence Factor Database showed that adhesion virulence factors were most abundant.

Multi-degree-of-freedom piezoelectric motors have the advantages of high torque and resolution, simple structure, and direct drive, which are widely used in robot wrist joints, deep-sea mechanisms, medical equipment, and space mechanisms. To solve the problems of high force/torque coupling degree and ball low stator and rotor bonding strength of the traditional traveling wave type three-degree-of-freedom piezoelectric spherical motor, a new structure of ball-hinged piezoelectric spherical motor is proposed. Through coordinate transformation and force analysis, the driven mathematical model of the spherical motor is given. The model shows that the three degrees of freedom of the motor are coupled with each other. According to the mathematical model of the spherical motor, the mechanical properties of the motor are analyzed by the computer simulation. The results show that the stalling torque coefficient kt has a linear relationship with the friction coefficient ε and the stator preload Fc, has a nonlinear relationship with the stator radius R and the rotor radius r, and increases with the increase of R and decreases with the increase of r. The no-load speed of motor ωn is not related to the friction coefficient ε and the stator preload Fc, and increases with the increase of R and decreases with the increase of r. The anisotropic characteristics of torque and speed of a spherical motor are further analyzed, which lays a theoretical foundation for the drive control of a spherical motor.

Variable pressure salting (VPS) is considered a novel salting approach to improve meat quality. This study aimed to investigate the effects of roasted duck’s edible and nutritional quality after VPS through serum biochemical indicators and in vivo digestion properties in rats. The results show that roasted duck after VPS led to an increase in the total protein content (57.24 g/L) and blood glucose levels (6.87 mmol/L), as well as a decrease in the blood urea nitrogen content (11.81 mmol/L), in rats. Compared to rats fed base diets and roasted duck after static wet salting (SWS), those ingesting roasted duck after VPS exhibited higher values of apparent protein digestibility (51.24%), pepsin activity (2.40 U/mg), and trypsin activity (389.80 U/mg). Furthermore, VPS treatment improved the textural properties and microstructure of duck breasts shown by a higher immobilized water relaxation area and more ordered protein structures (α-helixes and β-sheets). These improvements enhanced the protein anabolism capacity and in vivo digestion properties in rats. Therefore, VPS represents a beneficial salting method for promoting effective digestion and absorption in rats.

With the widespread promotion of the green feeding concept of “substitution and resistance”, there is a pressing need for alternative products in feed and breeding industries. Employing lactic acid bacteria represents one of the most promising antimicrobial strategies to combat infections caused by pathogenic bacteria. As such, we analyzed the intestinal tract of Anhui local pig breeds, including LiuBai Pig, YueHei Pig, and HuoShou Pig, to determine the composition and diversity of intestinal microbiota using 16S rRNA. Further, the functionality of the pigs’ intestinal microbiota was studied through metagenomic sequencing. This study revealed that lactic acid bacteria were the primary contributors to the functional composition, as determined through a species functional contribution analysis. More specifically, the functional contribution of lactic acid bacteria in the HuoShou Pig group was higher than that of the LiuBai Pig and YueHei Pig. Subsequently, the intestinal contents of the HuoShou Pig group were selected for the screening of the dominant lactic acid bacteria strains. Out of eight strains of lactic acid bacteria, the acid-production capacity, growth curve, and tolerance to a simulated intestinal environment were assessed. Additional assessments included surface hydrophobicity, the self-aggregation capability, co-agglutination of lactic acid bacteria with pathogenic bacteria, and an in vitro bacteriostatic activity assay. Lactobacillus johnsonii L5 and Lactobacillus reuteri L8 were identified as having a strong overall performance. These findings serve as a theoretical basis for the further development of pig-derived probiotics, thereby promoting the application of lactic acid bacteria to livestock production.

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

In recent years, with the intensification of climate change, the development of low-carbon buildings (LCBs) has gained great momentum, and building information modeling (BIM) is perceived as the most promising path. However, systematic integration, review, and analysis of research in the field of BIM for LCBs has been lacking, which may hinder the potential of BIM in assisting the achievement of the goal of LCBs. Therefore, this study explores the current research status of BIM for LCBs and the directions for further investigation. A hybrid literature review method was utilized, which consisted of quantitative and qualitative analyses. Firstly, a quantitative bibliometric analysis was conducted on 158 studies searched from the Web of Science core collection. The most influential institutions, journals, studies, and keywords were identified. The most often used terms were BIM, life-cycle assessment (LCA), design, construction, digital technologies (DTs), life cycle, and integration. Secondly, a systematic qualitative analysis was conducted of 117 carefully selected studies to identify the research focus of different stages (e.g., design, construction, operation, and demolition) of BIM for LCBs. The results showed that studies pertaining to BIM for LCBs mostly took a whole life-cycle perspective, followed by a focus on the design stage, while the volumes of studies focusing on BIM for LCBs in the operation and demolition stages were relatively small. Currently, research focuses on how the latest methods and technologies can be utilized to help reduce carbon dioxide emissions over the life cycle of a building, e.g., BIM-LCA and BIM combined with DTs. Lastly, the challenges and prospects of integrating BIM with LCA and emerging DTs for LCBs are discussed in depth. Five topics, such as BIM-based interdisciplinary collaboration and improving and validating the BIM integrated sustainability calculation models, are proposed as future research trends. This study points out the current research hotspots and future research trends in the field and builds a solid starting point for scholars who want to devote themselves to this field. For practitioners in LCBs, the research findings could serve as a practical reference for better understanding the potential of BIM for LCBs so as to take full advantage of BIM to more effectively realize the goal of LCBs.

White tea, known for its high polyphenol content, boasts impressive antioxidant properties, but its practical applications remain promising. In this study, we successfully developed a liquid polyphenolic preparation (wtofLPP) using white tea and osmanthus flowers, characterized by its rich antioxidant content and favorable rheological properties. This formulation offers a strong foundation for the creation and utilization of innovative antioxidant-rich food products. Notably, wtofLPP significantly enhanced the activity of certain antioxidant enzymes in both KM mice and their offspring, leading to a reduction in malondialdehyde (MDA) levels, prolonged swimming endurance, and a marked increase in levels of active antioxidant compounds. Furthermore, our study highlights that fatigue stress can impact offspring mice, suggesting that oxidative damage in parents may influence their offspring, potentially affecting their genetic function.

With the global attention given to energy issues, the electrification of aviation and the development of more electric aircraft (MEA) have become important trends in the modern aviation industry. The electric actuator plays multiple roles in aircraft such as flight control, making it a crucial technology for MEA. Given the limited space available inside an aircraft, the power density of electric actuators has become a critical design factor. However, the pursuit of high power density results in the need for larger rated power and higher switching frequency, which can lead to severe electromagnetic interference (EMI) issues. This, in turn, poses significant challenges to the overall reliability of the electric actuator. This paper provides a comprehensive review of EMI in high power density motor drive systems for electric actuator systems. Firstly, the state of the art of electric actuator systems are surveyed, pointing out the contradictory relationship between high power density and EMI. Subsequently, various EMI modeling approaches of motor control systems are reviewed. Additionally, the main EMI suppression methods are summarized. Active EMI mitigation methods are emphasized in this paper due to their advantages of higher power density compared with passive EMI filters. Finally, the paper concludes by summarizing the EMI research in motor drive systems and offering the prospects of electric actuators.

Objective: The objective of this study was to examine the preparation process of DSPE-PEG-C60/NCTD micelles and assess the impact of fullerenol (C60)-modified micelles on the nephrotoxicity and antitumor activity of NCTD. Method: The micelles containing NCTD were prepared using the ultrasonic method and subsequently optimized and characterized. The cytotoxicity of micelles loaded with NCTD was assessed using the CCK-8 method on human hepatoma cell lines HepG2 and BEL-7402, as well as normal cell lines HK-2 and L02. Acridine orange/ethidium bromide (AO/EB) double staining and flow cytometry were employed to assess the impact of NCTD-loaded micelles on the apoptosis of the HK-2 cells and the HepG2 cells. Additionally, JC-1 fluorescence was utilized to quantify the alterations in mitochondrial membrane potential. The generation of reactive oxygen species (ROS) following micelle treatment was determined through 2′,7′-dichlorofluorescein diacetate (DCFDA) staining. Results: The particle size distribution of the DSPE-PEG-C60/NCTD micelles was determined to be 91.57 nm (PDI = 0.231). The zeta potential of the micelles was found to be −13.8 mV. The encapsulation efficiency was measured to be 91.9%. The in vitro release behavior of the micelles followed the Higuchi equation. Cellular experiments demonstrated a notable decrease in the toxicity of the C60-modified micelles against the HK-2 cells, accompanied by an augmented inhibitory effect on cancer cells. Compared to the free NCTD group, the DSPE-PEG-C60 micelles exhibited a decreased apoptosis rate (12%) for the HK-2 cell line, lower than the apoptosis rate observed in the NCTD group (36%) at an NCTD concentration of 75 μM. The rate of apoptosis in the HepG2 cells exhibited a significant increase (49%), surpassing the apoptosis rate observed in the NCTD group (24%) at a concentration of 150 μM NCTD. The HK-2 cells exhibited a reduction in intracellular ROS and an increase in mitochondrial membrane potential (ΔψM) upon exposure to C60-modified micelles compared to the NCTD group. Conclusions: The DSPE-PEG-C60/NCTD micelles, as prepared in this study, demonstrated the ability to decrease cytotoxicity and ROS levels in normal renal cells (HK-2) in vitro. Additionally, these micelles showed an enhanced antitumor activity against human hepatocellular carcinoma cells (HepG2, BEL-7402).

Engagement ability plays a fundamental role in allocating attentional resources and helps us perform daily tasks efficiently. Therefore, it is of great importance to recognize engagement level. Electroencephalography is frequently employed to recognize engagement for its objective and harmless nature. To fully exploit the information contained in EEG signals, an engagement recognition method integrating multi-domain information is proposed. The proposed method extracts frequency information by a filter bank. In order to utilize spatial information, the correlation-based common spatial patterns method is introduced and extended into three versions by replacing different correlation coefficients. In addition, the Hilbert transform helps to obtain both amplitude and phase information. Finally, features in three domains are combined and fed into a support vector machine to realize engagement recognition. The proposed method is experimentally validated on an open dataset composed of 29 subjects. In the comparison with six existing methods, it achieves the best accuracy of 87.74±5.98% in binary engagement recognition with an improvement of 4.03%, which proves its efficiency in the engagement recognition field.

Contactless and non-destructive measuring tools can facilitate the moisture monitoring of bagged or bulk grain during transportation and storage. However, accurate target recognition and size prediction always impede the effectiveness of contactless monitoring in actual use. This paper developed a novel 3D reconstruction method upon multi-angle point clouds using a binocular depth camera and a proper Yolo-based neural model to resolve the problem. With this method, this paper developed an embedded and low-cost monitoring system for the in-warehouse grain bags, which predicted targets’ 3D size and boosted contactless grain moisture measuring. Identifying and extracting the object of interest from the complex background was challenging in size prediction of the grain silo-bag on a conveyor. This study first evaluated a series of Yolo-based neural network models and explored the most appropriate neural network structure for accurately extracting the grain bag. In point-cloud processing, this study constructed a rotation matrix to fuse multi-angle point clouds to generate a complete one. This study deployed all the above methods on a Raspberry Pi-embedded board to perform the grain bag’s 3D reconstruction and size prediction. For experimental validation, this study built the 3D reconstruction platform and tested grain bags’ reconstruction performance. First, this study determined the appropriate positions (−60°, 0°, 60°) with the least positions and high reconstruction quality. Then, this study validated the efficacy of the embedded system by evaluating its speed and accuracy and comparing it to the original Torch model. Results demonstrated that the NCNN-accelerated model significantly enhanced the average processing speed, nearly 30 times faster than the Torch model. The proposed system predicted the objects’ length, width, and height, achieving accuracies of 97.76%, 97.02%, and 96.81%, respectively. The maximum residual value was less than 9 mm. And all the root mean square errors were less than 7 mm. In the future, the system will mount three depth cameras for achieving real-time size prediction and introduce a contactless measuring tool to finalize grain moisture detection.

Daylighting serves as a crucial sustainable strategy in assessing the built environment. Climate-based daylight metrics (CBDMs) have been widely employed to evaluate the dynamic performance of daylight. However, conventional CBDM calculations heavily rely on time-consuming full-scale computer simulations. In addition, the CBDMs need representative annual daylight data that are essential for CBDM analysis, and can pose challenges in many locations. Even when suitable daylight data are available, they may not accurately reflect current trends and conditions. This study aims to determine the various CBDMs using both the 15 CIE Standard Skies and the three representative skies specific to Hong Kong. All data were simulated from a software named RADIANCE (version 5.3). The R2s of the CBDMs under both the 15 CIE Standard Skies and the three representative skies were more than 0.89, and the MBEs and RMSEs were not more than 5.4% and 9.1%, respectively, when the outdoor illuminance measured in 2004 was employed. The findings could be adopted for other locations where the required daylight parameters were not systematically recorded.

A comprehensive and scientific system for measuring the quality of economic development will provide the basis for and guarantee high-quality economic development (HQED) in China. In this paper, we constructed an indicator-evaluating system for the high-quality development of the western region’s economy according to a new development concept and the relevant requirements of western development and measured the composite index and sub-dimension index of its HQED from 2000 to 2020 using the entropy method; revealed the regional differences and sources of western HQED using the Dagum Gini index (GI) decomposition method; and analyzed the evolution of HQED using kernel density estimation and the Markov probability transfer matrix. The study showed that western HQED was on the rise year by year, but there was a large gap between the 11 provinces, characterized by “high in the middle and low on the edge” values in general; inter-regional differences constituted the main source of overall differences; and western HQED showed “club convergence” in a steady state, with upward shifts more likely than downward shifts.

Horizontal deformation is a key parameter in the structural assessment of concrete piles, especially in landslide cases. However, the existing deformation-monitoring methods cannot satisfy the demands of long-term monitoring. Therefore, a new method based on distributed optical-fibre sensing technology is proposed for the long-term monitoring of the horizontal deformation of concrete piles. First, a distributed long-gauge optical-fibre sensor is embedded into a fibre-reinforced polymer (FRP) for the excellent distributed strain measurement of the concrete piles in damage cases, such as concrete cracking and reinforcement yielding. Second, based on the typical Winkler beam model, a calculation theory can be constructed for the horizontal deformation of the concrete piles with the input of the strain measurement. Lastly, the proposed method is verified via finite element simulation and static experiments in a laboratory, and the results show good accuracy. Before the case of reinforcement yielding, the largest measurement error of deformation is about 1 mm. It can be up to several millimetres after reinforcement yielding due to the large gap between the calculation model and the actual structure, while the relative measurement error is only about 10%. Due to the distributed strain measurement, the inside horizontal deformation distribution of the concrete piles can be monitored online with the proposed method to implement a detailed assessment of the pile health. Additionally, considering the excellent long-term performance of FRPs and optical-fibre sensors, the proposed method can be applied for the long-term deformation monitoring of concrete piles.

Semiconductor oxide gas sensors have important applications in environmental protection, domestic health, and other fields. Research has shown that designing the morphology of sensitive materials can effectively improve the sensing characteristics of sensors. In this paper, by controlling the solvothermal reaction time, a unique hexagonal flower-like structure of In2O3 materials consisting of cuboid nanorods with a side length of 100–300 nm was prepared. The characterization results indicated that with the increase in reaction time, the materials exhibited significant morphological evolution. When the solvent heating time is 5 h, the flower-like structure is basically composed of hexagonal nanosheets with a thickness of several hundred nanometers and a side length of several micrometers. With the increase in reaction time, the apex angles of the nano sheets gradually become obtuse, and, finally, with the Ostwald ripening process, they become cuboid nanorods with side lengths of 100–300 nanometers, forming unique micro-flowers. Among them, the material prepared with a reaction time of 20 h has good sensing performance for NO2, exhibiting low operating temperature and detection limit, good selectivity, repeatability, and long-term stability, thus suggesting a good application prospect.

High water pressure has been identified as the direct cause of water seepage problems in tunnels. Consequently, it is imperative to ascertain the safety load-bearing limits of tunnel linings in high-pressure, water-rich strata. In this study, FLAC3D (V5.0) numerical simulation software was employed to establish seepage models of tunnels under high-pressure, water-rich conditions, taking an actual engineering project as a reference. The hydrostatic pressure on tunnel linings under various conditions, including different permeability coefficients of the surrounding rock, grouting rings, levels of the water table, and coordinates of lining positions, was computed. By extracting the results of these simulations, correlations between lining water pressure and various parameters were analyzed, and preliminary hydrostatic pressure calculation formulas were deduced. Through regression analysis using SPSS (19.0) software, a general calculation formula for lining water pressure was derived. Given similar surrounding rock conditions, it was revealed that railway tunnel lining types adhere to a universal standard. The calculation formula for lining water pressure, when integrated with lithostatic pressure in the seepage model, facilitates the computation of the maximum pressure head that the tunnel lining can withstand under different conditions. A tabulation summarizing safe water head heights under various conditions is also presented, which enables rapid consultation of the safe load-bearing range of tunnel lining under corresponding conditions. This study provides a new calculation method for the lining water pressure of a water-rich railway tunnel, filling the literature gap. The safe tunnel head query table provides a new research approach for the design of water-rich tunnels. The research method in this article is rare in the literature, and the research approach has obvious innovations. The findings of this study have the potential to provide a theoretical foundation and data reference for the structural design of tunnel linings and the remediation of related issues.

This study targets the low accuracy and efficiency of the support vector machine (SVM) algorithm in rolling bearing fault diagnosis. An improved grey wolf optimizer (IGWO) algorithm was proposed based on deep learning and a swarm intelligence optimization algorithm to optimize the structural parameters of SVM and improve the rolling bearing fault diagnosis. A nonlinear contraction factor update strategy was also proposed. The variable coefficient changes with the shrinkage factor α. Thus, the search ability was balanced at different early and late stages by controlling the dynamic changes of the variable coefficient. In the early stages of optimization, its speed is low to avoid falling into local optimization. In the later stages of optimization, the speed is higher, and finding the optimal solution is easier, balancing the two different global and local optimization capabilities to complete efficient convergence. The dynamic weight update strategy was adopted to perform position updates based on adaptive dynamic weights. First, the dataset of Case Western Reserve University was used for simulation, and the results showed that the diagnosis accuracy of IGWO-SVM was 98.75%. Then, the IGWO-SVM model was trained and tested using data obtained from the full-life-cycle test platform of mechanical transmission bearings independently researched and developed by Nanjing Agricultural University. The fault diagnosis accuracy and convergence value of the adaptation curve were compared with those of PSO-SVM (particle swarm optimization) and GWO-SVM diagnosis models. Results showed that the IGWO-SVM model had the highest rolling bearing fault diagnosis accuracy and the best diagnosis convergence.

Mycotoxins, secondary metabolites of fungi, are a major obstacle to the utilization of animal feed for various reasons. Wheat straw (WS) is hollow, and miscellaneous bacteria can easy attach to its surface; the secondary fermentation frequency after silage is high, and there is a risk of mycotoxin poisoning. In this study, a storage fermentation process was used to preserve and enhance fermentation quality in WS through the addition of Artemisia argyi (AA), which is an effective method to use WS resources and enhance aerobic stability. The storage fermentation of WS treated with AA had lower pH and mycotoxin (AFB1 and DON) values than the control due to rapid changes in microbial counts, especially in the 60% AA groups. Meanwhile, the addition of 60% AA improved anaerobic fermentation profiles, showing higher lactic acid contents, leading to increased efficiency of lactic acid fermentation. A background microbial dynamic study indicated that the addition of 60% AA improved the fermentation and aerobic exposure processes, decreased microbial richness, enriched Lactobacillus abundance, and reduced Enterobacter and Aspergillus abundances. In conclusion, 60% AA treatment could improve the quality by increase fermentation quality and improve the aerobic stability of WS silage by enhancing the dominance of desirable Lactobacillus, inhibiting the growth of undesirable microorganisms, especially fungi, and reducing the content of mycotoxins.

The mechanism of blast damage to steel-clad concrete-filled steel tube (SCCFST) arched protective doors is studied using the dynamic response characteristics of such loads under the action of blast shock wave loads, and the ultimate blast load-bearing capacity formula is derived based on the “plastic hinge” damage mode of the doors using limit analysis, which explores the effect of the blast shock wave. The effect of the design parameters of each component of the protective door on the load-bearing capacity subjected to blast shock waves is discussed. Results show that the damage mechanism under a uniform radial load on the outer surface of the SCCFST arched protective door is characterized by the plastic hinge lines at the two arch feet, which results in a slip fracture and renders the protective door unstable. The load-bearing capacity of the SCCFST arched protective door depends on the coordinated functioning of the cross-sectional outer cladding steel plate and inner connecting partition, concrete-filled steel tube, and restraining concrete outside the steel tube. The load-bearing capacity of each of the three parts differs with the varying cross-sectional occupancies.

Chinese prickly ash and cinnamon contain many antioxidants, which scavenge free radicals and can reduce many harmful compounds, such as heterocyclic aromatic amines (HAAs). Modern technologies used for cooking, such as the use of superheated steam roasting, are beneficial in decreasing the development of HAAs. The current study was based on the use of these two spices in roasted lamb patties to mitigate the formation of HAAs in superheated steam roasted patties. Results exhibited significant differences (p < 0.05) in the content of both polar and non-polar HAAs as compared to control patties. In cinnamon roasted patties, polar HAAs were reduced from 23.76 to 10.56 ng g−1, and non-polar HAAs were reduced from 21.34 to 15.47 ng g−1. In Chinese prickly ash patties, polar and non-polar HAAs were 43.60 ng g−1 and 35.74 ng g−1, respectively. Similarly, cinnamon-treated patties showed a significantly higher (p < 0.05) reduction in polar HAAs (23.52 to 12.41 ng g−1) than non-polar (16.08 to 9.51 ng g−1) at concentrations of 0.5–1.5%, respectively, as compared to the control, with 45.81 ng g−1 polar and 35.09 ng g−1 non-polar HAAs. The polar HAAs tested were PhIP, DMIP, IQx, and 8-MeIQx, while the non-polar were harman and norharman. Both spices and superheated steam controlled HAAs to a significant level in lamb meat patties.