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Introduction: Baidu San mainly treats viral colds and relieves muscle pain. They are widely used in clinical practice, but their therapeutic effects and anti-inflammatory mechanisms against influenza are unknown. Methods: Active compounds and targets were mined with the help of TCMSP platform, OMIM database and Gene Cards database. Protein-protein interaction networks and component-target networks were established to screen core targets and components, and GO and KEGG enrichment analyses were performed in the DAVID database and visualized by the Microbiology Letter Platform. Finally, the binding affinity between potential targets and active compounds was assessed by molecular docking. Results: Baidu San is effective in the treatment of influenza. network pharmacology studies have shown that TNF, AKT1 and EGFR are the core targets of action of Baidu San in the treatment of influenza. Luteolin, quercetin and kaempferol are the key compounds. GO and KEGG enrichment analyses suggest that the mechanism of action of Baidu San is related to antiviral, anti-inflammatory and modulation of immune function are closely related. Conclusion: This study highlights the potential of combining in vitro experiments and network pharmacology as a promising strategy to explore the potential mechanism of TCMs.

Soil salinization has become one of the major problems that threaten the ecological environment. The aim of this study is to explore the mechanism of salt tolerance of hybrid walnuts (Juglans major × Juglans regia) under long-term salt stress through the dynamic changes of growth, physiological and biochemical characteristics, and anatomical structure. Our findings indicate that (1) salt stress inhibited seedling height and ground diameter increase, and (2) with increasing salt concentration, relative water content (RWC) decreased, and proline (Pro) and soluble sugar (SS) content increased. The Pro content reached a maximum of 549.64 μg/g on the 42nd day. The increase in superoxide dismutase (SOD) activity (46.80–117.16%), ascorbate peroxidase (APX) activity, total flavonoid content (TFC), and total phenol content (TPC) under salt stress reduced the accumulation of malondialdehyde (MDA). (3) Increasing salt concentration led to increases and subsequent decreases in the thickness of palisade tissues, spongy tissues, leaves, and leaf vascular bundle diameter. Upper and lower skin thickness, root periderm thickness, root diameter, root cortex thickness, and root vascular bundle diameter showed different patterns of change at varying stress concentrations and durations. Overall, the study concluded that salt stress enhanced the antireactive oxygen system, increased levels of osmotic regulators, and low salt concentrations promoted leaf and root anatomy, but that under long-term exposure to high salt levels, leaf anatomy was severely damaged. For the first time, this study combined the anatomical structure of the vegetative organ of hybrid walnut with physiology and biochemistry, which is of great significance for addressing the challenge of walnut salt stress and expanding the planting area.

Hyperthermia therapy is considered an effective anticancer strategy. However, high temperature can trigger an excessive inflammatory response, leading to tumor self-protection, immunosuppression, metastasis, and recurrence. To address this issue, we reported a multifunctional photothermal nanoplatform to achieve mild hyperthermia photothermal therapy (mild PTT) based on cisplatin (DDP) and a ferrocene metal-organic framework (MOF-Fc) nanocomposite, which can specifically enhance ferroptosis-triggered oxidative stress levels and synchronously amplify mild hyperthermia PTT-mediated anticancer responses. Both in vitro and in vivo antineoplastic results verify the superiority of mild PTT with DDP/MOF-Fc@HA. The combination of DDP and MOF-Fc exhibits Fenton catalytic activity and glutathione depletion capacity, magnifying mild hyperthermia effects via the radical oxygen species (ROS)-adenosine triphosphate (ATP)-HSP silencing pathway, with important implications for clinical hyperthermia therapy.

Hydroxytyrosol (HT), a plant-derived phenolic compound, is recognized for its potent antioxidant capabilities alongside a spectrum of pharmacological benefits, including anti-inflammatory, anti-cancer, anti-bacterial, and anti-viral properties. These attributes have propelled HT into the spotlight as a premier nutraceutical and food additive, heralding a new era in health and wellness applications. Traditional methods for HT production, encompassing physico-chemical techniques and plant extraction, are increasingly being supplanted by biotechnological approaches. These modern methodologies offer several advantages, notably environmental sustainability, safety, and cost-effectiveness, which align with current demands for green and efficient production processes. This review delves into the biosynthetic pathways of HT, highlighting the enzymatic steps involved and the pivotal role of genetic and metabolic engineering in enhancing HT yield. It also surveys the latest progress in the biotechnological synthesis of HT, examining innovative strategies that leverage both genetically modified and non-modified organisms. Furthermore, this review explores the burgeoning potential of HT as a nutraceutical, underscoring its diverse applications and the implications for human health. Through a detailed examination of both the biosynthesis and biotechnological advances in HT production, this review contributes valuable insights to the field, charting a course towards the sustainable and scalable production of this multifaceted compound.

Membrane technology for carbon capture is becoming increasingly attractive to combat the excessive greenhouse gas emitted into the atmosphere, which involves the benefits of cost-effectiveness, environmental-friendly, easy scalability, high energy efficiency, simplicity in design, etc. However, most state-of-the-art membrane materials suffer from either low CO2 permeability, low selectivity towards CO2 separation, poor resistance to plasticization, or inadequate long-term stability, rendering it still challenging to be upscaled to an industrial level. Therefore, the development of advanced membrane materials as well as a reasonable design of the membrane separation process is crucial and urgent for its real-life application in the future. This account reviews the details of some recent research progress in our group on carbon capture from different scenarios including post-combustion carbon capture, biogas upgrading and natural gas sweetening and hydrogen purification. Notably, considerable efforts have been invested in the development of some novel membrane materials in our group, such as facilitated transport membranes, carbon molecular sieving membranes, mixed matrix membranes, composite membranes, and poly(ionic liquids)-based membranes. Meanwhile, some studies focusing on the techno-economic feasibility analysis of membrane technology have also demonstrated its promising application on practical carbon capture.

Chinese Steady High Magnetic Field Facility produced a steady field of 45.22 T by its hybrid magnet, which was the highest steady magnetic field in the world. The cooling water system was used to maintain the cool temperature environment for the insert resistive magnet coils and it was completed the upgrading in the year 2020 after ensuring the 40 T hybrid magnet experiment. The performance parameters and characteristics of the transformed cooling water system has been introduced. The variation trend of the magnet circulating water flow rate and the deionized water quality in 45.22 T hybrid magnet experiment has been analyzed, and also the heat exchange effect between the primary chilled water circuits and the secondary deionized water circuits were calculated. Some problems in cooling water system operation in this time hybrid magnet experiment have been pointed out.

In this paper, the influence of the different clamping zones of a web on the vibration of I-shaped composite beams is discussed. This current study is divided into two steps. In the first step, according to the different clamping spacings, through vibration simulation analysis, the optimal clamping spacing was selected. In the second step, the optimal new fixture was designed by means of different clamping positions and shapes. The analysis also reveals that a reduction in the clamping space does not contribute to a reduction in vibration. A newly selected fixture was designed based on the results that were delivered by the finite element model analysis of the L fixture in the upper and lower. Based on static analysis, the improved fixture was able to significantly reduce displacement, stress, and strain compared with the original one. By using dynamic analysis, modes, the frequency response, and random analyses, we found that the improved fixture could enhance the natural frequencies of the structure and reduce vibration displacement and acceleration during manufacturing. From the 2000 Hz sweep, the peak values of the power spectral density of displacement and acceleration went down by about 100 and 10 times, respectively.

The authors demonstrate a strategy for bacterial uptake of gold nanoparticles modified with glucose polymer. The particles aggregate in the bacterial cells upon laser irradiation, resulting in enhanced photoacoustic signal and antibacterial activity, enabling sensitive imaging of bacteria in vivo.

Monascus, a key player in fermented food production, is known for generating Monascus pigments (MPs) and monacolin K (MK), possessing bioactive properties. However, the limited stability of MPs and mycotoxin citrinin (CTN) constrain the Monascus industry. Extremolytes like ectoine, derived from bacteria, exhibit cytoprotective potential. Here, we investigated the impact of ectoine on Monascus purpureus ATCC 16365, emphasizing development and secondary metabolism. Exogenous 5 mM ectoine supplementation substantially increased the yields of MPs and MK (105%–150%) and reduced CTN production. Ectoine influenced mycelial growth, spore development, and gene expression in Monascus. Remarkably, ectoine biosynthesis was achieved in Monascus, showing comparable effects to exogenous addition. Notably, endogenous ectoine effectively enhanced the stability of MPs under diverse stress conditions. Our findings propose an innovative strategy for augmenting the production and stability of bioactive compounds while reducing CTN levels, advancing the Monascus industry.

Hydroxytyrosol, a valuable plant-derived phenolic compound, is increasingly produced from microbial fermentation. However, the promiscuity of the key enzyme HpaBC, the two-component flavin-dependent monooxygenase from Escherichia coli, often leads to low yields. To address this limitation, we developed a novel strategy utilizing microbial consortia catalysis for hydroxytyrosol production. We designed a biosynthetic pathway using tyrosine as the substrate and selected enzymes and overexpressing glutamate dehydrogenase GdhA to realize the cofactor cycling by coupling reactions catalyzed by the transaminase and the reductase. Additionally, the biosynthetic pathway was divided into two parts and performed by separate E. coli strains. Furthermore, we optimized the inoculation time, strain ratio, and pH to maximize the hydroxytyrosol yield. Glycerol and ascorbic acid were added to the co-culture, resulting in a 92% increase in hydroxytyrosol yield. Using this approach, the production of 9.2 mM hydroxytyrosol was achieved from 10 mM tyrosine. This study presents a practical approach for the microbial production of hydroxytyrosol that can be promoted to produce other value-added compounds.

Abstract Single-frame image super-resolution (SISR) technology in remote sensing is improving fast from a performance point of view. Deep learning methods have been widely used in SISR to improve the details of rebuilt images and speed up network training. However, these supervised techniques usually tend to overfit quickly due to the models’ complexity and the lack of training data. In this paper, an Improved Deep Recursive Residual Network (IDRRN) super-resolution model is proposed to decrease the difficulty of network training. The deep recursive structure is configured to control the model parameter number while increasing the network depth. At the same time, the short-path recursive connections are used to alleviate the gradient disappearance and enhance the feature propagation. Comprehensive experiments show that IDRRN has a better improvement in both quantitation and visual perception.

Background: Early integration of palliative care (PC) for patients with advanced cancer has been recommended to improve quality of care. This study aims to describe prevalence, temporal trend and predictors of PC use in metastatic breast cancer (mBCa) patients receiving critical care therapies (CCT; included invasive mechanic ventilation, percutaneous endoscopic gastrostomy tube, total parenteral nutrition, tracheostomy and dialysis). Methods: The National Inpatient Sample was queried for mBCa patients receiving CCT between 2005 and 2014. Annual percent changes (APC) were calculated for PC prevalence in the overall cohort and subgroups. Multivariable logistic analysis was used to explore predictors of PC use. Results: Of 5833 mBCa patients receiving CCT, 880 (15.09%) received PC. Rate of PC use increased significantly from 2.53% in 2005 to 25.96% in 2014 (APC: 35.75%; p

This paper presents an edge detection algorithm based on singular value eigenvector and gradient operator. In the proposed algorithm, the singular values of image blocks are first calculated, and the Sobel gradient template is extended to eight other directions. Then the gradient values of image pixels are determined according to the stability of the singular values of image blocks. The determination of gradient threshold is considered from both global and local aspects. After calculating the global and local gradient thresholds of the original image, the gradient threshold of the whole image is determined by weighting function. Then the edge pixels of the image are filtered according to the gradient threshold, and the edge information image of the original image is obtained. The experimental data show that the proposed algorithm can resist a certain degree of noise interference, and the accuracy and efficiency of edge extraction are better than other similar algorithms.

The authors present multifunctional nanoagents that can be used for imaging and treatment of bacterial infections. The nanoagents are made of fluorescent silicon nanoparticles functionalized with a glucose polymer and loaded with chlorin e6, and are taken up by bacteria via ABC transporters.

In this paper, two typical examples are used to illustrate the weak position of aircraft structure in the process of vibration. Through the modal analysis of the typical composite plate and I-shaped beam, the first 20-order modal strain energy of the plate is extracted, which is difficult to locate the weak spot due to the highly scattered location of the higher modal strain energy. The modal participation factor is introduced as the weight factor of the summation of the modal strain energy. The modal participation factor is large, the weighting factor is large, and the high modal strain energy of the composite plate moves diagonally in the 45° direction of the composite plate and the high strain energy region is consistent with the previous modes of the plate. This is the result of the weak in-plane shear stiffness of the composite panel, which shows the effectiveness of the mode weighted summation method. The I-shaped composite beam uses the modal strain energy summation of the weight factor, and the higher modal strain energy is concentrated on the middle part of the beam and at 1/4 and 3/4 of it. Therefore, the weak part of the vibration can be clearly identified. The higher modal strain energy is extracted by the method proposed to this paper, which can be used as a reference to structural design and dynamic on-line monitoring.

In this study, to screen for walnut salt-tolerant rootstocks, Juglans microcarpa L. seedlings were treated in different NaCl concentrations (0, 50, 100, 200, and 300 mmol/L), and the growth situation of seedlings was observed. Moreover, we determined the physiological indexes of seedlings on different days (6, 12, 18, and 24 d) after treatment. The results showed that after salt stress, the external morphology of seedlings displayed salt injury, which manifested as yellowing, withering, curling, and falling off of leaves. High concentrations and long-term stress led to more serious damage, with numerous leaves undergoing withering and shedding. Salt stress significantly inhibited the growth of seedlings. With the increase in salt concentration and stress time, the chlorophyll content and photosynthetic parameters of seedlings reduced to varying degrees; the relative electrical conductivity (REC) and malondialdehyde (MDA) increased. Superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities generally increased, followed by a decrease; proline (Pro) accumulated; and soluble sugar (SS) content first increased and then decreased. In addition, it promoted the production of abscisic acid (ABA) and inhibited the synthesis of indole-3-acetic acid (IAA), gibberellic acid 3 (GA3), and zeatin riboside (ZR). It was found that J.microcarpa L. seedlings were more tolerant under 100 mmol/L salt stress, whereas the damage to growth was more severe at 200 mmol/L to 300 mmol/L salt stress.

Walnut is one of the world’s four largest nuts. Currently, the bottleneck in walnut breeding is the production of resistant variants. Soil salinization is a global problem, and the use of salt-tolerant rootstocks is a basic strategy to overcome the challenge of sustained walnut production. Providing a scientific basis for the selection of walnut salt-tolerant rootstocks is possible by studying the physiological and biochemical response characteristics and salt tolerance variations of different walnut genotypes under salt stress. In the present study, seedlings of four genotypes of walnut rootstocks, including J1 (Juglans hindsii), J2 (J. mandshurica), J3 (J. regia × J. mandshurica), and J4 (J. regia × J. hindsii), were employed as test materials to conduct a 28-day pot experiment under NaCl stress with five NaCl concentrations (0, 50, 100, 200, and 300 mmol/L). Under different NaCl treatment concentrations, seedling morphology, growth indices, chlorophyll content, photosynthetic parameters, relative electrical conductivity (REC), malondialdehyde (MDA), proline (Pro), soluble sugar (SS), and the activity of superoxide dismutase (SOD) and peroxidase (POD) in the leaves were examined. Salt stress altered the morphological characteristics and growth indices of seedlings from four genotypes to varying degrees. In addition, according to the analysis of physiological and biochemical data, salt stress had a considerable impact on both the physiological and biochemical processes of seedlings. Salt stress decreased the chlorophyll content and photosynthetic parameters of four genotypes, the REC, MDA content, Pro content, and SS content of each genotype increased by different degrees, and the enzymatic activities showed different trends. The salt tolerance of rootstocks was evaluated thoroughly using principal component analysis and membership function analysis based on the 16 parameters. The results of a comprehensive evaluation of salt tolerance showed that the order of salt tolerance of the four genotypes was J4 > J1 > J3 > J2, which corresponded to the order of the morphological symptoms of salt injury. In conclusion, J4 has strong salt tolerance and is an important germplasm resource for walnut salt-tolerant rootstock breeding.

This paper provides a detailed description of the recommendation system and collaborative filtering algorithm to optimize the English learning platform through the collaborative filtering algorithm and analyses the algorithmic principles and specific techniques of collaborative filtering. After introducing the recommendation system and collaborative filtering algorithm, this paper elaborates on the theoretical basis and technical principles of the recommendation algorithm based on cognitive ability and difficulty and provides an in-depth analysis of the design and implementation of the recommendation algorithm by combining cognitive diagnosis theory, readability formula, and English knowledge map, which provides a comprehensive and solid theoretical guidance and support for the application development of the online English learning platform. The system is tested by building a Spring Cloud platform, importing actual business data, focusing on the validation of the recommendation model, and connecting the recommendation system to the formal production system to analyse the recommendation effect. Compared with the original recommendation method, the online English learning platform designed and implemented in this paper based on the cognitive ability and difficulty collaborative filtering recommendation algorithm has a better recommendation effect. The system is proved to be well designed and has certain reference and guiding value for the whole web-based online learning platform and has a broader application prospect nowadays and in the future.

Multidrug-resistant bacteria (MDR) are becoming a global health problem, and scientists are continuously investigating new strategies to fight against MDR. Seaweeds are an important source of biological compounds and can serve as natural sources for bacterial infection control. This study evaluated the antimicrobial and anti-quorum sensing (QS) activities of phlorotannins from Hizikia fusiforme. The phlorotannins exhibited antimicrobial activity against selected bacterial pathogens and inhibited QS activity of the reporter strain Chromobacterium violaceum 12472 by inhibiting purple pigment production. Phlorotannins can decrease the bacterial motility, reduce the production of extracellular protease, hemolysin, and pyocyanin and inhibit biofilm formation of Pseudomonas aeruginosa. In vivo studies showed that phlorotannins can reduce P. aeruginosa inflicted mortality in Caenorhabditis elegans. This study shows that phlorotannins from H. fusiforme have certain antimicrobial and anti-quorum sensing activities and have the potential to control bacterial infection for pharmaceutical usage.

Childhood nephrotic syndrome is a chronic disease harmful to growth of children. Scientific and accurate prediction of negative conversion days for children with nephrotic syndrome offers potential benefits for treatment of patients and helps achieve better cure effect. In this study, the improved backpropagation neural network with momentum is used for prediction. Momentum speeds up convergence and maintains the generalization performance of the neural network, and therefore overcomes weaknesses of the standard backpropagation algorithm. The three-tier network structure is constructed. Eight indicators including age, lgG, lgA and lgM, etc. are selected for network inputs. The scientific computing software of MATLAB and its neural network tools are used to create model and predict. The training sample of twenty-eight cases is used to train the neural network. The test sample of six typical cases belonging to six different age groups respectively is used to test the predictive model. The low mean absolute error of predictive results is achieved at 0.83. The experimental results of the small-size sample show that the proposed approach is to some degree applicable for the prediction of negative conversion days of childhood nephrotic syndrome.

Current mainstream super-resolution algorithms based on deep learning use a deep convolution neural network (CNN) framework to realize end-to-end learning from low-resolution (LR) image to high-resolution (HR) images, and have achieved good image restoration effects. However, as the number of layers in the network is increased, better results are not necessarily obtained, and there will be problems such as slow training convergence, mismatched sample blocks, and unstable image restoration results. We propose a preclassified deep-learning algorithm (MGEP-SRCNN) using Multilabel Gene Expression Programming (MGEP), which screens out a sample sub-bank with high relevance to the target image before image block extraction, preclassifies samples in a multilabel framework, and then performs nonlinear mapping and image reconstruction. The algorithm is verified through standard images, and better objective image quality is obtained. The restoration effect under different magnification conditions is also better.

Magnetic field sensing based on magnetic-fluid-clad multimode-singlemode- multimode fiber structures is proposed and experimentalized. The structures are fabricated out using fiber fusion splicing techniques. The sensing principle is based on the interference between the core mode and cladding modes. Two interference dips are observed in our spectral range. Experimental results indicate that the magnetic field sensing sensitivities of 215 pm/mT and 0.5742 dB/mT are obtained for interference dip around 1595 nm. For interference dip around 1565 nm, the sensitivities are 60.5 pm/mT and 0.4821 dB/mT. The response of temperature is also investigated. The temperature sensitivity for the dip around 1595 nm is obtained to be 9.93 pm/°C.

The effects of the gas pressure (pg), microcavity height (t), Au vapor addition, and microwave frequency on the properties of three-dimensional confined microwave-induced microplasmas were discussed in light of simulation results of a glow microdischarge in a three-dimensional microcavity (diameter dh = 1000 μm) driven at constant voltage loading on the drive electrode (Vrf) of 180 V. The simulation was performed using the PIC/MCC method, whose results were experimentally verified. In all the cases we investigated in this study, the microplasmas were in the γ-mode. When pg increased, the maximum electron (ne) or ion density (nAr+) distributions turned narrow and close to the discharge gap due to the decrease in the mean free path of the secondary electron emission (SEE) electrons (λSEE-e). The peak ne and nAr+ were not a monotonic function of pg, resulting from the two conflicting effects of pg on ne and nAr+. The impact of ions on the electrode was enhanced when pg increased. This was determined after comparing the results of ion energy distribution function (IEDFs) at various pg. The effects of t on the peaks and distributions of ne and nAr+ were negligible in the range of t from 1.0 to 3.0 mm. The minimum t of 0.6 mm for a steady glow discharge was predicted for pg of 800 Pa and Vrf of 180 V. The Au vapor addition increased the peaks of ne and nAr+, due to the lower ionization voltage of Au atom. The acceleration of ions in the sheaths was intensified with the addition of Au vapor because of the increased potential difference in the sheath at the drive electrode.

Hyperuricemia (HUA) is related to diabetes. Uric acid-induced inflammation and oxidative stress are risk factors for diabetes and its complications. Human urate transporter 1 (URAT1) regulates the renal tubular reabsorption of uric acid. IA-2(5)-P2-1, a potent immunogenic carrier designed by our laboratory, can induce high-titer specific antibodies when it carries a B cell epitope, such as B cell epitopes of DPP4 (Dipeptidyl peptidase-4), xanthine oxidase. In this report, we describe a novel multi-epitope vaccine composing a peptide of URAT1, an anti-diabetic B epitope of insulinoma antigen-2(IA-2) and a Th2 epitope (P2:IPALDSLTPANED) of P277 peptide in human heat shock protein 60 (HSP60). Immunization with the multi-epitope vaccine in streptozotocin-induced diabetes C57BL/6J mice successfully induced specific anti-URAT1 antibody, which inhibited URAT1 action and uric acid reabsorption, and increased pancreatic insulin level with a lower insulitis incidence. Vaccination with U-IA-2(5)-P2-1 (UIP-1) significantly reduced blood glucose and uric acid level, increased Th2 cytokines interleukin (IL)-10 and IL-4, and regulated immune reactions through a balanced Th1/Th2 ratio. These results demonstrate that the URAT1-based multi-epitope peptide vaccine may be a suitable therapeutic approach for diabetes and its complications.

Filtration during extracorporeal circulation (ECC) not only removes but also activates leukocytes; therefore, long-term leukocyte filtration may cause adverse effects. In the present study, we tested this hypothesis by priming ECC with 300 mL of canine blood and examining filtration effects in 3 groups (n=6 each) during 60 min ECC. In the control group (Group C) blood was filtrated with an arterial filter for 60 min; in long-term (Group L) and short-term (Group S) groups, blood was filtrated with a leukocyte filter for 60 and 5 min. We found that about 90% of leukocytes were removed after 5 min of filtration in both Groups L and S. Although leukocyte count continued to reduce, mean fluorescent intensities of CD11/CD18, free hemoglobin, and neutrophil elastase increased in Group L and were higher than those in Groups C and S at 60 min. Leukocyte rupture, cytoplasmic leakage, and circulating naked nuclei were also found in Group L. The data support our hypothesis that long-term filtration can induce inflammation and lead to leukocyte destruction.

Chinese High Magnetic Field Laboratory (CHMFL) will build a resistive magnet with steady magnetic field strength of 42 Tesla which will set a new record for a single resistive magnet. As one of the important auxiliary systems, the cooling water system needs to be fully upgraded to meet the higher cooling requirements of the magnet and the power system. In this paper, the reconstruction scheme of cooling water system is introduced firstly, then the parameters selection of the chilled water pumps and high-pressure pure water pumps are emphatically analyzed. The data fitting method and the applied fluid technology software ATF Fathom were used to analyze and check the selection of chilled water pump. After these pumps are in place, the effectiveness of the above analysis scheme has been verified through testing, which can provide a reference for the reconstruction of pumps in other systems. For the high-pressure pure water pump, the solution focuses on improving the overall cooling capacity of the pump group and also improving the system stability. Based on the large-circulation-flow magnet of CHMFL, tests were conducted on the parallel operation capability of the new and old pumps, and the system characteristic curve and pump performance curve are analyzed and researched. The result shows that the pump parameters selection is reasonable and the magnet cooling circulation capacity is effectively improved. [ABSTRACT FROM AUTHOR]

The traditional image super-resolution (SR) reconstruction methods do not carry out sparse coding when performing SR reconstruction, resulting in poor structural similarity of image SR reconstruction. Therefore, this paper proposes a a super-resolution reconstruction method for polymorphic sparsity regularized images based on machine learning algorithms and builds a sparse representation model of polymorphic regularized images. For sparse representation models with different norm constraints, the orthogonal matching tracking in the greedy algorithm is used perform sparse coding to solve the sparse representation coefficient. The least square method in machine learning algorithm is used to solve the inverse operation of dictionary matrix update, construct the image super-resolution reconstruction minimization objective function, and solve the loss function between the super-resolution reconstruction image and the actual image, so as to complete the super-resolution reconstruction of polymorphic sparsity regularized image. The experimental results show that the edge recovery of the image under the proposed method is clearer, and the edge with more distinct edges and corners can be reconstructed. The Peak-Signal-to-Noise Ratio (PSNR) of the super-resolution reconstruction image is 60.5dB, and the Structural Similarity (SSIM) of the super-resolution reconstruction image is as high as 0.99, which effectively improves the image reconstruction effect. [ABSTRACT FROM AUTHOR]