Search Results (15,350)

This review, “The Development of a River Quality Prediction Model That Is Based on the Water Quality Index using Machine Learning: A Review”, discusses and evaluates research articles and attempts to incorporate ML algorithms into the water quality index (WQI) to improve the prediction of river water quality. This original study confirms how new methodologies like LSTM, CNNs, and random forest perform better than previous methods, as they offer real-time predictions, operational cost saving, and opportunities for handling big data. This review finds that, in addition to good case studies and real-life applications, there is a need to expand in the following areas: impacts of climate change, ways of enhancing data representation, and concerns to do with ethics as well as data privacy. Furthermore, this review outlines issues, such as data scarcity, model explainability, and computational overhead in real-world ML applications, as well as strategies to preemptively address these issues in order to improve the versatility of data-driven models in various domains. Moving to the analysis of the review specifically to discuss the propositions, the identified key points focus on the use of complex approaches and interdisciplinarity and the involvement of stakeholders. Due to the added specificity and depth in a number of comparisons and specific technical and policy discussions, this sweeping review offers a broad view of how to proceed in enhancing the usefulness of the predictive technologies that will be central to environmental forecasting. Full article

In the current context of transformation within the Architecture, Engineering, and Construction (AEC) sector, and the growing adoption of interdisciplinary collaboration processes such as Integrated Project Delivery (IPD) and Building Information Modeling (BIM), information management systems are crucial to ensure both the security and reliability of data, and its effective distribution among project stakeholders. Collaborative centralized information systems have emerged as powerful tools for communication and data exchange. However, establishing efficient and flexible methodologies for managing this information remains a significant challenge. This study aims to demonstrate the effectiveness of collaborative centralized information systems in project information management through a real-world example. The research focuses on analyzing a pilot project developed by our organization using the Bimcollab digital collaborative platform. The methodology adopted includes the following: (i) descriptive characterization of the project; (ii) selection of a defined timeframe; (iii) description and characterization of the information management systems; and (iv) comparative analysis between non-centralized and centralized information management systems. The case study examines the Detail Design phase of a project for a pharmaceutical industry complex comprising six buildings, with a total area of approximately 18,000 m². From October to December 2022, a non-centralized information system was used, followed by the implementation of a centralized information system from January to March 2023. Key indicators, such as the number of occurrences, average number of recipients involved, response times, and resolution rates, were analyzed. The results showed that the complete resolution rate improved from 51% under the non-centralized system to 85% with the centralized system, representing a 34% increase. The pilot project underscores the benefits of centralized collaborative information systems, particularly in reducing response times and increasing resolution rates among stakeholders. These benefits are expected to apply across various functional programs, including residential construction, contributing to optimizing both project design and construction practices. While derived from a single case study, the findings highlight the need for further research involving multiple cases and phases of the project lifecycle to validate the generalizability of these outcomes. Full article

This study explored the role of airports in the aviation sector from both energy and sustainability perspectives, highlighting their potential contribution to reducing the sector’s carbon emissions. The methodology involved a literature review and a questionnaire distributed to both airports and aviation organizations. The results from these approaches indicated varying focuses on tackling the subject. The literature review results indicated a clear preference in the papers for SAF solutions over the development of more environmentally friendly airports. Adoption of 100% SAF in aircraft is still in its early stages of development and can be considered a long-term goal because it requires heavy engineering intervention and alteration of aircraft engines. The transition of airports’ infrastructures, on the other hand, can be visualized as a feasible and attainable goal and hence should be considered a short-term goal to attain. Many airports, including respondents to the questionnaire, have already worked on their infrastructure; however, they also expressed concerns about the lack of enabling policies and incentives. Other action steps, such as close collaborations among stakeholders, enhancing research and development, and government support, were also seen as significant for establishing greener airports. The literature results indicate a major research gap in a significant integral part of the aviation sector (i.e., greener airports). It is therefore important that member states collaborate and work closely with key organizations such as ICAO, IATA, and the UN through the latter’s Sustainable Development Goals (SDGs) to breach this research gap and establish more sustainable airports in the near future. Full article

Drylands cover a vast area, and biodiversity conservation in these regions represents a major challenge. A bibliometric study of published research highlighted several key aspects, including publication types, research fields, years of publication, contributing countries, institutions, languages, journals, publishers, authors, and frequently used keywords. The analysis also included plants related to biodiversity conservation in arid areas, animals related to biodiversity conservation in arid areas, and causes of biodiversity decline in arid regions, effects of biodiversity loss in these regions, and restoration methods aimed at improving biodiversity conservation in arid areas. A total of 947 publications were identified, starting from 1994, authored by researchers from 99 countries, primarily from Australia, the USA, China, Spain, and South Africa, and published in 345 journals, with the most prominent being Journal of Arid Environments, Biodiversity and Conservation, and Biological Conservation. The most commonly appearing keywords included biodiversity, conservation, diversity, vegetation, and patterns, with recent years showing an increased use of terms related to the causes and effects of aridification: climate change, land use, and ecosystem services. The causes of biodiversity loss in drylands are primarily linked to human activities and climatic changes, while the effects impact the entire ecosystem. Methods to improve biodiversity include traditional agroforestry systems, tree plantations and other plant species, grazing management, and other approaches. Combined actions among stakeholders and ecologically appropriate nature-based solutions are also recommended. Improvements in conservation biodiversity in arid areas are very important also for achieving the sustainability goals in these areas. However, numerous aspects of this topic remain to be studied in greater detail. Full article

Sexual exploitation is a pervasive issue affecting individuals globally, characterized by the abuse of vulnerability, power, or trust for sexual purposes. This study aims to explore the perceptions of professionals and stakeholders in Portugal regarding the prevention, assistance, and protection of victims of sexual exploitation. Employing a qualitative research approach, four online focus groups were conducted with 20 participants from various professional backgrounds. The results highlight a comprehensive understanding of sexual exploitation among participants, who emphasized the coercion and exploitation of vulnerabilities as central elements. Significant barriers to addressing sexual exploitation were reported, including underreporting, societal indifference, and the impact of new technologies. Participants called for enhanced training for professionals across sectors, increased societal awareness, and stronger legal and policy frameworks. The study concludes with recommendations for elevating sexual exploitation as a governmental priority, improving professional training, and fostering international cooperation to combat this complex issue effectively. Full article

Creating Shared Value (CSV), a contemporary management strategy aimed at generating both economic and social value, has gained increasing attention in the context of sustainable regional development. This study examines the implementation of CSV within local industrial clusters, specifically investigating the influence of institutional and geographic proximity on the sustainability of small and medium-sized enterprises (SMEs). Utilizing surveys conducted across 11 industrial clusters in Japan and employing structural equation modeling, the impact of proximity on CSV initiatives was explored. The findings reveal that firms within these clusters enhance their sustainability by fostering iterative knowledge transfer and technological collaboration, particularly with geographically and institutionally proximate organizations. Moreover, the study highlights that a clear understanding and alignment of sustainability-oriented goals within institutional proximity strengthen the synergy of management resources through alliance capabilities, ultimately leading to the simultaneous creation of social and economic value. This research underscores the critical role of proximity in shaping effective and sustainable CSV initiatives within local industrial clusters, providing valuable insights for policymakers, industry stakeholders, and researchers aiming to promote regional sustainability and resilience. Full article

Regulators in Spain transformed the savings bank by dividing each of them into a bank and a foundation. The bank continues lending activity, and the foundation focuses on social work. The aim of this paper is to explore how the governance structures and their dynamics in banking foundations relate to their social work. For this purpose, we use the relevant theoretical framework in the field of governance, focusing on agency, stewardship, and stakeholder theories. To achieve this aim, we perform semi-structured interviews with members of governance bodies, in the framework of a qualitative approach. We find that studied characteristics of governance relate to social work in different ways. Diversity in the governance bodies, through a balance between economic and social logic, and through representation of stakeholders, among other elements, relates positively to the level of social work. Additionally, it shapes the mix of social activity types. We conclude that the chosen theoretical framework helps us understand the phenomenon and interpret the results. The research question is answered but, at the same time, the empirical research reveals the complexity of the relationships and indicates future lines of research. Full article

Background/Objectives: Surveillance of antimicrobial resistance (AMR) and antimicrobial use (AMU) is needed to understand risks and implement policies. Collecting AMU data in the context of disease prevalence and therapeutic outcomes has been suggested for improving AMU. We describe the process of developing an information and communication technology (ICT) system to monitor AMU, diseases and treatment outcomes in poultry in East Africa. Methods: A prototype system to register drug sales in veterinary pharmacies, a mobile application for farmers to report their AMU, and a database for monitoring was developed. Contact information for participating veterinarians was included as well as information about poultry diseases, husbandry, AMR and prudent use of antibiotics. The system was pilot-tested for a 6-month period in Kenya. Results: A total of 15,725 records were submitted by the 14 participating pharmacies and 91 records were entered by the 15 participating farmers. Overall, the participants were positive about the system and were able to use it. The information available was appreciated by the farmers. The pharmacy representatives appreciated getting an overview of their sales and stated that it had given them new insights. Conclusions: Despite some challenges, the concept of the developed ICT system could be useful for future monitoring of animal health and the use of pharmaceuticals in animals, and connecting farmers with veterinarians to improve animal health management. Our results underline the importance of close collaboration with stakeholders so that developed tools can be transferred to national ownership after the finalization of externally funded projects. Full article

This study aims to investigate the impact of the market structure and efficiency on firm performance in the meat and milk processing industry in Poland, Czechia, and Slovakia. Using stochastic frontier analysis and a profitability regression model applied to data from 2015 to 2021, the results indicate no evidence of collusive behavior in the examined markets. Instead, profitability is significantly driven by efficiency, supporting the hypothesis of an efficient market structure. Companies with higher market shares do not exploit their market power to set higher prices and increase profitability. The findings highlight efficiency as a critical determinant of performance in unconcentrated markets, offering valuable insights for stakeholders in the food processing industry and policymakers. Full article

Some 500 million micro, small, and medium-sized enterprises (MSMES) are active across the globe. Data for Europe suggest that MSMEs are responsible for 40–60% of industrial pollution. Resource-Efficient and Cleaner Production (RECP) has been empirically demonstrated to mitigate waste generation, wastewater discharge, and emissions in industrial processes while maintaining cost-effectiveness. RECP has been applied in several thousand enterprises globally. RECP has shown the potential to reduce waste and emissions from industries by up to 30%. Applying RECP to MSMEs has some restrictions: the availability of data, the limited capacities of management, and limited financial resources make RECP application in MSMEs generally more challenging compared to bigger enterprises. This calls for the development of RECP approaches dedicated to MSMEs. This paper describes the systematic development of a delivery approach for MSMEs in Jordan. The results show that by minimizing the time required from management, active involvement of owner/managers, provision of tailored information on applicable options, and involving other stakeholders such as chambers and financial institutions, enterprises can be involved in big numbers with very reasonable efforts, reaching remarkable results. Full article

In recent decades, societies and economies across the globe have started to show signs of stress associated with water shortages. Meeting the sustainability benchmarks in arid and semi-arid regions has caused water reuse to be considered a viable alternate source to augment the existing water supply resources. Water reuse, resource recovery, and recycling are extensions of the concept of a circular economy that has been practiced in other fields. Globally, the U.S. has played a leadership role in the development of guidance and regulations for various water reuse applications. Other countries and organizations have also developed similar programs. This paper aims to propose a review of the existing literature and provide a broader perspective of water reuse focusing on the most pressing issues such as direct potable reuse with the backdrop of viral pathogens and perfluorinated compounds. The global history of statutory developments to regulate the selected contaminants has also been discussed by covering the recent advancement in water reuse applications. Technological developments and regulatory trends are chronicled in the context of emerging contaminants linked with an imminent social, industrial, and agricultural prospectus. The proposed high viral log removal credit for water reuse is a challenging task especially at regular intervals; therefore, the treatment requirements must be verified to ensure public safety. The extreme persistence of PFAS, their tendency for buildup in biotic systems, and their removal is another challenging task which requires development of cost effective and efficient technologies. Disparity in the financial and technological capabilities of regional or internal stakeholders of shared watershed or aquifer is a bottleneck in tangible advancements in this area. The role of public–private partnerships in addressing the impending water sustainability challenges is discussed as a model for future direction in funding, managing, and public acceptance. Full article

Financial distress prediction models have been extensively utilised to assess the financial health of companies. However, their predictive accuracy can be significantly affected by extraordinary economic disruptions, such as the COVID-19 pandemic. Traditional models, particularly those designed for stable economic conditions, necessitate evaluation and potential adaptation to maintain their effectiveness during unprecedented circumstances. This study seeks to evaluate the performance of financial distress prediction models developed by authors from the Visegrad Four (V4) when applied to Slovak automotive companies before, during, and after the COVID-19 pandemic. Initially, the best-performing models from those selected were identified in the pre-pandemic period (2017–2019). The performances of these models were subsequently analysed during the pandemic and post-pandemic periods (2020–2022). Finally, their coefficients were re-estimated to enhance accuracy while preserving the original variables, ensuring the interpretability of any changes. The objective is to identify the models with the highest performance during the pre-pandemic period, assess their reliability under crisis conditions, and suggest improvements through coefficient re-estimation. While the majority of models experienced significant declines in performance during the pandemic, some retained adequate predictive accuracy. The re-estimated coefficients improved the overall accuracy of the models and also enhanced the sensitivity of some, offering stakeholders the option to utilise either the original or adjusted models based on their specific context. To complement the analysis, we also constructed new models for the pandemic and post-pandemic periods, allowing for a more comprehensive evaluation of financial distress prediction under changing economic conditions. This study provides a framework for adapting financial prediction models to unprecedented economic conditions, contributing valuable insights for researchers and practitioners seeking to enhance predictive tools within dynamic economic environments. Full article

The revolution in biotechnology at the end of the 20th century has improved agricultural productivity, reduced environmental impact, and enhanced food nutrition. However, genetically modified food (GMF) consumption remains low, particularly in the European Union, including Spain. This study develops a GMF acceptance model based on the Theory of Planned Behavior, incorporating five key variables alongside gender and age as control factors. Attitude-related variables include perceived benefit (PB) and perceived risk (PR). Perceived control factors involve food neophobia (PHOB) and knowledge (KNOWL) about GMFs. Additionally, subjective norm (SN) is considered. Using a sample of 728 Spanish consumers, the model was validated, explaining 70% of the variance and demonstrating strong predictive capability. The results so PB, KNOWL, and SN positively influence GMF acceptance, whereas PR and PHOB have negative effects. PB and SN emerged as the most influential variables, which are also highlighted as priorities in the importance–performance map analysis (IPMA). Based on these findings, strategies have been proposed to enhance perceived benefits and influence subjective norms, potentially increasing GMF acceptance. This study provides valuable insights into consumer behavior and offers guidance for policymakers and industry stakeholders to promote the adoption of GMFs. Full article

Artificial intelligence (AI) has demonstrated success across various industries; however, its adoption in aviation remains limited due to concerns regarding the interpretability of AI models, which often function as black box systems with opaque decision-making processes. Given the safety-critical nature of aviation, the lack of transparency in AI-generated predictions poses significant challenges for industry stakeholders. This study investigates the classification performance of multiple supervised machine learning models and employs SHapley Additive exPlanations (SHAPs) to provide global model explanations, identifying key features that influence decision boundaries. To address the issue of class imbalance in the Australian Transport Safety Bureau (ATSB) dataset, a Variational Autoencoder (VAE) is also employed for data augmentation. A comparative evaluation of four machine learning algorithms is conducted for a three-class classification task:—Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and a deep neural network (DNN) comprising five hidden layers. The results demonstrate a competitive performance across accuracy, precision, recall, and F1-score metrics, highlighting the effectiveness of explainable AI techniques in enhancing model transparency and fostering trust in AI-driven aviation safety applications. Full article

Project Managers face many difficulties when scheduling the development and production of multiple, largely independent systems required for a new capability, especially when there are multiple stakeholders, uncertainties in the expected development time, and developmental dependencies among the systems. The Systems Developmental Dependency Analysis methodology provides a systemic approach to address these challenges by offering decision support for such a ‘System-of-Systems’. The method, based on a parametric piece-wise linear model of dependencies between elements in the developmental domain, propagates the interactions between systems to estimate delays in the development of individual systems and to evaluate the impact of such delays on the expected schedule of completion for the establishment of the whole desired capability. The schedule can be automatically re-generated based on new system information, changed dependencies, and/or modified risk levels. As demonstrated in this paper using a complex space mission case, the method enhances decision-support by identifying criticalities, computing possible delay absorption strategies, and comparing different development strategies in terms of robustness to delays. Full article