Search Results (264)

Understanding olive tree metabolism and its interactions with biotic and abiotic factors is crucial for the sustainability and resilience of olive cultivation in a changing agroclimatic context. In response to biotic stress, plants activate complex signaling pathways that trigger the production of specialized metabolites, particularly volatile organic compounds (VOCs). This study investigates the volatolomic profile naturally emitted by whole olive fruits using an integrated metabolomic strategy that combines design of experiments (DoE), targeted and untargeted analyses, and multivariate statistics. Optimal headspace solid-phase microextraction (HS-SPME) conditions were established using 30 g of sample, a 50 °C extraction temperature, a 50 min extraction time, and a 3 min injection at 250 °C, identifying extraction time and temperature as the most critical factors influencing VOC recovery. The data demonstrated significant cultivar-dependent variation in the volatile emissions from healthy olive fruit among six representative varieties. Furthermore, robust partial least squares-discriminant analysis (PLS-DA) and random forest models provided a clear separation between healthy and damaged olive fruits, achieving high predictive accuracy (90%) and identifying key volatile biomarkers derived from the lipoxygenase (LOX) pathway. This novel multivariate optimization approach (SPME–GC/MS) represents a powerful tool for establishing a reliable chemical fingerprint of the olive fruit “volatilome” under evolving agroclimatic challenges. Full article

Plant secondary metabolites remain indispensable for pharmaceuticals, nutraceuticals, and cosmeceuticals, yet conventional plant culture systems are increasingly limited by inconsistent yields, poor scalability, and inadequate capacity for real-time process monitoring. Microfluidic technologies and organ-on-a-chip (OoC) platforms, originally developed for mammalian biology, are now emerging as powerful tools to overcome these constraints. These systems enable laminar flow, precise gradient generation, single-cell resolution, and biosensor integration, providing unprecedented control over the cellular microenvironment and supporting non-destructive, real-time metabolomic monitoring. While recent reviews have surveyed plant microfluidics broadly covering developmental biology, single-cell phenotyping, and root–microbe interactions, this review provides, to our knowledge, the first synthesis focused specifically on organ-on-a-chip approaches for plant secondary metabolite biosynthesis and real-time metabolomic monitoring. Advances in device fabrication, including PDMS, paper-based, hydrogel, and thermoplastic materials, surface engineering, gradient-based elicitation strategies, and integration of optical, electrochemical, and mass spectrometric detection systems have also been critically examined. Special emphasis is placed on root-on-a-chip, shoot meristem, protoplast, callus, and 3D organoid platforms for studying cell wall mechanics, vacuolar dynamics, cytoskeletal responses, and signalling cascades. However, challenges remain in long-term culture stability and scalability; nonetheless, these technologies offer a roadmap toward programmable ‘plant biosynthetic factories’ to produce high-value natural products. Full article

This research evaluates the feasibility of implementing photovoltaic solar systems in the Ecuadorian Amazon to harness solar energy and increase energy security in the region. It is based on the need to reduce direct dependence on fossil fuels and existing hydroelectric systems. The overall framework is to transform the energy matrix to utilize incident solar energy, integrating it with current hydroelectric and thermal generation. The fundamental goal is to evaluate the energy resource using specialized software such as Homer Pro and develop designs for the proper operation of photovoltaic solar technology, which will contribute its surplus energy to the National Interconnected System (SNI) and, therefore, reduce the country’s high dependence on the hydrological cycle. The results obtained demonstrate that solar power plants can be of great benefit to the country, especially when combined with wind and existing hydroelectric power. This will contribute to the diversification of energy sources and, consequently, to energy security through the increase in renewable energy. In the worst-case scenario, the cost of energy can be 7 cents per kWh, and in the best-case scenario, in a combined dispatch, 3 cents per kWh. Full article

Heavy metal ion pollution has emerged as a global issue. These contaminants are not only present in water sources but are also commonly detected in air, soil, food, and consumer products, posing serious risks to ecosystems and human health. Even at very low concentrations, heavy metal ions can exhibit substantial toxicity. Traditional methods for the detection of heavy metal ions typically require complex laboratory equipment and specialized technicians, making them inadequate for rapid on-site monitoring. Microfluidic technology, as an innovative platform capable of precisely controlling and manipulating minute volumes of fluid, has demonstrated enormous potential in analytical chemistry, biomedicine, and environmental monitoring. In the rapidly developing field of microfluidics, paper-based microfluidic platforms have become prominent due to their low cost, straightforward fabrication, and eco-friendly nature, offering powerful tools for the detection of heavy metal ions in diverse samples. This survey consolidates the major advances reported from 2015 to 2025 in utilizing paper-based microfluidic systems for identifying heavy metal ion pollutants in diverse sample types, including air, explosive residues, water sources, herbal supplements, skin-whitening cosmetics, environmental aerosols, urine, soil, gunshot residues, cucumber plants, and food. The review analyzes in detail the principles and applications of detection strategies based on colorimetric methods, fluorescent methods, electrochemical methods, dual-detection systems, and other methods, as well as the role of nanomaterials and selective recognition elements in improving detection sensitivity and specificity. These portable, low-cost, and easy-to-operate detection systems provide viable solutions for environmental and public health monitoring, particularly suitable for resource-limited regions and scenarios requiring rapid detection. Full article

The study presents the results of research aimed at developing digital models for determining the operating parameters of railway power supply systems equipped with distributed generation plants based on renewable energy sources (RESs). RESs can be used in railway transport to increase the reliability of power supply to facilities located in areas with insufficiently developed power grids. This primarily applies to consumers, for whom a power failure can lead to significant damage, accidents, and a threat to human life. RES can serve as independent power sources for special-group consumers and can increase energy conversion efficiency. Furthermore, large-scale implementation of renewable energy sources can significantly reduce energy supply costs and improve power quality. The study employs phase-coordinate modeling, which is characterized by the following features: a systems approach, which implies determining operating conditions while considering the properties and characteristics of complex traction and supply networks; versatility, which enables modeling of power supply systems of various structures and designs; and comprehensiveness, which involves calculating normal, emergency, and special operating parameters—crucial for scenarios such as ice melting on catenary wires. The modeling results obtained using the Fazonord AC-DC software (ver. 5.3.5.2) show that RES-based distributed generation plants provide a variety of beneficial effects: reduction in electricity consumption from power system networks; decrease in voltage unbalance and harmonic distortion on the busbars of regional windings of traction substations; and stabilization of voltage levels on current collectors of electric locomotives. Full article

The classical localizationist framework in biology and neuroscience has provided a powerful approach for linking structure to function. However, increasing evidence indicates that biological functions emerge from distributed interactions across complex systems. While network and systems-based approaches have advanced this transition, they often remain focused on connectivity patterns or statistical dependencies. In this review, I argue that a further conceptual step is required: a coordination-based framework in which biological function emerges from the context-dependent selective stabilization of interactions among distributed components that become causally relevant for specific outcomes. I develop this perspective comparing brain network organization and plant signaling, two systems that exhibit adaptive behavior without relying on centralized control. Across both domains, function depends on the dynamic coordination of heterogeneous processes operating across multiple spatial and temporal scales. This framework acknowledges structural specialization but argues that specialized components become effective through coordinated interaction regimes. I further discuss how this perspective extends current systems biology approaches by prioritizing temporally structured interaction patterns as the primary explanatory target. Finally, I outline empirically testable predictions suggesting that biological function is better captured by time-resolved coordination dynamics, hub-mediated integration, and metastable interaction regimes than by localized activity or static connectivity. Full article

The triboelectric nanogenerator (TENG), which converts mechanical energy into electrical energy through the coupled effect of triboelectrification and electrostatic induction, has garnered significant interest among researchers due to its portability and self-powered characteristics. Despite its evident development potential, TENG continues to face challenges, including the necessity to enhance its triboelectric performance through the optimization of structures, materials, and manufacturing techniques to improve energy conversion efficiency. Additionally, its environmental stability and durability also need to be improved. TENGs designed inspired by non-human animals and plants offer feasible solutions to address these limitations. These bio-inspired TENGs optimize the structural design of TENGs and the materials of the triboelectric layers by imitating the structures, functions, and behaviors of organisms, thereby further improving the energy conversion efficiency, sensitivity, wear resistance, adaptability to special environments, biocompatibility, and wearing comfort of TENGs. This paper expounds on the progress of TENGs inspired by non-human animals and plants applied in environmental energy harvesting, human health and motion monitoring. It also discusses the current challenges, with a view to providing insights for the interdisciplinary integration and development of bionics and TENGs. Full article

The foundation of nuclear power plants is special as large-scale earth filling is often required. The properties of the backfill soil differ significantly from naturally deposited soils with regard to deformation and bearing capacity. For pile foundations, a thick backfill layer near the top may change the bearing mode around the pile. In this paper, six cast-in-place rock-socketed piles were tested, with three vertical loading tests and three horizontal loading tests. The lengths of four piles are 35–40 m, while the other two piles reach 55 m. The results show that shorter piles with more parts in the backfill layer can endure a hoop-tightening effect that caused by dilatancy at the upper part of the pile, resulting in very little frictional resistance being provided by the lower soil and smaller vertical displacement of the whole pile. The typical mechanism of transition from static to dynamic friction between soil and piles that leads to shaft resistance is more apparent for longer piles, but inhomogeneous soil like the backfill layer will make the transition complex. When subjected to lateral loading, piles with better integrity show more pronounced elastic features, smaller maximum horizontal displacement, and less residual horizontal displacement. The selection of the proportional coefficient for determining piles’ horizontal bearing capacity should correspond to the specific load and displacement in backfill soil. The results and in-depth analysis of the piles’ bearing capacity in backfill soil will provide intuitive experience for the analysis of pile foundations, thus offering references for the design and construction in similar engineering. Full article

The modern power system is characterized by large-scale networks, diverse types of sources and loads, and complex grid structures. Virtual Power Plants (VPPs) are proposed to address the operation problem after the integration of Distributed Energy Resources (DERs). Optimization problems in the VPP operation are predominantly mixed-integer programming (MIP) problems belonging to the class of NP-hard problems, motivating the application of quantum computers. Focusing on the VPP optimal dispatch problem under wind and solar uncertainty, we employ the Model Predictive Control (MPC) framework to conduct the VPP intraday rolling dispatch. The classical model and the Quadratic Unconstrained Binary Optimization (QUBO) model for the MPC-based intraday rolling dispatch problem are formulated, respectively. The QUBO formulation of the VPP dispatch problem renders it directly solvable by a specialized quantum computer based on dissipative optical systems: the Coherent Ising Machine (CIM). Compared with the benchmark classical solvers, the experimental results demonstrate the significant computational time reduction capability of CIM. Specifically, compared to Gurobi, Simulated Annealing and Tabu Search, the CIM achieves relative computational time reductions of $75.25\%$, $99.95\%$ and $99.96\%$, respectively, while maintaining competitive solution quality. Our work demonstrates the applicability of CIM and its acceleration potential in VPP intraday rolling dispatch, paving the way for the practical application of specialized photonic quantum computers in smart grids. Full article

Botanical extracts represent a rich and sustainable source of polyphenolic compounds with significant potential in anticancer research. Among these, hesperidin, naringenin, hydroxytyrosol, oleuropein, and quercetin have attracted considerable attention due to their abundance in widely consumed plants such as citrus fruits, olive derivatives, and various fruits and vegetables. However, their clinical translation is hindered by intrinsic limitations including poor solubility, low stability, and limited bioavailability. In this context, nanotechnology-based drug delivery systems have emerged as a promising strategy to enhance the therapeutic performance of these bioactive compounds. This review provides an overview of polyphenol-rich botanical matrices and focuses on recent advances in their nanoformulation. Various nanocarriers, including polymeric nanoparticles, liposomes, solid lipid nanoparticles, and nanoemulsions, are discussed in terms of their ability to improve physicochemical properties, protect against degradation, and enhance delivery efficiency. Special attention is given to the challenges associated with the encapsulation of complex botanical extracts and the need to preserve their compositional integrity and synergistic effects. Overall, nanoformulation represents a powerful approach to overcome current limitations and unlock the full potential of plant-derived polyphenols in anticancer applications. Full article

This paper examines an algorithm and evaluates the upper limits of technical parameters for step-by-step management of forecast coverage for aggregated generation from solar power plants (SPPs) in Ukraine, given the high share of renewable energy sources in the integrated power system of Ukraine. The relevance of the research is due to the growth in the installed capacity of SPPs, stricter requirements for forecasting accuracy, and the full financial responsibility of producers for imbalances in accordance with the current electricity market model. The problem is formulated as a special case of a hierarchically controlled quasi-dynamic power system, accounting for technological, energy, and economic constraints. The objective function is defined as the minimisation of the total hourly measure of discrepancy between the forecast and actual volumes of electricity supplied, whilst ensuring power balance through energy storage systems and flexible generation. The numerical implementation was carried out using the “SOPS” software and information complex. The input data used were hourly indicators of the forecasted and actual generation of Ukraine’s solar power plants for 2021–2025, published by the state-owned enterprise “Guaranteed Buyer”. Hourly, daily and monthly operating parameters for aggregated solar power generation in 2025 have been calculated. The calculations show that the maximum hourly mismatch between forecasted and actual solar generation in 2025 reached 3116 MW, while the maximum daily mismatch exceeded 19.8 GWh. Under the assumed operating conditions, an energy storage system with 30,000 MWh capacity and flexible generation of up to 7500 MW enabled full imbalance compensation, achieving IMB(t) = 0 for all hourly intervals in the analysed case. The required volumes of flexible generation and the operating parameters of the storage systems have been determined. The practical significance of the results lies in their potential use for operational planning of the operating modes of solar power plants, energy storage systems, and flexible generation on a daily and hourly basis, as well as for justifying technical and economic decisions aimed at reducing imbalances. The results obtained confirm the effectiveness of the proposed step-by-step control algorithm and demonstrate the potential to minimise imbalances through the rational coordination of solar power plants, energy storage systems, and flexible generation capacities. Full article

Industrial isolated power systems are highly sensitive to load disturbances due to their limited inertia and absence of large-grid support. This article analyzes the dynamic stability of an isolated system with a current available generation contribution of approximately 24 MW, evaluating the integration of a new production plant planned to be integrated in two construction phases of 2 MW each (total 4 MW). The system operates with local generation at 13.8 kV and distribution at 34.5 kV; therefore, demand expansion requires a detailed assessment to maintain safe operating conditions. In addition, the study verifies compliance with spinning reserve requirements for Phase 1 and Phase 2 in accordance with applicable industrial power system criteria, including IEEE 3007.1 and IEEE C37.106, as part of the N−1 security assessment. The developed stability analysis is based on time-domain dynamic simulations using IEEE AC8C excitation models and a UG-8 governor. The results show that, under severe contingencies, the frequency nadir can reach deviations close to 1.5 Hz and RoCoF values above 4 Hz/s. The results indicate that Phase 1 (2 MW) can be incorporated while maintaining acceptable spinning reserve margins, whereas the additional 2 MW corresponding to Phase 2 cannot be integrated under the current operating conditions without violating reserve criteria. However, the system remains stable when generators operate under automatic voltage control, while fixed power factor mode produces less robust responses. Based on this result, the dynamic analysis is focused on the Phase 1 condition under critical contingencies, particularly the sudden outage of the 5 MW and 8 MW generating units, with special emphasis on the outage of the largest generator, mitigated through spinning reserve support and a RoCoF-based load shedding scheme of approximately 4.4 MW. Likewise, the energization of the new plant through the 8 km line requires the evaluation of the available reactive compensation resources, including the use of capacitor banks/reactive support, to prevent underexcitation and maintain acceptable voltage conditions. Full article

Cyber-physical systems (CPSs) represent sophisticated intelligent architectures that tightly couple computational elements, communication networks, and physical processes. Their deployments now span virtually every industrial and civilian domain—from power grids and manufacturing plants to autonomous transportation networks. Ensuring the secure operation of CPSs relies fundamentally on effective time series anomaly detection, which remains a challenging task due to the complex, often unknown system dynamics and non-negligible sensor noise present in real-world environments. To address these challenges, we introduce a Neural Network-Enhanced Kalman Filter (NNEKF), a novel anomaly detection framework that combines model-based filtering with data-driven learning. The NNEKF employs a two-stage trained neural network with a specialized architecture: the first stage learns the underlying dynamics of the CPS, while the second stage optimizes the computation of the Kalman gain during the update step. At inference time, the enhanced Kalman filter recursively estimates the likelihood of observed sensor measurements to identify anomalies, supported by a batched parallel inference scheme that delivers substantial speedups. Extensive experiments on benchmark datasets demonstrate that the NNEKF attains an average F1-score of 0.935, coupled with rapid inference and minimal model footprint—surpassing all competitive baselines and facilitating dependable real-time anomaly detection for CPS environments. Full article

The upscaling of turbines in the offshore wind industry has been unprecedented, as compared to 5–6 MW rated turbines 10 years ago. A typical 20–26 MW rated turbine in modern commercial applications (MingYang MySE 18.X-20 MW installed in 2025 and 26 MW prototype by Dongfang Electric tested in 2025) has been demonstrated. This scaling has been made possible by increasing rotor diameters (>250 m) and hub heights (>150–180 m) to achieve capacity factors of up to 55–65%, annual energy generation of more than 80 GWh/turbine, and significant decreases in levelised cost of energy (LCOE) to current values of up to 63–65 USD 2023/MWh globally averaged in 2023 (with minor variability in 2024 due to market changes and new regional areas). The paper analyses turbine upscaling over three levels of hierarchy, including turbine scale—rated capacity and physical aspect, project scale—multi-gigawatts of farms, and market scale—the global pipeline > 1500 GW level, and combines techno-economic evaluation, structural evaluation of loads, and infrastructure needs assessment. The upscaling has the advantage of reducing the number of turbines dramatically (e.g., 500 to 67 turbines in a 1 GW farm, as turbine size is increased to 15 MW) and balancing-of-plant (BoP) CAPEX (turbine-to-turbine foundations and cables) by some 20 to 30 percent per unit of capacity, and serial production learning rates of between 15 and 18% per doubling of capacity. But the problems that come with the increase in ultra-large designs are nonlinear increments in mass and load (i.e., blade-root and tower-bending moments), logistical constraints (blades > 120 m, nacelle up to 800–1000 tonnes demanding special vessels and ports), supply-chain issues (rare-earth materials, vessel shortages increase day rates by 30–50%), and technology limitations (aeroelastic compounded by numerical differences between reference 5 MW, 10 MW, and 15 MW models), it becomes evident that there is a significant increase in deflections of the tower and blades and platform surge/pitch responses with continued increases in power levels, but without a correspondingly mature infrastructure. The regional differences (mature ports of Europe vs. U.S. Jones Act restrictions vs. scale-up of vessels/manufacturing in China) lead to the necessity of optimisation depending on the context. The analysis concludes that, to the extent of mature markets with adapted logistics, continuous upscaling is an effective business strategy and can result in 5 to 12 percent further reductions in LCOE, but beyond that point, gains become marginal or even negative, as risks and costs increase. The competitiveness of the future depends on multi-scale/multi-market-based approaches—modular-based families of turbines, programmatic standardisation, vibration control innovations, and industry coordination towards supply-chain alignment and standards. Its major strength is that it transcends mere size–cost relationships and shows how nonlinear structural processes, aero-hydro-servo-elastic interactions, and bottlenecks in logistical systems are becoming more determinant of the efficiency of ultra-large turbines. The study demonstrates that upscaling turbines has LCOE benefits through the support of associated improvements in installation facility, supply-chain preparedness, and structural vibration control potential, based on the comparisons of quantitative loads, techno-economic scaling trends, and regional market differentiation. Full article