Detection of adulteration in acerola (Malpighia emarginata DC.) pulps using a portable near-infrared (nir) spectrophotometer and chemometric.

This study examines the effectiveness of communication and stakeholder engagement in project meetings within the mechanical engineering industry. A descriptive statistics analysis of 10 variables reveals a neutral to slightly positive perception of communication and engagement. While stakeholder engagement and meeting effectiveness are positively rated, technical communication and complexity of information presented are identified as challenges. The study suggests that simplifying technical information, improving technical communication skills, and regularly soliciting feedback can enhance project communication and stakeholder engagement. Based on the findings, five theories are developed: Simplification of Technical Information Enhances Stakeholder Understanding; Effective Technical Communication Skills are Essential for Project Success; Regular Stakeholder Feedback Enhances Project Communication; Communication Tool Evaluation and Optimization Enhances Project Communication, and Meeting Optimization Enhances Communication Effectiveness. The study provides recommendations for improving communication effectiveness, enhancing stakeholder engagement, and ultimately contributing to project success.

This study investigates how work ethics, work climate, and work engagement affect project performance in project-based organizations across Malaysia. Emphasizing Islamic work ethics in a Muslim-majority context, the research collected 310 responses from employees in five Malaysian states. Using regression and moderation analysis, the study found that both work ethics and work climate significantly enhance project performance, with work engagement serving as a key moderating factor. These findings highlight the value of cultivating ethical behavior and a supportive work environment to boost organizational success. Practical implications suggest that project managers should foster a positive climate and align ethical values with organizational goals to improve employee engagement and project outcomes. The study’s originality lies in its focus on Islamic work ethics within the Malaysian setting, offering culturally relevant insights for leaders in similar environments. By integrating ethical principles into workplace practices, organizations can drive better performance and employee commitment. This research contributes to the growing body of knowledge on project management and organizational behavior, particularly in culturally specific contexts. Future studies are encouraged to explore these dynamics across different industries and countries to broaden the applicability of the findings and deepen understanding of how ethical and environmental factors shape project success globally.

Introduction The yield of ginkgo biloba leaves serves as a critical indicator for assessing their growth and health status. However, current assessment methods primarily rely on manual harvesting and weighing, which are time-consuming, labor-intensive, inefficient, and costly. Methods To address these limitations, this study designed an algorithm-based yield estimation approach: by employing airborne hyperspectral imaging technology at a research base to replace traditional manual measurements, a canopy hyperspectral dataset and Region of Interest Pixel (ROP) sets were constructed. Five preprocessing methods, Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV), Savitzky-Golay (SG), First Derivative (FD), and Standard Scaling (SS), were employed to develop Partial Least Squares Regression (PLSR) models, identifying the optimal hyperspectral data preprocessing approach. The optimal preprocessing model was subsequently integrated with Particle Swarm Optimization (PSO), Successive Projections Algorithm (SPA), Principal Component Analysis (PCA), Least Absolute Shrinkage and Selection Operator (LASSO), Competitive Adaptive Reweighted Sampling (CARS) and Particle Swarm Attention Mechanism Algorithm (PSAMA) for feature band selection. Traditional spectral vegetation indices were refined through random forest stepwise regression and spectral index correlation analysis, ultimately determining Soil-Adjusted Vegetation Index (SAVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Normalized Difference Red Edge Index (NDRE), Structure Insensitive Pigment Index (SIPI) as the final indices. The selected spectral bands and vegetation indices were then incorporated with PLSR, Random Forest (RF), K-Nearest Neighbors Regression (KNNR), Long Short-Term Memory (LSTM), Support Vector Regression (SVR), Bidirectional LSTM (BiLSTM), and BiLSTM- Grid SearchCV (BiLSTM-GS) machine learning models for yield prediction. Results Results demonstrated that the SNV-PLSR model achieved superior performance ( R p 2 = 0.7831, R M S E P = 0.0325). The optimal SNV- (SAVI - MSAVI - NDRE - SIPI - ROP) - (BiLSTM-GS) model, combining PSAMA-selected feature bands with vegetation index and ROP, yielded outstanding prediction accuracy ( R p 2 = 0.8795, R M S E P = 0.1021). Discussion This airborne hyperspectral canopy-based estimation technology provides an accurate, non-destructive solution for monitoring ginkgo leaf yield in field cultivation.

Background: Artificial intelligence (AI) and machine learning (ML) are progressively practical in project management to improve efficiency, prediction, resource distribution, and risk mitigation. The use of AI in American businesses keeps increasing yet researchers have found no solid proof about which AI features lead to success in various industry sectors. Methods: A quantitative survey was conducted among 210 project professionals across IT & Software, Construction, Healthcare, Manufacturing, Government, and Other Services sectors. The research gathered information about participant demographics and their use of AI technology and their views on project success. The measurement instrument showed reliability through Cronbach’s alpha which produced an overall score of 0.91. Results: Findings indicate that ML predictive analytics for forecasting contributed 25% to project success, followed by AI automation (15%) and risk intelligence (15%). The examination of deterioration results displays that ML predictive analytics harvests the most considerable result on project outcomes (β = 0.41, t = 7.12, p = 0.001) shadowed by AI mechanization (β = 0.33, t = 5.86) and danger intelligence (β = 0.29, t = 4.92). The sector analysis shows IT & Software professionals experience the most significant AI impact at 38.1% while Manufacturing, Government and Other Services report lower percentages. Conclusion: The study reveals that predictive analytics and automation and risk intelligence deliver substantial improvements in project efficiency and decision-making and quality outcomes. AI adoption shows different patterns across various sectors and workforce characteristics which makes strategic planning essential for successful project outcomes.

Abstract Dam health monitoring data encompasses a multitude of factors of diverse types, many of which do not significantly contribute to the performance of dam displacement prediction models. Conducting feature selection on these factors can reduce data acquisition costs, enhance model performance, and provide better interpretability. Although scholars have successfully developed a vast array of supervised feature selection methods, research on their application in dam displacement prediction remains limited. Therefore, this paper first provides a comprehensive review of supervised feature selection methods and explores different types of methods and their applications. Subsequently, the fundamental principles of 12 representative supervised feature selection methods are detailed, and their respective strengths and weaknesses are summarized. Finally, in an actual engineering project, the impact of these 12 methods on the performance of 5 machine learning (ML) and deep learning (DL) displacement prediction models is investigated, and their effectiveness and applicability are compared and analyzed. The results indicate that the performance of predictive models is indeed enhanced after feature selection. Among the 12 methods, in terms of model performance, Minimum-Redundancy-Maximum-Relevance (mRMR), Successive Projections Algorithm (SPA), and Extreme Gradient Boosting (XGBoost) excel in filter methods, wrapper methods, and embedded methods, respectively. Considering model performance, computational cost, and interpretability, XGBoost is identified as the most ideal supervised feature selection method. This study offers comprehensive guidance on selecting appropriate supervised feature selection methods to combine with ML or DL techniques to address dam displacement prediction issues.

Purpose The global festival landscape, while significant for community cohesion and economic growth, lacks research focused on the complex dynamics of Latin America, where most studies remain concentrated in the Global North. In this context, the purpose of this article is to analyze the role of community benefits in promoting social integration and the fulfillment of individual needs within community-based tourism settings. Design/methodology/approach An exploratory-descriptive quantitative approach was employed, with data collected through an online survey administered to 3,040 residents of Blumenau who attended the Oktoberfest festival. Structural equation modeling was used to analyze relationships among community benefits, need satisfaction and institutional trust. Findings The results indicate that institutional trust serves as a link that enhances the transformation of collective benefits into social integration and well-being, underscoring the importance of legitimate institutions for the sustainable success of community projects. Originality/value Despite the recognized importance of benefits and institutional trust, there is a gap in the integrated understanding of how institutional trust mediates the relationship between community benefits and the perception of individual needs being met, limiting both theoretical and practical advancements in this field.

Abstract The integration of Autonomous Haulage Systems (AHS) in surface mining has transformed operational practices in leading mining nations. This study offers a comparative analysis of the adoption and impact of driverless haul trucks in China and Australia, evaluating key dimensions such as labor economics, digital infrastructure, safety improvements, environmental benefits, and social challenges. While Australia has established itself as a global leader in mining automation—driven by high labor costs, remote operations, and private-sector innovation—China’s transition remains in its early stages, constrained by lower wages, infrastructure gaps, and a large mining workforce. Nonetheless, rising labor costs, national policy mandates, and successful pilot projects are accelerating interest in automation across China. This paper synthesizes data from industrial case studies, government reports, and academic sources to assess the feasibility of full-scale AHS deployment in China. It identifies both strategic opportunities and implementation barriers, including workforce displacement, capital investment requirements, and regulatory uncertainties. The study concludes with a roadmap for phased automation, emphasizing infrastructure readiness, workforce reskilling, and cross-sector policy alignment. By learning from Australia’s experience, China can adapt automation technologies to its unique socio-economic and industrial context, laying the groundwork for a safer, more efficient, and sustainable mining future.

The purpose of the article is to analyze the experience of implementing effective social projects and programs aimed at activating youth, as well as to substantiate the possibilities of their further application in the practice of youth policy in Ukraine. The concept of a “social project” in the context of youth activity is defined as a set of purposeful actions initiated and implemented by young people or with their participation, which has clearly defined objectives, temporal and resource boundaries, and is directed towards addressing socially significant problems, fostering civic responsibility, and enhancing the social activity of the youth community. The study examines the specific features of youth social projects and programs. A social project is considered as an instrument for the practical implementation of specific tasks in the field of youth policy, whereas a program determines its priorities and directions, serving as its strategic foundation. The study analyzes contemporary practices of implementing social projects and programs involving youth (“Youth Worker,” “YouthHere,” “VidNOVA.ua”), and takes into account the experience of other youth initiatives. It is concluded that successful social projects contribute to the activation of young people, the strengthening of social cohesion, and the formation of national identity. The consideration of accumulated experience makes it possible to improve youth policy in Ukraine and to create the prerequisites for developing new effective initiatives. It is demonstrated that best practices in youth work serve as examples of successfully implemented social projects and as a foundation for the formation of new initiatives oriented toward the needs and interests of young people. The transition from individual successful local projects to large-scale practices that expand and function in other communities creates a basis for further generalization of results and the development of effective strategies for activating the youth community.

The success of a construction project is not only measured by the achievement of technical aspects such as cost, quality, and time, but is also greatly influenced by stakeholder engagement. This is increasingly relevant for irrigation network rehabilitation projects that have a strategic role in supporting food security. This study aims to analyze the influence of stakeholder involvement consisting of project owners (owner/promoters), planning consultants (designer/defender), regulators and regional authorities (latent), as well as the end-user community or the Water User Farmers Association (P3A/apathetic) on the success of the irrigation network rehabilitation project of D.I. Buloila Kanan, Gorontalo. The research method uses a quantitative approach by collecting primary data through questionnaires to respondents who are directly involved in the project, both from elements of the government, consultants, contractors, and the community. Data were analyzed using descriptive methods and inferential tests to determine the partial and simultaneous influence of stakeholder involvement on the success of the project. The results show that the involvement of each stakeholder has a significant effect on the success of the project. The project owner plays a role in the provision of budgets, operating policies, and maintenance (O&M). The planning consultant determines the technical quality of the design according to local hydrological and socio-economic conditions. Regulators and regional authorities facilitate the administrative process and synchronization of spatial planning. Meanwhile, P3A contributes to the sustainability of irrigation functions through active participation in operations and maintenance. Simultaneously, the involvement of all stakeholders strengthens the success of the project, both in terms of physical output and long-term benefits. The conclusion of this study confirms that synergy between stakeholders is the main determinant of the success of irrigation network rehabilitation projects.

Software Development Life Cycle (SDLC) is a structured process followed by software organizations to design, develop, and maintain high-quality software systems. It defines a series of stages that transform user requirements into a fully functional software product. The SDLC framework ensures cost-effectiveness, efficiency, and quality by providing a systematic approach to software creation. This paper explores various SDLC models such as the Waterfall Model, Agile Model, Spiral Model, and V-Model. It highlights their advantages, limitations, and real-world applications. By comparing traditional and modern approaches, this study emphasizes how the right SDLC model selection enhances software reliability, reduces risks, and improves project success rates.

This interdisciplinary special issue discusses the salience of connectivity and disconnectivity at the local level, focusing on the South Caucasus. We use ‘connectivity’ as a theoretical tool to shed light on its complexity and dialectics, notably the different tangible and intangible dimensions of unevenness. Drawing on examples from Georgia, Azerbaijan, and Armenia, the articles illustrate that connectivity often manifests in large-scale infrastructure projects, which are typically associated with ideas of progress and the global circulation of goods, people, and capital. The issue’s contributions, based on original empirical research, explore the interplay of top-down and bottom-up perspectives in order to better understand the hidden mechanisms, power relations, decisions, and practices that lead to the success or failure of such projects. Like several infrastructure projects in the ‘Global South’, the large-scale projects addressed in this special issue are framed by the ideology of development, but as the articles demonstrate, they are more often accompanied by experiences of disenchanted modernity, immobility, and authoritarian practices.

The article examines the problems of investing in digitalization projects for corporate management. These problems arise, on the one hand, from the necessity to invest in such projects to ensure the enterprise’s long-term competitiveness, and on the other hand, from the low statistical success rates of digitalization projects, with corporate managers significantly risking their careers. The article also explores the reasons for the necessity of using outsourcing in the implementation of enterprise digital transformation projects within the corporate governance system. Among these reasons are the need to attract talented specialists with the skills and experience required for the successful execution of digital transformation, enhancing flexibility in an unstable external environment, as well as optimizing costs and project implementation time while ensuring high quality. Outsourcing is a powerful tool, but it requires a strategic and systematic approach in the context of corporate management. However, Ukrainian manufacturing enterprises make limited use of IT outsourcing opportunities, which indicates the presence of significant challenges for implementing this type of development. In contrast, enterprises from developed countries highly value the ability to access specialized expertise without the need for in-house development. The risks of outsourcing digitalization projects are highlighted, including possible strategic misalignment between the client enterprise and the outsourcer, disruption of control over digital assets and the decline of the enterprise’s digital competence, inefficient use of resources, and delays caused by low project execution transparency. It is determined that the success of a digitalization project using outsourcing can only be ensured through the integration of the outsourcer into the management model, with an emphasis on transparency, accountability, and shared value. Therefore, to mitigate these risks, it is important to apply modern management theories such as Lean and Agile, where Lean emphasizes successful principles of long-term partnership in outsourcing, and Agile highlights the principles of effective implementation of enterprise digitalization projects in conditions of an unstable external environment.

The article analyzes the concept and content of the legal regime of joint property rights of intellectual property in the field of economic activity. The peculiarities of legal regulation of joint ownership of intellectual property objects in the context of modern economic development are examined. Based on the positions of scholars, it is proven that it is impossible to fully equate the property rights of intellectual property with real (tangible) rights. It is established that the main powers in the exercise of joint property rights of intellectual property are use, disposal and protection. The necessity of improving the legal mechanism for regulation joint property rights of intellectual property is substantiated, and a systematic approach to their legal characterization is proposed. Proper legal regulation of economic activity is one of the main factors of a successful business project. The expansion of economic activity, the increase in its profitability also depends on the timely response of business owners to changes in today, which, in particular, involves the inclusion of intellectual property in production. It is also evident that the team approach makes it possible to create a unique product, since the latter is a synthesis of various ideas and methods, which are supported by the production capabilities of several entities. However, joint activities require a more detailed regulatory framework for its regulation, which necessitates the balancing of interests, rights and obligations of several subjects. The risks that exist due to fears of ineffective resolution of legal issues between the co-owners are a slowing down and sometimes blocking factor in the development of economic activity. Today, despite the understanding of the importance of cooperation between business entities of different areas of activity, the legal framework does not contain the necessary norms in terms of volume and quality that would regulate it. In addition, the dynamic development of science, relentless modernization, the latest technologies, coupled with such a phenomenon as the rapid obsolescence of new programs, methods, inventions, etc., which would seem to have become more common yesterday, coupled with the growing demands of consumers, indicate the need to create a regulatory framework that would be as universal and universal as possible for the conditions of the present, and for the future. Specific rules of conduct in the business environment must be based on a deep and unambiguous understanding of such basic elements as the concept and legal nature of legal elements. Therefore, the joint ownership of intellectual property rights should be understandable to the range of subjects that are involved in it by virtue of the relevant activity, primarily through the disclosure of its content and essential vision – the nature of the legal substance.

Agile project management has become a dominant paradigm for managing complex projects, emphasizing flexibility, customer collaboration, and self-organizing teams. However, traditional, hierarchical leadership models often conflict with Agile’s core values, creating a significant leadership gap. Servant leadership, a philosophy where the leader’s primary goal is to serve the team, is theorized to be a natural fit. This study empirically investigates the impact of servant leadership on key project outcomes within Agile environments. A quantitative, cross-sectional survey was administered to 68 project management professionals, selected via purposive sampling, who were actively working in Agile teams. Data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results provide robust support for all hypotheses, indicating that servant leadership has a significant positive effect on team performance (β = 0.45, p < 0.001), team member satisfaction (β = 0.52, p < 0.001), and project success (β = 0.38, p < 0.001). These findings underscore that adopting servant leadership is a strategic lever for enhancing team dynamics and achieving superior project outcomes in Agile settings. The study offers practical implications for organizations and lays the groundwork for future research.

The success of a construction project is not only measured by the achievement of technical aspects such as cost, quality, and time, but is also greatly influenced by stakeholder engagement. This is increasingly relevant for irrigation network rehabilitation projects that have a strategic role in supporting food security. This study aims to analyze the influence of stakeholder involvement consisting of project owners (owner/promoters), planning consultants (designer/defender), regulators and regional authorities (latent), as well as the end-user community or the Water User Farmers Association (P3A/apathetic) on the success of the irrigation network rehabilitation project of D.I. Buloila Kanan, Gorontalo. The research method uses a quantitative approach by collecting primary data through questionnaires to respondents who are directly involved in the project, both from elements of the government, consultants, contractors, and the community. Data were analyzed using descriptive methods and inferential tests to determine the partial and simultaneous influence of stakeholder involvement on the success of the project. The results show that the involvement of each stakeholder has a significant effect on the success of the project. The project owner plays a role in the provision of budgets, operating policies, and maintenance (O&M). The planning consultant determines the technical quality of the design according to local hydrological and socio-economic conditions. Regulators and regional authorities facilitate the administrative process and synchronization of spatial planning. Meanwhile, P3A contributes to the sustainability of irrigation functions through active participation in operations and maintenance. Simultaneously, the involvement of all stakeholders strengthens the success of the project, both in terms of physical output and long-term benefits. The conclusion of this study confirms that synergy between stakeholders is the main determinant of the success of irrigation network rehabilitation projects.

The environmental database management system, or EDMS, provide a set of fully-integrated high-tech tools enabling effective management of environmental data. EDMS provides a fundamental for successful remediation projects and ensuring regulatory compliance. This study emphasis on the significant challenges that an organization face in choosing the appropriate environmental database system. This provides a comprehensive study and evaluation of two widely used platforms Environmental Quality Information System (EQuIS) and Environmental Information Management (EIM). The two standard systems are analysed by employing descriptive and analytical approach to evaluates the key factors such as data management, authentication, accessibility, automation, GIS integration, security, and reporting capabilities. The results show that EQuIS is highly effective in providing strong data validation features and compliance with strict environmental regulatory and, while EIM extends greater flexibility, user-friendly web interfaces, and cloud-based advantages that support dynamic enterprise needs. This research proposes a practical framework to help professionals and organisations to select suitable environmental database systems that supports the improving data quality and better decision-making in environmental remediation efforts. In conclusion, the study highlights the critical role of EDMS in managing environmental data and ensuring regulatory compliance. The comparison between EQuIS and EIM reveals that EQuIS excels in data validation and regulatory adherence, while EIM offers superior flexibility and cloud-based accessibility. Organizations should select a system based on their specific operational needs and compliance requirements. Overall, adopting the proposed framework can enhance data quality and support more effective environmental decision-making.

IntroductionContext plays a critical role in shaping how interventions are designed and implemented, and must therefore be considered prior to implementation. There is consensus that the relationship between contextual factors and intervention outcomes is best understood using qualitative and quantitative methods, the process for considering and incorporating context remains unclear. Drawing on a recently completed study focusing on building hospital management capacity, this paper describes and discusses the benefits and learning from the implementation of an integrative and co-design approach.MethodsThis sequential mixed-methods study included managers and clinicians from two district hospitals in China. Focus Group Discussions [FGD] are a critical step in guiding the adaptation of several validated tools in the local hospital context. Data collected from FGDs and online surveys provides a comprehensive understanding of the current state of hospitals.ResultsThis study identified a wide range of difficulties faced by mid-level managers and clinical staff in two hospitals. While managers reported hospital-specific challenges, staff across both sites consistently cited issues such as inadequate support, lack of recognition, and lack of patient trust. Survey results also revealed low levels of psychological empowerment, job satisfaction, and perceived leadership effectiveness. Self-assessment using the MCAP tool highlighted significant competency gaps among mid-level managers, particularly in operations management and leading change.DiscussionThe use of a co-design approach broadly engaging relevant key stakeholders from the design and implementation of the project and formulation of improvement strategies is key to enabling project success and maximizing and sustaining project impact.

The study reveals certain aspects of the cognitive component of educational mathematics projects in basic secondary education. In accordance with the objective, the study reveals the essence of the cognitive component: it is the process and result of acquiring and meaningfully applying the knowledge and skills obtained through mental processes during the mastery of basic secondary education in the field of mathematics. The content of the cognitive component consists of a set of theoretical and practical mathematical knowledge. The methodology for developing the cognitive component of educational mathematics projects in basic secondary education is based on a systematic approach and the appropriate use of a range of methods. An important feature of the content of the cognitive component is its systematic nature and reflection of the latest achievements in mathematics. Attention is drawn to the importance of focusing on the hypothetical-deductive method of cognition. This method of cognition is characteristic of students in basic secondary education. It is noted that it is important in mathematics teaching projects to ensure, through the content and organization of work, the formation of students' ability to effectively solve problems and apply knowledge in non-standard situations. Research results. Methodological support for the cognitive component of educational mathematics projects in basic secondary education involves active learning content. Such content is developed taking into account the idea of incidental learning stimuli in the educational and cognitive activities of basic school students. The organizational elements of the cognitive component of educational projects in mathematics have been identified: the involvement of the teacher as a coach, the balance between cognitive load and lesson productivity, the phased use of the effects of internal cognitive load (lack of a specific goal, divided attention, a worked-out example, hypothetical perception, partial solution; memory segmentation in the architecture of searching for new information, modality, assertiveness. The prospect for further development of the problem is defined as the expansion and characterization of the advantages and challenges of the effects of internal cognitive load during the development and implementation of project and research work in mathematics lessons in basic secondary education. It is also proposed to create cases of successful educational projects for basic secondary school students within the framework of the STEM model program.

Purpose EPC+PPP projects are gaining prominence across diverse industries; however, challenges arise from intricate stakeholder relationships and the dual role of the private sector as Party A and Party B, potentially compromising project success. The research’s objective is to mitigate project risks by elucidating intricate stakeholder interactions and the private sector’s dual influence, thereby enhancing decision-making processes in complex EPC+PPP environments. Design/methodology/approach An integrated approach is proposed. First, it proposes an evaluation system for assessing the implementation difficulty of projects under EPC+PPP. This system incorporates a balance coefficient for public-economic interests, reflecting the impact of the dual status of the private sector, which is determined using the stratified full consistency method (SFUCOM) and triangular fuzzy numbers (TFNs). Second, a two-layer network is established to depict stakeholder relationships and associated risks, thus providing a comprehensive view of the risk landscape. Subsequently, risk prioritization is executed using DSM to identify critical risk areas. Finally, an optimization model is developed to maximize the decision-maker’s utility to facilitate effective risk response decisions. Findings The findings underscore the system’s effectiveness in assessing project implementation difficulties and prioritizing risks, demonstrating the pivotal role of economic interests in shaping risk response strategies. Originality/value The study’s originality is evident in its integrated approach to risk assessment and decision optimization in EPC+PPP projects, providing a novel framework that bridges the gap between theoretical models and practical project management.