Field Of Management Research Articles

Machine Learning Approaches for Diagnostics and Prognostics of Industrial Systems Using Industrial Open Source Data

In the field of Prognostics and Health Management (PHM), recent years have witnessed a significant surge in the application of machine learning (ML). Despite this growth, the field grapples with a lack of unified guidelines and systematic approaches for effectively implementing these ML techniques and comprehensive analysis regarding industrial open-source data across varied scenarios. To address these gaps, this paper provides a comprehensive review of ML approaches for diagnostics and prognostics of industrial systems using opensource datasets from PHM Data Challenge Competitions held between 2018 and 2023 by PHM Society and IEEE Reliability Society and summarizes a unified ML framework. This review systematically categorizes and scrutinizes the problems, challenges, methodologies, and advancements demonstrated in these competitions, highlighting the evolving role of both conventional machine learning and deep learning in tackling complex industrial tasks related to detection, diagnosis, assessment, and prognosis. Moreover, this paper delves into the common challenges in PHM data challenge competitions by emphasizing data-related and model-related issues and evaluating the limitations of these competitions. The potential solutions to address these challenges are also summarized. Finally, we identify key themes and potential directions for future research, providing opportunities and prospects for next-generation ML-PHM development in PHM domain.

When you hop, what do you hope? Evolution of success parameters for expatriates across assignments

PurposeInternational assignments are not just opportunities for career advancement but also for personal growth and exploration. This paper, by capturing the changing expectations and success parameters across the assignments, is a timely and relevant resource for individuals navigating the complexities of international careers. In addition, the paper aims to help organizations build policies for enabling successful assignments for international assignees and managers.Design/methodology/approachOur research took a unique two-pronged approach to understanding the success parameters of international assignments. We first interviewed 16 managers to understand the success parameters they set for expatriates. Then, we interviewed 19 international assignees to explore their choices and how they defined success in their international experiences.FindingsOur comprehensive research, based on 35 interviews with international assignees and their supervisors, reveals that an assignment's success evolves with different stages of the assignment, over the assignments that the assignees choose, and varies according to the intent of the mobility.Originality/valueThis paper makes a significant contribution to the field of cross-cultural management and international assignments. By discussing the evolving definition of success across various international assignments, it not only provides valuable insights for expatriates in their international careers but also to managers to build aligned policies and practices.

History of health care development in the Republic of Kazakhstan

Introduction: The urgent need to modernize Kazakhstan's healthcare system arises from deep-rooted economic crises and systemic challenges exacerbated during the transition to capitalism from Soviet-era centralized planning. Objective: The research aims to analyze the stages of development of healthcare in the Republic of Kazakhstan since the country gained its independence. Methods: To solve the set tasks the authors applied such methods of knowledge as historical, comparative, systemic, and method of political-legal analysis. Results: Research results consist in the formulation of the basic stages of development of public health in Kazakhstan, the definition of advantages and disadvantages of functioning of the given branch on each of them, and also in the designation of transformations and innovations in the public health sphere for last years. Conclusions: The materials of this research can be applied in the applied and research spheres. In particular, the research may be of interest to the employees of the state authorities who are dealing with the problems of reforming the health care system in post-Soviet countries. In addition, the materials can be used in the work of scientists whose sphere of interest includes the formation of policy in the field of health care management

Líneas de investigación y perspectivas futuras de los estudios organizacionales: una revisión

Organizational studies allow us to analyze and understand the functioning of organizations, generate knowledge and improve their management and performance, from perspectives different from the classic ones with which the organizational phenomenon has been analyzed in a traditional way; These perspectives invite a critical look at this phenomenon. However, it is relevant to evaluate its potential to provide theories, models and tools that help advance the field of management and improve the effectiveness and sustainability of organizations. To date, no review has been identified in Scopus that synthesizes the literature on organizational studies from a bibliometric analysis, by doing so, this article provides a basis for researchers in organizational studies to learn about various future lines of research. The objective of this document is to review scientific documents published in Scopus(r) on organizational studies, to propose a structure of published scientific knowledge, so that different future lines of research are offered. 1091 documents were found that met the inclusion and exclusion criteria in the database that were processed with Bibliometrix, VosViewer and ToS. The main lines of research identified were: a) Leadership and management of organizational change; b) Changing, diverse and inclusive work environments; c) Legitimation, sustainability and organizational responsibility.

Performance management in the prosocial market economy: a new paradigm for economic performance and sustainability

Purpose The purpose of this multi-voiced paper is to propose a prosocial paradigm for the field of performance management and management control systems. This new paradigm suggests cultivating prosocial behaviour and prosocial groups in organizations to simultaneously achieve the objectives of economic performance and sustainability. Design/methodology/approach The authors share a common concern about the future of humanity and nature. They challenge the influential assumption of economic man from neoclassical economic theory and build on evolutionary science and the core design principles of prosocial groups to develop a prosocial paradigm. Findings Findings are based on the premise of the prosocial paradigm that self-interested behaviour may outperform prosocial behaviour within a group but that prosocial groups outperform groups dominated by self-interest. The authors explore various dimensions of performance management from the prosocial perspective in the private and public sectors. Research limitations/implications The authors call for theoretical, conceptual and empirical research that explores the prosocial paradigm. They invite any approach, including positivist, interpretive and critical research, as well as those using qualitative, quantitative and interventionist methods. Practical implications This paper offers implications from the prosocial paradigm for practitioners, particularly for executives and managers, policymakers and educators. Originality/value Adoption of the prosocial paradigm in research and practice shapes what the authors call the prosocial market economy. This is an aspired cultural evolution that functions with market competition yet systematically strengthens prosociality as a cultural norm in organizations, markets and society at large.

Gamification in supply chain education: A comparative study of supply chain card games and board games in Malaysian tertiary institutions

Gamification has gained popularity in educational settings as a tool to enhance learning experiences. This research compares two well-known gamification tools, supply chain master card games and supply chain board games, in their capacity to teach supply chain management (SCM) concepts. Random sample interviews were conducted with students and employees to gather their perspectives on the games and SCM topics. The study evaluates the content delivery, level of understanding, and the advantages and disadvantages of using it for teaching and learning in a criteria table. It is aligned with the Sustainability Development Goal (SDG) 4 which is Quality Education in empowering sustainability through quality education. The findings demonstrate that gamification, including the use of these games, positively impacts the teaching and learning of supply chain management in Malaysian tertiary education. The results indicate that both the Supply Chain Card Game and the supply chain board game have significant advantages in enhancing student engagement, experiential learning, and the understanding of key SCM concepts which involve three (3) main measurements which are characteristics, content delivery, and level of understanding. It improves student engagement, facilitates active learning, and fosters essential skill development. The recognition of gamification's potential has led to policy initiatives supporting its integration into the curriculum, aligning with the goals of learner-centered and experiential education. However, challenges remain in implementing gamified learning approaches effectively. The Malaysian government should acknowledge gamification's potential and provide support for teachers to incorporate gamification tools, including training programs, workshops, and educational resources. By addressing implementation challenges, the sustained integration of gamified learning approaches can be ensured in the Malaysian education system. This research emphasizes the significance of gamification in enhancing teaching techniques and its positive impact on student learning outcomes in the field of supply chain management.

SYNERGY OF ORGANIZATIONAL STRUCTURE AND ANTI-CRISIS STRATEGIES IN ENSURING ENTERPRISE STABILITY

The article considers the current problem of ensuring the stability of an enterprise in conditions of economic instability through the synergy of the organizational structure and anti-crisis strategies. The research aims to learn about different approaches to the integration of organizational structures with strategic management, which contribute to increasing the adaptability of an enterprise to external challenges. The main elements of synergy are considered to be, in particular, the mechanisms of implementing anti-crisis measures within the existing organizational structure, which allow for increasing the stability of an enterprise in conditions of market instability. The article draws attention to the fact that effective cooperation of the organizational structure with anti-crisis strategies significantly improves the ability of an enterprise to adapt to changes in the external environment. Based on the data obtained, recommendations are formulated for improving management decisions aimed at increasing the adaptive potential of an enterprise. In particular, the possibilities of optimizing internal processes in order to react faster to changes and minimize risks related to crisis phenomena were analyzed in detail, which ensures the stability and competitiveness of the enterprise. The possibilities of optimizing internal processes in order to react faster to changes in the external environment are considered. Particular attention was paid to the role of leadership in implementing strategic changes. The effectiveness of using the company's resources in crisis conditions was assessed. The role of leadership in implementing strategic changes is considered separately. Leadership in crisis times plays an important role in ensuring the effectiveness of implementing anti-crisis measures, as well as in strengthening the corporate culture, which contributes to increasing the level of trust and cohesion of the team. The article shows that the effective use of the company's resources in crisis conditions is a key factor in ensuring its long-term stability. The conclusions from the work indicate the need to improve the organizational structure of the company in order to ensure its greater integration with anti-crisis strategies, which will allow the company to effectively face external challenges and strengthen its competitive position on the market. Therefore, the presented article contains practical recommendations that may be useful both for business managers and researchers in the field of strategic management and organizational development in conditions of economic instability.

County-Level Cultivated Land Quality Evaluation Using Multi-Temporal Remote Sensing and Machine Learning Models: From the Perspective of National Standard

Scientific evaluation of cultivated land quality (CLQ) is necessary for promoting rational utilization of cultivated land and achieving one of the Sustainable Development Goals (SDGs): Zero Hunger. However, the CLQ evaluation system proposed in previous studies was diversified, and the methods were inefficient. In this study, based on China’s first national standard “Cultivated Land Quality Grade” (GB/T 33469-2016), we constructed a unified county-level CLQ evaluation system by selecting 15 indicators from five aspects—site condition, environmental condition, physicochemical property, nutrient status and field management—and used the Delphi method to calculate the membership degree of the indicators. Taking Jimo district of Shandong Province, China, as a case study, we compared the performance of three machine learning models, including random forest, AdaBoost, and support vector regression, to evaluate CLQ using multi-temporal remote sensing data. The comprehensive index method was used to reveal the spatial distribution of CLQ. The results showed that the CLQ evaluation based on multi-temporal remote sensing data and machine learning model was efficient and reliable, and the evaluation results had a significant positive correlation with crop yield (r was 0.44, p < 0.001). The proportions of cultivated land of high-, medium- and poor-quality were 27.43%, 59.37% and 13.20%, respectively. The CLQ in the western part of the study area was better, while it was worse in the eastern and central parts. The main limiting factors include irrigation capacity and texture configuration. Accordingly, a series of targeted measures and policies were suggested, such as strengthening the construction of farmland water conservancy facilities, deep tillage of soil and continuing to construct well-facilitated farmland. This study proposed a fast and reliable method for evaluating CLQ, and the results are helpful to promote the protection of cultivated land and ensure food security.

THEORETICAL AND METHODOLOGICAL PRINCIPLES OF PERSONNEL MANAGEMENT IN THE ASPECT OF RISK MANAGEMENT

The purpose of the article is to study the theoretical and methodological aspects of personnel management risks and the specifics of developing their management strategies in the context of modern dynamic business conditions. The work highlights the key aspects of personnel risks, methods of their analysis, methods of management and regulation, and gives practical recommendations for managers and managers. Method. To achieve the goal, the methods of analysis and synthesis, comparison, etc. are applied. The results. The theoretical aspects of risk management with human capital are studied. Analyzed and systematized methods aimed at reducing the impact of personnel risks on the productivity and stability of the enterprise. The result of the application of such strategies is an increase in the efficiency of personnel management, a reduction in the probability of problems, and the optimization of work processes. Scientific novelty. The article offers a comprehensive view of risk management in the context of personnel management. The use of modern methods of risk analysis and management allows in-depth solving of problems arising in personnel management and the development of effective strategies for their elimination, taking into account today's conditions. Practical significance. The results of the research can be useful for leaders and managers in the field of personnel management, contributing to the stability and efficiency of the organization. The considered strategies and methods can help to implement practical management solutions with the aim of reducing personnel risks and increasing labor productivity.

Experimental investigation and Monte Carlo simulation of landfill leachate treatment using physicochemical method and a non-thermal plasma reactor

ABSTRACT Leachate treatment is one of the challenging subjects in the field of waste management. Leachate as a dumpling sites hazardous byproduct due to the high concentration of chemical oxygen demand (COD) and toxic compounds with dark colour is a potential pollutant of the environment, causing a lot of problems in the absence of treatment and direct discharge to the environment. In this study, the combinatory performance of sequential chemical flocculation and coagulation process and non-thermal plasma (NTP) technology on leachate from the Sarāvān city former controlled landfill, Iran, was investigated. The outcomes of Jar test illustrated that hydrated aluminium sulphate (PAC) was selected the best coagulant compared with hydrated aluminium sulphate (HAS) and ferric chloride (FC) to remove suspended solids and colour. The optimised parameters for 10% PAC pre-treatment were obtained 3 g lime and cationic 0.1 g polyelectrolyte per 1 litre of leachate. After pre-treatment by using jar test, NTP was used to remove turbidity, colour, COD and so forth. The sequential system-based all stages of pretreatment and NTP diminished the turbidity and colour removal to 98.6% and 99.2%, respectively. Furthermore, COD, BOD5, TSS, and TDS were also reduced. As a result, combination of pre-treatment and NTP technology are able to remove the landfill leachate effectively. Monte Carlo calculations exhibited that Al3+ and H2O2 had the most effects to decompose HA (Humic acid) compound in physicochemical pre-treatment and treatment stages.

Examining Occupation Fields of Programs According to Artificial Intelligence: Anadolu University Open Education System Case

Anadolu University's Open Education System (OES) accommodates over one million students and has incorporated an AI-based Virtual Assistant for non-academic support since 2022. While OES offers abundant information about its programs on its website, there is a notable absence of support services providing job recommendations related to students' chosen programs. This gap in student support extends to the post-graduation phase, with the Virtual Assistant lacking a concept for guiding students in finding employment opportunities. Recognizing the need for comprehensive assistance, this study sought to leverage AI capabilities to offer job recommendations by extracting information from the objectives of 63 OES programs. The initial inquiry involved requesting AI-generated job recommendations based on the stated objectives of these programs. Subsequently, the Virtual Assistant was tasked with providing insights into the occupation fields associated with OES programs. Analysis of the AI's responses, along with the classification of occupations according to the International Standards of Classifications of Occupations (ISCO) and the International Standard Classification of Education (ISCED), forms the core of this study. Contrary to trends observed in most European countries, the predominant number of graduates in Türkiye emerges from business and management fields. However, the correlation between graduation rates and subsequent job placements appears suboptimal within the labor force and employment landscape. The study advocates for the integration of AI in offering job recommendations, incorporating graduation and employment rates. This approach enables students to seek guidance on suitable programs aligned with their skills, fostering a more informed decision-making process. The study underscores the potential for higher education institutes to share employment and labor force data.

Addressing endogeneity in the relationship between early entry and performance: The case of foreign market expansion

Addressing endogeneity issues has been identified as a key priority for ensuring continued progress in the field of strategic management. We contribute to this research agenda by developing a generalized method of moments (GMM) estimation approach that accounts for endogeneity in dynamic models. To illustrate how endogeneity bias impedes reliable interpretation, we examine the relationship between early mover strategies and performance using data on multinational enterprises entering transition economies. Our empirical results demonstrate that early mover advantages are significantly greater after controlling for endogeneity. Additionally, we find evidence that the level of institutional development weakens the advantages of pursuing an early mover strategy in transition economies. After accounting for endogeneity, the negative moderating effect of institutional development is far more pronounced. The magnitude of these two biases underscore the necessity for scholars to adequately address endogeneity and how GMM estimation can facilitate in better understanding the performance implications of strategic choices.

Remaining useful life prediction based on time-series features and conformalized quantile regression

Abstract The remaining useful life (RUL) prediction is a key task in the field of prognostics and health management (PHM) and plays a crucial role in preventive maintenance tasks. Traditional prediction methods have mostly focused on point prediction issues, neglecting the uncertain factors in the prediction task, thus failing to ensure the credibility of the prediction. In light of this, this paper focuses on improving the accuracy of point prediction models for RUL and interval prediction issues, proposing the introduction of multi-scale convolutional neural networks (MCNN), decomposed time-sequential linear layers (DL), and conformal quantile regression (CQR) techniques into the RUL prediction task of aero-engines. The aim is to provide timely and accurate failure warnings for aero engines, effectively ensure their reliability and safety, and reduce maintenance costs throughout their life cycle. In response to the limitations of current point prediction models in capturing the temporal features of life data, a MCNN-DL-based RUL prediction model is proposed to capture life data's long-term trends and local variations for precise point predictions. Furthermore, an interval estimation approach for RUL is presented, which integrates the MCNN-DL model with CQR to account for prediction uncertainty. Finally, the method in this paper is verified using the CMAPSS dataset, and the results show that the method has achieved excellent results in both RUL point prediction and interval prediction tasks.

Artificial Intelligence in Pain Management: Advancing Translational Science in Digital Health Research from Bench to Bedside

Artificial Intelligence (AI) is rapidly transforming the landscape of healthcare, with particularly profound implications in the field of pain management. This chapter delves into the integration of AI-driven tools that revolutionize the way pain is assessed, monitored, and treated. Through the use of predictive modeling, real-time monitoring, and personalized treatment plans, AI significantly enhances the precision, efficiency, and effectiveness of pain management strategies. The discussion extends to various AI applications, shedding light on the ethical considerations that accompany these technological advancements, as well as outlining future research directions. Collectively, these insights underscore the immense potential of AI to not only improve pain management practices but also to significantly elevate patient outcomes. Central to this transformation is the role of translational science in bridging the gap between theoretical AI models and their practical, clinical applications. This "bench to bedside" approach ensures that innovations in AI are not merely confined to research environments but are actively integrated into real-world patient care. For instance, AI-powered predictive analytics in pain management, driven by sophisticated machine learning algorithms, have progressed from computational experiments to clinical trials, and ultimately, to widespread implementation in healthcare settings. These AI models are now being utilized in hospitals to assess patient pain levels in real-time, predict opioid requirements, and optimize pain management protocols. This progression exemplifies how translational science is facilitating a paradigm shift in healthcare, positioning AI as an indispensable tool in modern pain management.

Screening nitrogen-fixing cyanobacteria that can alleviate cadmium toxicity to rice and reduce cadmium accumulation in brown rice

Among food crops, rice is the most serious food crop contaminated with cadmium (Cd). It is critical to reduce Cd bioavailability in the soil and prevent its accumulation in brown rice. The use of microorganisms to lessen Cd toxicity in rice has been the subject of numerous studies carried out in recent years. The nitrogen-fixing cyanobacterium (NFC) is a potent biofertilizer and heavy metal biosorbent. However, there is a dearth of research on the impact of NFC supplementation on rice's susceptibility to Cd poisoning. This study screened for Cd-tolerant NFCs and assessed how well they might promote growth and lower the amount of Cd in rice. Four NFCs with tolerance to 1 mg L−1 Cd were selected from ten NFCs. The results of seedling experiment showed that SCAU-10 treatment increased plant height and biomass while reducing Cd levels in seedlings by 62.0 %. The pot experiment also demonstrated that SCAU-10 was effective in lowering Cd content in brown rice by 85.3 %. Reducing the bioavailability of soil Cd, shielding rice roots, preventing Cd transfer from below to above ground, generating phytohormones, and enhancing the photochemical electron quantum yield of rice leaves are a few possible action mechanisms of the NFC. It indicates that Trichormus sp. SCAU-10 has a great deal of promise for use as a biofertilizer in the safe management of Cd-contaminated rice fields. This is the first report on using Trichormus sp. biofertilizer for relieving the toxicity of Cd to rice and reducing Cd accumulation in brown rice.

Comparative Analysis of Traditional Wealth Management Services vs. AI-Based Wealth Management Software

The integration of artificial intelligence (AI) is transforming the wealth management industry. This paper compares traditional wealth management with AI-based solutions to assess their value to customers, focusing on factors like cost, customization, accessibility, performance, and accuracy. Traditional wealth management offers personalized human interaction, expert advice, and tailored financial planning but often comes with higher costs and limited scalability. In contrast, AI-based wealth management uses advanced algorithms and data analytics for scalable, efficient, and cost-effective services, though it may lack the personal touch of human advisors. The study finds that traditional wealth management excels in comprehensive planning and trust-based relationships, crucial for clients with complex needs. AI-driven solutions enhance accessibility and affordability, providing sophisticated insights to a wider audience. However, concerns about personalization quality and data reliance remain. The research suggests that a hybrid model combining traditional and AI-based approaches may offer the best solution, leveraging AI’s efficiency while maintaining personalized service and expert advice. Overall, this paper provides valuable insights for financial planners, identifying strategies to enhance value in the evolving wealth management field. Keywords: Wealth Management, Artificial Intelligence (AI), Financial Planning, AI-based Solutions, Personalized Financial Advice, Hybrid Wealth Management.

Polystyrene shell-based “coconut-like” and “pomegranate-like” microencapsulated phase change materials: Formation mechanism, thermal conductivity/stability enhancement and their application in thermal management

Encapsulation of phase change materials (PCMs) using polystyrene (PS) can be an effective solution to the leakage of PCMs, but the low thermal conductivity/stability of the prepared microencapsulated phase change materials (MEPCMs) remain unresolved. Here, we investigated the formation mechanism of PS shell-based MEPCMs via Pickering emulsion polymerization: coconut-like and pomegranate-like MEPCMs were obtained for the first time before and after the introduction of divinylbenzene (DVB), and the thermal conductivity and stability of the former were lower than that of the latter with the same graphene nanosheets (GNSs). Among them, MEPCM-4–7 wt% GNSs (St:DVB=1:1) has the highest thermal conductivity of 0.9358 W∙m−1∙k−1 (222.47 % higher than MEPCM without GNSs) and optimal anti-leakage performance. The thermal stability (thermogravimetric results) is slightly weaker than MEPCM-3–7 wt% GNSs (St:DVB=5:1), but has the highest thermal reliability (the melting enthalpy only decreases by 0.19 % after 100 cycles). The phase change composites (PCCs) was prepared by dispersing MEPCMs in PDMS matrix and applied to the simulated chip thermal management, which can achieve a 10.85 % decrease in the chip equilibrium temperature compared with PDMS. The method of improving the heat transfer properties and thermal stability of MEPCMs based on their structure provides a new idea to solve the problem of low thermal conductivity and stability of MEPCMs, and the prepared PCCs show great potential for practical applications in the field of thermal management.

High performance flexible phase change hydrogel applied to thermal management of new cigarette device

To address the thermal management challenges of new heat-not-burn (HNB) cigarette devices, this study aims to enhance overall energy conversion efficiency while maintaining unchanged battery capacity. The goal is to minimize heat dissipation and reduce the temperature of the device's housing that contacts the user. In this research, CaCl2·6H2O (CCH) was selected as the phase change material (PCM), and a polyacrylamide (PAM) phase change hydrogel encapsulating CCH was prepared via in-situ polymerization. Additionally, konjac glucomannan (KGM) was incorporated into the three-dimensional network structure of PAM through hydrogen bonding to promote the formation of a porous gel structure. CNTs-CuO composites, featuring in-situ generated CuO nanoparticles on carbon nanotubes (CNTs), were synthesized using a microwave hydrothermal method and employed to enhance the thermal conductivity of the phase change hydrogel.This study demonstrates that the three-dimensional porous network structure of the hydrogel not only provides effective encapsulation protection for CCH and maintains high latent heat (144.9 J/g), but also imparts excellent flexibility and stability to the composites. The incorporation of CNTs-CuO composites introduces efficient heat transfer channels, significantly increasing the thermal conductivity of the hydrogels by approximately 37 % (0.687 W·m−1·K−1). Moreover, the hydrogel composites exhibit exceptional temperature regulation properties.The innovative design and preparation of these hydrated salt-based flexible hydrogel composites offer a novel approach in the fields of thermal management and energy storage. This material demonstrates practical applications not only in HNB devices but also in various thermal management systems, such as wearable electronics, battery thermal management, and electronic device cooling. Furthermore, its application in energy storage systems, including thermal energy storage units and smart textiles, underscores its broad applicability and significance.

Development and Preliminary Validation of a Central Venous Access Device-Associated Skin Impairment Classification Tool Using Modified Delphi and Clinimetric Methods.

An evidence and consensus-based instrument is needed to classify central venous access device-associated skin impairments. The aim of this study was to design and evaluate the central venous access device-associated skin impairment classification tool. A two-phase modified Delphi study. This two-phase study consisted of a literature review, followed by the development and validation of a classification instrument, by experts in the fields of central venous access devices and wound management (Phase 1). The instrument was tested (Phase 2) using 38 clinical photographs of a range of relevant skin impairments by the same expert panel. The expert panel consisted of registered nurses who were clinical researchers (n = 4) and clinical experts (n = 3) with an average of 24 years of nursing and research experience and 11 years of experience in wound management. Measures to assess preliminary content validity and inter-rater reliability were used. The instrument consists of five overarching aetiological classifications, including contact dermatitis, mechanical injury, infection, pressure injury and complex clinical presentation, with 14 associated subcategory diagnoses (e.g., allergic dermatitis, skin tear and local infection), with definitions and signs and symptoms. High agreement was achieved for preliminary scale content validity and item content validity (I-CVI = 1). Inter-rater reliability of aetiologies was high. The overall inter-rater reliability of individual definitions and signs and symptoms had excellent agreement. The development and preliminary validation of this classification tool provide a common language to guide the classification and assessment of central venous access device-associated skin impairment. The comprehensive and validated classification tool will promote accurate identification of central venous access device-associated skin impairment by establishing a common language for healthcare providers. The availability of this tool can reduce clinical uncertainty, instances of misdiagnosis and the potential for mismanagement. Consequently, it will play a pivotal role in guiding clinical decision-making, ultimately enhancing the quality of treatment and improving patient outcomes. The Guidance on Conducting and Reporting Delphi Studies (CREDES) was adhered to. No patient or public contribution.

Can ecological zoning act as an environmental management tool for protecting regional habitat quality: Causal evidence from the national key ecological function zone in China

Habitat degradation is one of the most serious environmental problems worldwide, which threatens human wellbeing and sustainable development. Exploring how to protect natural habitats has become a research hotspot in the environmental management field. Ecological zoning has been widely used in habitat protection, but its actual effectiveness has been rarely revealed, especially with the robust and reliable causal inference method. Therefore, taking the Yangtze River Economic Belt (YREB) in China as the study area, we first quantified habitat quality and changes at the district/county scale during 2005–2019. Then, we used the National Key Ecological Function Zone (NKEFZ) as a representative ecological zone scheme, and explored the effectiveness of the NKEFZ in protecting habitat quality with the Propensity Score Matching and Difference-in-Difference combined method, which is a representative causal inference method. We found that habitat quality showed an uneven distribution during the study period, and habitat quality of districts/counties within the NKEFZ was higher than that outside the NKEFZ with statistical significance. Most districts/counties experienced a habitat quality decrease, but the decrease within the NKEFZ is less than that outside the NKEFZ. We observed that the NKEFZ can protect habitat quality from the causal relationship perspective, but there was the spatio-temporal heterogeneity of the NKEFZ effectiveness. In terms of the spatial dimension, the NKEFZ was the most effective in the Lower Reach of the YREB. In terms of the temporal dimension, there was a 1-year time-lag effect of the NKEFZ effectiveness, and NKEFZ effectiveness experienced a sharp increase from 2016. The NKEFZ contributed to protecting habitat quality through multiple management strategies such as urban land quota, high pollution industry prohibition, and ecological compensation. Overall, this study verified that the ecological zone scheme can contribute to habitat quality protection, and emphasizes that the effectiveness of ecological zoning may vary across time and space. This work can support ecological zoning implementation with robust evidence, and provides a novel perspective for understanding the effectiveness of ecological zoning.