Application Value Research Articles

Gust Response and Alleviation of Avian-Inspired In-Plane Folding Wings.

The in-plane folding wing is one of the important research directions in the field of morphing or bionic aircraft, showing the unique application value of enhancing aircraft maneuverability and gust resistance. This article provides a structural realization of an in-plane folding wing and an aeroelasticity modeling method for the folding process of the wing. By approximating the change in structural properties in each time step, a method for calculating the structural transient response expressed in recursive form is obtained. On this basis, an aeroelasticity model of the wing is developed by coupling with the aerodynamic model using the unsteady panel/viscous vortex particle hybrid method. A wind-tunnel test is implemented to demonstrate the controllable morphing capability of the wing under aerodynamic loads and to validate the reliability of the wing loads predicted by the method in this paper. The results of the gust simulation show that the gust scale has a significant effect on the response of both the open- and closed-loop systems. When the gust alleviation controller is enabled, the peak bending moment at the wing root can be reduced by 5.5%∼47.3% according to different gust scales.

Impact and mechanisms of drag-reducing polymers on shear stress regulation in pulmonary hypertension.

Pulmonary hypertension (PH) is a refractory disease characterized by elevated pulmonary artery pressure and resistance. Drag-reducing polymers (DRPs) are blood-soluble macromolecules that reduce vascular resistance by altering the blood dynamics and rheology. Our previous work indicated that polyethylene oxide (PEO) can significantly reduce the medial wall thickness and vascular resistance of the pulmonary arteries, but the specific mechanism is still unclear. This study was designed to investigate the role and mechanism of PEO on intracellular calcium [Ca2+] i and cytoskeletal proteins of endothelial cells (ECs) induced by low shear stress (LSS) in PH. Primary Pulmonary Artery Endothelial Cells (PAECs) were subjected to steady LSS (1 dyn/cm2) or physiological shear stress (SS) (10 dyn/cm2) for 20 h in a BioFlux 200 flow system. Calcium influx assays were conducted to evaluate the mechanisms of PEO on [Ca2+] i. Subsequently, taking the key protein that induces cytoskeletal remodeling, the regulatory light chain (RLC) phosphorylation, as the breakthrough point, this study focused on the two key pathways of PEO that regulate phosphorylation of RLC: Myosin light chain kinase (MLCK) and Rho-associated kinase (ROCK) pathways. Our current research revealed that PEO at LSS (1 dyn/cm2) significantly suppressed LSS-induced [Ca2+] i and the expression level of transient receptor potential channel 1(TRPC1). In addition, ECs convert LSS stimuli into the upregulation of cytoskeletal proteins, including filamentous actin (F-actin), MLCK, ROCK, p-RLC, and pp-RLC. Further experiments using pharmacological inhibitors demonstrated that PEO at the LSS downregulated cytoskeleton-related proteins mainly through the ROCK and MLCK pathways. This study considered intracellular calcium and cytoskeleton rearrangement as entry points to study the application of PEO in the biomedical field, which has important theoretical significance and practical application value for the treatment of PH.

Bi-TAM-Net framework: fault diagnosis for insulated bearing based on new noise-resistant time-series framework

Abstract Insulated bearings are extensively employed in wind turbines and other applications as essential core parts of high-power frequency control motors. However, the influence of the wind turbine structure makes it difficult to define the wind turbine insulated bearing fault signal extraction, and there is no distinctive index or qualitative formula to describe the bearing fault. In order to solve the above challenges, Bi-TAM-Net framework is developed to diagnose the insulated bearing fault signals and achieve accurate identification of bearing faults. Firstly, the temporal information feature fusion model is created by the Bi-TAM-Net framework using the time-series bearing dataset as the model data input with recursive and chain linking rules in the direction of time-series evolution. By virtue of its parallel approach and deep stacking structure, it comprehensively portrays the bearing fault data and temporally fuses the global feature information, which can effectively improve the classification performance of insulated bearing fault data. Then the self-attention mechanism is introduced into the structure of the designed temporal information fusion model for optimization, which can be modeled in sequences of arbitrary length, extracting the correlation between the features, isolating the unimportant noise information, and strengthening the extraction ability of the proposed framework for important information. Finally, in order to verify the accuracy and superiority of the developed Bi-TAM-Net framework for bearing faults, based on the same dataset, the Bi-TAM-Net framework is compared and analyzed with seven methods such as the advanced TAM-Net model, and the results show that the Bi-TAM-Net framework has better superiority. This study offers the analytical approach with engineering application value for the design and maintenance of insulated bearings used in wind turbines.

A new combined transient electromagnetic noise reduction method of VMD-SVD-WTD based on improved dung beetle optimization algorithm with multi-strategy fusion

Abstract The transient electromagnetic method (TEM) is now commonly used in the detection of coal mined-out areas, but it is susceptible to various sources of noise during field site probing, significantly impacting the accuracy of detection. Variational mode decomposition (VMD) has gained widespread adoption for eliminating noise in TEM signals. However, a single VMD may not effectively address both full-band noise and residual Gaussian white noise. To address this limitation, the singular value decomposition (SVD) and wavelet threshold denoising (WTD) are introduced correspondingly. Furthermore, this paper tackles challenges related to parameters selection in VMD and traditional optimization algorithms by proposing the integration of dung beetle optimization (DBO) enhanced with circle chaotic mapping, random walk strategy, and crisscross optimization algorithm (CRCDBO). Consequently, a new combined TEM noise reduction method, VMD-SVD-WTD based on CRCDBO is presented. Through comprehensive simulation tests and comparative analyses, the signal-to-noise ratio of this method is improved by 12.79% compared with VMD and the RMSE is 0.0011, which demonstrate the superiority and effectiveness of VMD-SVD-WTD based on CRCDBO in noise reduction. Meanwhile, this method is applied to an iron ore mine in Shanxi, which can accurately monitor the location of the mined-out area and has good application value.

Practical exploration of BOPPPS model combined with situational teaching method in clinical training of intensive medicine: novel pedagogy and perception.

To explore the application value of bridge-in, learning objective, pre-assessment, participatory learning, post-assessment, and summary (BOPPPS) model combined with situational teaching method in the clinical teaching of intensive care unit (ICU), and to provide experience for the reform of ICU clinical teaching and standardized training of intensive medicine. A randomized trial was conducted using a multi-center, prospective cohort study. A total of 293 residential physicians in ICU of Fujian Medical University Union Hospital, the Affiliated Hospital of Putian University and the First Affiliated Hospital of Gannan Medical University from January 2021 to December 2023 were selected as subjects, and the residential physicians in ICU in each medical center were divided into control group and experimental group using random number table method. The control group adopted bedside teaching and demonstration teaching method, and the experimental group adopted BOPPPS model combined with situational teaching method. Clinical teaching performance was evaluated by ICU admission examination, and study process questionnaire (SPQ) and the critical thinking disposition inventory-Chinese version (CTDI-CV) was used to evaluate the learning motivation and critical thinking ability of the two groups. At the same time, the effect evaluation and satisfaction questionnaire of ICU training (EESQ) was used to evaluate the teaching satisfaction. The scores of the experimental group in ICU theoretical knowledge, clinical thinking and skills, and the treatment of clinical critical cases were higher than those of the control group [(87.31 ± 13.15), (92.86 ± 12.35), (81.45 ± 11.28)] vs. [(83.94 ± 12.73), (88.37 ± 12.61), (78.83 ± 10.47)], the difference between the two groups was statistically significant (p < 0.05). The scores of surface motivation, deep motivation, achievement motivation and SPQ total scores of the experimental group were all higher than those in control group (p < 0.05), and the scores of seek truth, open mind, analytical ability, systematic ability, self-confidence of critical thinking and intellectual curiosity of the experimental group were also higher than those in the control group, and the CTDI total score was statistically significant (p < 0.05). In addition, the results of the questionnaire showed that the experimental group was better than the control group in terms of learning interest in ICU, improvement of humanistic care and doctor-patient communication ability, improvement of teamwork ability, improvement of job identity, ICU training harvest and satisfaction with teacher style (p < 0.05). The combination of BOPPPS model and situational teaching method is likely a more effective and helpful which may improve the clinical comprehensive ability and training quality of residential physicians, and it may be worth learning and promoting.

Coronary heart disease evaluation using PCAT radiomics model based on coronary CT angiography and pericoronary adipose tissue.

To explore the clinical application value of radiomics model based on pericoronary adipose tissue (PCAT) in predicting coronary heart disease. A retrospective analysis was performed for inpatients who had undergone coronary computed tomography angiography from January to December 2023, and 164 cases of coronary artery lesions were screened as the lesion group and 190 cases of normal coronary artery samples were selected as the control group. The clinical data and imaging data of all patients were collected, the radiomics features were extracted by relevant software, and the "region of interest" of pericoronary fat was delineated, and the selection operator and multivariate logistic regression were used to screen the radiomic features of pericoronary fat. A coronary heart disease evaluation model was constructed by the best radiomics features. Area under the curve values of the PCAT radiomics scoring model for predicting the receiver operating characteristic curve of coronary heart disease were 0.863 and 0.851 in training and test sets, respectively. After calibration curve analysis, PCAT radiomics scoring model has a high consistency between the predictive evaluation results and the actual results of coronary heart disease events. In addition, in the training set, the PCAT radiomics scoring model has a net benefit on all threshold probabilities. In the test set, the model has a negative net return with only a small number of threshold probabilities. After combining the clinical characteristics model, the evaluation accuracy of the model for coronary heart disease can reach 0.896. PCAT radiomics model based on coronary computed tomography angiography can effectively predict and evaluate coronary heart disease, which is of great value for the clinical diagnosis of coronary artery disease.

The value of postoperative contrast-enhanced ultrasound parameters in lymph node metastasis, tumor node metastasis, and treatment response evaluation of resected hepatocellular carcinoma.

To explore the application value of postoperative contrast-enhanced ultrasound (CEUS) parameters for lymph node metastasis (LNM), tumor, node, metastasis staging, and treatment response evaluation of resected hepatocellular carcinoma (HCC). We retrospectively analyzed 100 patients with liver cancer who underwent liver CEUS at our hospital between October 2020 and October 2022. The patient's LNM, pathological staging, and therapeutic effects were recorded based on the histopathological results. CEUS parameters were analyzed and compared CEUS parameters between different lymph node metastases, pathological stages, and therapeutic effects. Twenty-three patients experienced LNM, 77 patients did not experience LNM; and the rise time (RT), peak intensity (PI), and area under the curve (AUC) of the metastatic group were significantly smaller than those of the nonmetastatic group (P < .05). 44 cases were classified into groups I to II by pathological staging, and 56 cases were classified into groups III to IV. The RT, PI, and AUC of groups III to IV were significantly lower than those of groups I-II (P < .05). Seventy-nine cases were complete necrosis, 21 cases were residual or recurrent; The RT, PI, and AUC of the residual or recurrent group were significantly lower than those of the complete necrosis group (P < .05). The receiver operating characteristic curve shows that RT, PI, and AUC have a certain value in evaluating LNM, pathological staging, and treatment response of HCC, and the combined evaluation/evaluation value of these 3 factors is relatively high. The postoperative CEUS parameters RT, PI, and AUC can be used for LNM, pathological staging evaluation, and treatment response evaluation of HCC. Moreover, the combination of the 3 parameters is feasible and valuable in evaluating LNM, tumor, node, metastasis staging, and treatment response of HCC.

Application value of SOMATOM Force computed tomography in assisting the preoperative localization of colorectal cancer resection surgery

Background The objective of this study was to assess the application value of SOMATOM Force computed tomography (CT) in assisting the preoperative localization of colorectal cancer resection surgery. Method Retrospectively, the medical data of 120 inpatients with colorectal cancer were collected. The Kappa consistency test was used to evaluate diagnostic consistency in the localization and staging of colorectal cancer. The diagnostic value of preoperative SOMATOM Force CT detection was analyzed. Results In 120 colorectal cancer patients, the accuracy of SOMATOM Force CT for preoperative localization, T staging, and N staging of colorectal cancer were 91.7% (kappa = 0.837), 88.3% (kappa = 0.772) and 91.7% (kappa = 0.773), respectively. Among 45 rectum cancer patients, there were 19 positive cases with circumferential resection margin involvement, and the accuracy of SOMATOM Force CT detection was 86.7% (kappa = 0.767). The sensitivity, specificity, positive predictive value, and negative predictive value of SOMATOM Force CT detection in evaluating the circumferential resection margin involvement of rectum cancer were 78.95%, 96.15%, 93.75%, and 86.21%, respectively. Conclusions There was an important application value of SOMATOM Force CT in assisting the preoperative localization and tumor staging of colorectal cancer resection surgery. There was a good diagnostic value of preoperative SOMATOM Force CT detection in evaluating the circumferential resection margin involvement of rectum cancer.

MRI-based radiomics model for predicting endometrial cancer with high tumor mutation burden.

To evaluate the performance of MRI-based radiomics in predicting endometrial cancer (EC) with a high tumor mutation burden (TMB-H). A total of 122 patients with pathologically confirmed EC (40 TMB-H, 82 non-TMB-H) were included in this retrospective study. Patients were randomly divided into training and testing cohorts in a ratio of 7:3. Radiomics features were extracted from sagittal T2-weighted images and contrast-enhanced T1-weighted images. Then, the logistic regression (LR), random forest (RF), and support vector machine (SVM) algorithms were used to construct radiomics models. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of each model, and decision curve analysis was used to determine their clinical application value. Four radiomics features were selected to build the radiomics models. The three models had similar performance, achieving 0.771 (LR), 0.892 (RF), and 0.738 (SVM) in the training cohort, and 0.787 (LR), 0.798 (RF), and 0.777 (SVM) in the testing cohort. The decision curve demonstrated the good clinical application value of the LR model. The MRI-based radiomics models demonstrated moderate predictive ability for TMB-H EC and thus may be a tool for preoperative, noninvasive prediction of TMB-H EC.

Meta-analysis of RCTs on the safety of non-fixation of mesh in TAPP inguinal hernia repair: an updated meta-analysis

ObjectiveThis meta-analysis aims to compare the clinical efficacy of mesh non-fixation and fixation in laparoscopic transabdominal preperitoneal (TAPP) inguinal hernia repair, systematically evaluating the application value of the mesh non-fixation technique in clinical settings.MethodsA computerized search of PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov databases was conducted to identify randomized controlled trials (RCTs) comparing mesh non-fixation and fixation in TAPP inguinal hernia repair. Meta-analysis was performed using RevMan 5.3 software, and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) evidence grading system was employed for outcome quality assessment. Publication bias analysis was performed using Begg’s test. A trial sequential analysis (TSA) was performed using TSA 0.9.5.10 Beta software.ResultsA total of nine RCTs involving 1,879 inguinal hernia patients were included. Meta-analysis results demonstrated that, compared to the fixation group, the non-fixation group exhibited significantly lower seroma occurrence rate [RR = 0.43, 95% CI (0.20, 0.89), P = 0.02, heterogeneity P = 0.28, I²=22%], Visual Analog Scale (VAS) pain score at 6 months postoperatively [MD=-0.21, 95% CI (-0.29, -0.12), P < 0.00001, heterogeneity P = 0.34, I²=0%], and cost [MD=-3.23 thousand yuan, 95% CI (-4.26, -2.19), P < 0.00001, heterogeneity P = 0.0003, I²=92%]. There were no statistically significant differences in overall complication rate [RR = 0.88, 95% CI (0.62, 1.23), P = 0.45, heterogeneity P = 0.11, I²=44%], overall infection event rate [RR = 0.96, 95% CI (0.36, 2.56), P = 0.93, heterogeneity P = 0.62, I²=0%] and recurrence rate [RR = 0.75, 95% CI (0.28, 1.99), P = 0.56, heterogeneity P = 0.44, I²=0%] between the two groups. The results of the TSA indicated that the observed lower seroma occurrence rate in the non-fixation group compared to the fixation group requires further validation through the inclusion of additional RCTs.ConclusionMesh non-fixation in TAPP inguinal hernia repair is deemed safe and does not elevate the risk of hernia recurrence. However, given certain limitations in this study, future comprehensive and reliable validation will require further multicenter, high-quality, large-sample double-blind RCTs.

Multimodal deep learning radiomics model for predicting postoperative progression in solid stage I non-small cell lung cancer

PurposeTo explore the application value of a multimodal deep learning radiomics (MDLR) model in predicting the risk status of postoperative progression in solid stage I non-small cell lung cancer (NSCLC).Materials and MethodsA total of 459 patients with histologically confirmed solid stage I NSCLC who underwent surgical resection in our institution from January 2014 to September 2019 were reviewed retrospectively. At another medical center, 104 patients were reviewed as an external validation cohort according to the same criteria. A univariate analysis was conducted on the clinicopathological characteristics and subjective CT findings of the progression and non-progression groups. The clinicopathological characteristics and subjective CT findings that exhibited significant differences were used as input variables for the extreme learning machine (ELM) classifier to construct the clinical model. We used the transfer learning strategy to train the ResNet18 model, used the model to extract deep learning features from all CT images, and then used the ELM classifier to classify the deep learning features to obtain the deep learning signature (DLS). A MDLR model incorporating clinicopathological characteristics, subjective CT findings and DLS was constructed. The diagnostic efficiencies of the clinical model, DLS model and MDLR model were evaluated by the area under the curve (AUC).ResultsUnivariate analysis indicated that size (p = 0.004), neuron-specific enolase (NSE) (p = 0.03), carbohydrate antigen 19 − 9 (CA199) (p = 0.003), and pathological stage (p = 0.027) were significantly associated with the progression of solid stage I NSCLC after surgery. Therefore, these clinical characteristics were incorporated into the clinical model to predict the risk of progression in postoperative solid-stage NSCLC patients. A total of 294 deep learning features with nonzero coefficients were selected. The DLS in the progressive group was (0.721 ± 0.371), which was higher than that in the nonprogressive group (0.113 ± 0.350) (p < 0.001). The combination of size、NSE、CA199、pathological stage and DLS demonstrated the superior performance in differentiating postoperative progression status. The AUC of the MDLR model was 0.885 (95% confidence interval [CI]: 0.842–0.927), higher than that of the clinical model (0.675 (95% CI: 0.599–0.752)) and DLS model (0.882 (95% CI: 0.835–0.929)). The DeLong test and decision in curve analysis revealed that the MDLR model was the most predictive and clinically useful model.ConclusionMDLR model is effective in predicting the risk of postoperative progression of solid stage I NSCLC, and it is helpful for the treatment and follow-up of solid stage I NSCLC patients.

Unravelling the physiological and molecular mechanisms of leaf color change in Acer griseum through multi-omics analysis

Paperbark maple (Acer griseum), an endemic and endangered wild plant in China, has red-colored autumn leaves of high ornamental and garden application value. Leaf color change serves as a crucial indicator for evaluating garden tree aesthetics; however, research on A. griseum's leaf color change remains limited. This study aims to elucidate the physiological and molecular mechanisms underlying leaf color change in maple leaves through physiological, transcriptional, and metabolic assays. Data analysis encompasses gene expression levels and metabolite changes in three distinct states of maple leaves: green, half-red, and red. The progessive decrease of chlorophyll and carotenoids and the continuous accumulation of anthocyanidins caused a sharp change in leaf coloration, which was most drastic in the green to half-red period. Subsequently, targeted metabolomics analysis was performed, and a total of 71 anthocyanidins were detected, and the content of eight types of anthocyanidins increased significantly in the half-red and red periods, compared with that in the green period; of which the multiplicative difference was the largest for cyanidin-3,5-O diglucoside, delivering the largest multiplicative difference. Thus, it was plausible that cyanidin-3,5-O-diglucoside-dominated compoundswere likely to be the main metabolites associated with leaf reddening. Correlation analysis revealed that 12 key transcription factors (TFs) were significantly correlated with the anthocyanin-related metabolites and structural genes, which play important regulatory roles during the biosynthesis of anthocyanosides in A. griseum. These findings offered useful insights into the molecular basis of leaf color variation in A. griseum; providing valuable information to guide targeted genetic breeding and varietal improvement strategies.

The Effectiveness of Tiktok in Increasing Brand Awareness Among Users

Technological advancements have revolutionized marketing strategies, particularly in the realm of social media. As businesses recognize the importance of brand awareness in consumer decision-making, platforms like TikTok have emerged as powerful tools for enhancing brand visibility. Despite its rapid rise in popularity, TikTok's effectiveness in increasing brand awareness remains underexplored. This study investigates "The Effectiveness of TikTok in Increasing Brand Awareness Among Users" with three primary objectives: (RO1) to identify the effect of Mobile Application Values, Information Quality, System Quality, and Influencer Trust on Brand Awareness; (RO2) to identify the effect between Brand Awareness and Word of Mouth; and (RO3) to analyze the effect between Brand Awareness on Purchase Intention. The research adopts a quantitative approach, utilizing a questionnaire distributed to B2C TikTok users. A sample size of 343 respondents was determined using stratified sampling. Descriptive and regression analyses were conducted to interpret the data. The results indicate that Mobile Application Value, System Quality, and Influencer Trust significantly influence Brand Awareness on TikTok, while Information Quality does not exhibit a significant effect. Moreover, Brand Awareness positively impacts both Word of Mouth and Purchase Intention, underscoring its pivotal role in consumer behavior. This study contributes to a deeper understanding of TikTok's potential as a branding tool and offers practical insights for marketers seeking to leverage the platform effectively. Despite limitations in sample size and survey biases, the findings provide a foundation for future research and the refinement of marketing strategies in the dynamic landscape of social media.

3D-printed magnesium-doped micro-nano bioactive glass composite scaffolds repair critical bone defects by promoting osteogenesis, angiogenesis, and immunomodulation

Magnesium ions play an important immune-regulatory role during bone repair. For this study, we prepared micro-nano bioactive glass (MNBG) containing magnesium, which can release magnesium, silicon, and calcium ions and has a positive impact on osteogenic differentiation and vascular regeneration. In this study, MgMNBG was compounded and combined with poly(lactic-co-glycolic acid (PLGA) and polycaprolactone (PCL) for 3D printing. Afterwards, the physicochemical properties and bone repair performance of the scaffolds were evaluated throughin vitroandin vivoexperiments. We also investigated the effects of MgMNBG on osteogenic differentiation, immune regulation, and vascular regeneration. The results showed that MgMNBG can inhibit inflammation and promote osteogenesis and angiogenesis by regulating macrophages. PLGA/PCL/MgMNBG scaffolds have good osteogenic and angiogenic effects, and the composite scaffolds have excellent bone repair performance and potential application value.

Obtaining Highly Efficient Radon Adsorbents by Adjusting the Pore Structure of Bamboo Charcoal with Particle Size Fractionated Activation.

To achieve highly efficient adsorbents for radon (Rn), this study prepared bamboo activated carbon (BAC) using bamboo charcoal as the precursor and KOH and NaOH as activators and employed a method of activation by adjusting the pore structure through particle size fractionation. Under the same activation conditions, KOH was consumed less and showed better Rn adsorption performance than NaOH, and the solid milling method saved more activator dosage compared to the liquid immersion method. After carbonizing the bamboo, the highest Rn adsorption coefficients of the bamboo charcoal activated with particle size fractionation (0.43-0.85, 0.25-0.43, 0.18-0.25, and <0.18 mm) were 8.41 ± 0.05, 10.03 ± 0.24, 9.31 ± 0.01, and 8.15 ± 0.21 L/g, respectively under N2 conditions (at a temperature of 25 °C and humidity of 35%), which were significantly greater than those of bamboo charcoal with overall activation (7.05 ± 0.23 L/g). After optimization, all of the bamboo charcoals with different particle sizes had the highest volume ratio for pores with a diameter of 0.77 nm. BC0.43-0.85K1.25 and BC0.25-0.43K0.75 maintained 95.74 and 92.36%, respectively, of the original adsorption coefficient after 5 cycles of regeneration under nitrogen. As the bamboo charcoal particle size decreased, the optimal mass ratio of alkali/carbon also decreased. This indicates that particle-size-fractionated activation can reduce the raw material and activator waste. The optimized BAC has a significantly higher Rn adsorption coefficient than the currently used coconut shell activated carbon (4.13 ± 0.51 L/g), making it an efficient and economical adsorbent with excellent application value for radon removal.

Web log mining techniques to optimize Apriori association rule algorithm in sports data information management

To optimize the current college sports data information management system, this study combines the Apriori association rule algorithm with web application development technology to upgrade the management system. Firstly, this study explores novel log mining techniques in genetic algorithms and web application development technology. Secondly, by integrating log mining techniques to optimize the Apriori algorithm, associations between sports data and information are discovered. Through the optimized algorithm, this study identifies key association rules of sports data information and validates the optimized system’s reliability and effectiveness through experiments. The experimental results show that the running time of the traditional Apriori algorithm exponentially grows with the increase in information volume, while the optimized execution efficiency is improved by approximately 10–15%. Additionally, the average retrieval accuracy of this optimized system can reach 98.3%, although the retrieval time also increased by 23%. Therefore, the technology and algorithms proposed in this study have certain application value in the sports information management system and contribute to the optimization of data information management in this field.

CuFe Cooperativity at the Membrane-Electrode Interface Elicits a Tandem 2e-+2e- Mechanism for Exclusive O2-To-H2O Electroreduction.

High O2 reduction reaction (ORR) kinetics and exclusive 4e- pathway selectivity are keys to realizing a sustainable society. However, nonprecious electrocatalysts at present cannot enhance the ORR turnover frequency and H2O Faradaic efficiency (FE) concurrently. To address these two challenges, hybrid bilayer membrane (HBM) electrodes with earth-abundant metal centers are developed to control proton-coupled electron transfer (PCET) in ORR. Here, an oxidase-inspired CuFe active site is supported on a tris(2-pyridylmethyl)amine HBM and explored as a unique interface for efficient ORR. This bimetallic HBM displayed an ORR activity 1.4 times higher than the monometallic systems and exhibited the highest FE for H2O (∼94%) among Cu-, Fe-, Ni-, and Co-based HBMs. Contrary to previous studies where the ORR current decreases upon embedding the metal center in a hydrophobic lipid environment, here, the incorporation of a nitrile-terminated proton carrier at the HBM interface boosts the ORR current by 1.7 folds relative to the case where the catalytic site is directly exposed to protons in solution. This intriguing dual improvement is supported by density function theory calculations where an additional 2e-+2e- mechanism occurs in parallel to the direct 4e- pathway, highlighting the synergistic effect of the CuFe HBM for facilitating high-performance ORR. A Zn-air battery is constructed using this CuFe HBM for the first time, further demonstrating that the knowledge gained from this HBM technology holds practical values in real-life applications. These findings on interfacial PCET are envisioned to spark new design principles for future catalysts with optimal electrochemical properties for advanced energy conversion schemes.

Design of an Energy-Saving System for Smart Home Decoration Based on Situational Awareness

This article analyzes the specific energy-saving requirements for smart home decoration in the current market to determine the overall plan of the entire smart home decoration energy-saving system. Based on situational analysis combined with grounded theory, organize and summarize the original data, and use factor analysis for dimensionality reduction analysis. Combining the multi-level analysis method, experts evaluated and scored the user experience evaluation indicators, obtained the weight assignment of each influencing factor, and constructed a user experience evaluation model for smart home products based on situational theory. After extensive testing, it was found that the ZigBee based smart home network implemented in this article has low energy consumption, overcomes many shortcomings of smart home networks, and has high application value.

Fine structure control of Fe3O4/ Fe2O3 film by Nitridation-Oxidation-Reduction treatment and high corrosion resistance

The nitriding post-oxidation composite treatment is clean and pollution-free, and the high corrosion resistance of the modified layer has aroused extensive research interest. The phase composition and microstructure of Fe3O4/Fe2O3 film are key factors determining corrosion resistance. We propose a Nitridation-Oxidation-Reduction (NOR) treatment technology nitriding followed by oxidation treatment and then reduction treatment. The precise phase composition and microstructure of the oxide film were characterized and analyzed, and the corrosion resistance of the oxide film was evaluated. Through reduction treatment, the Fe3O4 phase content increased from 54.95 % to 84.75 %, the corrosion potential increased by 0.07 V and the corrosion current density decreased by 2.06 × 10-6A. After NOR treatment, the oxide film has extremely high corrosion resistance, which will have important theoretical and engineering application value.

Global transcription and metabolic profiles of five tissues in pepper fruits

Studying the regulatory mechanisms in different tissues of pepper is crucial for understanding organ formation, growth, and development. However, relevant studies are far from sufficient. In the current study, the stipe, calyx, pericarp, placenta, and seed of ripe pepper were sampled, and metabolites were determined by the untargeted metabolomics method. Transcriptome sequencing was performed by Illumina NovaSeq 6000, and then a high-throughput data set was built. The results showed that a total of 4879 annotated metabolites were detected in 15 samples of the five tissues under positive and negative ion mode. A total of 110.66 Gb of clean data was obtained by transcriptome sequencing, the clean data of each sample reached 6.21 Gb, and a total of 35 336 annotated expression genes were obtained. Furthermore, validate the accuracy of the data by combining principal component analysis and other methods. In summary, this study provides valuable information for the genetic improvement and breeding of peppers, and it holds potential application value, particularly in enhancing the quality and nutritional value of pepper fruits.