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This article presents the results of deformation characteristics and crack stress thresholds of cement stone under different acid treatment times. A series of true triaxial tests were conducted on cement stones under four sulfuric acid treatment times (0, 7, 14, and 28 days). The microstructures of cement stone under different acid treatment times were examined. In the range of 0 to 14 days, the damaging effect of sulfuric acid dominated, and the structural integrity was damaged by sulfuric acid. In the range of 14 to 28 days, the strengthening effect of calcium sulfate precipitate dominated, and the structural integrity was enhanced by calcium sulfate precipitate. The cement stone exhibited anisotropic deformation characteristics under true triaxial stress states. With an increase in acid treatment time, the deformation modulus of cement stone first decreased and then slightly increased. The crack stress thresholds first increased and then decreased with an increasing intermediate principal stress coefficient. With an increase in acid treatment time, the crack stress thresholds first decreased and then slightly increased. Substantially, the ratio of crack stress thresholds was analyzed. The proportion of the unstable crack growth stage and crack growth stage increased with minimum principal stress. Additionally, the proportion of the unstable crack growth stage and thecrack growth stage first increased and then decreased with increasing acid treatment time. However, the proportion of the stable crack growth stage had the opposite variation law to that of the unstable crack growth stage and crack growth stage.

Residual stress induced by solution treatment in 6061 aluminum alloy can lead to workpiece deformation, or even premature failure. The efficiency of traditional heat treatment for relieving residual stress is relatively low. Therefore, this study introduces a novel cryogenic treatment technique to reduce residual stress. The optimal cryogenic process parameters were achieved by orthogonal experiments: cryogenic temperature of 113 K, holding time of 24 h, 1 cryogenic cycle, and a cooling rate of 3 K·min−1, and the residual stress of aluminum alloy was measured by the blind hole method. The microstructural evolutions in 6061 aluminum alloy were tested by OM, SEM, and TEM. The results show that the introduction of cryogenic treatment can reduce residual stress in 6061 aluminum alloy by 64%, mainly due to the reduction of dislocations and the uniform distribution of β’’ phase.

This study presents the development of predictive models for concrete performance, specifically targeting the compressive strength and slump value, utilizing the quantities of individual raw materials in the concrete mix design as input variables. Three distinct machine learning approaches—Backpropagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF)—were employed to establish the prediction models independently. In the model construction process, the Particle Swarm Optimization (PSO) algorithm was integrated with cross-validation to fine-tune the hyperparameters of each model, ensuring optimal performance. Following the completion of training and modeling, a comprehensive comparison of the predictive accuracy among the three models was conducted, with the aim of selecting the most suitable model for incorporation into an optimized objective function. The findings reveal that among the chosen machine learning techniques, BPNN exhibited superior predictive capabilities for the compressive strength of concrete. Specifically, in the validation set, BPNN achieved a high correlation coefficient (R) of 0.9531 between the predicted and actual outputs, accompanied by a low Root Mean Square Error (RMSE) of 4.2568 and a Mean Absolute Error (MAE) of 2.6627, indicating a precise and reliable prediction. Conversely, for the prediction of the concrete slump value, RF outperformed the other two models, demonstrating a correlation coefficient (R) of 0.8986, an RMSE of 9.4906, and an MAE of 5.5034 in the validation set. This underscores the effectiveness of RF in capturing the complexity and variability inherent in slump behavior. Overall, this research highlights the potential of integrating advanced machine learning algorithms with optimization techniques for enhancing the accuracy and efficiency of concrete performance predictions. The identified optimal models, BPNN for compressive strength and RF for slump, can serve as valuable tools for engineers and researchers in the field of construction materials, facilitating the design of concrete mixes tailored to specific performance requirements.

Conventional pulp capping materials have limited anti-inflammatory capacity. It is necessary to develop more effective pulp capping material for the treatment of inflamed pulps. Tannic acid (TA) is a natural, water-soluble polyphenol with antimicrobial and anti-inflammatory properties. This study aimed to investigate the effects of a tannin-containing hydroxypropyl chitin hydrogel (HPCH/TA hydrogel) as an innovative pulp capping material. The physicochemical properties of the composite hydrogels were characterized. The effects of HPCH/TA hydrogel as a pulp capping material were evaluated in vitro and in vivo. The underlying mechanism of the anti-inflammatory effects of HPCH/TA hydrogel was explored. The HPCH/TA hydrogel demonstrated favorable temperature sensitivity, injectability, and antibacterial properties. In vitro, the HPCH/TA hydrogel effectively promoted the proliferation of human dental pulp cells and inhibited interleukin-1β, interleukin-6, and tumor necrosis factor-α expression, possibly by suppressing the nuclear factor kappa-B pathway. In vivo, on the fourth day after capping, the HPCH/TA hydrogel group showed lower inflammatory scores compared to the control and iRoot BP Plus (commercial pulp capping material) group. By the sixth week, complete reparative dentin formation was observed in the HPCH/TA hydrogel group, with no difference in thickness compared to the iRoot BP Plus group. Collectively, the HPCH/TA hydrogel holds promise as a bioactive pulp capping material for promoting the repair of inflamed pulp in vital pulp therapy.

Herein, we conducted an experimental test on basalt fiber-reinforced concrete with a high content of construction and demolition waste and then established some mathematical models based on Taylor’s formula. The concrete was prepared by using recycled clay brick powder in place of cement and recycled coarse aggregates as a substitution for natural coarse aggregates. The basalt fiber in weight dosages of 0, 0.1, 0.3, and 0.5% was used for reinforcement. The results showed that the compressive strength of concrete declined as the content of recycled aggregates increased, while the compressive strength first increased and then decreased as the basalt fiber dosage lifted. Regarding the splitting tensile strength, the reinforcement effect of basalt fiber in concrete with a high content of recycled aggregate is more significant when compared to its to its counterpart, which contains no or fewer recycled aggregates. The concrete with 0.5% basalt fiber dosage and 100% recycled aggregate content retains an equivalent compressive strength as to that of natural aggregate concrete and has about a 90% splitting tensile strength. In addition, the cubic function in comparison to the quadratic function has a higher fitting accuracy.

Ubiquitination modifications permit the degradation of labelled target proteins with the assistance of proteasomes and lysosomes, which is the main protein degradation pathway in eukaryotic cells. Polyubiquitination modifications of proteins can also affect their functions. De-ubiquitinating enzymes reverse the process of ubiquitination via cleavage of the ubiquitin molecule, which is known as a de-ubiquitination. It was demonstrated that ubiquitination and de-ubiquitination play key regulatory roles in fatty acid transport, de novo synthesis, and desaturation in dairy mammary epithelial cells. In addition, natural plant extracts, such as stigmasterol, promote milk fat synthesis in epithelial cells via the ubiquitination pathway. This paper reviews the current research on ubiquitination and de-ubiquitination in dairy milk fat production, with a view to providing a reference for subsequent research on milk fat and exploring new directions for the improvement of milk quality.

To improve the reliability and maintainability of the nuclear safety-class digital control system (DCS), this paper conducts a study on the fault prediction of critical components in the output circuit of the nuclear safety-class signal conditioning module. To address the issue of insufficient feature extraction for the minor offset fault feature and the low accuracy of fault prediction, a predictive model based on stacked denoising autoencoder (SDAE) feature extraction and an improved gated recurrent unit (GRU) is proposed. Therefore, fault simulation modeling is performed for critical components of the signal output circuit to obtain fault datasets of critical components, and the SDAE model is used to extract fault features. The fault prediction model based on GRU is established, and the number of hidden layers, the number of hidden layer nodes, and the learning rate of the GRU model are optimized using the adaptive gray wolf optimization algorithm (AGWO). The prediction performance evaluation metrics include the root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and absolute error (EA), which are used for evaluating the prediction results of models such as the AGWO-GRU model, recurrent neural network (RNN) model, and long short-term memory network (LSTM). The results show that the GRU model optimized by AGWO has a better prediction accuracy (errors range within 0.01%) for the faults of the circuit critical components, and, moreover, can accurately and stably predict the fault trend of the circuit.

In this paper, a new method involving a wear-resistant and reusable template is proposed for the preparation of high-mechanical-strength superhydrophobic polymer film based on wire electrical discharge machining (WEDM). A solid−liquid-contact-angle simulation model was established to obtain surface-texture types and sizes that may achieve superhydrophobicity. The experimental results from template preparation show that there is good agreement between the simulation and experimental results for the contact angle. The maximum contact angle on the template can reach 155.3° given the appropriate triangular surface texture and WEDM rough machining. Besides, the prepared superhydrophobic template exhibits good wear resistance and reusability. PDMS superhydrophobic polymer films were prepared by the template method, and their properties were tested. The experimental results from the preparation of superhydrophobic polymer films show that the maximum contact angle of the polymer films can be up to 154.8° and that these films have good self-cleaning and anti-icing properties, wear resistance, bending resistance, and ductility.

This paper describes a study on the heat transfer properties of the deeply buried pipeline energy pile group, which is an efficient and convenient geothermal development technology. Through in situ experiments and a simulation algorithm, the research investigated the heat transmission characteristics of the deeply buried pipe energy pile group and optimized different intermittent operation schemes. The findings suggest that prolonged operation of the pile cluster intensifies heat buildup within the pile foundation, thereby adversely affecting the system’s overall heat exchange efficiency. Employing an intermittent operating mode can alleviate this heat accumulation phenomenon, thereby promoting sustained heat exchange performance of the piles over time. To evaluate the comprehensive thermal interaction and energy efficiency ratio of the energy pile heat exchange system, various intermittent operation strategies were compared in the study. Among them, the intermittent operational scheme with a ratio of n = 5 was found to be optimal, with the total average heat transfer rate of the pile set only 0.51% lower than that of the continuous operational mode, but the overall energy efficiency ratio improved by 19.6%. The intermittent operational mode proposed in this study can achieve the goal of saving energy and efficiently extracting geothermal resources, providing theoretical guidance for the extraction and utilization of subsurface geothermal power by energy piles.

Long-afterglow materials have a broad of applications in optoelectronic devices, sensors, medicine and other fields due to their excellent luminescent properties. The host-guest long-afterglow MOFs material combines the advantages of multi-component characteristics and the stability of MOFs, which improves its luminous performance and expands its other properties. This review introduces the classification, synthesis and application of host-guest MOFs materials with long afterglow. Due to their rigid frames and multi-channel characteristics, MOFs can load common guest materials including rare earth metals, organic dyes, carbon dots, etc. The synthesis methods of loading guest materials into MOFs include solvothermal synthesis, post-encapsulation, post-modification, etc. Those long-afterglow host-guest MOFs have a wide range of applications in the fields of sensors, information security and biological imaging.

This paper proposes an advanced model predictive control (MPC) scheme for the attitude tracking of coaxial drones under wind disturbances. Unlike most existing MPC setups, this scheme embeds steady-input, steady-output, and steady-state conditions into the optimization problem as decision variables. Consequently, the coaxial drone’s attitude can slide along the state manifold composed of a series of steady states. This allows it to move toward the optimal reachable equilibrium. To address disturbances that are difficult to accurately measure, an extended state observer is employed to estimate the disturbances in the prediction model. This design ensures that the algorithm maintains recursive stability even in the presence of disturbances. Finally, numerical simulations and flight tests are provided to confirm the effectiveness of the proposed method through comparison with other control algorithms.

The nutritional value of goat milk is determined by the composition of its fatty acids, with particular importance placed on the role of unsaturated fatty acids in promoting human health. CircRNAs have been known to affect fatty acid metabolism through different pathways. In this study, high-throughput sequencing was employed to construct expression profiles of mammary tissue harvested during the dry period and peak lactation stages of dairy goats. Differentially expressed circRNAs and mRNAs were screened, revealing significantly higher expression levels of circRNA-08436 and ELOVL6 during the peak lactation period compared with the dry period. Thus, circRNA-08436 and ELOVL6 were chosen for subsequent studies. The findings demonstrated that circRNA-08436 not only promotes the synthesis of triglyceride (TAG) and cholesterol in goat mammary epithelial cells (GMECs), but also increases the concentrations of saturated fatty acids in the cells. Through the utilization of software prediction, the dual luciferase reporter system, and qRT-PCR, it was observed that circRNA-08436 binds to miR-195, with its overexpression reducing the expression levels of miR-195 and inhibiting TAG synthesis. In addition, circRNA-08436 upregulated the expression levels of the miR-195 target gene ELOVL6. The data also revealed that YTHDC1 facilitated the transport of circRNA-08436 from the nucleus to the cytoplasm, while YTHDC2 in the cytoplasm functioned as a “reader” to identify and degrade circRNA-08436. Taken together, these findings contribute to a better understanding of the molecular regulation of fatty acid metabolism in the mammary glands of dairy goats, thus offering a sound theoretical basis for the production of high-quality goat milk.

This paper aims to improve the deicing performance and energy utilization of bridge pylon crossbeams with built-in carbon fiber electric heating (BPB–CFEH). Therefore, a three-dimensional thermal transfer model of BPB–CFEH with one arrangement is established. Two ice-melting regions and two ice-melting stages were set up according to the characteristics of the icing of the crossbeam. The effects of wind speed and ambient temperature on the paving power required to reach the complete melting of the icicles within 8 h were analyzed. The effects of the laying spacing and rated voltage of the carbon fiber heating cable on the melting ice sheet and the thermal exchange of the two regions of the icicle after heating for 8 h were compared. Additionally, its effect on energy utilization of the process from the ice sheet melting stage to the ice column melting stage was analyzed. Ice-melting experiments verified the applicability and reasonableness of the simulated ice-melting calculation formula. The results show that under ambient temperature of −10 °C and wind speed of 4.5–13.5 m/s, the proposed paving power is 817.5–2248.12 W/m2. Increasing the rated voltage and shortening the spacing increases the thermal exchange capacity of the two melting regions. The shortening of the spacing improves the energy utilization rate of the melting stage of the ice sheet to the melting stage of the icicle processes. The difference between the melting time obtained from the formula proposed by numerical simulation and the melting time obtained from indoor tests is about 10 min. This study provides a design basis for the electrothermal ice melting of bridge pylon crossbeams.

The quasi-steady diffusiophoresis of a soft particle composed of an uncharged hard sphere core and a uniformly charged porous surface layer in a concentric charged spherical cavity full of a symmetric electrolyte solution with a concentration gradient is analyzed. By using a regular perturbation method with small fixed charge densities of the soft particle and cavity wall, the linearized electrokinetic equations relevant to the fluid velocity field, electric potential profile, and ionic concentration distributions are solved. A closed-form formula for the diffusiophoretic (electrophoretic and chemiphoretic) velocity of the soft particle is obtained as a function of the ratios of the core-to-particle radii, particle-to-cavity radii, particle radius to the Debye screening length, and particle radius to the permeation length in the porous layer. In typical cases, the confining charged cavity wall significantly influences the diffusiophoresis of the soft particle. The fluid flow caused by the diffusioosmosis (electroosmosis and chemiosmosis) along the cavity wall can considerably change the diffusiophoretic velocity of the particle and even reverse its direction. In general, the diffusiophoretic velocity decreases with increasing core-to-particle radius ratios, particle-to-cavity radius ratios, and the ratio of the particle radius to the permeation length in the porous layer, but increases with increasing ratios of the particle radius to the Debye length.

A molecular pump is the core component of vacuum systems in portable mass spectrometers and other analytical instruments. The forms of the existing molecular pumps mainly are the combinations of vertical bleed and compression channel, which have the shortcomings of heavy mass and large volume, which seriously restricts the application and development of portable mass spectrometers. Aiming at the problems of low strength and insufficient pumping performance under the miniaturization constraints (mass of 1.8 kg; exhaust diameter of 25 mm) of molecular pumps, a compound pump consisting of a horizontal bleed channel and multi-stage spiral compression channel is proposed. The pumping principle of the compound molecular pump is analyzed to obtain its preliminary structural size parameters. The test particle Monte Carlo method is presented for establishing an aerodynamic model for a high-speed small compound molecular pump, which can be used to investigate the pumping performance of bleed blades and compression channels in a thin air environment. On the basis of the aerodynamic model, the NNIA multi-objective optimization algorithm is presented to optimize the structural parameters of the compound molecular pump. After structural parameter optimization, the maximum flow rate and compression ratio of the compound molecular pump are increased by 13.6% and 41.6%, respectively. The experimental results of the pumping performance show that the predicted data of the aerodynamic model are in good agreement with the experimental data, with an error of 12–27%. Namely, the established aerodynamic model has high accuracy and the optimized structural parameters of the compound molecular pump can provide basic conditions for the large-scale application and promotion of portable mass spectrometers.

Owing to the important role of and increasing demand for lithium resources, lithium extraction is crucial. The use of molecular extractants is a promising strategy for selective lithium recovery, in which the interaction between lithium and the designed extractant can be manipulated at the molecular level. Herein, we demonstrate that anion receptors of tripodal hexaureas can selectively extract Li2SO4 solids into water containing DMSO (0.8% water) compared to other alkali metal sulfates. The hexaurea receptor with terminal hexyl chains displays the best Li+ extraction selectivity at 2-fold over Na+ and 12.5-fold over K+. The driving force underpinning selective lithium extraction is due to the combined interactions of Li+-SO42− electrostatics and the ion–dipole interaction of the lithium–receptor (carbonyl groups and N atoms); the latter was found to be cation size dependent, as supported by computational calculations. This work indicates that anion binding receptors could drive selective cation extraction, thus providing new insights into the design of receptors for ion recognition and separation.

This study aimed to investigate how diets supplemented with DHA-rich algae affect the expression of liver lipid synthesis genes in dairy goat bucks. The results revealed that when supplemented with DHA-rich algae, liver weight and serum HDL-C were significantly increased (p < 0.05), as well as serum LDL-C was significantly decreased (p < 0.05). Transcriptome sequencing indicated that algae supplementation alters liver gene expression. The differentially expressed genes were predominantly enriched in fatty acid metabolism and the biosynthesis of unsaturated fatty acids. The expression of fatty acid desaturation and transcription factors (SCD, FADS1, INSIG1), de novo synthesis fatty acids (FASN), fatty acid transport (LDLR), and cholesterol and steroid synthesis (HMGCR, HMGCS1, SQLE) genes were significantly increased (p < 0.05), and fatty acid oxidation (ALDH3B1) genes were significantly decreased (p < 0.05). In conclusion, this research provided preliminary evidence that supplementation with algae in dietary supplements altered the expression of the liver lipid synthesis genes in the Saanen dairy goat bucks.

Despite great scientific efforts, deep understanding of coronavirus-19 disease (COVID-19) immunopathology and clinical biomarkers remains a challenge. Pre-existing comorbidities increase the mortality rate and aggravate the exacerbated immune response against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, which can result in more severe symptoms as well as long-COVID and post-COVID complications. In this study, we applied proteomics analysis of plasma samples from 28 patients with SARS-CoV-2, with and without pre-existing comorbidities, as well as their corresponding controls to determine the systemic protein changes caused by the SARS-CoV-2 infection. As a result, the protein signature shared amongst COVID-19 patients with comorbidities was revealed to be characterized by alterations in the coagulation and complement pathways, acute-phase response proteins, tissue damage and remodeling, as well as cholesterol metabolism. These altered proteins may play a relevant role in COVID-19 pathophysiology. Moreover, several novel potential biomarkers for early diagnosis of the SARS-CoV-2 infection were detected, such as increased levels of keratin K22E, extracellular matrix protein-1 (ECM1), and acute-phase response protein α-2-antiplasmin (A2AP). Importantly, elevated A2AP may contribute to persistent clotting complications associated with the long-COVID syndrome in patients with comorbidities. This study provides new insights into COVID-19 pathogenesis and proposes novel potential biomarkers for early diagnosis that could be facilitated for clinical application by further validation studies.

The identification of stay cable icing is crucial for robot deicing to improve efficiency and prevent damage to stay cables. Therefore, it is significant to identify the areas and degree of icing in the images of stay cables. This study proposed a two-stage model that combines U-Net and ResNet50. In the first stage, this model used U-Net to segment the surface ice and icicles from the stay cable. The image of icing obtained after segmentation was used as the input for the second stage. In the second stage, ResNet50 was used to classify the degree of icing. The experimental results show that the proposed model can successfully segment the icicles and surface ice from the stay cable icing image to complete the classification of the icing degree. The mean pixel accuracy and intersection over the union of icing were 96.65% and 82.10%, respectively. The average accuracy of the icing degree classification was 95.71%. The method proposed in this study meets the requirements of robustness, segmentation accuracy, and classification accuracy for stay cable icing recognition, which provides a research basis for the precise icing recognition of cable-deicing robots.

Milk, known for its high content of short- and medium-chain fatty acids and unsaturated fatty acids, has attracted substantial attention due to its nutritional and health value. The regulation of fatty acid metabolism by non-coding RNAs has become a subject of growing attention, particularly in relation to fatty acid production at the transcriptional/epigenetic and post-transcriptional levels. This study established the circRNA-11228/miR-103/INSIG1 (insulin-inducible gene) regulatory network using methods such as qRT-PCR, dual luciferase reporting, and Western blot, with INSIG1 serving as the starting point. The experimental validation of circRNA-11228’s impact on cholesterol levels, lipid droplet secretion, and unsaturated fatty acid content was conducted using various assays, including triglycerides, cholesterol, oil red O, andEdU(5-ethynyl-2’-deoxyuridine) in bovine mammary epithelial cells (BMECs). Furthermore, the transfection of mimics and inhibitors synthesized from miR-103 into BMECs confirmed that miR-103 can promote cholesterol synthesis and lipid droplet secretion. Conversely, the INSIG1 gene was found to inhibit cholesterol synthesis and lipid droplet secretion. The “remediation” experiment validated the ability of miR-103 to alleviate the cellular effect of circRNA-11228. Taken together, our findings indicate that the binding of circRNA-11228 to miR-103 inhibits the expression of the target gene INSIG, thereby regulating milk fat production in BMECs. This study offers novel insights into producing high-quality milk and new ways to improve the dietary composition of residents.

In order to improve the preparation efficiency, quality stability, and large-area preparation of superhydrophobic thin films, a roll-to-roll continuous micro–nano imprinting method for the efficient preparation of superhydrophobic polymer films is proposed. A wear-resistant mold roller with hierarchical microstructure is prepared by wire electrical discharge machining (WEDM). The rheological filling model is constructed for revealing the forming mechanism of superhydrophobic polymer films during continuous micro/nano imprinting. The effects of imprinting temperature, rolling speed and the surface texture size of the template on the surface texture formation rate of polymer films are analyzed. The experimental results show that, compared with other process methods, the template processed by WEDM shows excellent wear resistance. Moreover, the optimal micro/nano imprinting parameters are the mold temperature of 190 °C (corresponding film temperature of 85 ± 5 °C), rolling speed of 3 rpm and roller gap of 0.1 mm. The maximum contact angle of the polymer film is 154°. In addition, the superhydrophobic polymer thin film has been proven to have good self-cleaning and anti-icing performance.

Aboveground biomass (AGB) of shrubs and low-statured trees constitutes a substantial portion of the total carbon pool in temperate forest ecosystems, contributing much to local biodiversity, altering tree-regeneration growth rates, and determining above- and belowground food webs. Accurate quantification of AGB at the shrub layer is crucial for ecological modeling and still remains a challenge. Several methods for estimating understory biomass, including inventory and remote sensing-based methods, need to be evaluated against measured datasets. In this study, we acquired 158 individual terrestrial laser scans (TLS) across 45 sites in the Yanshan Mountains and generated metrics including leaf area and stem volume from TLS data using voxel- and non-voxel-based approaches in both leaf-on and leaf-off scenarios. Allometric equations were applied using field-measured parameters as an inventory approach. The results indicated that allometric equations using crown area and height yielded results with higher accuracy than other inventory approach parameters (R2 and RMSE ranging from 0.47 to 0.91 and 12.38 to 38.11 g, respectively). The voxel-based approach using TLS data provided results with R2 and RMSE ranging from 0.86 to 0.96 and 6.43 to 21.03 g. Additionally, the non-voxel-based approach provided similar or slightly better results compared to the voxel-based approach (R2 and RMSE ranging from 0.93 to 0.96 and 4.23 to 11.27 g, respectively) while avoiding the complexity of selecting the optimal voxel size that arises during voxelization.

Aims: The aims of this study are to investigate the etiology, microbiological spectrum, and risk factors associated with visual outcomes of fungal endophthalmitis (FE) in a tertiary eye specialty hospital in Shanghai, China. Methods: This was a retrospective, single-center case series. The clinical characteristics, etiology, microbiological spectrum, and management, as well as the visual outcomes, were analyzed. Logistic regression was used to analyze the factors related to visual outcomes. Results: This study involved 102 eyes of 92 patients with FE, including 63 males (66.3%). The mean age was 44.4 ± 19.8 years. The most common etiology of FE was trauma (56.5%). The predominant fungal species isolated were Aspergillus spp. (31/93, 33.3%). Pars plana vitrectomy (PPV) and intravitreal antifungal agents was performed initially in 86 (84.3%) and 83 (81.4%) eyes, respectively. Only 35 (34.3%) eyes achieved final best corrected visual acuity (BCVA) of 20/400 or better. Ten (9.8%) eyes had a final BCVA of light perception or worse, and five (4.9%) had to be enucleated. The factors determining better visual outcomes included initial visual acuity better than finger-counting (FC) (odds ratio (OR) 5.811, p = 0.036), the absence of corneal infiltrate (OR 10.131, p = 0.002), and Candida species infection (OR 6.325, p = 0.011). Conclusions: Early diagnosis of FE and a timely vitrectomy, combined with an intravitreal injection of an antifungal drug, can mitigate the devastating results of intraocular fungal infection. Not being infected by Aspergillus spp., an initial BCVA that was no worse than FC, and the absence of corneal involvement were related to better visual prognosis.

Annually, hundreds of individuals tragically lose their lives at sea due to shipwrecks or aircraft accidents. For search and rescue personnel, the task of locating the debris of a downed aircraft in the vastness of the ocean presents a formidable challenge. A primary task these teams face is determining the search area, which is a critical step in the rescue operation. The movement of aircraft wreckage on the ocean surface is extremely complex, influenced by the combined effects of surface winds, waves, and currents. Establishing an appropriate drift motion prediction model is instrumental in accurately determining the search area for the wreckage. This article initially conducts maritime drift observation experiments on wreckage, and based on the results of these experiments, analyzes the drift characteristics and patterns of the debris. Subsequently, employing a wealth of observational experimental data, three types of drift prediction models for the wreckage are established using the least squares method. These models include the AP98 model, the dynamics model, and an improved model. In conclusion, the effectiveness and accuracy of the three models is evaluated and analyzed using Monte Carlo techniques. The results indicate that the probability of positive crosswind leeway (CWL) is 47.4%, while the probability of negative crosswind leeway (CWL) is 52.6%. The jibing frequency is 7.7% per hour, and the maximum leeway divergence angle observed is 40.4 degrees. Among the three drift prediction models, the refined AP98 drift model demonstrates the highest forecasting precision. The findings of this study offer a more accurate drift prediction model for the search of an aircraft lost at sea. These results hold significant guiding importance for maritime search and rescue operations in the South China Sea.

The Hutuo River Drinking Water Source Area is an important water source of Shijiazhuang (North China Plain). Knowing the characteristics of groundwater chemistry/quality is essential for the protection and management of water resources. However, there are few studies focused on the groundwater chemistry evolution over the drinking water area. In this study, total of 160 groundwater samples were collected in November 2021, and the spatial distribution of groundwater chemistry and related controlling factors were analyzed using hydrological and multivariate analysis. The entropy-weighted water quality index (EWQI) was introduced to assess the groundwater quality. The results show that the hydrogeochemical types of groundwater are Ca-HCO3 (78.1%), mixed Ca-Mg-Cl (20%), and Ca-Cl (1.9%) in the area. Graphical and binary diagrams indicate that groundwater hydrochemistry is mainly controlled by water–rock interaction (i.e., rock weathering, mineral dissolution, and ion exchange). Five principal components separated from the principal component analysis represent the rock–water interaction and agricultural return, redox environment, geogenic sources, the utilization of agricultural fertilizer, the weathering of aluminum silicates, and dissolution of carbonates, respectively. More than 70% of the samples are not recommended for irrigation due to the presence of high salt content in groundwater. EWQI assessment demonstrates that the quality of the groundwater is good. The outcomes of this study are significant for understanding the geochemical status of the groundwater in the Hutuo River Drinking Water Source Area, and helping policymakers to protect and manage the groundwater.

Cage aquaculture makes it easier to produce high-quality aquatic products and allows full use of water resources. 3Therefore, cage aquaculture development is highly valued globally. However, the current digitalization level of cage aquaculture is low, and the farming risks are high. Research and development of digital management of the fish population in cages are greatly desired. Real-time monitoring of the activity status of the fish population and changes in the fish population size in cages is a pressing issue that needs to be addressed. This paper proposes an improved network called CC-YOLOv5 by embedding CoordConv modules to replace the original ConV convolution modules in the network, which improves the model’s generalization capability. By using two-stage detection logic, the target detection accuracy is enhanced to realize prediction of the number of fish populations. OpenCV is then used to measure fish tail lengths to establish growth curves of the fish and to predict the output of the fish population in the cages. Experimental results demonstrate that the mean average precision (mAP) of the improved algorithm increases by 14.9% compared to the original YOLOv5, reaching 95.4%. This research provides an effective solution to promote the intelligentization of cage aquaculture processes. It also lays the foundation for AI (Artificial Intelligence) applications in other aquaculture scenarios.

BI-X, a therapeutic protein under development for the treatment of human ocular disease via intravitreal administration, binds to its therapeutic targets and endogenous albumin in the vitreous humor. A monkey ocular pharmacokinetic (PK) study following BI-X administration was conducted to measure drug and albumin levels in plasma, the vitreous humor, the aqueous humor, and retina tissue at various timepoints post-dose. A comprehensive bioanalytical approach was implemented in support of this study. Five immunocapture-LC-MS/MS assays were developed and qualified for quantitating BI-X in different matrices, while ELISA was used for albumin measurement. Immunocapture at the protein or peptide level was evaluated to achieve adequate assay sensitivity. Drug and albumin assays were applied for the analysis of the monkey study samples.

In order to improve the reliability and maintainability of rod control power cabinets in nuclear power plants, this paper uses insulated gate bipolar transistors (IGBTs), the key power device of rod control power cabinets, as the object of research on cross-working-condition fault prediction. An improved transfer learning (TL) model based on a temporal convolutional network (TCN) is proposed to solve the problem of low fault prediction accuracy across operating conditions. First, the peak emitter voltage of an IGBT aging dataset is selected as the source domain failure characteristic, and the TCN model is trained after the removal of outliers and noise reduction. Then, the time–frequency features are extracted according to the characteristics of the target domain data, and the target domain representation data are obtained using kernel principal component analysis (KPCA) for dimensionality reduction. Finally, the TCN model trained on the source domain is transferred; the model is fine-tuned according to the target domain data, and the learning rate, the number of hidden layer nodes, and the number of training times in the network model are optimized using the dung beetle optimization (DBO) algorithm to obtain the optimal network, making it more suitable for target sample fault prediction. The prediction results of this TCN model, the long short-term memory (LSTM) model, the gated recurrent unit (GRU) model, and the recursive neural network (RNN) model are compared and analyzed by selecting prediction performance evaluation indexes. The results show that the TCN model has a better predictive effect. Comparing the prediction results of the TCN-based optimized transfer learning model with those of the directly trained TCN model, the mean square error, root mean square error, and mean absolute error are reduced by a factor of two to three, which provides an effective solution for fault prediction across operating conditions.

Coprophagy prevention (CP) affects the growth performance, hepatic lipid synthesis, and gut microbiota in rabbits. Supplementation with Clostridium butyricum (C. butyricum, Strain number: CCTCC M 2019962) has been found to improve growth performance in rabbits. However, it remains unknown whether C. butyricum can ameliorate the effects of CP on hepatic lipid synthesis and the underlying mechanisms are yet to be elucidated. Therefore, this study aimed to investigate the impact of CP on hepatic lipid synthesis and the underlying mechanism based on the gut–liver axis. The findings revealed that supplementation with C. butyricum could reverse CP-related growth performance, lipid accumulation, bile acid synthesis, and inflammation. Furthermore, C. butyricum exerted protective effects on the gut by preserving intestinal barrier integrity and modulating gut microbiota composition; these factors may represent potential mechanisms through which C. butyricum improves CP-related outcomes. Specifically, C. butyricum reshaped the microbiota by increasing butyric acid levels, thereby maintaining secondary bile acid (deoxycholic acid, chenodeoxycholic acid) balance and attenuating the inhibitory effects of the FXR/SHP pathway on lipid synthesis (SREBP1c/ApoA1). Moreover, the activation of butyrate/GPR43pathway by C. butyricum reduced damage to the intestinal barrier (ZO-1/Occludin/Claudin1) and restored the gut immune microenvironment in CP rabbits. In summary, supplementation with C. butyricum can alleviate the adverse effects of CP on growth performance and hepatic lipid synthesis by modulating the gut–liver axis.

Carbon fiber heating technology has been widely used in pavement surfaces in practical engineering projects as an environmentally friendly, efficient, and safe ice melting technique. However, the current design of carbon fiber-heated pavement focuses primarily on the ice melting effect while neglecting the crucial mechanical performance evaluation. Therefore, this study aims to investigate the temperature and thermal strain distributions of concrete pavement through model tests and develop a corresponding three-dimensional numerical model to analyze the temperature stress field distribution of carbon fiber-heated pavement. The accuracy of the numerical model is verified by comparing the model test results with the numerical analysis results. The numerical model test results indicate that the maximum compressive stress near the carbon fiber wire is 4 MPa, while the maximum tensile stress between the two carbon fiber wires is 1 MPa. According to the design standard for highway cement concrete pavement, the temperature stress induced by temperature change is significantly lower than the design value of the material’s inherent strength. In addition, a linear relationship between the depth and temperature gradient affecting temperature stress is observed after establishing a correlation between the temperature gradient and temperature stress. The findings of this study can provide valuable insight into the design of carbon fiber-heated concrete pavements.

As a valuable nutrient in milk, fat accounts for a significant proportion of the energy requirements of ruminants and is largely responsible for determining milk quality. Fatty acids (FAs) are a pivotal component of milk fat. Conjugated linoleic acid (CLA) is one of the naturally occurring FAs prevalent in ruminant dairy products and meat. Increasing attention has been given to CLA because of its anti-cancer, anti-inflammatory, immune regulation, and lipid metabolism regulation properties, and these benefits potentially contribute to the growth and health of infants. In breast milk, CLA is present in trace amounts, mainly in the form of cis-9, trans-11 CLA. Notably, cis-9, trans-11 CLA improves the milk fat rate while trans-10, cis-12 CLA inhibits it. Apart from having multiple physiological functions, CLA is also a pivotal factor in determining the milk quality of ruminants, especially milk fat rate. In response to growing interest in green and healthy functional foods, more and more researchers are exploring the potential of CLA to improve the production performance of animals and the nutritional value of livestock products. Taken together, it is novel and worthwhile to investigate how CLA regulates milk fat synthesis. It is the purpose of this review to clarify the necessity for studying CLA in ruminant milk fat and breast milk fat.

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

Acoustic metasurfaces, as two-dimensional acoustic metamaterials, are a current research topic for their sub-wavelength thickness and excellent acoustic wave manipulation. They hold significant promise in noise reduction and isolation, cloaking, camouflage, acoustic imaging, and focusing. Resonant structural units are utilized to construct acoustic metasurfaces with the unique advantage of controlling large wavelengths within a small size. In this paper, the recent research progresses of the resonant metasurfaces are reviewed, covering the design mechanisms and advances of structural units, the classification and application of the resonant metasurfaces, and the tunable metasurfaces. Finally, research interest in this field is predicted in future.

Acute post-cataract surgery endophthalmitis (APSE) is a serious vision-threatening complication of cataract surgery. Analysis of the management and prognosis in cases of APSE may provide better guidance for future treatment. Fifty-six patients (56 eyes) diagnosed with APSE between 2013 and 2022 were retrospectively reviewed. The incidence of APSE rate was 0.020% (95% CI: 0.011–0.029%). Intraocular cultures were positive in 18 (32.1%) cases, with 21 organisms isolated. Coagulase-negative staphylococci was the predominant isolate (12/21; 57.1%). The time from surgery to the onset of endophthalmitis was 7 days (interquartile range: 3–16) in patients with good best-corrected visual acuity (BCVA) (≥20/70) and 3 days (interquartile range: 1–8) in those with poor BCVA (p < 0.001), time from onset to initial intravitreal antibiotics (IVAs) (p < 0.001), and positive culture of highly virulent pathogens (p = 0.018) displayed significantly positive associations with the final BCVA (logMAR). Adjunctive use of intravitreal corticosteroids and systemic antibiotics were unrelated to a favorable final BCVA. In conclusion, the severity of the visual condition at baseline, as well as delayed treatment, are risk factors for poor visual outcomes in APSE.

The stress and deformation of pile-supported immersed tunnels under seismic loads is a critical issue in tunnel design. This paper utilizes ABAQUS (version 2020) finite element software to analyze the seismic load response of the sand compaction pile-immersed tunnel–seawater pressure (SIS) system, which is verified by a physical model. The study shows that the suppression effect of the seawater on the vertical frequency of the tunnel increases with depth. When the replacement rate of the piled foundation reaches 50%, the deformation of the tunnel “H-shaped” structures increases, which also changes the vertical frequency of the tunnel. However, the presence of the suppression effect causes resonance injury at the far end of the tunnel from the earthquake source, resulting in a shift of the peak stress point. It was also found that seawater pressure affects the resistance–deflection (p-y) at the tip of the pile more than at the end of the pile. The slenderness ratio (γ) of the pile affects the p-y value at the end of the pile more than at the tip of the pile. The connection between the piled foundation and the tunnel is most stable when γ is in the range of 9.25 to 15.

The plastic region of piles under seismic loads is a crucial concern in seafloor improvement design. This paper establishes a physical model of the sand compaction pile-immersed tunnel–water pressure system. This research studies pile arrangements that minimize the sand compaction pile plastic region under seismic loads. The experiments were validated through numerical simulations. The results show that “X-shaped” and rectangular pile groups increase the Energy Residual Index (ERI) due to differences in pile spacing and the instability of the quadrilateral prism damping units formed by piles and soil. In this scenario, piles are limited to heavy and mild plastic regions, with boundary depths at L = 2.25 D and L = 2.08 D (L represents the pile length, and D is the pile diameter). Furthermore, increased water pressure amplifies the structural resonance injury, increasing ERI. In conjunction with the soil, hexagonal pile groups create triangular prism damping units that counteract seismic wavefronts. The total kinetic energy and strain energy of the piled foundation are lower than those of the “X-shaped” and rectangular pile groups. The boundaries between the heavy plastic region, the moderate plastic region, and the mild plastic region are located at depths of L = 4 D and L = 8 D, respectively. This study also reveals that a top-heavy mass distribution in the structure leads to maximum deformation in the heavy plastic region. Pile–soil damping units primarily operate within the moderate plastic region.

Green forage maize harvesters face challenges such as high soil humidity and soft soil in the field, mismatched working parameters, and poor reliability and adaptability. These challenges often result in header blockage, significant harvest loss, and increased energy consumption. Traditional testing and statistical analysis methods used in most existing studies are limited by complex test processes, their time-consuming nature, high costs, and poor prediction accuracy. To address these problems, a test bench was constructed to analyze the effects of forward speed, cutting height, number of rows, and their interactions on specific energy consumption and harvest loss of the green forage maize (GFM) header. A combined response surface method (RSM)–artificial neural network (ANN) approach is proposed for modeling and predicting the performance parameters of the header. The optimal conditions were determined by optimizing the specific energy consumption and loss rate. The optimal combination parameters are a forward speed of 1.6 km/h, a cutting height of 167 mm, and a number of rows of 4. However, RSM–ANN has larger R2 values and lower root mean square errors (RMSE) and mean square errors (MSE) compared to RSM. Specifically, the R2 of the RSM–ANN model for specific energy consumption and loss rate a 0.9925 and 0.9906, MSE are 0.00001775 and 0.004558, and RMSE are 0.004214 and 0.006752, respectively. The results show that the combined RSM–ANN method has higher precision and accuracy and can better predict and optimize the header performance. This study overcomes the limitations of traditional methods and has the potential to provide data and method references for the design, optimization, prediction, and intelligent diagnosis of faults in the operational parameters of agricultural machinery.

The functional composition of plant communities (FCPC) makes a significant contribution to ecosystem properties, functions, and services. Here, we used 18 plant functional traits from the sPlot database v2.1 and the global forest management type dataset to explore the links between forest management and the FCPC. We used the post hoc Tukey test to explore the differences in the community-weighted mean (CWM) and community-weighted variance (CWV) among different forest management types [i.e., intact forests, managed forests with natural regeneration, planted forests, plantation forests (with up to a 15-year rotation), and agroforestry]. We found that different forest management types can result in significant variability in plant communities’ functional composition. Plantation forests could result in significantly higher CWM and CWV compared to intact forests, and significant differences could occur between natural and managed forests with natural regeneration. Furthermore, the relationship between forest management practices and the FCPC depends on ecozone type changes. There were significant differences between natural and plantation forests for CWM and CWV in temperate forests. Our study provides an effective reference for applying plant functional traits to regulate and optimize the functions and services of forest ecosystems.

Properties of recycled aggregate concrete (RAC) are influenced by the composition and particle size distribution of recycled coarse aggregate (RCA). The study herein designed seven distinct groups of RACs with varying aggregate fractal dimensions (D) and one group of natural concrete (NAC). The impact of D on the workability, compressive strength, resistance to chloride ion penetration, and carbonation resistance of RAC was measured. It was found that an increase in the D value led to a decrease in the slump and slump flow, with the compressive strength and chloride ion penetration increasing and then decreasing, and carbonation gradually declined. The optimal fractal dimension was thereby determined to be 2.547 by a strength model accommodating two parameters of D and the curing age. Additionally, the mass percentage of each particle size for the corresponding gradation was presented. The compressive strength and chloride permeation resistance of RAC (D = 1.0) relative to RAC (D = 2.5) was increased by 16.7% and 13.3%, respectively. Furthermore, the carbonation depth of RAC (D = 2.5) was comparable to that of NAC. Additionally, the carbonation resistance of RAC was influenced by both the size distribution and the degree of natural carbonation of RCA, resulting in four distinct features relative to NAC. It is thereby feasible to enhance RAC performance through the manipulation of RCA’s fractal dimensions.

In remote communities of Canada, diesel is the primary source of electricity and heat. Promoting sustainable and diverse means of heat and power generation is essential to providing reliable and less carbon-intensive energy supply to remote communities. Among renewable energy sources in Canada, biomass is a major source of energy, with wood pellets being a notable contributor. In this study, using wood pellets in a remote community of Canada is investigated using life cycle analysis (LCA). Furthermore, wood pellet combustion is compared with diesel combustion, the most common fossil fuel in these regions. SimaPro (version 8.4.0.0) was used with Ecoinvent 3 as the primary library because of the nature of the feedstock. Harvesting, transportation, sawmill operation, pelletization, and combustion stages are considered in LCA. In doing so, first, life cycle data related to each of these stages are collected with respect to eight impact categories of global warming, ozone depletion, carcinogenic, non-carcinogenic, smog, respiratory effects, acidification, eutrophication, ecotoxicity, and fossil fuel depletion. The results indicate that pelletization and combustion stages have the greatest environmental impact, specifically in terms of non-carcinogenic effects from pelletization and respiratory effects from pellet combustion. Additionally, when comparing wood pellets to diesel, wood pellet combustion exhibits superior performance across various impact categories, particularly in non-carcinogenic effects.

Zinc finger and SCAN domain-containing 4 (ZSCAN4), a DNA-binding protein, maintains telomere length and plays a key role in critical aspects of mouse embryonic stem cells, including maintaining genomic stability and defying cellular senescence. However, the effect of ZSCAN4 in porcine parthenogenetic embryos remains unclear. To investigate the function of ZSCAN4 and the underlying mechanism in porcine embryo development, ZSCAN4 was knocked down via dsRNA injection in the one-cell stage. ZSCAN4 was highly expressed in the four- and five- to eight-cell stages in porcine embryos. The percentage of four-cell stage embryos, five- to eight-cell stage embryos, and blastocysts was lower in the ZSCAN4 knockdown group than in the control group. Notably, depletion of ZSCAN4 induced the protein expression of DNMT1 and 5-Methylcytosine (5mC, a methylated form of the DNA base cytosine) in the four-cell stage. The H3K27ac level and ZGA genes expression decreased following ZSCAN4 knockdown. Furthermore, ZSCAN4 knockdown led to DNA damage and shortened telomere compared with the control. Additionally, DNMT1-dsRNA was injected to reduce DNA hypermethylation in ZSCAN4 knockdown embryos. DNMT1 knockdown rescued telomere shortening and developmental defects caused by ZSCAN4 knockdown. In conclusion, ZSCAN4 is involved in the regulation of transcriptional activity and is essential for maintaining telomere length by regulating DNMT1 expression in porcine ZGA.

A crucial part of the livestock industry is dairy cattle which contribute significantly to the livestock economy [...]

Addressing the leakage rate prediction problem of the PEMFC sealing system is of great importance for its stable operation. The leakage calculation method of the PEMFC sealing system is proposed based on thermal coupling. The parallel plate leakage model is improved to make it applicable to the leakage rate calculation with a variable channel cross-section height. The interface macroscopic contact pressure is solved using a finite element simulation for solid mechanics analysis. The Greenwood–Williamson model is used for contact mechanics analysis to solve for the average height of the leakage channel. The effects of the ambient temperature, compression ratio, bipolar plate misalignment, and gasket size on the cell sealing effect were studied numerically. The data indicated that as the ambient temperature, compression ratio, and gasket size became larger, the volume leakage rate began to be reduced. The leakage rate as a parameter to characterize the sealing performance, considering the influence of gasket size, operating conditions, and other factors on the cell sealing effect, is more meaningful for the durability study and failure analysis of PEMFC.

Ecdysteroids are crucial in regulating the growth and development of insects. In the fruit fly Drosophila melanogaster, both C27 and C28 ecdysteroids have been identified. While the biosynthetic pathway of the C27 ecdysteroid 20-hydroxyecdysone (20E) from cholesterol is relatively well understood, the biosynthetic pathway of C28 ecdysteroids from C28 or C29 dietary sterols remains unknown. In this study, we found that different dietary sterols (including the C27 sterols cholesterol and 7-dehydrocholesterol, the C28 sterols brassicasterol, campesterol, and ergosterol, and the C29 sterols β-sitosterol, α-spinasterol, and stigmasterol) differentially affected the expression of 20E biosynthetic genes to varying degrees, but similarly activated 20E primary response gene expression in D. melanogaster Kc cells. We also found that a single dietary sterol was sufficient to support D. melanogaster growth and development. Furthermore, the expression levels of some 20E biosynthetic genes were significantly altered, whereas the expression of 20E signaling primary response genes remained unaffected when flies were reared on lipid-depleted diets supplemented with single sterol types. Overall, our study provided preliminary clues to suggest that the same enzymatic system responsible for the classical C27 ecdysteroid 20E biosynthetic pathway also participated in the conversion of C28 and C29 dietary sterols into C28 ecdysteroids.

After T5 (forging + aging) and different T6 (forging + solution + aging) heat treatments, the AZ80A Mg alloys exhibited microstructures with different fractions of continuous precipitate (CP) regions and discontinuous precipitate (DP) regions. The effects of the fractions of DP regions and CP regions on the tensile properties and fracture behaviors were investigated using microstructural characterizations and analysis. The results showed that increasing the fraction of DP regions enhanced the yield strength and tensile strength at room temperature. However, at the same high temperature, increasing the fractions of DP regions improved the elongation but deteriorated the tensile strength significantly. The different resultant tensile properties at different temperatures were caused by the different precipitation-strengthening effects in the CP and DP regions. The strengthening contribution of the DP regions was more effective at room temperature but became inferior to the effect brought about by the CP regions at high temperatures. Micro-cracks were usually initiated and propagated in the CP regions at room temperature. At high temperatures, however, micro-voids formed more easily in the DP regions, and the fracture path preferred to locate there.

The working load on automotive components is continuously rising, and the mechanical performance requirements for component materials are rising along with the growth trend toward light weight and high dependability in automobiles. In this study, the response characteristics of 51CrV4 spring steel were taken to be its hardness, wear resistance, tensile strength, and impact toughness. Prior to tempering, cryogenic treatment was introduced. Through the Taguchi method and gray relational analysis, the ideal process parameters were discovered. The ideal process variables were the following: a cooling rate of 1 °C/min, a cryogenic temperature of −196 °C, a holding time of 24 h, and a cycle number of three. An analysis of variance revealed that the holding time had the greatest effect on the material properties, with an effect of 49.01%. The yield limit of 51CrV4 was increased by 14.95% and the tensile strength was increased by 15.39% with this group of processes, and the wear mass loss was reduced by 43.32%. The mechanical qualities had a thorough upgrade. Microscopic analysis revealed that cryogenic treatment resulted in refinement of the martensite structure and significant differences in orientation. Additionally, bainite precipitation occurred, exhibiting a fine needle-like distribution, which positively influenced impact toughness. Analysis of the impact fracture surface showed that cryogenic treatment led to an increase in dimple diameter and depth. Further analysis of the elements revealed that calcium (Ca) weakened the negative effect of sulfur (S) on 51CrV4 spring steel. The overall improvement in material properties provides guidance for practical production applications.

To address the issues of low efficiency and lengthy running time associated with trajectory planning for 6-degree-of-freedom manipulators, this paper introduces a novel solution that generates a time-optimal path for a manipulator while adhering to its kinematic limitations. The proposed method comprises several stages. Firstly, the kinematics of the manipulator are analyzed. Secondly, the manipulator’s joint-space path points are interpolated via the quintic B-spline curve. Subsequently, the non-dominated sorting genetic algorithm II (NSGA-II) is improved by applying reinforcement learning to optimize its crossover and mutation probabilities, and the variable neighborhood search (VNS) algorithm is integrated to enhance its local search capability. Finally, the joint increments and running time of the manipulator are optimized using the improved NSGA-II, and the time-optimal trajectory is then determined by simulation on MATLAB. Furthermore, compared with other conventional optimization methods, the proposed approach has reduced the total running time by 19.26%, effectively improving the working efficiency of the manipulator.

The bridge tower beams of long-span bridges freeze during winter. The accumulated ice on the beam flakes off and falls into the bridge deck from a high altitude with temperature rise, threatening traffic safety. To solve this problem, an electric heating method is used to melt the snow and ice on bridge tower beams. A design scheme based on embedding carbon fiber heating wires in a bridge tower beam is proposed in which electrical energy is converted into heat energy to melt the snow and ice on the beam. In this paper, a beam icing test and beam de-icing test are carried out through a laboratory model test. The model test results show that under the conditions of a wind speed of 4.5 m/s and an ambient temperature of −15 °C, the average internal temperature of the beam after heating stabilization is 1.37 °C; this is higher than the average critical temperature of 1.31 °C. This temperature is sufficient to melt the ice and proves the practicability of this method. The de-icing method of embedded carbon fiber heating is simple, efficient, and environmentally friendly. This can provide a reliable reference for the practical application of de-icing a bridge beam.

The development of high-performance mass spectrometer and vacuum coating technology has placed higher demand on the vacuum level of turbomolecular pumps (TMPs), which are required to possess a greater compression ratio and faster pumping speed. There exists a relation of “as one falls, another rises” between the compression ratio and the pumping speed when traditional improvement methods are used. How to simultaneously increase the compression ratio and pumping speed is a very important question for the high-end turbomolecular pumps. In this study, on the basis of a parallel blade and thin gas aerodynamic model, several types of curved blade are presented to improve the pumping performance of TMPs. The comparison results show that the positive quadratic surface exhibited a better pumping performance than the other curved blades. After that, a hybrid optimization method based on a support vector machine (SVR) and particle swarm optimization (PSO) are proposed to obtain the structural parameters of the rotor blade for the highest pumping speed and maximum compression ratio. The optimization results show that, compared with the parallel blades, the compression single-stage blade row with quadratic surface structure was able to increase the maximum compression ratio by 10.35% and the maximum pumping speed factor by 4.61%. In addition, the intermediate single-stage blade row with quadratic surface structure increased the maximum compression ratio by 9.15% and the maximum pumping speed factor by 2.53%.

Terahertz (THz) communication has a large available bandwidth, which is expected to be deployed in future communication networks. As THz wave suffers from severe propagation loss in wireless transmission, we consider a THz near-field scenario where a base station (BS) is equipped with a large-scale antenna array with a low-cost hybrid beamforming architecture to serve mobile users nearby. However, the large-scale array and the user mobility incur difficulty in channel estimation. To tackle this issue, we propose a near-field beam training scheme that can align a beam to the user in a fast way by searching the codebook. Specifically, the BS employs a uniform circular array (UCA), and the radiation pattern of the beams in our proposed codebook appears as ellipsoids. To cover the serving zone with the minimum codebook size, we develop a near-field codebook by tangent arrangement approach (TAA). To reduce the time overhead, we leverage the hybrid beamforming architecture to realize multi-beam training concurrently since each RF chain can enable a codeword whose element has a constant magnitude. Numerical results validate that our proposed UCA near-field codebook achieves less time cost while achieving a comparable coverage performance compared to the conventional near-field codebook.