Search Results (266)

The rapid advancement of Artificial Intelligence (AI) technologies has significantly transformed teaching, learning, and research practices within higher education institutions (HEIs). Although a growing body of literature has examined the application of AI in higher education, existing studies remain fragmented, often focusing on isolated tools or outcomes, with limited synthesis of best practices, core functionalities, and implementation challenges across diverse contexts. To address this gap, this systematic review aims to comprehensively examine the best practices, functionalities, and challenges associated with the integration of AI in HEIs. A comprehensive literature search was conducted across major academic databases, including Google Scholar, Scopus, Taylor & Francis, and Web of Science, resulting in the inclusion of 35 peer-reviewed studies published between 2014 and 2024. The findings suggest that effective AI integration is supported by best practices, including promoting student engagement and interaction, providing language support, facilitating collaborative projects, and fostering creativity and idea generation. Key AI functionalities identified include adaptive learning systems that personalize educational experiences, predictive analytics for identifying at-risk students, and automated grading tools that improve assessment efficiency and accuracy. Despite these benefits, significant challenges persist, including limited knowledge and skills, ethical concerns, inadequate infrastructure, insufficient institutional and management support, data privacy risks, inequitable access to technology, and the absence of standardized evaluation metrics. This review provides evidence-based insights to inform educators, institutional leaders, and policymakers on strategies for leveraging AI to enhance teaching, learning, and research in higher education. Full article

The Netherlands is widely recognised as the global leader in water management, with its flood risk management (FRM) infrastructure lauded as being of the best in the world. This status notwithstanding, Dutch FRM primarily maintains established infrastructural practices and experimental applications of NBSs remain less frequent than established structural projects. This paper details and examines the challenges associated with the prevailing ‘business-as-usual’ approach to FRM in The Netherlands, in which traditional ‘grey’ infrastructural techniques are prioritised over innovative ‘green’ nature-based solutions (NBSs). In line with emerging international trends, such as the EU Water Resilience Strategy, NBSs are increasingly advocated as a strategic, complementary layer to enhance the resilience of existing safety frameworks rather than a self-evident replacement for them. Contrary to grey infrastructure, NBSs provide a number of environmental and social co-benefits extending beyond their flood and drought protection utility. The literature on NBSs details the design, effectiveness, and positive socio-economic impact of the operationalisation of such projects for FRM. This notwithstanding, the uptake and practical implementation of NBSs have been slow in The Netherlands. From a legal and policy perspective, this has been attributed to a lack of political will and the corresponding failure to include NBSs in long term FRM planning. Given the long planning horizons associated with FRM (50–100 years), the failure to incorporate NBSs can lead to policy lock-in that blocks future adaptations. Against this backdrop, this paper employs a semi-systematic literature review to clarify the obstacles to implementing NBSs in Dutch FRM and sets a research agenda that charts a course to mainstreaming NBSs in Dutch FRM. Seven core focus areas for future research are identified. The paper concludes by drawing on these identified focus areas to construct a research agenda aimed at systematically addressing each barrier to the practical operationalisation of NBSs in Dutch FRM, emphasising a hybrid green–grey approach which may serve to inspire similar research in other jurisdictions. Full article

Grain yield is one of the most critical indicators for evaluating the performance of wheat breeding. However, the assessment process, from early-stage breeding lines to officially registered varieties that have passed the DUS (Distinctness, Uniformity, and Stability) test, is often time-consuming and labor-intensive. Multispectral remote sensing based on unmanned aerial vehicles (UAVs) has demonstrated significant potential in crop phenotyping and yield estimation due to its high throughput, non-destructive nature, and ability to rapidly collect large-scale, multi-temporal data. In this study, multi-temporal UAV-based multispectral imagery, RGB images, and canopy height data were collected throughout the entire wheat growth stage (2023–2024) in Xuzhou, Jiangsu Province, China, to characterize the dynamic growth patterns of both breeding lines and registered cultivars. Vegetation indices (VIs), texture parameters (Tes), and a time-series crop height model (CHM), including the logistic-derived growth rate (GR) and the projected area (PA), were extracted to construct a comprehensive multi-source feature set. Four machine learning algorithms, namely a random forest (RF), support vector machine regression (SVR), extreme gradient boosting (XGBoost), and partial least squares regression (PLSR), were employed to model and estimate yield. The results demonstrated that spectral, texture, and canopy height features derived from multi-temporal UAV data effectively captured phenotypic differences among wheat types and contributed to yield estimation. Features obtained from later growth stages generally led to higher estimation accuracy. The integration of vegetation indices and texture features outperformed models using single-feature types. Furthermore, the integration of time-series features and feature selection further improved predictive accuracy, with XGBoost incorporating VIs, Tes, GR, and PA yielding the best performance (R² = 0.714, RMSE = 0.516 t/ha, rRMSE = 5.96%). Overall, the proposed multi-source modeling framework offers a practical and efficient solution for yield estimation in early-stage wheat breeding and can support breeders and growers by enabling earlier, more accurate selection and management decisions in real-world production environments. Full article

Construction and demolition (C&D) waste remains a critical challenge in India due to accelerated urbanisation and material-intensive construction practices. This study integrates survey-based assessment with machine learning to identify key causes of C&D waste and recommend targeted minimization strategies. Data were collected from 116 professionals representing junior, middle, and senior management, spanning age groups from 20 to 60+ years, and working across building construction, consultancy, project management, roadworks, bridges, and industrial structures. The majority of respondents (57%) had 6–20 years of experience, ensuring representation from both operational and decision-making roles. The Relative Importance Index (RII) method was applied to rank waste causes and minimization techniques based on industry perceptions. To enhance robustness, Random Forest, Gradient Boosting, and Linear Regression models were tested, with Random Forest performing best (R² = 0.62), providing insights into the relative importance of different strategies. Findings show that human skill and quality control are most critical in reducing waste across concrete, mortar, bricks, steel, and tiles, while proper planning is key for excavated soil and quality sourcing for wood. Recommended strategies include workforce training, strict quality checks, improved planning, and prefabrication. The integration of perception-based analysis with machine learning offers a comprehensive framework for minimising C&D waste, supporting cost reduction and sustainability in construction projects. The major limitation of this study is its reliance on self-reported survey data, which may be influenced by subjectivity and regional bias. Additionally, results may not fully generalize beyond the Indian construction context due to the sample size and sectoral skew. The absence of real-time site data and limited access to integrated waste management systems also restrict predictive accuracy of the machine learning models. Nevertheless, combining industry perception with robust data-driven techniques provides a valuable framework for supporting sustainable construction management. Full article

Optimizing field cropping practices to improve nitrogen use efficiency is imperative to promote intensive and sustainable wheat production. As a cultivation method commonly adopted in arid and semi-arid regions globally, the ridge–furrow mulching system (RFMS) is capable of efficiently harvesting rainfall, reduce evaporation losses, enhancing soil moisture levels in the root zone, and boosting crop productivity. However, the combined effects of varying ridge–furrow ratios (RD), ridge heights (RH), and nitrogen application rates (RN) on nitrogen fertilizer bias productivity (PFPN) under the influence of climatic conditions, soil types, and field management practices remain poorly understood due to a lack of systematic evaluation. This study conducted a meta-analysis of 462 comparative datasets from 98 research projects to reveal the interactive effects of RFMS and nitrogen fertilizer across climatic gradients. The results showed that RH, RD, and RN increased by 23.78%, 22.37%, and 23.07% respectively (p < 0.05), with the most significant enhancement of PFPN being demonstrated by RH. The most significant improvement in PFPN was observed when RD = 1:1, R < 10 cm, and RN > 200 kg∙hm⁻², with PFPN increasing by 27.7%, 29.50%, and 29.32% respectively (p < 0.05). Climatic and soil physico-chemical factors and field management practices are the key factors influencing the RFMS. When average annual evapotranspiration (AE) < 1000, RN > 200 has the best effect on nitrogen utilization efficiency, while under the condition of AE > 1500, RN < 100 is more effective. In terms of mulching strategy, full mulching of ridges and furrows is recommended in areas with severe drought and low temperatures, while mulching only ridges or furrows is more appropriate in areas with relatively mild climate. The present study provides a scientific basis for the optimal design of ridge–furrow mulching configuration and nitrogen application level. This is achieved by considering climatic conditions, soil fertility, and field management in agro-ecosystems in arid and semi-arid areas. Full article

The conversion of livestock manure and peat into value-added fertilizers provides an environmentally sustainable approach to nutrient recycling and waste management. In this study, organic fertilizers were formulated from poultry, pig, and cattle manure mixed with peat and wood ash, with or without inoculation of the phosphate-solubilizing bacterium Priestia megaterium. Their efficiency was evaluated through plant growth and soil microbiological experiments involving conifer seedlings, herbaceous crops, and ornamental plants. Germination and growth trials with Norway spruce (Picea abies) and Scots pine (Pinus sylvestris) revealed clear species-specific responses: spruce seedlings performed best in substrates containing poultry or cattle manure, while pine showed enhanced growth with pig manure combined with bacterial inoculant. In pansies (Viola × wittrockiana), growth responses varied by cultivar; cattle manure enriched with bacteria increased leaf projection area, whereas poultry manure markedly suppressed growth. For cucumbers, basil, barley, radish, and garden beans, yields were lower than with mineral fertilizers, yet bacterial inoculation significantly influenced soil microbial activity by modifying respiration rates and hydrolytic enzyme intensity in plant- and manure-specific ways. The results demonstrate that microbial supplementation can alter soil biological processes and nutrient turnover, though its effects on plant productivity remain inconsistent. Further research is required to assess long-term performance under field conditions, as practical application will depend on achieving stable and reproducible results. Full article

Higher education institutions face growing pressure to demonstrate excellence and strategic alignment in quality assurance, particularly to meet international accreditation standards. This paper presents a case study of a business faculty that undertook a leadership-driven initiative to develop a comprehensive Quality Manual aimed at continuous improvement and accreditation readiness. The project was structured as a multi-phase, collaborative effort involving broad stakeholder engagement, benchmarking of best practices, and alignment with international accreditation frameworks and the European Standards and Guidelines (ESG), as well as relevant national quality assurance requirements. The resulting Quality Manual provides a unified framework for quality assurance (QA) across all key areas—governance, academic programmes, research, student support, partnerships—linking institutional strategy to daily processes. Key outcomes of the case include clarified roles and procedures, integrated feedback loops, and enhanced readiness for accreditation. The development process highlighted the critical role of educational leadership in fostering a quality culture; by engaging faculty, staff, students, and external partners, the leadership built shared ownership of QA goals. The study is guided by two research questions: (1) How can collaborative and distributed leadership support the development of a strategically aligned Quality Manual at the faculty level? (2) How does the process of designing and implementing a Quality Manual contribute to strengthening internal QA and fostering a quality culture? The study discusses challenges and lessons learned in leading such change, emphasising the importance of stakeholder collaboration, strategic alignment, and change management. The findings contribute theoretically by illustrating how faculty-level leadership operationalizes QA frameworks into concrete institutional tools, and practically by offering a structured model for developing a strategic Quality Manual in higher education. Full article

Background: Chilean salmon aquaculture, a sector crucial for global food security, faces persistent challenges from bacterial pathogens, particularly Piscirickettsia salmonis, resulting in substantial antimicrobial use (351.1 tons in 2024). Objective and methods: To address this issue, the “Sustainable Management of Aquaculture Bacterial Diseases” workshop convened 27 experts to develop a roadmap for prudent antimicrobial stewardship, with the goal of informing public policies and industry best practices. Discussions focused on four critical areas. Results: Antimicrobial Resistance Prevention recognized aquaculture’s dual role in antimicrobial resistance development, underscoring its ecological dimension, the need for international collaboration, proactive policy design, and the establishment of comprehensive “One Health” surveillance systems guided by expert committees. Communication and Education identified critical gaps in specialized veterinary aquaculture training and public outreach, advocating for interdisciplinary teams and clear communication strategies, with a projected timeline of a decade for effective implementation. Therapeutic Alternatives acknowledged current limitations of vaccines against P. salmonis but underscored promising Chilean innovations, including the use of plant extracts, gut-microbiota modulation, and passive immunotherapy, as well as the importance of early intervention. Finally, environmental impact discussions revealed data deficiencies in aquatic ecosystems, emphasizing the need for advanced molecular tools, adaptive regulatory frameworks, and harmonized requirements for environmental risk-assessment procedures. Conclusions: The workshop’s findings provide a vital framework for advancing sustainable antimicrobial use within the Chilean salmon industry as a case study. The insights and lessons derived from this sector can significantly contribute to global aquaculture’s transition toward sustainability, providing a solid foundation for developing a comprehensive roadmap and universally applicable recommendations for stakeholders across aquaculture and other animal-farming industries worldwide. This roadmap, with its essential components, is designed to enhance the understanding of AMU in farmed salmon through a One Health approach, incorporating global guidance for all aquaculture stakeholders. Full article

Human skeletal remains are a crucial source for understanding biocultural and evolutionary processes. Yet, their study and management are challenged by social, religious, and political factors, placing them in a ‘grey area’ within cultural heritage. Human skeletal collections often carry colonial legacies, raising ethical concerns and new challenges for research, curation, and public engagement in academic and museum institutions. In this context, digitization offers expanding opportunities for public exhibition and definition of human remains as part of our culture, while ensuring long-term preservation. Virtual approaches serve also as a useful tool to investigate human variability from evolutionary, bioarchaeological, and forensic perspectives. Moreover, digital access fosters interdisciplinary collaboration and research by enabling global scholarly engagement beyond physical limitations. Through the CHANGES project, we have initiated the digitization of the Documented Human Osteological Collections (DHOC) of the University of Bologna—one of Italy’s largest collections—making these resources available via the 3D data repository MorphoSource. This contribution provides updates on newly digitized material and reports on access requests received to date. We conclude by considering the emerging responsibilities of anthropologists in the use of virtual human skeletal collections, promoting best practices for the management of the anthropological digital twins. Full article

Cities are increasingly using electric buses as a viable alternative to diesel buses. This is a crucial undertaking to achieve sustainability in the transport sector. However, integrating them in transport systems in developing countries such as Sri Lanka, which is characterized by environmental and economic challenges, is complex. This work examines the factors that influence the shift from diesel to electric buses with particular attention to the stakeholders, their motivations, and how they seek to achieve their objectives regarding each other, both conflicting and cooperative angles. This study adopts a comprehensive stakeholder-centric methodology to analyze electric bus adoption in the public transit system in Sri Lanka. The research employs a mixed-methods approach that combines qualitative stakeholder analysis with quantitative barrier prioritization, following established project management principles. Based on the case study of Sri Lanka, the research investigates how the electric bus transition can be expedited by leveraging such alliances while considering local challenges like infrastructural deficits, policy gaps, and funding limitations. Lessons learned and best practices from international case studies are considered to provide strategic recommendations to policymakers and other stakeholders to promote the electric bus. By mapping out the interactions between various stakeholders and outlining where key leverage exists, the research provides a roadmap for introducing electric buses. This will be aligned with the sustainability targets and the vision to deliver sustainability goals for the long term. Full article

In agile, adaptive, and hybrid project management, the Weighted Shortest Job First (WSJF) technique is increasingly being used to prioritize the most relevant business opportunities for organizations. However, this decision-making process often involves the evaluation of multiple interconnected factors whose interactions can influence outcomes in unforeseen ways. Traditional decision-making models tend to assume independence between variables for the sake of simplicity and tractability. In real-world contexts, however, variables rarely operate in isolation; their interdependence introduces complexities that challenge the validity, robustness, and practical applicability of conventional decision-making tools. The objective of this research is to address the problem of interdependence among WSJF variables. To achieve this, Fuzzy Cognitive Mapping (FCM) was applied to evaluate the impact and influence of interdependencies during the decision-making process. The findings demonstrate that incorporating FCM into WSJF yields a 76% correlation in prioritization order with the best outcomes, compared to linear WSJF, while revealing a 24% variation that highlights areas for further study. This evidence indicates that accounting for interdependence leads to more efficient and reliable decision-making than traditional approaches. Full article

It is well established that exposure to heat-stress conditions significantly impacts the physiology, health, welfare, and productivity of both sheep and cattle. The aim of this study was to apply the Temperature Humidity Index (THI) in order to assess the impact of future climate conditions on the thermal stress exposure of sheep and cattle in Greece. The Weather Research and Forecasting (WRF) model was used as a high-resolution regional climate model to simulate climate conditions for two decades in Greece at a 10 Km spatial resolution and a 1 h temporal resolution. The WRF model was applied to two emission scenarios, namely SSP2-4.5 (intermediate) and SSP5-8.5 (worst-case). Projections were made for the near-future decade (2046–2055), with the decade (2005–2014) serving as the reference period for comparative analysis. The data analysis indicated that under the SSP2-4.5 emission scenario, the mean temperature is projected to increase by 1.2–1.4 °C and 1.4–1.6 °C across 38% and 58% of the country’s territory, respectively. Increases higher than 1.6 °C are projected across 32% of the Greek territory under the SSP5-8.5 emission scenario. The mean THI (sheep) and mean THI (adj) (cattle) are projected to increase by 5–10% and by 4% across 74% and 82% of the Greek territory, respectively, when considering the SSP2-4.5 emission scenario. Slightly more severe mean heat-stress conditions were projected when considering the SSP5-8.5 emission scenario. The analysis of the hourly THI values showed that sheep and cattle are expected to experience heat-stress conditions during extended periods in the future, in which hot weather will prevail. Specifically, the number of severe/danger heat-stress hours is projected to double in the greater part of the country. To mitigate the adverse effects of climate-change-induced thermal stress on animal productivity, health, and welfare, the implementation of adaptation measures and best management practices is strongly recommended for sheep and cattle farmers. These measures encompass improvements in breeding strategies, livestock housing and microclimate management, nutritional interventions, and the adoption of precision livestock farming technologies. Given the outstanding economic, social, and environmental importance of sheep and cattle farming in Greece, effective adaptation to and mitigation of climate change impacts represent urgent priorities to ensure the long-term sustainability and resilience of the livestock sector. Full article

The transition to a circular economy requires effective food waste (FW) collection and recycling systems. This study aims to evaluate general public attitudes, behaviours, and systemic challenges related to FW sorting in Latvia, in light of the recent mandate for separate biowaste collection. The study covers two important sections—assessment of the amount of FW generated in primary production sectors, and a pilot case study of biodegradable waste sorting in selected households in Latvia. A mixed-methods approach was used, combining a nationwide survey of 458 entities involved in primary food production and 115 households, followed by 99 households with backyards voluntarily participating in a pilot case study to evaluate their BW management practices. The research findings reveal that there is a need to establish a precise/specific framework for the evaluation of FW for each sector; the development of appropriate coefficients would facilitate the process of estimating waste generated by primary production in the future. Research findings revealed that inhabitants are interested in home composting; however, the implementation of home composting requires active support from project implementers, including increasing environmental awareness and providing financial incentives. These results offer practical insights for municipalities and national stakeholders aiming to increase biowaste collection rates and support country-level broader sustainability goals. The research results have practical application with the possibility to replicate the best practices and recommendations to other countries or regions within the EU and beyond. Full article

In recent years, the construction sector has experienced a significant technological transition, driven by the introduction of innovative digital tools and the evolution of the legislative environment. This article presents a Systematic Scoping Review conducted in accordance with the PRISMA-ScR guidelines, aiming to examine the role of Public Administration (PA) regarding the adoption of innovative technologies, such as Building Information Modelling (BIM) and Digital Twin (DT), to improve the management of construction and public procurement processes. The review analyses the state of the art in the implementation of digitalised procedures for project management in the construction phase, according to PA organisational purposes and national and international standard requirements. The data obtained was used to structure the analysis in order to provide a useful framework for understanding the level of convergence between the academic world and public administration in the use of digital technologies and their combined applications. The review results are organised in a thematic matrix classifying contributions according to key topics, building process phases, and operational aims. This approach highlights adopted strategies and emerging best practices, aiming to support both PAs and professionals in overcoming digitalisation challenges. A specific focus has been dedicated to the need for continuous training and legislative adaptation, which are essential for integrating digital technologies into building processes. The analysis and verification of the results of the systematic scoping review on the digitalisation process in the construction sector, conducted between academia and the public administration, is supported by a comparison with an Italian case study from the Emilia-Romagna region, which illustrates the specific application of the strategies identified in the digital management of public construction processes. Full article

This paper presents a flexible approach to a multipurpose, heterogeneous archive and data management system model that merges the robustness of legacy grid-based technologies with modern cloud and edge computing paradigms. It leverages innovations driven by big data, IoT, AI, and machine learning to create an adaptive data storage and processing framework. In today’s digital age, where data are the new intangible gold, the “gold rush” lies in managing and storing massive datasets effectively—especially when these data serve governmental or commercial purposes, raising concerns about privacy and data misuse by third-party aggregators. Astronomical data, in particular, require this same thoughtful approach. Scientific discovery increasingly depends on efficient extraction and processing of large datasets. Distributed archival models, unlike centralized warehouses, offer scalability by allowing data to be accessed and processed across locations via cloud services. Incorporating edge computing further enables real-time access with reduced latency. Major astronomical projects must also avoid common single points of failure (SPOFs), often resulting from suboptimal technological choices driven by collaboration politics or In-Kind Contributions (IKCs). These missteps can hinder innovation and long-term project success. The principal goal of this work is to outline best practices in archival and data management projects—from policy development and task planning to use-case definition and implementation. Only after these steps can a coherent selection of hardware, software, or virtual environments be made. The proposed model—CTAARCHS (Cloud-based Technologies for Astronomical Archiving Research Contents and Handling Systems)—is an open-source, multidisciplinary platform supporting big data needs in astronomy. It promotes broad institutional collaboration, offering code repositories and sample data for immediate use. Full article