Correlation Analysis Model Research Articles

Lean Management, IATF Automotive Standard, Industry 4.0, and Operational Excellence: Correlation Analysis and Synergy Model Development

Following the constant development of the sector and differentiating themselves from the competition, automotive organizations aim to control their operations, improve their performance, and respond to customers’ needs. Lean management has become a universal management method adopted by organizations wishing to ensure their operational continuity. Compliance of quality management systems with the requirements of the international automotive standard IATF 16949:2016 is one of the major challenges facing automotive companies. Industry 4.0 enables organizations to improve their effectiveness, flexibility, and performance. The objective of this article is to demonstrate to automotive organizations the synergistic impact of the combined implementation of lean management tools in correlation with the requirements of the automotive standard and the adoption of Industry 4.0 pillars on operational excellence dimensions. Following the correlation analysis carried out, an original model specific to the automotive sector was developed with a view to guiding automotive organizations wishing to improve their operational excellence while controlling the value chain, establishing an effective management system, and creating a smart factory. This study demonstrates that, for a better result of operational excellence, it is necessary to implement lean management tools in correlation with the compliance of systems with IATF requirements and the adoption of Industry 4.0 pillars.

Spatial distribution of soil pore structure and response characteristics of physical parameters in the subsidence area induced by shallow-buried extra-thick coal seam mining

The development of ground fissures in the subsidence area induced by shallow-buried extra-thick coal seam mining leads to a decrease in soil water-holding capacity and vegetation withering. The investigation of the spatial distribution characteristics of soil pore structure in mining-induced subsidence areas and the elucidation of the response mechanism between soil physical parameters and soil structure are essential prerequisites for achieving effective ecological environment protection and restoration in mining areas. In this study, three-dimensional visualization reconstruction of soil porosity, pore diameter, roundness rate and pore connectivity at different profile depths in subsidence area caused by ultra-thick coal seam mining was conducted by using the soil CT scanning technology. Additionally, a correlation analysis model was established between physical parameters such as soil moisture content, bulk density, and pore structure parameters. The results indicate that: (1) Compared to the non-subsidence area, the number, size, and proportion of soil pores significantly increase in the tension zone, compression zone, and neutral zone, and the pore network and connectivity are extensively interconnected, and the fissure development in the tension zone is most significant, and the soil pores in the subsidence compression zone are concentrated on one side due to the influence of soil deformation. (2) As the depth of the soil profile increases, the level of soil pore development significantly decreases. The large profile depth (40–100 cm) causes a significant decrease in pore development. (3) There is a significant correlation between soil pore structure parameters and soil physical parameters (P ≤ 0.05), a highly significant correlation between soil pore structure parameters and soil moisture content (P ≤ 0.01), and a highly significant correlation between soil texture and soil moisture content (P ≤ 0.01). This research is of great significance for guiding underground production layout and repairing damaged soil.

Quantitative Relationship Between Strength and Porosity of Nano-Silica-Modified Mortar Based on Fractal Theory

Nano-silica (NS) is an ideal modifier for mortar materials, and exploring the evolution of the fractal dimension of the pore structure in NS-modified mortar is crucial for elucidating the mechanism by which NS enhances mortar strength. In this study, NS reinforced mortar was prepared using an NS sol solution, which inhibited the aggregation of NS particles. The relationship between the strength and pore structure of NS-modified mortar was quantitatively analyzed based on fractal dimension theory and gray correlation degree. The experimental system evaluated the mortar strength, pore structure distribution, and micro-morphology. Based on this evaluation, the fractal dimension of the mortar pore volume was calculated in detail. Subsequently, models for mortar strength and NS content were further established using grey analysis. The results indicate that NS significantly enhances the strength of mortar while also increasing its porosity due to reduced fluidity. NS can improve the compressive strength of mortar by up to 35%. The curve fitting of volume fractal dimension and box dimension is effective and can accurately reflect the complexity of the pore structure. The calculation of the grey correlation analysis model shows that the impact of varying silica content on the mechanical properties of mortar specimens is not linear; the distribution and quantity of bubbles are the main factors affecting the strength of the specimen.

The Interplay Between Depression, Probiotics, Diet, Immunometabolic Health, the Gut, and the Liver—A Secondary Analysis of the Pro-Demet Randomized Clinical Trial

(1) Background: Depression, metabolic alternations, and liver diseases are highly comorbid. Studies have shown that probiotics might be helpful in the treatment of the above-mentioned states. The aim of this secondary analysis was to search for possible predictors of probiotics’ efficacy on liver-related outcome measures. (2) Methods: Data from 92 subjects from a randomized clinical trial on the effect of probiotics on depression were analyzed. The shift in liver steatosis and fibrosis indices was assessed in the context of baseline immunometabolic, psychometric, dietary, and intestinal permeability factors. Correlation analysis and linear regression models were used. (3) Results: A total of 30% of the variance of the improvement in the score of the aspartate transferase to platelet ratio index was explained by probiotic use, higher pre-intervention triglycerides, cholesterol, C-reactive protein levels, increased cereal intake, and a lower consumption of sweets. Then, the model of the change in alanine transferase indicated that probiotics were efficient when used by subjects with higher basal levels of intestinal permeability markers. (4) Conclusions: Probiotics being used along with a healthy diet may provide additional benefits, such as decreased cardiovascular risk, for patients with measures consistent with the immunometabolic form of depression. Probiotic augmentation may be useful for liver protection among subjects with a suspected “leaky gut” syndrome. ClinicalTrials.gov: NCT04756544.

Survival strategies of Eisenia fetida in antibiotic-contaminated soil based on screening canonical correlation analysis model

Soil pollution from antibiotics has become increasingly severe, posing significant environmental and human health threats. Many soil organisms can survive and sustain their roles in maintaining soil ecosystems, even in polluted conditions. Exploring the life-sustaining mechanisms of these organisms in contaminated environments is scientifically significant. This study used Eisenia fetida as the test organism and antibiotics (oxytetracycline hydrochloride) as exogenous stress substances. Oxidative stress response experiments were conducted using the artificial soil method to examine the response of earthworms to oxidative stress. Additionally, 16S rRNA technology was employed to analyze the succession of microbial community structures inside and outside the earthworms. A screening canonical correlation analysis (SCCA) model was developed to investigate the relationship between microbial communities and earthworm oxidative stress system under oxytetracycline stress, revealing survival strategies in antibiotic-contaminated soil. The results showed that Proteobacteria and Bacteriodetes were the dominant phyla of microbial communities in earthworms under oxytetracycline stress, while Proteobacteria and Firmicutes were dominant bacterial phyla in soil. Bacteriodetes and Firmicutes in earthworms worked synergistically with catalase (CAT) and glutathione peroxidase (GPX) in oxidative stress responses. In soil, Actinobacteria, Verrucomicrobia, and Spirochaeta synergistically resisted oxytetracycline stress alongside peroxidase (POD) and glutathione S-transferase (GST). Earthworm mucus played a crucial role in this synergistic resistance. These findings provide a scientific and experimental basis for assessing the ecological safety risks of antibiotic-contaminated soil.

Aliphatic carbon regulates soil water repellency in a chronosequence of grassland enclosure in the Loess Hilly Region

Considering the potential enhancement of soil water repellency (SWR) due to the increased accumulation of soil organic matter (SOM) under grassland enclosure, there may be an increased risk of soil erosion and degradation as it can reduce water infiltration and penetration into the soil. There remains a knowledge gap pertaining to the relationship between SWR and plant growth, soil physicochemical properties, SOM composition, and particle size in enclosed grassland. The main objective is to investigate the impact of different grassland enclosure years (14a, 23a, 32a, 40a, and 51a) on SWR in temperate grasslands of the Loess Hilly Region using the water drop penetration time (WDPT) method. Results showed that, at the early stage of enclosure (<32 years), in-situ grassland soils mainly showed slight water repellent and hydrophilic characteristics. In contrast, grassland soils at the late stage of enclosure (>32 years) exhibited a transition towards strong water repellency, accompanied by the emergence of severe hydrophobicity. The potential SWR also exhibited a significantly higher trend in the 40a and 51a grassland compared to the previous 32 years of enclosed grassland. Moreover, the SWR increased as the soil particle size decreased, and exhibited an upward trend with increasing years of grassland enclosure. Notably, in the 40a and 51a grasslands, SWR for sieve size of soils <0.05 mm was significantly higher than that observed in the initial 32a grasslands, reaching a strong water repellent level. These findings highlight that grassland enclosure significantly promoted the development of the SWR. Correlation analysis and random forest models showed that NO3--N, litter biomass, plant height, TN, CO, C–H, bulk density and plant richness were identified as the primary factors controlling SWR. The structural equation model (SEM) analyses further suggested that grassland enclosure indirectly affected SWR through aliphatic C–H groups, which was influenced by plant properties. Consequently, the consideration of SWR formation mechanism is imperative in order to mitigate the risk of soil erosion and degradation in enclosed grassland ecosystems.

Characterization and correlation analysis of surface topography in ball-end milling

Abstract Surface texture is the most commonly used parameter for the quantitative characterization of surface topography. It is important for the study of the topography characteristics and functional properties of surfaces. In this paper, the surface topography characteristics, surface texture parameters, and change rule of the bearing area curve when the cutting vibration of the adjacent teeth of the ball-end milling cutter is asymmetric were analyzed, and the correlation between the inflection points and the surface texture parameters of the bearing area curve were studied according to the improved correlation analysis model. This study provides essential insights into the mechanism that drives the formation of the surface topography of ball-end milling and the intrinsic characteristic laws of the surface topography.

Correlation between microbial communities and flavor compounds in Suantangzi dough from Liaoning Province, China

Suantangzi is a fermented corn food product with Manchu characteristics from Liaoning Province, China. To analyze the microbial diversity and flavor compounds in Suantangzi dough, this study utilized high-throughput sequencing of the 16S rRNA and internal transcribed spacer regions, high-performance liquid chromatography, and gas chromatography time-of-flight mass spectrometry. Spearman correlation analysis and random forest model were conducted to investigate the correlation between the dominant genera and flavor compounds. A total of 267 and 123 bacterial and fungal genera, respectively, were identified. Flavor compound analysis identified 7 and 156 organic acids and other flavor compounds, respectively, and partial least squares discriminant analysis was used to screen 22 differential flavor compounds. Additionally, Paucilactobacillus, Pediococcus, and Tausonia genera were speculated to produce different flavors in Suantangzi dough made in different regions. These findings provide a theoretical foundation for microbial community dynamics and the formation of key flavor compounds in Suantangzi dough.

Investigating the influence of land cover on land surface temperature

The increasingly serious urban heat island (UHI) effect is unfavorable to urban development. This study utilized land cover data and land surface temperature (LST) data of China in 2020 by using correlation analysis and spatial regression models to analyze the relationships between LST and two influencing factors (land cover and digital elevation model (DEM)). The results showed the following: (1) The correlation between LST and forest was highest in the Northeast China Plain (NCP), Huang-Huai-Hai Plain (HHP), Qinghai Tibet Plateau (QTP), and Loess Plateau (LP). DEM mean displayed its highest correlation in the Northern arid and semiarid region (NAR), Sichuan Basin and surrounding regions (SCR), Yunnan-Guizhou Plateau (YGP), and Middle-lower Yangtze Plain (MYP). Southern China (SC) had the highest correlation between LST and construction land. (2) There was spatial heterogeneity between land cover and LST. Unused land on LP had larger impact on LST. For every 1% increase in the proportion of unused land area, the LST increased by 0.250 °C. LST in some central and western regions of China (the NAR, the LP, the SCR, and the YGP) was mainly affected by local land cover; LST in eastern coastal regions (the HHP, MYP, NCP, SC) and QTP was not only affected by local land cover, but also by LST or land cover of neighboring regions. The warming effect of construction land on LST was more significant, with LST increasing by 0.079 °C to 0.338 °C for every 1% increase in the proportion of construction land area. Coordination of land use planning and synergistic remediation in different regions and rational planning of construction land are essential to mitigate the UHI effect. (3) Water bodies in the NCP, NAR, and MYP had the greatest cooling impact on LST, with LST decreasing by 0.277 °C, 0.246 °C, and 0.079 °C, respectively, for every 1% increase in the proportion of water bodies area. Forest on the QTP, LP, SC, and YGP had the greatest cooling impact on LST, and for every 1% increase in the proportion of forest area, LST decreased by 0.144 °C, 0.089 °C, 0.086 °C, and 0.038 °C, respectively. Actively planting trees and increasing the area of forests and water bodies are of positive significance in alleviating the UHI effect and improving the ecological environment.

Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes.

The great gerbil (Rhombomys opimus) is a gregarious rodent in Central Asia and is one of the major pests found in desert forest and grassland areas. The distribution changes and migration routes of R. opimus in Central Asia under climate change remain unexplored. This study employed multi-model ensemble, correlation analysis, jackknife method, and minimum cumulative resistance (MCR) model to simulate the potential habitat of R. opimus under current and future (2030 and 2050) climate scenarios and estimate its possible migration routes. The results indicate that the ensemble model integrating Random Forest (RF), Gradient Boosting Machine (GBM), and Maximum Entropy Model (MaxEnt) performed best within the present climate context. The model predicted the potential distribution of R. opimus in Central Asia with an area under the curve (AUC) of 0.986 and a True Skill Statistic (TSS) of 0.899, demonstrating excellent statistical accuracy and spatial performance. Under future climate scenarios, northern Xinjiang and southeastern Kazakhstan will remain the core areas of R. opimus distribution. However, the optimal habitat region will expand relative to the current one. This expansion will increase with the rising CO2 emission levels and over time, potentially enlarging the suitable area by up to 39.49 × 104 km2. In terms of spatial distribution, the suitable habitat for R. opimus is shifting toward higher latitudes and elevations. For specific migration routes, R. opimus tends to favor paths through farmland and grassland. This study can provide guidance for managing and controlling R. opimus under future climate change scenarios.

A rapid protocol for distinguishing the quality of Sanshengyin and identifying potential markers by the “three-in-one” fingerprint profiles with antioxidant activity

It is imperative to establish a standardized model for the quality control of traditional prescriptions, exemplified by Sanshengyin (SSY). This study introduces a multi-component and multi-level "three-in-one" fingerprint quality evaluation system designed to predict the comprehensive quality of traditional Chinese medicine (TCM). Initially, a five-wavelength high-performance liquid chromatography (HPLC) fusion spectrum was developed to enhance the stability of SSY within the chromatographic system. Additionally, a quantification method was employed to streamline the calculation and visualization processes of ultraviolet (UV) and infrared (IR) spectral systems. Through this approach, chromatographic and spectral fingerprints were amalgamated into a holistic analytical strategy. The average linear quantitative fingerprint method (ALQFM) was employed to swiftly differentiate the grades of 17 sample batches. Additionally, six quality markers were identified for content determination. Correlation analysis between the total content of these quality markers and macroscopic quantitative similarity was conducted to assess the accuracy of ALQFM in evaluating the quality of TCM represented by SSY. Finally, the binary correlation analysis model was employed to investigate the correlation between antioxidant activity and fingerprint profiles, facilitating the prediction of potential bioactive compounds in SSY. This research offers a straightforward, cost-effective, and holistic approach for assessing the quality consistency of TCM. The method is recommended for adoption by medical institutions and enterprises to enhance the standardization of TCM quality control.

The clinical significance of the Neutrophil-to-Lymphocyte Ratio as a novel inflammatory biomarker for assessing the severity of intervertebral disc degeneration.

Inflammation is integral to the pathogenesis of intervertebral disc degeneration, yet the role of systemic inflammatory markers in this process remains underexplored. This study aims to explore the association between the Neutrophil-to-Lymphocyte Ratio (NLR) and the severity of disc degeneration. A retrospective analysis was conducted on 375 patients diagnosed with lumbar disc degeneration between April 2018 and May 2021. All patients underwent a complete blood cell count examination. We applied the Pfirrmann grading system for cumulative disc grading, stratifying patients into two groups: a high-score group (cumulative grade > 17) and a low-score group (cumulative grade ≤ 17), based on the median cumulative grade. The association between the NLR and and the severity of disc degeneration was further analyzed using correlation analysis and logistic regression models. Furthermore, the predictive capacity of the NLR for lumbar disc degeneration was assessed using the Receiver Operating Characteristic (ROC) curve. We found a significant positive correlation between high NLR levels and severe disc degeneration. The high-score group exhibited a significantly higher NLR compared to the low-score group [2.63 (1.91-4.18) vs. 2.04 (1.38-2.74), respectively, p < 0.001]. Significant correlations were found between NLR and patient characteristics (including age, BMI, VAS, NSAIDs usage, hemoglobin) and the cumulative grading. Logistic regression analysis identified age and NLR as independent predictors of the severity of disc degeneration. The ROC curve analysis demonstrated a good predictive capability of NLR for lumbar disc degeneration. NLR could serve as a promising biomarker for assessing the severity of lumbar disc degeneration and offer potential benefits in both early diagnosis and treatment strategies.

Regional agricultural drought vulnerability prediction based on interpretable Random Forest.

Drought is one of the leading natural disasters in the world. It severely restricts the normal functioning of societies and economies. The purpose of this paper is to predict the drought vulnerability index in Henan Province so that timely measures can be taken to mitigate the impact of drought and to ensure the continued stability of people's lives and social development. First, the drought vulnerability index of Henan Province for 2010-2022 was calculated based on relevant literature and the regional situation of Henan Province. In addition, the main factors of sensibility and resilience are selected, the prediction indicator system is established, and the grey correlation analysis model is applied to select the top 10 main factors of drought vulnerability. Second, the Random Forest model was trained and simulated, and the drought vulnerability index of Henan Province was predicted for 2023-2025. Finally, the SHapley Additive exPlanations model was used to explain the specific effects of the influences of the Random Forest model. The interpretable Random Forest model not only accurately predicts the drought vulnerability index in Henan Province but also alleviates concerns about the "black box" problem of indirect interpretation of the Random Forest model. The results of the study show that the Average Percentage Error of the drought vulnerability index in Henan Province from 2010 to 2022 simulated by the Random Forest model is as low as 3.0457%, and the simulation accuracy is as high as 96.9643%. Drought vulnerability prediction for Henan Province was also made for the period 2023-2025, showing an increasing trend. Relevant sectors should enhance awareness and early warning of drought, improve resilience, and take effective measures to reduce the socio-economic impact of drought.

Research on the Development of New Energy Electric Vehicles in China Based on Correlation Analysis and Ridge Regression Models

This paper analyses the main factors affecting China's new energy electric vehicles and their influencing factors. Firstly, it is necessary to collect data, construct indicators, analyse the correlation between indicators, then construct a ridge regression model to obtain the correlation coefficient of each indicator, and finally compare the size of the absolute value of the normalised correlation coefficient to analyse the degree of influence of each indicator. It is found that the development of new energy electric vehicles in China is influenced by four areas: policy, technology, economy and market. Eleven factors were selected as sub-indicators, including policy subsidies, number of policies, battery life, energy efficiency ratio, number of patents, GDP per capita, petrol price, average price of new energy electric vehicles, charging cost, industry chain size and number of charging piles. The sales volume as the dependent variable reflects the impact of the development of new energy electric vehicles, the higher the sales volume, the better the development of new energy electric vehicles. Data analysis and modelling were carried out through Spearman correlation analysis, ridge regression model construction and other methods to derive the degree of influence of each indicator on sales volume. The results show that the number of charging piles has the greatest impact on the development of new energy electric vehicles in China, while the energy efficiency ratio has the least impact. The ridge regression model predicts sales better, but performs poorly under special circumstances.

The individualized optimal pillow height and neck support design for side sleepers.

An optimal pillow effectively increases sleep quality and prevents cervical symptoms. However, the influence of body dimension on optimal pillow design or selection strategy has not been clarified quantitatively. This study aims to investigate the individualized optimal pillow height and neck support for side sleepers. Nine healthy subjects were recruited and laid laterally on foam-latex pillow with four height levels (8 cm, 10 cm, 12 cm, 14 cm) and with/without neck support, respectively. Healthiness was evaluated using cervical spine morphology (measured by motion capturing system) and musculoskeletal internal force (simulated by a multi-body model). Comfortability was evaluated by a deviation standardized overall comfort rating. Individualized pillow height was identified by Hφ (calculated by the subject's shoulder width and absolute pillow height). Correlation analysis and linear mixed model were performed between C1-T1 slope and Hφ. A paired-t test was performed on the cervical curve and comfort score comparisons between neck support pillow and flat pillow. The C1-T1 slope of the cervical curve showed statistically significant correlation to Hφ and was well predicted by Hφ through linear relation (R2 = 0.80 for flat pillow, R2 = 0.82 for neck support pillow). The correlation between comfort score and Hφ was moderate or weak. Medium individualized height pillow (Hφ 9.74-11.76 cm) with neck support showed a cervical curve closest to natural standing and the lowest musculoskeletal internal force. Sub-low individualized height pillow (Hφ 11.76-13.78 cm) with neck support showed the highest average comfort score. For side sleepers, cervical curve morphology and optimal individualized pillow height are well predicted by Hφ. Comfortability perception is not sensitive to Hφ. Sub-low individualized height pillow showed the best comfortability and relatively good healthiness. Medium individualized height pillow with neck support showed the best healthiness.

Relationship between Body Mass Index, Dynamic Balance, and Core Muscle Endurance in Firefighter Candidates: A Cross-Sectional Study

This study aimed to examine the effects of Body Mass Index (BMI) on dynamic balance and core muscle endurance in firefighter candidates. In physically demanding professions, such as firefighting, understanding the impact of BMI on physical performance metrics is crucial for both occupational safety and effectiveness. The study was conducted with 89 firefighter candidates, with a gender distribution of 23.6% female (n=21, age 19.86±1.86 years, height 1.64±0.05 m, weight 59.47±7.26 kg) and 76.4% male (n=68, age 19.82±1.25 years, height 1.78±0.04 m, weight 74.36±12.09 kg). Within the scope of the research, the results of the BMI, balance, and core muscle endurance tests were evaluated. BMI was calculated based on measurements of participant height and weight. Dynamic balance performance was assessed using the Y-Balance Test, while core muscle endurance was measured using the plank test. The performances of the participants in both tests were recorded and subjected to statistical analysis. Pearson correlation analysis and multiple regression models were used to examine the relationships among BMI, dynamic balance, and core muscle endurance. The findings indicated that an increase in BMI has adverse effects on balance and core muscle endurance performance. Specifically, firefighter candidates with higher BMI values exhibited shorter plank durations (females: r=-0.63; p=0.002, males: r=-0.566; p

Instructional delivery mode, response format, and student performance in accounting: evidence from Brazil

ABSTRACT This study investigates how instructional delivery modes (i.e. face-to-face vs. distance education) are associated with multiple measures of student performance. More than 52,000 unique observations were collected from a Brazilian nationwide exam. Descriptive statistics, Welch’s t-tests, correlation analysis, and regression models were employed. The results indicated that, in general, students enrolled in face-to-face education outperformed their distance education counterparts, especially on accounting-specific questions. The results also showed that, although face-to-face education is more effective than distance education, students in both delivery modes presented poor performance. Additionally, the response format is relevant to student performance as higher grades were observed for multiple-choice questions than open-ended ones. Accounting faculty may want to consider the findings of this study when designing their exams in terms of format and content.

Different Radiological Indices of Patellar Height Predict Patients' Diverse Outcomes Following Total Knee Arthroplasty.

Total knee arthroplasty (TKA) is a common surgical procedure for patients with knee osteoarthritis. The patellar component plays a crucial role in knee biomechanics and can influence postoperative outcomes. This study aimed to investigate the relationship between radiological indices of patellar height and patient outcomes following TKA. A retrospective analysis was conducted on patients who underwent TKA for osteoarthritis. Radiographic measurements of patellar height, including the Insall-Salvati (IS) ratio, modified Blackburne-Peel (mBP) ratio, Caton-Deschamps ratio, and plateau-patellar angle (PPA), were obtained. Clinical outcomes were assessed using the Knee Society Score (KSS) and the Forgotten Joint Score-12 (FJS-12). Patient satisfaction and postoperative complications were also evaluated. Statistical analyses, including correlation analysis and multiple regression models, were performed to determine the association between radiological indices and patient outcomes. The study included 330 cases that met the inclusion criteria. The analysis revealed significant correlations between different radiological indices of patellar height and patient outcomes. Lower postoperative PPA was correlated with worse KSS and range of motion scores. A decreased mBP ratio was associated with poorer FJS-12 responses and higher risks of dissatisfaction and patellar clunk or crepitus. Increased IS ratio was linked to a lower likelihood of incidental giving way of the knee. Advanced age was associated with reduced dissatisfaction and incidental giving way probabilities. The findings of this study demonstrate that radiological indices of patellar height can predict patient outcomes following TKA. Assessing patellar height using various radiographic measurements provides valuable information for surgical planning and prognostic evaluation. Understanding the impact of patellar height on clinical outcomes can aid in optimizing TKA procedures and improving patient satisfaction. These findings emphasize the importance of considering patellar height as a predictive factor in TKA and highlight its potential role in guiding postoperative management and rehabilitation strategies.

Comparison of the Patient Demographics, High-Resolution Computed Tomography Features of the Pulmonary Ground-Glass Opacity and Its Diagnostic Value Analysis

Introduction Pulmonary ground-glass opacity (GGO) observed on computed tomography (CT) is widely regarded as a diagnostic feature of lung adenocarcinoma; however, a significant radiological predictive sign remains controversial. In this retrospective study, we conducted a comprehensive analysis of 206 patients with GGO to establish a correlation analysis model between CT images and diagnosis of GGO nodules. Methods Histopathologic specimens were obtained from 206 patients (130 women, 76 men; age range 24–77). The clinical data, pathologic findings, and thin-section CT features of solid, pure GGO (pGGO), and mixed GGO (mGGO) nodules were compared using rigorous statistical methods, such as t-test, Fisher’s exact test, or univariate logistic regression analysis. Results Significant differences were observed among the 3 groups in terms of patient demographics, including gender (P = 0.016), smoking history (P = 0.002), and nodule size (P = 0.002). Morphologic CT characteristics, such as the presence of spiculated sign, lobulated sign, vascular sign, bubble-lucency sign, or pleural retraction, exhibited significant differences among the solid nodule, pGGO, and mGGO groups. However, no significant differences were observed in terms of air-bronchogram sign. Notably, the incidence of malignancy was significantly higher in pGGO nodules (76.52%) than in solid (48.48%) and mGGO (73.86%) nodules. Patients with mGGO had up to 2.988 times higher hazard of malignant lesions than those with solid nodules [P = 0.036, hazard ratio (HR) = 2.988]. Similarly, the hazard of malignant lesions was 2.941 times higher in patients with pGGO than in those with solid nodules (P = 0.007, HR = 2.941). Conclusion Clinical, pathological, and thin-section CT features of solid, pGGO and mGGO nodules were found to be significantly different. Based on our comprehensive analysis, patients presenting with a mGGO or pGGO on CT scans were more likely to be diagnosed with lung cancer.

대학생의 정서지능이 대학생활적응에 미치는 영향: 성장 마인드셋과 그릿의 병렬이중 매개효과를 중심으로

Objective: This study examined the parallel dual mediating effects of growth mindset and grit on college students' emotional intelligence in adaptation to college life. Method: The subjects of the study were 219 students currently enrolled in university. A survey was conducted to measure emotional intelligence, college-life adaptation, growth mindset, and grit. Descriptive statistics, correlation analysis, and SPSS Process Macro Model 4 were employed to evaluate the collected data and verify the significance of the parallel double mediating effects. Results: First, emotional intelligence, growth mindset, and college-life adaptation demonstrated positive correlations; emotional intelligence, grit, and college-life adaptation also demonstrated positive correlations. However, there was no correlation seen between growth mindset and grit. Second, emotional intelligence had a significant positive effect on growth mindset, grit, and college-life adaptation. Growth mindset did not have a statistically significant effect on college-life adaptation, but grit was found to have a statistically significant effect on college-life adaptation. Third, growth mindset did not demonstrate a statistically significant mediating effect on emotional intelligence and college-life adaptation; however, grit was found to have a statistically significant mediating effect on both emotional intelligence and college-life adaptation. No statistically significant differences in the indirect effects between the two variables grit and growth mindset were found. Conclusion: Study results suggested that college students should build both grit and emotional intelligence to improve their adaptability and adjustment to college life.