Performance Indicators Research Articles

Consequences of Covid-19 outbreak on Indian listed SMEs: sector-specific analysis in the context of performance perspectives

PurposeThe repercussions of the “Covid-19 pandemic” have been felt across all the global economies. Therefore, this study evaluates its consequences on the performance of Indian-listed SMEs across the manufacturing, service, and pharmaceutical sectors in terms of financial performance, solvency position, and market performance.Design/methodology/approachThis study selects 100 Indian SMEs that trade their shares on the BSESME exchange. The selected SMEs are divided into three sectors: manufacturing (56), service (35), and pharmaceutical (9). Total revenue, operating profit, net profit ratio, current ratio and market capitalization serve as Performance parameters. These performance indicators are analysed for the periods before the pandemic (2019–20) and during the pandemic (2020–21) using the Wilcoxon signed-rank test.FindingsThe performance of Indian SMEs has been notably affected by the Covid-19 outbreak. The analysis reveals that the financial performance, solvency, and market performance of SMEs in the manufacturing sector drastically dropped during the pandemic period. Additionally, the analysis demonstrates that the performance of SMEs in the service industry has not been considerably impacted. In contrast, the pharmaceutical industry witnessed a significant improvement in its financial and market performance, but faced a substantial fall in its solvency position over the pandemic period.Practical implicationsThis study offers insightful practical implications for policymakers, decision-makers, investors and other stakeholders in the SME context.Originality/valueThis study makes a pioneering attempt to add new insights to the existing body of literature. It presents a sector-by-sector analysis of the impact of the Covid-19 pandemic on Indian SME. This empirical inquiry in the setting of Indian SMEs has not been attempted in the earlier literature.

Risk Management Policies and the Financial Performance of Commercial Banks in Mbale City

The effect of risk management practices on the financial performance of commercial banks in Mbale City, Uganda, is investigated in this study. Effective risk management plays a fundamental role in safeguarding financial institutions against market volatility, credit defaults, operational disruptions, and liquidity crises. Banks face various risks that, if unmanaged, can lead to significant financial distress and erosion of profitability. The objectives were to evaluate the specific types of risk that affect banks’ financial performance and analyse the relationship between risk management policies and the banks' financial performance. To examine the challenges of implementing risk management policies that affect the banks' financial performance in Mbale City, measured through key financial indicators like Return on Assets (ROA), Return on Equity (ROE), and Non-Performing Loans (NPLs) in Mbale City. A mixed-method research design was adopted, where quantitative and qualitative approaches. Statistical analysis was used to establish correlations between risk management policies and financially stronger financial resilience during periods of market uncertainty. These performance indicators, while thematic analysis helped interpret insights from the interviews. The findings reveal that banks with robust and proactive risk management policies tend to experience better financial outcomes. Precisely, the study found that credit risk management was highly correlated with lower levels of Non-Performing Loans (NPLs), while liquidity risk management was associated with higher levels of stability and profitability. Also, banks that invested in advanced technological systems for risk assessment and management showed research highlights the importance of successively improving risk management frameworks to familiarize with the varying financial landscape. It is recommended the adoption of dynamic risk assessment tools, enhanced regulatory compliance, and regular training of staff involved in risk management processes. Finally, it highlights that effective risk management is not only a regulatory requirement but also a critical factor for ensuring sustained profitability and competitive advantage.

A comparative study of Islamic conformity, profitability, and green performance in Southeast Asian Islamic banks

Southeast Asian countries, as members of the Association of Southeast Asian Nations (ASEAN), hold the second-largest Sharia financial assets globally. This study aims to assess the comparative performance of Islamic banks across ASEAN, examine the relationship between Islamic conformity, profitability, and green banking practices, and compare performance indicators between Malaysian and Indonesian Islamic banks. The sample includes Islamic banks from Indonesia, Malaysia, Brunei Darussalam, Thailand, and the Philippines. The findings reveal consistent adherence to Sharia principles across all banks, demonstrating strong Islamic conformity. However, financial performance indicators such as Return on Assets (ROA), Return on Equity (ROE), and Net Profit Margin (NPM) show significant variability, reflecting differences in operational efficiency and profitability. Green banking practices positively correlate with profitability, particularly ROA and NPM, emphasizing the role of Environmental, Social, and Governance (ESG) initiatives in enhancing operational efficiency and customer loyalty. The comparative analysis highlights that while both Malaysian and Indonesian Islamic banks exhibit consistent Islamic conformity, Malaysian banks outperform their Indonesian counterparts in green banking practices and profitability. This advantage is attributed to Malaysia’s advanced regulatory environment, which promotes sustainable finance, whereas Indonesian banks face greater profitability variability, necessitating improved governance and operational strategies. These findings offer valuable insights for policymakers and stakeholders, showcasing how Islamic financial principles can integrate with sustainability practices to achieve profitability and environmental responsibility in Islamic banking. Acknowledgment(s)The authors extend their gratitude to the Ministry of Higher Education, Science and Technology of the Republic of Indonesia for funding this research and to the Research and Community Service Centre of Universitas Mercu Buana for their valuable support.

Optimising the thicknesses of porous transport layers of a PEM fuel cell

This work presents a three-dimensional numerical study on the impact of geometrical parameters of the porous transport layers of a proton exchange membrane fuel cell (PEMFC) on its overall performance using ANSYS Fluent, with the overall current density as the key performance indicator under typical operating voltages of an automotive PEMFC, meanwhile maintaining proper two-phase water transport throughout the transport layers on both electrodes. The coupled charge, mass, momentum, species and energy conservation equations with source terms due to electrochemical reactions and phase change among different phases of water were solved to obtain a steady-state solution, typically using over 1.5 million meshes for the fuel cell, with each transport layer “resolved” in the height direction measuring the layer thickness. The modelling approach is validated against the measured polarisation profile of a PEMFC. Optimising the thicknesses h ’s of the porous transport layers is the focus of this study. Without changing other characteristics of these porous media, it would naturally be the first step to optimise the configuration of a fuel cell, which requires the least monetary and knowledge investment but potentially leads to substantial performance improvement, especially if the volume of the fuel cell can be reduced, which is important for automotive applications. Although past numerical studies that usually focused on one transport layer have offered valuable insights into optimising a fuel cell’s configutration to achieve optimal performance, it will be necessary to investigate a fuel cell as an integrated entity when performance optimisation is the objective, since realistic boundary conditions for all porous transport layers are determined in real time rather than assumed. Via an iterative approach, the present study has attempted to optimise the thicknesses of all porous transport layers of a single fuel cell. Optimal performance of the PEMFC was achieved with a reduction of its volume by 5.1%.

The Value of Sustainability: How Environmental, Social, and Governance Cost Investments Impact Corporate Financial Performance

This study aims to explore the impact of environmental, social, and governance (ESG) cost investment on corporate financial performance, using sustainable development theory, stakeholder theory, and agency theory as a comprehensive theoretical framework to clarify the definition and measurement standards of ESG cost investment (including environmental, social, and governance expenditures). The ESG cost investment data comes from the annual reports, sustainable development reports, or social responsibility reports released by listed companies, and return on assets and return on equity are selected as financial performance indicators for enterprises. The findings indicate that ESG cost investment, as well as environmental investment, social responsibility investment, and governance investment, have a positive impact on corporate financial performance. In addition, the study also considered corporate ownership structure and industry-specific factors to understand how ESG cost investment affect business performance in different contexts. By studying enterprise heterogeneity and industry-specific dynamics, this study aims to provide tailored management recommendations for enterprises in different ownership and industries. This study aims not only to contribute to academic discussions on corporate sustainability, but also to provide practical significance for businesses and investors by emphasizing the financial benefits of strategic ESG investments.

A Fusion XGBoost Approach for Large-Scale Monitoring of Soil Heavy Metal in Farmland Using Hyperspectral Imagery

Heavy metal pollution of farmland is worsened by the excessive introduction of heavy metal elements into soil systems, posing a substantial threat for global food security and human health. The traditional laboratory-based methods for monitoring soil heavy metals are limited for large-scale applications, while hyperspectral imagery data-based methods still face accuracy challenges. Therefore, a fusion XGBoost model based on the superposition of ensemble learning and packaging methods is proposed for large-scale monitoring with high accuracy of soil heavy metal using hyperspectral imagery. We took Xiong’an New Area, Hebei Province, as the study area, and acquired heavy metal content using chemical analysis. The XGB-Boruta-PCC algorithm was used for precise feature selection to obtain the final modeled spectral response features. On this basis, the performance indicators of the Optuna-optimized XGBoost model were compared with traditional linear and nonlinear models. The optimal model was extended to the entire region for drawing the spatial distribution map of soil heavy metal content. The results suggested that the XGB-Boruta-PCC method effectively achieved double dimensionality reduction of high-dimensional hyperspectral data, extracting spectral response features with a high contribution, which, combined with the XGBoost model, exhibited greater general estimation accuracies for heavy metal (Pb) in farmland (i.e., Pb: R2 = 0.82, RMSE = 11.58, MAE = 9.89). The results of the mapping indicated that there were exceedances for the southwest and parts of the west over the research region. Factories and human activities were the potential causes of heavy metal Pb contamination in farmland. In conclusion, this innovative method can quickly and accurately achieve monitoring large-scale soil heavy metal contamination in farmland, with ZY-1-02E spaceborne hyperspectral imagery proving to be a reliable tool for mapping soil heavy metal in farmland.

Scaling of urban environmental performance in Chinese cities

Modeling how green performance attributes scale over cities of different size reveals how an urban system performs environmentally as a whole, establishes population-adjusted limits for expected urban management targets, identifies cities doing better or worse than expected for their size, and is a starting point for systematically explaining such variation from the mean. This seems a useful contribution to devising strategies for sustainable urban development and environmental management. However, existing studies have focused solely on the scaling of limited pollutants, hindering a comprehensive understanding of urban environmental performance scaling. Our study investigates scaling patterns of urban environmental attributes covering the full cycle of generation-treatment-outcomes on environmental quality of key types of urban pollution and the economic-technical support capacity of cities. We examine 28 environmental performance indicators in seven categories for Chinese cities in 2020. Our findings reveal that 27 indicators show good alignment with urban scaling theory. Larger cities tend to perform better than smaller ones, exhibiting lower per capita pollution generation and carbon emissions, higher environmental investment, stronger technological innovation capabilities, and more efficient waste treatment and recycling. We also find systematic geographical effects, with cities in northeastern and Midwestern China underperforming compared to the national average for their size. Gross domestic product per capita has the most far-reaching impact on variation in population-adjusted urban environmental performance. The study reveals regularities in the relationships between city size and environmental performance, which will improve the sophistication of differentiated pollution control strategies aimed at mitigating human-environment conflicts arising from rapid urbanization.

COMPARATIVE ANALYSIS OF THE EFFICIENCY OF CAPITAL USE OF ADVERTISING AND MARKETING COMPANIES IN POLAND AND SLOVAKIA

The study examines the capital efficiency dynamics of advertising and marketing companies in Poland and Slovakia during 2021-2023, focusing on Return on Equity (ROE) and Return on Capital Employed (ROCE) indicators. The research is based on financial data from 404 companies (215 from Poland and 189 from Slovakia) operating under NACE Rev. 2 code 73 «Advertising and market research». The analysis reveals a significant downward trend in capital efficiency across both markets, albeit with distinct patterns. Polish companies demonstrated higher volatility and a more pronounced decline in performance indicators, with average ROE falling from 56,5 % to 23,9 % (a 57,7 % decrease) over the study period. Slovak companies showed greater stability but maintained consistently lower profitability levels, with ROE declining from 36 % to 30,7 % (a 14,7 % decrease). Similar trends were observed in ROCE, with Polish companies experiencing a decline from 43,3 % to 29,9 %, while Slovak companies saw a more moderate decrease from 30,9 % to 24,7 %. The study identifies a convergence of performance indicators between the two markets by 2023, suggesting the emergence of new industry efficiency standards. The research attributes these changes to several factors, including post-pandemic market correction following the 2020-2021 online advertising boom, overall economic uncertainty leading to reduced marketing budgets, and structural transformation of the advertising market toward digital channels. The findings indicate significant market stratification, where some companies successfully adapt to new conditions while others struggle with business model transformation. This research contributes to understanding the evolving dynamics of advertising and marketing sectors in Central European markets and provides insights into the impact of recent economic changes on industry capital efficiency. The stabilization of median ROCE values at approximately 22 % after 2022 and the establishment of new maximum profitability levels in the range of 180-188 % suggest the formation of new industry standards and structural reorganization in response to post-pandemic market conditions.

Integration between Islamic financial technology and Islamic financial principal to improve performance of SMEs in Indonesia

This study investigates the integration of Islamic financial technology and principles and their impact on small and medium enterprise (SME) performance in Indonesia. Utilizing a quantitative research methodology, the study employs a correlational design to examine the relationships between Islamic financial technology adoption, adherence to Islamic financial principles, and SME performance metrics. The research sample comprises 230 Muslim SME owners from Java Island, selected through stratified random sampling. Data collection involved structured questionnaires designed to measure the adoption levels of Islamic financial technology, adherence to Islamic financial principles, and various indicators of SME performance. The study employed multiple regression analysis to assess the relationships between the variables. Results indicate statistically significant positive correlations between the implementation of Islamic financial technology, adherence to Islamic financial principles, and SME performance. The regression model accounts for 79.5% of the variance in SME performance. Islamic financial technology adoption emerged as a particularly strong predictor of improved SME outcomes, suggesting the potential for technological innovation within an Islamic financial framework to drive business success. This research contributes to the growing body of literature on Islamic finance and financial technology in emerging markets. It provides empirical evidence for the potential synergies between Islamic financial principles and modern financial technology in enhancing SME performance in Indonesia. The findings have implications for policymakers, financial institutions, and SME owners in leveraging Islamic financial technology to promote sustainable economic growth.

PROCESS-ORIENTED MANAGEMENT OF ENTERPRISE TRANSFORMATION IN THE CONDITIONS OF CIRCULAR ECONOMY DEVELOPMENT

The article explores the theoretical and practical aspects of implementing process management for change management at enterprises in the context of the transition to a circular economy. A comprehensive analysis of the current state of implementation of the process approach at industrial enterprises of Ukraine was carried out and the key problems of its implementation were identified, including: insufficient theoretical and methodological base, lack of practical experience in implementing circular business models, limited resources for system transformations and a low level of staff readiness for changes. A methodology for evaluating the effectiveness of process changes has been developed, which is based on a multi-level system of key performance indicators (KPI) and takes into account economic (operating costs, resource saving, profitability), environmental (waste, emissions, energy efficiency) and operational (cycle duration, productivity, quality) aspects of activity enterprises. A mechanism for integrating the principles of circularity into the business processes of industrial enterprises is proposed, which includes interrelated components: organizational, technological and infrastructural support, which creates the basis for the effective transformation of a linear model of production into a circular one. A set of practical recommendations for the implementation of a process approach to change management has been formed, which covers nine key areas: strategic level, organizational support, technological aspects, process changes, infrastructural support, interaction with stakeholders, monitoring and control, risk management and development of corporate culture. The key factors for the success of the implementation of process changes in the conditions of the transition to a circular economy have been determined, including: a clear strategic vision, an effective change management system, the involvement of personnel, the development of the necessary competencies and the formation of an appropriate corporate culture.

Decarbonizing Economies: Balancing Growth and Green in South Africa, Mozambique, the United Kingdom and Sweden

This article critically examines climate change taxes, environmental pollution levies and related policies in South Africa, the United Kingdom and Sweden, assessing their design, implementation, economic impacts and efficacy in reducing carbon emissions and promoting green growth, while also analysing Mozambique's potential to adopt such strategies given its current absence of such taxes. Key performance indicators, including emission reductions and tax revenues, are analysed to gauge the effectiveness and limitations of each model. Sweden’s pioneering carbon tax demonstrates the intricate balance between economic growth and environmental targets, providing a well-documented case of both successes and trade-offs. The United Kingdom’s Carbon Price Floor, emissions trading system, Aggregates Levy and Climate Change Levy show a flexible yet complex approach that integrates various economic sectors. South Africa’s carbon tax, implemented within a developing economy context, sheds light on the socio-economic challenges and potential benefits of carbon taxation in emerging markets. In contrast, Mozambique—a low-income, climate-vulnerable country—offers a unique perspective with its existing environmental policies but lack of specific climate change tax measures, highlighting an area for potential climate change mitigation policy innovation.

Assessment of the Efficiency of Coupling Sustainable Well‐Being in Mountain Villages: A Case Study of Qinba Mountain Areas in China

ABSTRACTUnder the global Sustainable Development Goals initiative, the pursuit of well‐being is gradually shifting from wealth to sustainable development. Re‐examining the contribution of regional economic, ecological, and social development to the common creation of well‐being, analyzing their deep connections, will help us understand the multidimensional concepts and processes of development, and provide ideas for further promoting the construction of a more equitable and sustainable world. China is moving from comprehensive prosperity to common prosperity, and the continuous improvement of sustainable well‐being provides effective samples for our research. This study focuses on 46 counties in the Qinba Mountains Areas of China and constructs a coupled performance indicator system for sustainable well‐being in mountain villages. The Super SBM model is used to evaluate the matching performance of input and output factors, with Economic capital, Ecological capital, and Social capital as explanatory variables and Sustainable Happiness Index as the expected output. Research has found that: (1) There is a mismatch between the input and output factors of sustainable well‐being in the Qinba Mountain Areas, and management techniques are a key factor hindering the improvement of the coupling performance level of sustainable well‐being in the Qinba Mountain Areas; (2) The coupling performance level of sustainable happiness in the Qinba Mountain Areas is showing a downward trend, and only adjusting the input–output relationship by about 1.02% can achieve optimization and growth in performance level; (3) There is a significant shortage of input factors, with 87% of counties experiencing insufficient economic capital, about 76% experiencing insufficient arable land, and 41% experiencing insufficient social capital. In order to solve the above problems, it is necessary to strengthen the level of sustainable management in the ecological, economic, and social integration of the counties, respectively. Continuously promote capital investment in the mountain economy, such as logistics, industry, consumption, and public services, in order to upgrade the economy. Strict use of arable land and optimization of the land use structure, and implementation of arable land protection policies. Strengthening the level of social governance and enhancing the satisfaction of residents, thereby raising the level of sustainable well‐being. This research will provide a useful reference for achieving sustainable development goals in similar regions of the world.

MODELING THE CONDITION OF TACTICAL PLANNING IN THE SYSTEM OF CIRCULAR BUSINESS MODELS OF ENTERPRISES

This study investigates the implementation conditions, content, and features of tactical planning within the framework of circular business models in enterprises. It aims to identify effective methods, techniques, tools, and approaches for developing tactical plans in the system of circular business models of enterprises. Methodological provisions were employed to analyse approaches to tactical planning in circular business models. The primary focus was on evaluating the effectiveness of tactical planning, which is determined by the use of appropriate planning methods, adherence to implementation principles, and the application of relevant planning tools (technologies) in the context of the circular economy. This effectiveness is reflected in various performance indicators of the enterprise. To assess the state of tactical planning in circular business models, economic and mathematical modeling was conducted using partial least squares structural equation modeling (PLS-SEM). PLS-SEM facilitated the establishment of relationships between observed variables, including digital innovations, tactical planning mechanism methodology, and the effectiveness of circular enterprise models. The modeling results confirmed the hypotheses regarding the impact of digital technologies on the methodology of the tactical planning mechanism in the system of circular business models of enterprises. Key digital technologies identified as significant and effective include artificial intelligence (AI), green supply chain management (ML), and social media marketing (SMM). The methodology of the tactical planning mechanism was found to have the greatest impact on enterprise profit, transaction costs, and the utilization of industrial solid waste. Model validation results, based on quality criteria, indicated the absence of multicollinearity and highlighted the need to increase the number of variables to achieve a higher level of consistency in the regression model. The elimination of variables associated with unconfirmed hypotheses will optimize the model structure, normalize residuals, and reduce the average residual value between the observed and implicit covariance (correlation) matrix (SRMR).

A Study on the Emergence and Resilience of Integrated Management Systems in Organizations with an Industrial Profile in Romania

This paper aims to highlight the specific elements regarding emergence and resilience in implementing integrated management systems (IMSs) in organizations with an industrial profile in Romania. The purpose of the research was to carry out an extensive study in the industrial field to identify key elements in the implementation of IMSs, considering the identification and analysis of those elements that can generate risks (emerging elements) as well as the identification and analysis of components that can be used to intervene quickly in the event of the manifestation of risks and that may produce unexpected disturbances (resilient management). A quantitative survey distributed to 147 managers of an industrial organization that has a minimum of two integrated management systems was used for data collection. The present study highlights the opinions of the managers from Romanian industrial enterprises regarding the elements that contribute when implementing an integrated management system. For this purpose, the survey focused on the following main topics: the advantages achieved from the integration, the internal and external barriers encountered, the strategies followed for integration, the risks that occurred, some of the internal and external performance indicators (KPIs) that guide the organization, the elements that are not susceptible to integration, the integration model used, the audit typology, the documents that are needed and the main aspects improved after implementing the integrated management system. The information obtained from the study outlined several themes that management should consider in order to obtain a framework for integration guidance.

An anomaly detection scheme for data stream in cold chain logistics.

Anomaly detection is widely used in cold chain logistics (CCL). But, because of the high cost and technical problem, the anomaly detection performance is poor, and the anomaly can not be detected in time, which affects the quality of goods. To solve these problems, the paper presents a new anomaly detection scheme for CCL. At first, the characteristics of the collected data of CCL are analyzed, the mathematical model of data flow is established, and the sliding window and correlation coefficient are defined. Then the abnormal events in CCL are summarized, and three types of abnormal judgment conditions based on cor-relation coefficient ρjk are deduced. A measurement anomaly detection algorithm based on the improved isolated forest algorithm is proposed. Subsampling and cross factor are designed and used to overcome the shortcomings of the isolated forest algorithm (iForest). Experiments have shown that as the dimensionality of the data increases, the performance indicators of the new scheme, such as P (precision), R (recall), F1 score, and AUC (area under the curve), become increasingly superior to commonly used support vector machines (SVM), local outlier factors (LOF), and iForests. Its average P is 0.8784, average R is 0.8731, average F1 score is 0.8639, and average AUC is 0.9064. However, the execution time of the improved algorithm is slightly longer than that of the iForest.

GREEN INFRASTRUCTURE AS NATURE-BASED SOLUTIONS FOR WATER RESOURCES MANAGEMENT IN INDONESIA

Law No. 17/2019 declared that the main objective of Indonesia’s national water resources management is one that is managed in a comprehensive, integrated, and environmentally conscious manner, with the purpose of establishing justice and the welfare for the people. Not only stating if the national water resources management must be environmentally conscious, but the law also defines conservation as one of the efforts required for water resources management. Thereby, in the interest of carrying out the formulation and implementation process of water resources management as defined by the law, currently the Directorate General of Water Resources has included water resources conservation as one of its thirteen general policies. Even so, these conservation and environmentally conscious efforts can be found in the operational strategies, goals and performance indicators. Aims: This study was aimed to obtain additional insights can be benefited for the formulation and implementation process in Indonesia. Methodology and results: Corresponding to the recent development in water resources management strategies which have begun to lead into the direction of nature-based solutions, or popularly also known as green infrastructure, this study conducts a literature review on the utilization of green infrastructure as water resources management strategies in several other countries. Conclusion, significance and impact study: Directorate General of Water Resources’ strategic planning document for the year 2020-2024 also indicates if the objective of Indonesia’s national water resources management is still focusing on grey infrastructure, particularly the construction of multipurpose dams.

Evaluating the Utility of Hierarchical Multiple Regression and Quantile Regression in Determining Critical Factors for Success in Elite Men's Basketball

This research investigates the effectiveness of stratified multiple regression (MLR) and quantile regression (QR) in identifying the key performance indicators (KPIs) that impact the outcomes of elite men's basketball games. Using performance data from the Paris 2024 Olympic Games, the study compares MLR and QR across various quartiles to explore both general trends and specific variations within different distributions. Important predictors such as inside-out scoring, centre-back scoring, three-point shooting, free-throw percentage, and pace of play were found to be significant in both models. However, QR uncovered additional insights not captured by MLR, including the relevance of Q50 Offensive Rebounds and Q75 Assists and Caps. QR also demonstrated a higher sensitivity in revealing the intricate, context-dependent relationships between KPIs and game outcomes, offering a more detailed understanding of how these factors fluctuate across different levels of competition. While MLR provided stable results, it was less effective at capturing this variation. This study underscores the importance of quantitative analysis in sports research, shedding light on subtle performance dynamics and offering valuable insights for optimizing team strategies, tactical choices, and training plans. By incorporating advanced statistical techniques, the research contributes to a deeper understanding of basketball performance and establishes a robust framework for future studies in sports analytics.

Effect of Post-Activation Performance Enhancement in Combat Sports: A Systematic Review and Meta-Analysis—Part I: General Performance Indicators

Background/Objectives: Post-activation performance enhancement (PAPE) has been explored for its potential to improve general performance in combat sports. This systematic review and meta-analysis investigated the effects of PAPE protocols on physical performance, focusing on differences across disciplines, competitive levels, and testing methods. Methods: A PRISMA-guided search (2010–2023) identified 19 studies examining PAPE protocols in combat sports athletes. The inclusion criteria required human trials using defined PAPE protocols, with outcomes of general performance indicators such as countermovement jumps (CMJs). A meta-analysis was conducted on data from 866 athletes using random effects modeling. Results: The PAPE protocols yielded a pooled effect size of 0.136 (95% CI, 0.008–0.263) across 866 athletes. Taekwondo athletes exhibited the most pronounced improvements in CMJ performance, particularly when using protocols that combined repeated vertical jumps with heavy-resistance cluster sets, and with dynamic, sport-specific movements such as the bandal chagui protocol achieving an effect size of 1.19 (p < 0.001). Conversely, Muay Thai athletes experienced performance declines when the protocols incorporated highly specific techniques, such as roundhouse kicks (ES = −1.36, p = 0.009). Analysis by competitive level revealed pooled effect sizes of 0.14 (95% CI, −0.01 to 0.29) for amateur athletes and 0.13 (95% CI, −0.11 to 0.38) for elite athletes, with no statistically significant differences observed between these groups. Conclusions: PAPE’s effectiveness depends on tailoring protocols to the competitive level and discipline. Short rest intervals support plyometric protocols for amateurs, while heavy-resistance exercises enhance elite performers. Further research is needed to standardize PAPE protocols and explore discipline-specific adaptations.

Frost resistance prediction of recycled aggregate concrete based on supervised algorithms

The frost resistance of recycled aggregate concrete (RAC) is a crucial performance indicator in its engineering application. Considering the complexity of factors that affect the frost resistance of RAC, in this study five neural network algorithms were employed, back-propagation neural network, radial basis function network, convolutional neural network, support vector machine and random forest regressor, along with two optimisations methods, particle swarm optimisation-back-propagation (PSO-BPNN) and genetic algorithm-back-propagation to predict the frost resistance of RAC. A database was compiled from 616 mixes in the peer-reviewed literature, and eight variables affecting the freeze–thaw resistance of RAC were taken as inputs. The compressive strength, mass loss rate and relative dynamic elastic modulus after freeze–thaw cycles were taken as outputs. The results showed that the main factors affecting the freezing resistance of RAC were the number of freeze–thaw cycles, the replacement rate of recycled aggregates, crushing index and water–cement ratio. Among the seven algorithms, the PSO-BPNN model had the best comprehensive prediction performance, with R2 of predicted compressive strength reaching 0.9714. It provides a reference value for further research on RAC frost resistance.

Network Traffic Prediction Based on Decomposition and Combination Model

ABSTRACTIn this paper, a combination model based on complementary ensemble empirical mode decomposition (CEEMD) is proposed. First, CEEMD is applied to decompose original network traffic to generate high‐frequency component, low‐frequency component, and residual component. Then, the high‐frequency components are modeled and predicted using bi‐directional long short‐term memory (BiLSTM). The low‐frequency components and the residual component are modeled and predicted using autoregressive integrated moving average (ARIMA). Meanwhile, considering that the BiLSTM model is influenced by the hyperparameters, an Improved Bald Eagle Search (IBES) algorithm is proposed and applied to optimize three hyperparameters of BiLSTM, avoiding the blindness and subjectivity of manual selection of parameters. Finally, the prediction values of BiLSTM and ARIMA model are summed to obtain the final predicted value of network traffic. The comparisons with other models proved that the proposed network traffic prediction model is closer to the real data, with the optimal performance indicators, which is very suitable for high precision occasions.