Search Results (7,373)

Sustainable agriculture in semi-arid regions like the Awash Basin is critically dependent on water availability, which is increasingly threatened by rapid land use and land cover (LULC) change. This study assesses the impact of multi-decadal LULC changes on water resources essential for agriculture. Using satellite-derived LULC scenarios (2001, 2010, 2020) to drive the WRF-Hydro/Noah-MP modeling framework, we provide a holistic assessment of water dynamics in Ethiopia’s Awash Basin. The model was calibrated and validated with observed streamflow (R² = 0.80–0.89). Markov analysis revealed rapid cropland expansion and urbanization (2001–2010), followed by notable woodland recovery (2010–2020) linked to national initiatives. Simulations show that early-period changes increased surface runoff, potentially enhancing reservoir storage for large-scale irrigation. In contrast, later changes promoted subsurface flow, indicating a shift towards enhanced groundwater recharge, which is critical for small-scale and well-based irrigation. Evapotranspiration (ET) trends, validated against GLEAM (monthly R² = 0.88–0.96), reflected these shifts, with urbanization suppressing water fluxes and woodland recovery fostering their resurgence. This research demonstrates that land use trajectories directly alter the partitioning of agricultural water sources. The findings provide critical evidence for designing sustainable land and water management strategies that balance crop production with forest conservation to secure irrigation water and support initiatives like Ethiopia’s Green Legacy Initiative. Full article

This article reviews the state of the art, implementation barriers, and emerging trends in industrial digitalization, drawing on studies published between 2020 and July 2025. It analyzes how classical Industry 4.0 technologies, simulation and modeling, and Industry 5.0 priorities are transforming production processes in smart factories, yielding higher productivity, reduced downtime, and improved quality. At the same time, the literature documents persistent obstacles, including system integration and interoperability, security and data-privacy risk, and financial constraints, especially for SMEs. Looking ahead, future directions point to a gradual shift towards sustainable intelligent manufacturing with human–robot collaboration and data-centric operations. In addition, the article proposes and validates a conceptual framework for the digitalization of manufacturing companies and provides practical recommendations for stakeholders seeking to leverage digital technologies for operational excellence and sustainable value creation. Full article

The rapid evolution of platform technologies is transforming industries, interoperability, and innovation. Despite numerous studies on individual technologies, no prior review unifies AI, IoT, blockchain, and 5G with cross-sector standards, governance, and technical enablers to provide a comprehensive view of platform convergence. This narrative review synthesizes conceptual and technical literature from 2015–2025, focusing on how converging platform technologies interact across sectors. The review organizes findings by technological enablers, cross-domain integration mechanisms, sector-specific applications, and emergent trends, highlighting systemic synergies and challenges. The study demonstrates that AI, IoT, blockchain, cloud-edge architectures, and advanced communication networks collectively enable interoperable, secure, and adaptive ecosystems. Key enablers include standardized protocols, edge–cloud orchestration, and cross-platform data sharing, while challenges involve cybersecurity, regulatory compliance, and scalability. Sectoral examples span healthcare, finance, manufacturing, smart cities, and autonomous systems. Platform convergence offers transformative potential for sustainable and intelligent systems. Critical research gaps remain in unified architectures, privacy-preserving AI and blockchain mechanisms, and dynamic orchestration of heterogeneous systems. Emerging technologies such as quantum computing and federated learning are poised to further strengthen collaborative ecosystems. This review provides actionable insights for researchers, policymakers, and industry leaders aiming to harness platform convergence for innovation and sustainable development. Full article

A secure and sustainable building access control system plays a vital role in protecting organisational assets worldwide. Physical access management at Auckland University of Technology (AUT) is still primarily done through traditional card-based authentication. The system is susceptible to replay and cloning attacks because the conventional Mifare Classic credentials employ outdated Crypto1 encryption. Such weaknesses provide significant threats in laboratories, engineering testing facilities, and research and technological areas that require strict security procedures. To overcome the above issues, we propose a secure and sustainable university building access control system using mobile app credentials. This research grounded a thorough risk analysis of the university’s current infrastructure, mapping potential operational continuity threats. We analyse card issuance records by identifying high-risk areas such as restricted laboratories and evaluating the resilience of the current Gallagher–Salto system against cloning and replay attacks. We quantify the distribution and usage of cards that are vulnerable. To evaluate the risks to operational continuity, the system architecture is examined. Additionally, a trial implementation of the Gallagher Mobile Connect platform was conducted, utilising cloud registration, multi-factor authentication (PIN or biometrics), and books. Pilot implementation shows that mobile-based credentials improve user experience, align with AUT’s environmental sustainability roadmap, and increase resilience against known attacks. Results have shown that our proposed mobile credentials can improve the system performance up to 80%. Full article

Automated pollen recognition is a foundational tool for diverse scientific domains, including paleoclimatology, biodiversity monitoring, and agricultural science. However, conventional methods create a critical data bottleneck, limiting the temporal and spatial resolution of ecological analysis. Existing deep learning models often fail to achieve the requisite localization accuracy for microscopic pollen grains, which are characterized by their minute size, indistinct edges, and complex backgrounds. To overcome this, we introduce HieraEdgeNet, a novel object detection framework. The core principle of our architecture is to explicitly extract and hierarchically fuse multi-scale edge information with deep semantic features. This synergistic approach, combined with a computationally efficient large-kernel operator for fine-grained feature refinement, significantly enhances the model’s ability to perceive and precisely delineate object boundaries. On a large-scale dataset comprising 44,471 annotated microscopic images containing 342,706 pollen grains from 120 classes, HieraEdgeNet achieves a mean Average Precision of 0.9501 (mAP@0.5) and 0.8444 (mAP@0.5:0.95), substantially outperforming state-of-the-art models such as YOLOv12n and the Transformer-based RT-DETR family in terms of the accuracy–efficiency trade-off. This work provides a powerful computational tool for generating the high-throughput, high-fidelity data essential for modern ecological research, including tracking phenological shifts, assessing plant biodiversity, and reconstructing paleoenvironments. At the same time, we acknowledge that the current two-dimensional design cannot directly exploit volumetric Z-stack microscopy and that strong domain shifts between training data and real-world deployments may still degrade performance, which we identify as key directions for future work. By also enabling applications in precision agriculture, HieraEdgeNet contributes broadly to advancing ecosystem monitoring and sustainable food security. Full article

Teaching is among the most fulfilling yet psychologically demanding professions. Expanding administrative responsibilities, technological adaptation, and increasingly diverse student needs have intensified workloads and contributed to widespread burnout and attrition. For arts educators, these pressures are compounded by the challenge of sustaining multiple professional identities as an educator, researcher, and artist (ERA) within institutional systems. Grounded in Structural Symbolic Interactionism and Social Identity Theory, this autoethnographic inquiry examines how integrating these identities within a portfolio career can enhance professional efficacy and personal well-being. Using reflective narrative analysis framed through the perspective of the educator–researcher–artist, this study emphasizes identity security as central to sustaining creativity, engagement, and career longevity. Findings suggest that balanced engagement across artistic, pedagogical, and scholarly domains mitigates identity fragmentation and reduces the risk of vocational burnout. The article concludes with a call for institutional frameworks that legitimize creative and research activity as integral to educational practice. Supporting such multidimensional engagement enables educators to maintain authenticity, motivation, and resilience in contemporary learning environments. Full article

Introduction: Advancements in diabetes technology have transformed diabetes management, yet technology implementation remains inconsistent due to barriers at both the clinician and patient levels. Team-based collaborative care offers a promising strategy to bridge these gaps. Framework: The Practical, Robust Implementation and Sustainability Model (PRISM), which incorporates the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework, was applied to identify clinician and patient-level barriers to technology implementation and guide development of team-based strategies for improvement. Application of this framework is illustrated through a rural primary care clinic implementing a remote patient monitoring program. Results: Analysis across RE-AIM domains identified team-based, interprofessional strategies for enhancing technology implementation and sustainability. Recommended strategies include structured onboarding and digital literacy support for both patients and clinicians, clear delineation of team roles and intentional integration of workflows, continuous quality improvement through feedback and huddles, and sustained organizational and policy support that ensures security, reimbursement, and equitable access. Conclusions: Application of the PRISM framework to improve diabetes technology implementation allows for translation of technological innovation into meaningful outcomes. Full article

Coconut (Cocos nucifera L.) plays a vital economic and cultural role in many tropical and subtropical regions. A comprehensive review of the existing literature underscores that advanced biotechnologies are pivotal in unlocking the full potential of coconut germplasm exchange, which is crucial for the future sustainability of this crop. While traditional exchange methods are hampered by phytosanitary risks and logistical burdens, biotechnological interventions such as in vitro conservation and cryopreservation present targeted solutions to overcome these bottlenecks. The exchange, facilitated by these technologies, allows for the efficient introduction of desirable traits. We indicate that diversification and germplasm exchange hold the key to improving coconut quality and yield, developing varieties resistant to pests and diseases, and ensuring long-term conservation of coconut genetic diversity. This review highlights the potential to overcome the challenges faced by regional breeding programs often hindered by restricted genetic resources. Furthermore, by examining past successes and challenges in coconut germplasm identification and exchange, we offer perspectives on optimizing strategies to conserve diversity. This work emphasizes that germplasm exchange paves the way for coconut varieties that can thrive under changing environmental conditions, securing the future of this highly valuable crop. Full article

Potato (Solanum tuberosum L.) is the third most important food crop worldwide and a cornerstone of food security across the Andean region. However, its production is increasingly threatened by the potato psyllid Bactericera cockerelli (Šulc), the vector of Candidatus Liberibacter solanacearum, the causal agent of the purple-top complex associated with zebra chip disease, which severely reduces both tuber yield and quality. This study was conducted from September 2024 to February 2025 in the province of Huancabamba, Peru, to evaluate the efficacy of biological and chemical control agents against B. cockerelli under field conditions. A randomized complete block design was implemented with five treatments and four replicates, totaling 20 experimental units, each consisting of 20 potato plants (S. tuberosum L.), of which 10 plants were evaluated. Treatments included an untreated control (T0), a chemical control (thiamethoxam + lambda-cyhalothrin, abamectin, and imidacloprid) (T1), and three biological control agents: Beauveria bassiana CCB LE-265 (>1.5 × 10¹⁰ conidia g⁻¹) (T2), Paecilomyces lilacinus strain 251 (1.0 × 10¹⁰ conidia g⁻¹) (T3), and Metarhizium anisopliae (1.0 × 10¹⁰ conidia g⁻¹) (T4). Foliar applications targeted eggs, nymphs, and adults of the psyllid. Results indicated that B. cockerelli mortality across developmental stages was lower under biological treatments compared with T1, which achieved the lowest probability of purple-top symptom expression (46%) and a zebra chip incidence of 60.60%. Among the biological agents, M. anisopliae (T4) reduced incidence to 56.60%, while P. lilacinus (T3) demonstrated consistent suppression of nymphal populations. In terms of yield, T1 achieved the highest tuber weight (198.86 g plant⁻¹) and number of tubers (7.74 plant⁻¹), followed by T3 (5.08) and T4 (4.24). Nevertheless, all treatments exhibited low yields and small tuber sizes, likely due to unfavorable environmental conditions and the presence of the invasive pest. Overall, chemical control was more effective than biological agents; however, the latter showed considerable potential for integration into sustainable pest management programs. Importantly, vector suppression alone does not guarantee the absence of purple-top complex symptoms or zebra chip disease in potato tubers. Full article

Climate change and increased human activity are causing the Doñana wetlands, an important ecological reserve in southern Europe, to lose water more quickly. This research presents the Water Inference Moisture Index (WIMI), a spectral index designed to evaluate surface water dynamics utilizing Sentinel-2 L2A imagery from 2016 to 2024. The index, carried out using a machine learning approach, uses near-infrared (B08) and red (B04) bands to find wetland water with a high level of sensitivity, even when there is a lot of vegetation. We looked at how water availability changed over time and space by combining WIMI with long-term records of precipitation and climate data. The results show that surface water is slowly disappearing across the study area, even in years with normal rainfall. This suggests that the water retention capacity is changing and the stress on groundwater is rising. The annual WIMI values were somewhat related to rainfall, but they have been becoming less and less related in recent years. Comparing this to the IPCC Sixth Assessment Report shows that the local effects of climate change are part of a larger trend toward aridification. The study shows that WIMI is a useful, low-cost, and scalable tool for monitoring wetlands and helping with climate adaptation and conservation efforts. The results call for immediate policy actions to protect groundwater resources and support the Sustainable Development Goals for climate action and water security. Full article

Common bean (Phaseolus vulgaris L.) is a cornerstone of global food security, yet its production is persistently challenged by biotic and abiotic stresses. This study conducted a bibliometric analysis following PRISMA guidelines on 549 documents published between 1971 and mid-2025, using Biblioshiny, VOSviewer, and CiteSpace. Results reveal a scientific output concentrated in leading institutions such as Michigan State University (MSU, USA) and the International Center for Tropical Agriculture (CIAT, Colombia). Collaboration networks are dominated by influential authors including Beebe, S. and Kelly, J.D., with Euphytica and Crop Science emerging as primary publication outlets. Research trends highlight salinity tolerance, oxidative stress, and chromosomal mapping, where advanced technologies such as SNP chips have supplanted RAPD markers. Critical challenges remain, including limited phenotyping capacity and the complexity of polygenic resistance, with urgent implications for developing countries where beans are vital for food security but face barriers to technology adoption and restricted participation in global research networks. Concurrently, mitigation strategies have shifted toward sustainable approaches, incorporating beneficial microorganisms for biotic stress and bio-stimulants or plant extracts for abiotic stress. Since 2020, the field has increasingly embraced multifunctional strategies leveraging natural mechanisms to enhance crop resilience. This analysis offers a comprehensive knowledge base to guide future research agendas. Full article

This paper examines the Harirud (Harirod, Tejen) River Basin, a vital transboundary water source shared by Afghanistan, Iran, and Turkmenistan. The basin supports farming, energy production, and home supply in a dry area. Despite its ecological, socio-economic, and geopolitical importance, the basin lacks a cooperative governance framework, leaving it vulnerable to unilateral development, institutional weakness, and climate stress. Addressing an important research gap, this study investigates how unilateral water infrastructure and climate change jointly reshape water security and governance between Afghanistan and Iran. A qualitative case study approach integrates insights from hydropolitics, benefit sharing, and environmental security to analyse ecological and political dynamics. Findings show that climate change has disrupted hydrological regimes—average temperatures have increased by about 1.7 °C and rainfall has declined by roughly 150 mm since 1980. Unilateral dam constructions have altered seasonal flows and intensified hydro-political tensions. The study concludes that implementing Integrated Water Resources Management (IWRM), joint hydrological monitoring, climate adaptation, and equitable benefit-sharing can transform the Harirud from a contested river into a foundation for regional stability and sustainable development. Full article

Grain crops are regarded as fundamental to China’s agricultural production and food security. Effective control of nocturnal phototactic pests is essential for ensuring crop yields and achieving sustainable agricultural development. However, traditional solar insecticidal lamps often suffer from low energy utilization efficiency, dynamic switching control schemes, and poor adaptability in multi-pest coexistence scenarios. A multi-period intelligent switching control optimization scheme based on integrating a multi-pest phototactic rhythm is proposed, focusing on Cnaphalocrocis medinalis and Chilo suppressalis in rice fields. By considering the phototactic behavioral rhythm, energy consumption patterns, and residual energy levels, the proposed scheme dynamically optimizes the switching cycles of solar insecticidal lamps to maximize pest control effectiveness and energy efficiency. The rhythm modeling approach and dynamic adjustment mechanisms are employed to accurately align insecticidal working hours with varying pest activity patterns, thereby improving the pest control effectiveness of IoT-based solar insecticidal lamps. Simulation experiments demonstrate that, compared to traditional switching control schemes, the dynamic switching control scheme improves the average insecticidal rate by 17.7%, increases the effective insecticidal energy efficiency value by approximately 66.1%, and enhances the energy utilization rate by about 38.5%. The proposed dynamic switching control and intelligent energy management scheme not only improves the precision of pest control and energy utilization but also promotes the more efficient application of networked solar insecticidal lamps in smart agriculture. This work provides theoretical support and practical reference for intelligent pest control in complex agricultural environments, promoting the precision and sustainability of pest management practices. Full article

High-yielding lactating cows generate considerable internal heat, making thermoregulation challenging in warm conditions. Traditionally, sprinkler systems have cooled dairy cows by spraying water droplets onto their skin to aid heat dissipation, especially when used with fans. This study explores the benefits of AI-assisted monitoring of water usage for cooling dairy cows, aiming to optimize water consumption and enhance sustainability. An object detection model, trained with 200 random images from a fisheye security camera installed above pens of dairy cows in a dairy farm, was used to detect the presence or absence of cows in headgate sections to guide water sprinkler activity. According to the object detection model, the implementation of AI-assisted detection of cows’ presence or absence in headgates with an accuracy of 0.924 has the potential to save up to 75 percent of water annually for cooling cows. Additionally, the model can detect cows’ behavior patterns regarding location in the pens depending on the occurrence of heat stress. The implementation of AI-powered detection systems in dairy farms has been proven to enhance sustainability and significantly reduce expenses by curbing the excessive use of water. Full article