Search Results (21,214)

structural characteristics of hickory trees exhibit a significant correlation with their fruit yield. As a distinctive high-quality nut of Zhejiang Province, hickory is a unique high-end dry fruit and woody oil plant in China. However, the long growth cycle and extended maturation period make their management particularly challenging, especially in the absence of high-precision 3D digital models. This study aims to optimize hickory tree management and identify trees with the most optimal structural features. It employs gradient-boosted machine learning modeling based on 23 key tree characteristics, transforming the experiential knowledge of forest farmers into quantifiable parameters. The consensus model achieved an LOOCV average accuracy of $87\%$, a training set accuracy of $100\%$, and a test set accuracy of $78\%$. Through this approach, three structural parameters that significantly impact the hickory tree were identified: the number of branches, the total length of all branches, and the crown base height from the ground. These parameters were used to select trees with superior structural traits. Furthermore, a novel method based on distance metrics was developed to assess the structural similarity of trees. This research not only highlights the importance of incorporating tree structural characteristics into forest management practices but also demonstrates how modern technological tools can enhance the productivity and economic returns of hickory forests. Through this integration, both the sustainability and economic viability of hickory forests are improved. Full article

Nostoc flagelliforme, a filamentous cyanobacterium inhabiting desert biological soil crusts (BSCs), has developed exceptional strategies to endure extreme environmental stresses, including severe desiccation, intense ultraviolet (UV) radiation, and drastic temperature fluctuations. These organisms must effectively sense and predict environmental changes, particularly the onset of desiccation. This review explores recent advancements in the molecular mechanisms that enable N. flagelliforme to survive under such harsh conditions, with a focus on stress signal sensing, transduction pathways, and photosynthetic adjustments. Key molecular adaptations include the production of extracellular polysaccharide (EPS) sheaths for water retention, the accumulation of compatible solutes like trehalose, and the synthesis of UV-absorbing compounds such as scytonemin and mycosporine-like amino acids (MAAs). Furthermore, N. flagelliforme utilizes a complex signal transduction network, including light-sensing pathways, to regulate responses to rehydration and desiccation cycles. This review emphasizes the integrative nature of N. flagelliforme’s adaptive mechanisms and highlights their potential for biotechnological applications, such as enhancing drought tolerance in crops and advancing ecological restoration in arid regions. Full article

This study analyzes the economic impacts of integrating floating offshore wind farms with a Floating Production, Storage and Offloading (FPSO) unit to reduce carbon dioxide emissions. The idea is to replace the use of natural gas for power supply with an offshore wind farm, considering the effects of carbon pricing. Results show that wind integration reduces emissions by 23% to 76%, depending on the installed capacity. However, higher wind capacity increases total system costs, initial investment, electricity and operational expenses. The Brazilian carbon credit market adversely impacts existing FPSO units as a result of the compulsory carbon trading costs necessary to mitigate their emissions. In contrast, wind-integrated scenarios benefited from carbon pricing, improving financial indicators such as payback period and Return on Investment. Wind shares of 30% and 70% yielded the best financial results for carbon prices between 10 and 50 United States Dollars per ton, with higher penalties further improving viability. These findings elucidate the significance of carbon pricing in mitigating emissions and enhancing the economic feasibility of offshore wind farms within the context of the Brazilian national FPSO decarbonization strategy. Full article

Photovoltaic (PV) energy production in Western countries increases yearly. Its production can be carried out in a highly distributed manner, not being necessary to use large concentrations of solar panels. As a result of this situation, electricity production through PV has spread to homes and open-field plans. Production varies substantially depending on the panels’ location and weather conditions. However, the integration of PV systems presents a challenge for both grid planning and operation. Furthermore, the predictability of rooftop-installed PV systems can play an essential role in home energy management systems (HEMS) for optimising local self-consumption and integrating small PV systems in the low-voltage grid. In this article, we show a novel methodology used to predict the electrical energy production of a 48 kWp PV system located at the Campus Feuchtwangen, part of Hochschule Ansbach. This methodology involves hybrid time series techniques that include state space models supported by artificial intelligence tools to produce predictions. The results show an accuracy of around 3% on nRMSE for the prediction, depending on the different system orientations. Full article

This paper presents an analysis of energy use and sector coupling in a local energy community using a model based on energy cost centres (ECCs), functional units for decentralised responsibility and optimisation of energy use within defined system boundaries. The ECC model enables structured identification and optimisation of energy and material flows in complex industrial and urban settings. It was applied to a case study involving an energy-intensive steel plant and its integration with the surrounding community. The study assessed the potential for renewable electricity production (7914 MWh annually), green hydrogen generation, battery storage, and the reuse of 11,440 MWh of excess heat. These measures could offset 9598 MWh of grid electricity through local production and savings, reduce natural gas use by 4,116,850 Nm³, and lower CO₂ emissions by 10,984 tonnes per year. The model supports strategic planning by linking sectoral actions to measurable sustainability indicators. It is adaptable to data availability and stakeholder engagement, allowing both high-level overviews and detailed analysis of selected ECCs. Limitations include heterogeneous data sources, uneven stakeholder participation, and the need for refinement of sub-models. Nonetheless, the approach offers a replicable framework for integrated energy planning and supports the transition to sustainable, decentralised energy systems. Full article

Nuclear energy is a cornerstone of the global energy mix, delivering reliable, low-carbon power essential for sustainable energy systems. However, the safety of nuclear reactors is critical to maintaining operational reliability and public trust, particularly during accidents like a Loss of Coolant Accident (LOCA) or a Steam Line Break Inside Containment (SLBIC). This study introduces a Bayesian Network (BN) framework used to enhance nuclear energy safety by predicting accident severity and identifying key factors that ensure energy production stability. With the integration of simulation data and physical knowledge, the BN enables dynamic inference and remains robust under missing-data conditions—common in real-time energy monitoring. Its hierarchical structure organizes variables across layers, capturing initial conditions, intermediate dynamics, and system responses vital to energy safety management. Conditional Probability Tables (CPTs), trained via Maximum Likelihood Estimation, ensure accurate modeling of relationships. The model’s resilience to missing data, achieved through marginalization, sustains predictive reliability when critical energy system variables are unavailable. Achieving R² values of 0.98 and 0.96 for the LOCA and SLBIC, respectively, the BN demonstrates high accuracy, directly supporting safer nuclear energy production. Sensitivity analysis using mutual information pinpointed critical variables—such as high-pressure injection flow (WHPI) and pressurizer level (LVPZ)—that influence accident outcomes and energy system resilience. These findings offer actionable insights for the optimization of monitoring and intervention in nuclear power plants. This study positions Bayesian Networks as a robust tool for real-time energy safety assessment, advancing the reliability and sustainability of nuclear energy production. Full article

Recent technological advances in the context of Industry 4.0 (I4.0) profoundly affect machine design and the operator’s role. The machines are not only more complex to operate but must be adapted to non-specialist profiles because of the shortage of skilled labor in the industrial sector. To ensure the sustainability of their activities in a rapidly changing industrial landscape, machine manufacturers need to place greater emphasis on the user experience (UX) of their machines to offer interactions that are more intuitive, efficient, safe, and appealing. However, despite a recognized need for UX practices in I4.0 from the industry and their documented benefits in software development, the Swiss machinery industry (SMI) faces difficulties in implementing such practices. This paper uses quantitative and qualitative research methods based on action research to provide an in-depth analysis of the relationship between the SMI and UX practices. A study of the organizational structure and product development dynamics of three partner companies identified specific barriers to the effective integration and adoption of UX practices. Strategies for overcoming them were then identified and validated through field testing with practitioners of two companies. Finally, the strategies deployed have been reformulated into 28 broader recommendations for action aimed at machine manufacturers. Full article

Rapid urbanization, climate variability, and land degradation are increasingly challenging traditional open-field farming systems. Soilless farming (SLF) has emerged as a complementary approach to enhance horticultural resilience in space-constrained and climate-stressed environments. This review critically evaluates the role of SLF within the broader framework of climate-smart agriculture (C-SA), with a particular focus on its applications in urban and peri-urban settings. Drawing on a systematic review of the existing literature, the study explores how SLF technologies contribute to efficient resource use, localized food production, and environmental sustainability. By decoupling crop cultivation from soil, SLF enables precise control over nutrient delivery and water use in enclosed environments, such as vertical farms, greenhouses, and container-based units. These systems offer notable advantages regarding water conservation, increased yield per unit area, and adaptability to non-arable or degraded land, making them particularly relevant for high-density cities, arid zones, and climate-sensitive regions. SLF systems are categorized into substrate-based (e.g., coco peat and rock wool) and water-based systems (e.g., hydroponics, aquaponics, and aeroponics), each with distinct design requirements, nutrient management strategies, and crop compatibility. Emerging technologies—including artificial intelligence, the Internet of Things, and automation—further enhance SLF system efficiency through real-time data monitoring and precision control. Despite these advancements, challenges remain. High setup costs, energy demands, and the need for technical expertise continue to limit large-scale adoption. While SLF is not a replacement for traditional agriculture, it offers a strategic supplement to bolster localized food systems and address climate-related risks in horticultural production. Urban horticulture is no longer a peripheral activity; it is becoming an integral element of sustainable urban development. SLF should be embedded within broader resilience strategies, tailored to specific socioeconomic and environmental contexts. Full article

Climate change requires efficient water resource management, especially in regions where viticulture is developing. This study evaluates the water requirements, precipitation deficits, and irrigation needs of vineyards in two locations in southern Poland. The analysis covers both a reference period (1931–2020) and a forecast period (2030–2100), based on two climate change scenarios: RCP 4.5 and RCP 8.5. Grapevine water requirements were estimated using a crop coefficient tailored to Poland’s agroclimatic conditions, combined with meteorological data on air temperature and precipitation. Monthly crop coefficient values were calculated as the ratio of grapevine potential evapotranspiration, estimated using the Penman–Monteith method, to reference evapotranspiration, calculated using the Treder approach for the period 1981–2010. Precipitation deficits were assessed for normal, medium dry, and very dry years using the Ostromęcki method. Irrigation water demand was estimated for light, medium, and heavy soils using the Pittenger method. The results indicate a significant increase in both water demand and precipitation deficits in the forecast period, regardless of the scenario. In very dry years, irrigation will be necessary for all soil types. In medium dry years, water deficits will primarily affect vineyards on light soils. These findings underscore the urgent need for improvements in irrigation planning, especially in areas with low soil water. They offer practical insights for estimating future water storage needs and implementing precision irrigation adapted to changing climate conditions. Adopting such adaptive strategies is essential for sustaining vineyard productivity and improving water use efficiency. This study also supports the integration of climate projections into regional planning and calls for investment in innovative, water-saving technologies to strengthen the long-term resilience of Poland’s wine industry. Full article

Carbon capture, utilization and storage (CCUS) represents a vital technological strategy for mitigating greenhouse gas emissions and facilitating sustainable development. Supercritical CO₂ (SC-CO₂) pipeline transportation serves as an essential intermediary step towards attaining the “Dual Carbon Goals” and CCUS, representing the optimal and most cost-effective solution for ultra-long distance transport. In the CO₂ capture process, trace amounts of impurities, such as H₂O, O₂, H₂S, NO_x and SO_x, are inevitable. These gases react to form acidic compounds, thereby accelerating pipeline corrosion. With the progression of CCUS initiatives, corrosion within supercritical CO₂ pipeline transportation has become a critical challenge that significantly affects the safety and integrity of pipeline infrastructure. This review paper provides an in-depth analysis of the corrosion behavior of pipeline materials in a supercritical CO₂ environment, with particular attention to the effects of impurity, temperature, and pressure on corrosion rates, corrosion products, and corrosion morphology. Furthermore, an analysis of the corrosive behavior of welded joints in supercritical CO₂ transport pipelines is performed to provide valuable reference data for research and construction projects related to these pipelines. Full article

A paradigm transition from centralized to decentralized energy systems has occurred, which has increased the deployment of renewable energy sources (RESs) in renewable energy communities (RECs), promoting energy independence, strengthening local resilience, increasing self-sufficiency, and moving toward CO₂ emission reduction. However, the erratic and unpredictable generation of RESs like wind, solar, and other sources make these systems necessary, and a lot of interest in energy storage systems is increasing because they have rapidly become the cornerstone of modern energy infrastructure, and there is a trend towards using more RESs and decentralization, resulting in increased self-sufficiency. Additionally, ESS is increasingly being installed at or close to the point of energy generation and consumption, like within residences, buildings, or community microgrids, instead of at centralized utility-scale facilities, referred to be decentralized. By storing and using energy in the same location, this localized deployment reduces transmission losses, facilitates quicker response to changes in demand, and promotes local autonomy in energy management. Since the production of renewable energy is naturally spread, decentralizing storage is crucial to optimizing efficiency and dependability. This article also focuses on energy storage systems, highlighting the role and scope of ESSs along with the services of ESSs in different parts of the power system network, particularly in renewable energy communities (RECs). The classification of various ESS technologies and their key features, limitations, and applications is discussed following the current technological and significant information trends and discussing the ESS types for the RECs with different options as per the capacity, like small, medium, and large scale. It covers the overall scenario and progress, like overall European ESS installed capacity, and the work relevant to ESSs in RECs with different aspects, following the literature review. Additionally, it draws attention to the gaps and significant challenges related to ESS technologies and their deployment. Key future suggestions have also been given as per the current trends of technological information and significant information that may affect those trends globally in the future and would be helpful in the growth of ESSs integration in RECs. The authors also suggest the role of the government, stakeholders, and supportive policies that can aid in the implementation of ESS technologies in RECs. Full article

Background/Objectives: Gliomas, including the most aggressive subtype—glioblastoma multiforme, are brain tumors with an unfavorable prognosis and high mortality. Early diagnosis is essential to improve treatment efficacy. Positron emission tomography PET with O-(2-[¹⁸F] fluoroethyl)-L-tyrosine ([¹⁸F]FET) has been supported by clinical studies for its role in diagnosis and monitoring the disease. However, the low availability of [¹⁸F]FET in Italy has limited its use in clinical praxis. This study describes the technological transfer of the radiopharmaceutical IASOglio^® (the commercial [¹⁸F]FET developed by Curium Pharma in Italy), with the aim of improving national access to this advanced diagnostic technology. Methods: Three consecutive batches were produced using the automated Trasis AllinOne module, and quality control was performed, including chemical and microbiological tests, to successfully validate the production process. Additionally, the stability of the radiopharmaceutical for its entire shelf life has been demonstrated with stability testing at 14 h after end of synthesis (EOS). Results: The production of [¹⁸F]FET achieved a non-corrected yield between 49% and 52%, with a corrected decay rate ranging from 73% to 79%. The process met the required quality specifications, including bio-burden control and filter integrity. The technological transfer was successfully completed, and production authorization was obtained from the Italian Medicines Agency (AIFA) for the Officina Farmaceutica of Institute of Clinical Physiology of the National Research Council (CNR-IFC) located in Pisa. Conclusions: Local production of [¹⁸F]FET in Italy marks a milestone in glioma diagnosis, thereby contributing to timely treatment and improved clinical outcomes. Full article

Fast-growing technology and the development of IT services give the idea of founding a new application of stochastic processes and their properties. We give a new connection between electronic process management and a stochastic process named the bivariate Pólya–Aeppli counting process. This process is applied as a counting process in the mathematical construction of the given model and it has been introduced as a counting process in electronic process management. In our current study, we assume a company that has two locations in two countries—Bulgaria and Romania. For seamless communication and data sharing, the integrated factories leverage the System Applications and Products in Data Processing (SAP) system. By combining these functions into one structure, we optimize coordination, streamline operations, and improve the company’s productivity and profitability. The automated tools within the system facilitate uninterrupted production and secure supply chains and thus the decision making is improved. A key benefit of these tools is to boost production and procurement activities for success in today’s competitive market which results in cost savings, will increase visibility, and also will improve rapid decision making. Full article

The Australian agriculture sector currently relies on imported fertilizers, which poses risks to price stability and increases the potential for supply chain disruptions. This study aims to investigate the trends and factors affecting fertilizer consumption in Australia, considering the moderating effects of agricultural GDP and agri R&D expenditure. The econometric models, including ARDL bound tests, Granger causality tests, and FMOLS, were used to analyze quarterly data from 2000 to 2023. The findings confirm that a significant long-run relationship exists among the variables of agricultural GDP, crop production, arable land, agricultural export–import ratio, and agricultural R&D expenditure. The moderating effects of agricultural GDP and agricultural R&D expenditure on fertilizer consumption were also found to be significant. The Granger causality test results indicate that bidirectional causality exists between agricultural GDP and fertilizer consumption, arable land and fertilizer consumption, employment and fertilizer consumption, and the export–import ratio and fertilizer consumption. The findings from the robustness checks confirm that all variables are co-integrated with fertilizer consumption. Thus, policymakers are advised to prioritize investment in agricultural R&D to promote sustainable fertilizer consumption and enhance agricultural value addition in Australia. Full article

The increasing accumulation of polymer waste presents a significant environmental challenge and a critical opportunity for the development of circular and sustainable membranes. The answer to this complex topic requires an integral approach covering different aspects of the problem. This paper, therefore, explores innovative approaches for the chemical recycling of polymer waste into value-added products, with a specific emphasis on the production of advanced biopolymer membranes. By converting discarded materials into functional polymers through depolymerization and chemical modification processes, new pathways are emerging for the fabrication of high-performance membranes used in filtration, biomedical applications, and energy systems. Among these, electrospinning has gained prominence as a versatile and scalable technique for producing nanostructured membranes with tailored properties. As a key case study presented, the focus was on the optimization of electrospinning parameters, including solvents, polymer concentration, voltage, and flow rate, for the investigation of membranes derived from recycled materials to achieve net-zero technology. Moreover, the environmental benefits of this approach are discussed within a zero-waste and net-zero carbon framework, emphasizing the integration of life cycle assessment to evaluate sustainability metrics. This paper underscores the potential of polymer waste as a feedstock for circular membrane technologies and provides a roadmap for future innovations in waste-to-resource strategies. The results of the demonstrated case example clearly demonstrate how the effects of processing conditions on the production of fine-tuned biodegradable membranes with controlled porosity influenced membrane properties, including mechanical strength and surface functionality, for the desired suppression of the coffee-ring effect. Full article