Performance In Relation Research Articles

Effect of chloramine T and chlorhexidine in reducing gingivitis in patients admitted to a reference hospital for cardiopulmonary care: a randomized, controlled clinical trial.

The aim of this study is to evaluate the effect of Chloramine T in reducing gingivitis in hospitalized patients, in addition to providing an alternative to the use of Chlorhexidine. A randomized, triple-blind, placebo controlled clinical trial was performed with 45 volunteers presenting with gingivitis, using the Löe Gingival Index (LGI). Patients were randomly allocated into one of three groups: (G1): Chloramine T 0.2%; (G2): Chlorhexidine 0.12% and (G3): distilled water. After five days, the control group (G3) remained without relevant differences in relation to the first pre-treatment assessment, while the groups tested with chlorhexidine and chloramine T showed improvement in the LGI (p < 0.05). After ten days, G3 maintained the results of the previous assessments, G1 repeated the five-day assessment and G2 obtained a statistically significant difference, with a better result in relation to the previous assessment (p < 0.05). After fifteen days, G3 showed no differences in relation to the other assessments, G1 had a statistically significant difference, showing better performance in relation to the previous assessment and G2 continued the gradual improvement it had been showing in the LGI (p < 0.05). Chloramine T and Chlorhexidine present similar results in the treatment of gingivitis, when evaluated by probing by the LGI, and Chloramine T can be used effectively, without causing the adverse effects inherent to prolonged use of chlorhexidine. Importance of oral hygiene for patients admitted to hospitals with the use of adjuvant substances that do not present adverse effects such as chlorhexidine, which is considered the gold standard, seeking to provide better clinical protocols.

Characterization and Performance Analysis of TiO&lt;sub&gt;2&lt;/sub&gt; Coated UHMWPE for Biomedical Applications

Ultra-high Molecular Weight Polyethylene (UHMWPE) is a highly versatile polymer known for its exceptional mechanical properties, however, its limited life as an implant material for Total Joint Replacement (TJR) necessitates surface modification to extend its lifespan. This study aims to enhance the surface properties of UHMWPE through application of ceramic coatings. Magnetron sputtering method was used to deposit thin film of white Titania (TiO2) on the material’s surface. To evaluate the surface characteristics, such as surface roughness, uniformity and structure, coated and uncoated samples were analyzed through Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM) and X-ray Diffraction Analysis (XRD). The material performance in relation to biological context was investigated through Contact Angle measurement. A comparative analysis of coated and uncoated samples was then performed. The coated samples showed better wettability compared to uncoated sample. This fact highlights the hydrophilic nature of film. The results of the coated UHMWPE suggest that this surface modification technique could significantly extend the lifespan of UHMWPE implants in TJR, potentially addressing the current limitations associated with their longevity.

Individual learning ambidexterity behavior and individual job performance in services: the role of organizational structure

AbstractThis study analyzed the impact of individual learning ambidexterity on individual job performance and tested the moderating effects of the organizational structure, represented in this research by formalization, decentralization, and structural differentiation. Despite the importance of individual learning ambidexterity, there is a limited understanding of how employees’ explorative and exploitative learning behaviors affect their individual job performance. The study expands the research by confirming the relevance of individual learning ambidexterity for individual performance for non-managerial employees; an understudied research setting for individual ambidexterity. We demonstrate that individual learning ambidexterity is positively correlated with individual job performance. We also provide evidence that formalization, decentralization, and structural differentiation moderate the effects of individual learning ambidexterity on individual job performance. The empirical context for the research was non-managerial employees from the Romanian IT services industry. Prior research has shown that ambidexterity is important in the IT industry, making it an adequate setting to analyze the effects of individual learning ambidexterity on individual job performance. By using polynomial regressions on a sample consisting of 342 employees, we were able to analyze four research hypotheses. This study demonstrates the moderating mechanism of organizational setting in the improvement of individual job performance in relation to individual learning ambidexterity. Taken as a whole, our findings provide new insights into how and under which organizational conditions the individual-level explorative and exploitative learning behaviors affect individual job performance.

Automated cardiac arrest detection using a photoplethysmography wristband: algorithm performance in relation to sex, skin color type and arm hair density

Abstract Background While survival from witnessed out-of-hospital cardiac arrest (OHCA) has improved, this is not the case for unwitnessed cardiac arrest as the event goes unnoticed. Automated cardiac arrest detection and alerting through a wristband is considered a promising technique also facilitating early assistance for this large group. In the DETECT-1 study, a photoplethysmography(PPG) algorithm for circulatory arrest detection was developed in patients with induced circulatory arrest. However, patient characteristics, such as skin color and arm hair density, can influence the accuracy of the PPG signal. Thus, we performed further analyses to study the effect of patient characteristics on the algorithm’s performance. Purpose To assess the performance of the developed PPG algorithm for cardiac arrest detection in relation to sex, skin color type and arm hair density. Methods Patients who underwent short-lasting circulatory arrest induction during transcatheter aortic valve implantation, ventricular tachycardia ablation or subcutaneous ICD implantation wore a PPG wristband during the procedure. Continuous ECG and invasive blood pressure recordings served as reference standards. A PPG algorithm for circulatory arrest detection was developed. The algorithm’s performance was assessed in subgroups based on sex, skin color type (according to the Fitzpatrick scale), and arm hair density. The sensitivity for the detection of circulatory arrest and false positive alarms were compared between the different subgroups. Results In total, 151 patients were included in the current analysis. Analyzed data consisted of 159 hours of PPG data including 176 induced circulatory arrest events. The population consisted of 57 (38%) females and 94 (62%) males. The sensitivity for circulatory arrest detection was 100% in the female group vs. 98% in the male group (p=ns); false positive alarms occurred in 4 females and 9 males, resulting in a positive predictive value (PPV) of 94% and 92% (p=ns), respectively. Within the skin color subgroup analysis, 114 (75%) patients had skin color type I or II, and 37 (25%) patients had a skin color type III, IV, V or VI. There were no differences in sensitivity (p=ns) and PPV (p=ns) in the skin color subgroup (table 1). The population consisted of 106 (71%) patients with nil or sparse arm hair density, 43 (29%) patients with moderate or dense arm hair density, and 2 not reported. There were no differences in sensitivity (p=ns) and PPV (p=ns) within the arm hair density subgroup (table 1). Conclusions Automated cardiac arrest detection using a smartwatch is feasible and its accuracy is not affected by sex, skin color type or arm hair density in this study. Further study is needed to assess performance of the algorithm in a larger sample size and a more diverse study population. If proven to be effective, automated cardiac arrest detection has the potential to improve survival from OHCA.Sensitivity/PPV for arrest detection

Measurement Instruments When Comparing Academic Performance and Physical Activity: A Comprehensive Systematic Review.

This study offers a comprehensive review of academic performance measurement instruments in physical activity and education settings, aiming to provide a comprehensive list of tools used for measuring academic performance in relation to variables associated with physical activity. Academic performance outcomes, including cognitive skills, attitudes, academic achievement, and academic behavior categorized by CDC, were investigated using specific keywords in search engines between 2000 and June 2022, with 233 articles (describing 220 studies) included. Participant demographics, mainly elementary students, displayed variability. The review found that 37.3% of studies measured cognitive skills and attitudes (primarily attention), 57.3% assessed academic achievement (GPA, subject scores, or standardized tests), and 15.9% evaluated academic behaviors (mostly on-task/off-task behaviors). Various instruments were employed, notably those measuring attention, intelligence, memory, and attitude. Positive associations were found in 63.4%, 78.6%, and 85.7% of studies for cognitive skills, academic achievement, and academic behavior, respectively. This literature review highlights the prevalence of studies on academic achievement, diverse cognitive skills instruments, and a focus on attention. Despite predominantly positive relationships, some studies reported non-significant or negative associations, particularly for cognitive skills. Future research should emphasize these areas using reliable instruments.

A Study on Work Environment and its Impact on Employees Performance at Boston Business Solutions

This research presents a thorough examination of the supermarket's sales data, focusing on customer behaviour, regional performance, and payment preferences. The supermarket has successfully cultivated a diverse customer base, with a nearly equal split between normal customers and members. This balanced customer distribution suggests a stable foundation for growth, particularly through strategic initiatives aimed at increasing membership and enhancing customer loyalty. The supermarket's regional presence is well-balanced across major cities, including Mandalay, Naypyitaw, and Yangon. Sales are dispersed equally among these regions, indicating that the supermarket has established a strong foothold in each market. This balanced distribution provides an opportunity to tailor strategies to the specific characteristics and preferences of each city, potentially driving increased market share and customer satisfaction through localized approaches. Analysing supermarket sales data is necessary for selecting wisely in business situations and ensuring long-term success. Sales data can also uncover issues in the supply chain, helping supermarkets run more smoothly and efficiently. By examining sales in different regions, supermarkets can adjust their products and promotions to better fit local preferences, improving sales in specific areas. Financially, analysing sales data helps with accurate budgeting and pricing strategies, leading to higher profits. Additionally, it allows supermarkets to evaluate their performance in relation to rivals and quickly adapt to changes in the market, helping them stay ahead. Analysing sales data helps supermarkets understand their customers, operate more efficiently, tailor strategies to different regions, and make better financial decisions, all of which contribute to their growth and success

Evaluating CD1a Immunohistochemistry for Tegumentary Leishmaniasis Diagnosis in the New World: A Focus on Colombia.

Leishmaniasis, a chronic vector-borne disease caused by parasites of the genus Leishmania, presents diagnostic challenges. Conventional diagnostic methods struggle with accurate visualization of these parasites. Immunostaining with CD1a has demonstrated effectiveness in visualizing Leishmania parasites, particularly in the Old World. However, the application of CD1a immunostaining in Colombian leishmaniasis remains unexplored. To determine the utility of CD1a as an immunomarker in detecting chronic forms of tegumentary leishmaniasis. This proof-of-concept study involved 48 paraffin-embedded samples categorized into 3 groups: moderate-to-high parasite load (n = 15), low load (n = 15), and chronic granulomatous inflammation (n = 13); 5 samples diagnosed with cutaneous histoplasmosis. These samples were stained with the immunomarker CD1a clone EP3622 for comparative analysis. In addition, CD1a immunohistochemistry was compared with 18S rDNA qPCR and hematoxylin-eosin staining to evaluate its performance in relation to these established methods. CD1a immunohistochemistry was positive in 46.51% of the samples evaluated. This immunomarker showed lower sensitivity and negative predictive value than 18S rDNA qPCR and hematoxylin-eosin staining; specificity and negative predictive value were consistent. ROC indicated inferior discrimination for leishmaniasis compared with 18 s rDNA qPCR and hematoxylin-eosin staining. Immunohistochemistry for CD1a could be a diagnostic support in the detection of chronic forms of tegumentary leishmaniasis.

Application of experimental planning methods for an analytical description of the areas of operability of marine electromechanical systems

The topic of the study is to consider the possibility of using experimental planning methods to mathematically describe areas of performance in relation to marine electromechanical systems. A definition is given and a graphic illustration of the field of operability is provided. It is shown that information about the boundary of the field of operability allows solving the most important tasks of controlling the state of ship electromechanical systems of various functional purposes. Possible ways of solving the problem of constructing a field of efficiency and the difficulties of their practical implementation are given. The method of analytical description of the operability domain is considered, which assumes an independent approximation of each hypersurface that makes up the operability domain. It is shown that for such an approximation it is convenient to use polynomial dependencies, which can be obtained as a result of using experimental planning methods. The main advantages of this approach are considered, including the possibility of solving the problem in the case of a high dimension of the space of primary parameters, in the space of which the area of operability is built. It is noted that in order to obtain a unified analytical description of the field of operability, the properties of logical R-functions can be used, which make it possible to make the transition from logical functions to analytical dependencies. It is proved that polynomial dependencies have the properties of R-functions and can be used in such a transformation. The resulting analytical description of the health area is universal and does not depend on the configuration of the area itself. Unlike the known methods of analytical approximation of the field of operability, it is characterized by an exceptionally low methodological error and allows us to solve with high reliability the problem of parametric synthesis of marine electromechanical systems according to the criterion of the reserve of operability, as well as the tasks of evaluating and predicting their condition during operation. The considered example clearly demonstrated the sequence of solving the problem of analytical description of the field of operability and allowed us to conclude about the complex configuration of this area even for special cases and the simplest electromechanical systems.

The Influence of Work Environment, Management Support, Organizational Culture, and Employee Engagement on Employee Performance Through Employee Satisfaction

In an era of globalization, companies must optimize their resources to meet customer needs. To improve the quality of human resources, companies must focus on areas such as the work environment, management support, organizational culture, employee engagement, and employee satisfaction. The study aims to identify the employee's performance in relation to its association with the variable studied and analyze it based on the supporting component. Data collection occurs through surveys and questionnaires, while analysis methods include Structural Equation Modeling (SEM). The results showed that a significant relationship between employee performance and employee characteristics on the work environment variable of 0.473 and employer engagement of 0.440 has been demonstrated. Employees who work in a positive and supportive work environment and feel engaged in their work tend to be more committed, more productive and qualified, more satisfied and motivated, and have a positive work culture. These aspects have the ability to increase employee satisfaction and employee performance, which in turn contribute to the overall success of the company.

The ESG Performance in Relation to the Board of Directors’ Characteristics and Sustainability Incentives: a Cross-national Study

The ESG Performance in Relation to the Board of Directors’ Characteristics and Sustainability Incentives: a Cross-national Study

Hypoxia-associated gene signatures are not prognostic in high-risk localised prostate cancers undergoing androgen deprivation therapy with radiotherapy

PurposeMen with high-risk prostate cancer (PCa) are treated with androgen deprivation therapy (ADT) and radiotherapy, but the disease reoccurs in 30% of patients. Biochemical recurrence of PCa after treatment is influenced by tumour hypoxia. Tumours with high levels of hypoxia are aggressive, resistant to treatment, and have increased metastatic capacity. Gene expression signatures derived from diagnostic biopsies can predict tumour hypoxia and radiosensitivity, but none are in routine clinical use, due to concerns about the applicability of these biomarkers to new patient cohorts. There has been no or limited testing in cohorts of high-risk PCa. Methods and materialsWe generated transcriptomic data for cohorts of high-risk PCa patients. Patients were treated with ADT followed by external beam radiotherapy with or without a brachytherapy boost. Biomarkers curated from the literature were calculated from pre-treatment biopsy gene expression data. The primary endpoint for survival analyses was biochemical recurrence-free survival (bRFS) and the secondary endpoints were distant metastasis-free survival (DMFS) and overall survival. ResultsThe performance of the selected biomarkers was poor, with none achieving prognostic significance for bRFS or DMFS in any cohort. The brachytherapy boost cohort received shorter durations of ADT than the conventionally fractionated or hypofractionated cohorts (Wilcoxon rank sum test, p=2.1 × 10-18 and 2.3 × 10-10 respectively) and had increased risk of distant metastasis (log-rank test, p=8 × 10-4). There were no consistent relationships between biomarker score and outcome for any of the endpoints. ConclusionsHypoxia and radiosensitivity biomarkers were not prognostic in high-risk PCa patients treated with ADT plus radiotherapy. We speculate that the lack of prognostic capability could be caused by the variable hypoxia-modifying effects of the ADT that these high-risk patients received before and during definitive treatment with radiotherapy. A deeper understanding of biomarker construction, performance and inter-cohort transferability in relation to patient characteristics, sample handling and treatment modalities is required before hypoxia biomarkers can be recommended for routine clinical use in the pre-treatment setting.

An Improved Product Defect Detection Method Combining Centroid Distance and Textural Information

In order to solve the problems of a high mismatching rate and being easily affected by noise and gray transformation, an improved product defect detection method combining centroid distance and textural information is proposed in this paper. Based on image preprocessing, the improved fuzzy C-means clustering method is used to extract the closed contour features. Then, the contour center distance description operator is used for bidirectional matching, and a robust coarse matching contour pair is obtained. After the coarse matching contour pair is screened, the refined matching result is obtained by using the improved local binary pattern operator. Finally, by comparing whether the number of fine matching pairs is consistent with the number of template outlines, the detection of good and bad industrial products is realized, and the closed contour extraction experiment, the anti-rotation matching experiment, the anti-gray difference matching experiment, and the defect detection experiment of three different products are designed. The experimental results show that the improved product defect detection method has good performance in relation to anti-rotation transformation and anti-gray difference, the detection accuracy can reach more than 90%, and the detection time is up to 362.6 ms, which can meet the requirements of industrial real-time detection.

Repeated Sprint Variations According to Circadian Rhythm at Different Menstrual Cycle Phases.

This study assessed the repeated sprint performance in relation to circadian rhythm during different menstrual cycle phases (MCP). Twelve volunteer eumenorrheic women team sport athletes performed 5×6-s cycling sprints in morning (9 am to 10 am) and evening (6 pm to 7 pm) sessions during the mid-follicular (FP, 6th-10th d) and luteal phases (LP, 19th-24th d). Body weight, oral body temperature, resting heart rate and lactate levels together with estradiol, progesterone and cortisol levels were determined before tests. Relative peak and mean power and performance decrements were determined as performance variables and maximum heart rate, lactate and ratings of perceived exertion were determined as physiological variables. Evening body temperatures were significantly higher. Cortisol levels were higher in the morning and in the FP. Resting lactate levels did not vary with MCP or time of day, but a significant MCP x time of day interaction was observed. Body weight showed no change according to time of day and MCP. There was no significant effect of MCP and time of day on performance and physiological variables, in contrast, maximum lactate values were notably higher in the evening. In conclusion, MCP and time of day need not be considered during repeated sprint exercises of eumenorrheic women athletes.

Analysis of the efficiency of a Solar Photovoltaic Power Plant linked to the electrical grid

The growing need for energy in emerging nations gives rise to apprehensions over energy security, so underscoring the criticality of harnessing the potential of renewable resources. Empirical evidence has demonstrated that photovoltaic systems integrated into the network are the optimal options for large-scale renewable energy. The analysis of the performance of these network-connected centrals can enhance the design, operation, and maintenance of new systems. The commissioning of a 12 MW photovoltaic solar power plant in Sidi Bel Abbès, located in the Dhaya region, has established it as one of the largest solar power plants in Algeria. The site yields a mean solar radiation of 5.21 kilowatt-hours per square metre per day and an average yearly temperature of 18.9 degrees Celsius. The present work provides an analysis of the yearly performance and conceptual aspects of the photovoltaic central unit. We compare the performance outcomes of the power plant with the simulated values generated by the SolarGis PvPlanner program. Analysis of real-world performance in relation to simulations allows for the detection of inconsistencies and the enhancement of future initiatives. SolarGis PvPlanner is an essential modelling program for accurately forecasting performance and effectively strategising solar projects, therefore guaranteeing sustainable and dependable energy for the future.

Assessment of Motor Performance and Self-Perceived Psychophysical Well-Being in Relation to Body Mass Index in Italian Adolescents.

The relationship between psychophysical self-perception (PSP), body mass index (BMI) and motor performance (MP) levels, in quantitative and qualitative terms, can be a very interesting connection to investigate. This study aimed to assess MP and PSP according to gender and weight differences (normal weight-Nw/overweight-obese-Ov-Ob) and their relationship to BMI in Italian adolescents. In total, 144 students (F = 72; M = 72) aged between 11 and 13 y.o. participated in this study. They were divided into two groups by gender and into two subgroups based on weight (Nw/Ov-Ob). Standing long jump, sit-and-reach, 10 × 5 m shuttle and sit-up tests to assess MP were carried out, and an ad hoc questionnaire to evaluate PSP was administrated. In comparing the Nw and Ov-Ob subgroups on the basis of BMI for each gender, statistically significant differences emerged in all motor skill tests administered. Regarding PSP, the Nw subgroup showed high and positive levels, while Ov-Ob showed low and negative levels, highlighting a relationship between high BMI and poor motor performance as well as negative psychophysical perception in the Ov-Ob subgroup. this study supports the importance of physical sport activity to regulate excess weight but also contribute to better psychophysical well-being.

Institutional Quality in Green and Digital Transition of EU Regions – A Recovery and Resilience Analysis

AbstractThis paper assesses the National Recovery and Resilience Plans (NRRPs) of EU member states and regions to uncover commonalities and differences between green and digital transitions, focusing on the role of institutions, among additional socio‐economic drivers, in modeling them. To that end, relevant indicators have been assembled, and several econometric models have been developed and tested to evaluate institutional performance in relation to green and digital transformations. The study reveals discrepancies in the two explored transition fields and highlights the power of institutional factors in boosting them. Specifically, the findings demonstrate that the green transition in EU regions is positively associated with variables such as life expectancy, institutional quality, tertiary education attainment, and small and medium enterprises (SMEs) with innovative activities, while the fruits of digitalization are mainly allied to population with higher studies, core creative class employment, accountability of institutions, and innovative SMEs. These insights offer valuable guidance for decision‐makers to draw lessons from high‐performing or successful regions and strategically assign resources. This includes paying attention to regional financial allocations and their alignment with territorial planning and long‐term policies.

Identification of medication-related fall risk in adults and older adults admitted to hospital: A machine learning approach

The study aimed to develop and validate, through machine learning, a fall risk prediction model related to prescribed medications specific to adults and older adults admitted to hospital. A case-control study was carried out in a tertiary hospital, involving 9,037 adults and older adults admitted to hospital in 2016. The variables were analyzed using the algorithms: logistic regression, naive bayes, random forest and gradient boosting. The best model presented an area under the curve = 0.628 in the older adult subgroup, compared to an area under the curve (AUC) = 0.776 in the adult subgroup. A specific model was developed for this sample. The gradient boosting model presented the best performance in the sample of older adults (AUC = 0.71). Models developed to predict the risk of falls based on medications specifically aimed at older adults presented better performance in relation to models developed in the total population studied.

DEVELOPMENT AND PERFORMANCE EVALUATION OF A MODEL CUTTING FLUID DEVELOPED FROM SHEA BUTTER OIL

This research was carried out to develop a model cutting fluid from Shea Butter oil and evaluate its performance in relation to temperature and surface roughness when compared to a commercial cutting fluid. The effectiveness of the cutting fluid was evaluated on a mild steel using a turning operation on the lathe machine. Temperature variations during the turning operation were measured using an infra-red gun thermometer while surface roughness was evaluated by employing a surface roughness tester. In this work Taguchi method was used to guide the selection of machine parameters such as cutting speed (rev/min), feed rate (mm/rev), and depth of cut (mm). Using Minitab, the cutting temperature and resulting surface roughness were measured for both the developed cutting and commercial fluids. The results obtained for the average cutting temperature of ~ 30oC and overall surface roughness value of 0.32μm for shea butter oil show a significant difference from that of ~ 35oC and 0.47 μm respectively for commercial grade cutting fluids. These results show that the shea butter oil-based cutting fluid not only exhibits great potential but also surpasses the current capabilities of commercial cutting fluids in terms of its cooling and surface finishing performances.

Empirical Analysis of Sustainable Performance in Relation to Stock Exchange Performance: Evidence from Romania

Given the substantial advancements in worldwide financial markets and the sharp increase in sustainability concerns, this article proposes an incursion into the empirical analysis of the interaction between companies' sustainable performance and stock market performance, focusing on the specificities of the Romanian financial market. It emphasizes the importance of a comprehensive approach that goes beyond simple financial figure analysis to include aspects such as sustainability, corporate governance, and social impact. The article aims to shed light on this complex relationship through rigorous empirical analysis applied to data specific to the Romanian market. We will thoroughly investigate the connections between companies' sustainability practices and the evolution of stock prices, taking into account the economic particularities of Romania, culminating with the estimation of a multiple linear regression model. Our study reveals that there is a correlation between the market capitalization of a company, its corporate performance and the specific industry or sector in which it operates.

The impact of ESG performance on corporate sustainable growth from the perspective of carbon sentiment

With the increasing importance of environmental and economic sustainability concerns, the concept of Environmental, Social, and Governance (ESG) has gained significant attention. In the era of digitalization, a research approach called carbon sentiment analysis has emerged as an innovative method. This study aims to explore the connections between carbon sentiment, ESG, and corporate sustainable growth within the context of the green economy. By using Ordinary Least Squares (OLS) regression analysis and establishing a panel data model of ESG performance and sustainable growth for Chinese listed companies, a notable positive correlation between the two variables was observed. Endogeneity was addressed using the two-stage instrumental variable method (2SLS) and the dynamic panel Generalized Method of Moments (GMM) model, with the results remaining robust both before and after the COVID-19 pandemic. Carbon-related news and textual information were collected and analyzed using advanced deep learning methods in Natural Language Processing (NLP), specifically Bidirectional Encoder Representations from Transformers (BERT) and Long Short-Term Memory (LSTM) models. This analysis enabled sentiment analysis and identification of the sentiment orientation of carbon news. The obtained sentiment scores were then integrated with company data to establish a moderation effect model. The findings of the study reveal that carbon sentiment significantly and positively moderates ESG performance in relation to corporate sustainable growth. Furthermore, the construction of a mediation effect model showed that carbon sentiment can moderate ESG performance by reducing environmental uncertainty, enhancing social trust, and alleviating financing constraints, thereby influencing corporate sustainable growth. The results of the heterogeneity group regression analysis demonstrate that the impact of ESG performance driven by carbon sentiment on sustainable growth is more pronounced in carbon market pilot regions, non-heavily polluting industries, and labor-intensive industries. This research provides a fresh perspective for understanding the dynamics of ESG, online carbon sentiment, and their implications for corporate sustainable growth. Additionally, it contributes to the development of the green economy and the formulation of environmental management policies.