Search Results (12,620)

The use of virtual reality for pilot flight training, whether as a stand-alone device, or to augment or replace a conventional simulator, has gained significant attention in recent years. The primary purported benefit of virtual reality is its increased ability to achieve immersion of the trainee, which has particular benefits for visuospatial awareness. This benefit of the technology would appear to offer little advantage in the training of instrument-flying skills, where only the aircraft’s instrumentation needs to be accurately rendered in order that the status of the ownship can be known. However, given the wide-scale intention toward the adoption of the technology, it is likely that instrument flight training will be one of its uses at flight schools. In order that the effectiveness of the VR Simulator can be evaluated, for instrument flight training, a quasi-randomised separate-sample pretest–posttest design study was completed. The ability of this low-cost VR simulator to transfer the flying skills required to conduct an ILS approach, after establishment on approach, was evaluated with 44 participants. Results indicate significant improvement in participants’ flying skills based on operational (r_rb = 0.508) and synthetic (g = 0.844) performance metrics. The findings indicate that the VR simulator appears effective for the training of these skills, and that the immersion and presence are not detrimental, even when the primary focus is the instrument panel. The idea that VR is an effective tool for training instrument flight skills has not previously been demonstrated. Due consideration must, however, be given to the context of this study and the noted limitations of the VR technology. Full article

With its benefits of high efficiency and cheap cost, solar photovoltaic is rebuilding the energy supply and demand system as the world’s energy structure shifts to a clean one. This research investigates the wind-induced vibration response of a multi-row flexible photovoltaic system using large eddy simulation and the two-way fluid–solid coupling approach. Firstly, the two-way coupling and the standard shape coefficient are compared to verify the reliability of the simulation method. Then, the model of multi-row flexible photovoltaics is analyzed to determine the natural frequency and vibration mode of the photovoltaic system. Finally, the vertical displacement of the photovoltaic system and the internal force of the cable are studied by investigating different wind direction angles and initial pretension. It is discovered that the natural frequency of the flexible photovoltaic system exhibits a stepwise increase in three distinct stages. Both the internal force in the load-bearing cable and the vertical displacement of the photovoltaic system decrease with increasing wind direction angle, with the cable force lagging behind at the peak time. The internal force and vertical displacement of the first row of load-bearing cables are at their highest at the 0° direction angle. The difference between the cable’s internal force’s peak and valley values grows when the pretension is low. The cable pretension significantly affects the vibration response of the flexible photovoltaic more than the angle of direction. The response law of direction angle and pretension to multi-row flexible photovoltaic wind-induced vibration is revealed, which provides a basis for wind-resistant design. Full article

Against the backdrop of carbon quota trading policies and Energy Performance Contracting (EPC), Energy Service Companies (ESCOs) engage in supply chain emission reduction via embedded low-carbon services. However, the impact mechanism of their financing mode selection on emission reduction efficiency and economic benefits has not been fully revealed, and there is a lack of support from a systematic theoretical and engineering design framework. Therefore, this study innovatively constructs a multi-agent Stackelberg game model with bank financing, green bond financing, and internal factoring financing. We incorporate the embedding degree, emission reduction cost coefficient, and financing mode selection into a unified analysis framework. The research findings are as follows: (1) There is a significant positive linear relationship between supply chain profit and the embedding degree. In contrast, the profit of ESCOs shows an inverted “U-shaped” change trend. Moreover, there is a sustainable cooperation threshold for each of the three financing modes. (2) Green bond financing can significantly increase the overall emission reduction rate of the industrial supply chain in high-embedding-degree scenarios. However, due to emission reduction investment cost pressure, ESCOs tend to choose bank financing. (3) The dynamic change of the emission reduction investment cost coefficient will trigger a reversal effect on the financing preferences of the supply chain and ESCOs. This study unveils the internal mechanism of multi-party decision-making in the low-carbon industrial supply chain and is supported by cross-country institutional evidence and comparative case-based analysis, providing a scientific basis and engineering design guidance for optimizing ESCO financing strategies, crafting incentive contracts, and enhancing government subsidy policies. Full article

Electrochemical reduction of carbon dioxide (CO₂RR) to methanol represents a promising approach for sustainable methanol production. Despite this potential, current technological limitations constrain both economic viability and environmental benefits. This research introduces a solar-driven multigeneration system that integrates CO₂RR to enable the coproduction of electricity and green methanol. A comprehensive energy integration analysis was conducted, alongside a combined techno-economic, energy-efficiency, and environmental (3E) assessment. Multiobjective optimization was conducted using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). For solution selection, the analytic hierarchy process (AHP) was integrated with the order preference by similarity to ideal solution (TOPSIS) methodology. Results indicate that the integrated system achieves a 4.2% reduction in total utility consumption. The optimal levelized cost of methanol (LCOM), net specific carbon emissions (Net_SCE), and energy efficiency (η_EN) are USD 0.526/kg, −1.16 kg CO₂SCE/kg CH₃OH, and 6.52%, respectively. LCOM decreases by 30.6% compared to the initial system, Net_SCE increases by 3.44%, and η_EN improves by 5.84%. Under optimal operating conditions, CH₃OH production capacity and grid power consumption reach 45.27 tons/day and 475.83 MWh/day, respectively. The system does not currently meet the commercial threshold and becomes economically viable only if the electricity price exceeds USD 0.223/kWh. This study provides a valuable reference for future research in system-level integration of CO₂RR and multiobjective solution selection. Full article

A parallel-stirred tank bioreactor system on a 10 mL-scale automated with a liquid handling station introduces significant benefits in bioprocess analysis and design regarding preserving time, cost, and workload, thereby enabling quick generation of bioprocess results that can be easily scaled up. Although up-to-date approaches enable the online analysis of individual reactors for pH, dissolved oxygen (DO), and optical density (OD), the automated calibration of a new online laser-based infrared OD sensor device and noise reduction are still required. Among the extensive research on the full-data smoothing tools, the Savitzky–Golay (Savgol) filter was determined as the most effective one. Scattered and transmitted online light values were successfully aligned with the reference at-line OD values measured at 600 nm by the liquid handler with a step time of a few hours. The growth of an engineered Gluconobacter oxydans designed for specific whole-cell oxidations has been investigated in two parallel batch process setups with varied sugar types at varying sugar concentrations, combinations of sugars, and altered concentrations of complex media. Simulation of real-time smoothing was applied with a Kalman filter. Rapid adaptation was observed within a few upcoming data points by altering the parameters for the estimation of the noise in the signal. For almost all tested reaction conditions, a successful alignment of the simulation of real-time smoothed online OD with at-line values was achieved. The best growth condition was determined in the presence of 120 g L⁻¹ glucose and 30 g L⁻¹ fructose with the tripled peptone concentration. Under these conditions, OD₆₀₀ increased by 109%, from 2.1 to 4.4, compared to the reference process. Full article

Electric vehicles (EVs) and renewable energy generation are widely regarded as key drivers of low-carbon transformation in the transportation and energy sectors due to their emission reduction potential and environmental benefits. However, the inherent intermittency and volatility of photovoltaic (PV) power, coupled with increasingly stochastic and disorderly EV charging demand, pose significant challenges to grid stability and local renewable energy utilization. To address these issues, this paper proposes a dynamic pricing optimization approach based on a Stackelberg game framework, in which the PV charging station operator acts as the leader and EV users as followers. Unlike conventional models, the proposed framework explicitly incorporates user psychological expectations and response deviations through a three-stage “dead-zone-linear-saturation” responsiveness structure, thereby capturing the uncertainty and partial rationality of EV charging behavior. The upper-level objective seeks to maximize operator profit and enhance PV self-consumption, while the lower-level objective minimizes user energy cost under price-responsive charging decisions. The bilevel optimization problem is solved via a differential evolution (DE) algorithm combined with YALMIP+CPLEX. Simulation results for a regional PV-EV charging station show that the proposed strategy increases PV self-consumption to about 90.5% and shifts the load peak from 18:00–20:00 to 10:00–15:00, effectively aligning charging demand with PV output. Compared with both flat and standard time-of-use (TOU) tariffs, the dynamic pricing scheme yields higher operator profit (about 7% improvement over flat pricing) while keeping total user energy expenditure essentially unchanged. In addition, the cumulative carbon reduction cost over the operating cycle is reduced by approximately 4.1% relative to flat pricing and 1.9% relative to TOU pricing, demonstrating simultaneous economic and environmental benefits of the proposed game-based dynamic pricing framework. Full article

The collaboration between economic and ecological departments in land-use planning is crucial for advancing sustainable development. However, existing research has largely focused on macro-level policies and technical instruments, paying insufficient attention to the micro-level logics of behavior and strategic interactions between these two departments. This research employs a rigorous mixed-methods approach to bridge empirical depth with analytical rigor. The qualitative phase, encompassing 41 semi-structured interviews and analysis of 327 internal documents, examines the departments’ real-world motivations, strategic behaviors, and the cost–benefit structures underlying their decision-making. Based on these empirical findings, a tailored evolutionary game theory model is constructed to formally simulate the dynamic pathways and stable equilibria of collaboration between the Economic and Ecological Departments. Our analysis reveals that the evolutionary game system converges toward a dichotomy of stable states: a non-cooperative equilibrium characterized by development-oriented land-use planning with adaptive regulation, and a cooperative equilibrium underpinned by green-coordinated planning supported by stringent regulatory enforcement. A cooperative equilibrium is more readily achieved when both departments demonstrate a willingness to simultaneously increase their cost investment parameters in sustainable land-use planning. Conditions contrary to this mutual commitment lead to a non-cooperative equilibrium. Building on these findings, the study synthesizes this interplay into a novel “Institutional-Situational-Behavioral” (ISB) framework. This framework provides a cohesive theoretical lens for diagnosing and fostering interdepartmental collaboration in sustainable land governance. The research thus offers a theoretical foundation for analyzing the evolutionary dynamics of interdepartmental collaboration and delivers mechanism-informed policy guidance for enhancing sustainable land-use planning. Full article

As a critical institutional arrangement for regulating the distribution of ecosystem service benefits, the scientific setting of ecological compensation standards is particularly vital in cross-regional watershed governance. However, there is currently a lack of methods grounded in the multifunctionality of forests and residents’ preferences for determining compensation. Taking the Jinghe watershed as a case study, this research employed a contingent valuation questionnaire survey (n = 747 valid responses) to analyze residents’ perceptions and willingness for forest ecological compensation. The results show that (1) watershed residents generally understand the multifunctional services of forests (cognitive rate: 71.6%–96.4%), and most agree that upstream forest construction benefits downstream ecology, but 30%–40% remain unclear about specific compensation policies. (2) The average willingness to accept (WTA) compensation for upstream residents is 314.10 CNY/mu/year, while the average willingness to pay (WTP) for downstream residents is 289.59 CNY/mu/year. This translates to a compensation standard range of 4343.85 to 4711.5 CNY/ha/year, approximately twice the local afforestation cost but one-sixth of the estimated total ecosystem service value. (3) While over 60% of respondents prefer compensation via governmental funds, there is notable and growing acceptance for development-oriented mechanisms like industrial collaboration and joint park construction under fiscal constraints. (4) Regression analysis indicates that occupation, annual income, and ecological cognition positively influence willingness, whereas age and household size show negative correlations; formal education level showed no significant impact. This study provides empirical evidence and a preference-based framework for setting scientifically grounded and socially accepted multifunctional ecological compensation standards in cross-regional watersheds. Full article

Safe and sample-conscious controller synthesis for nonlinear dynamics benefits from reinforcement learning that exploits an explicit plant model. A nonlinear mass–spring–damper with hardening effects and hard stops is studied, and off-plant Q-learning is enabled using two data-driven surrogates: (i) a piecewise linear model assembled from operating region transfer function estimates and blended by triangular memberships and (ii) a global nonlinear autoregressive model with exogenous input constructed from past inputs and outputs. In unit step reference tracking on the true plant, the piecewise linear route yields lower error and reduced steady-state bias (MAE = $0.03$; SSE = $3\%$) compared with the NLARX route (MAE = $0.31$; SSE = $30\%$) in the reported configuration. The improved regulation is obtained at a higher identification cost (60,000 samples versus 12,000 samples), reflecting a fidelity–knowledge–data trade-off between localized linearization and global nonlinear regression. All reported performance metrics correspond to deterministic validation runs using fixed surrogate models and trained policies and are intended to support methodological comparison rather than statistical performance characterization. These results indicate that model-based Q-learning with identified surrogates enables off-plant policy training while containing experimental risk and that performance depends on modeling choices, state discretization, and reward shaping. Full article

To address the power and energy balancing challenges faced by high-penetration renewable energy systems under long-term intermittent output conditions, this study proposes a multi-source, multi-timescale collaborative dispatch strategy (2MT-S) integrating wind, solar, hydro, thermal, and hydrogen energy resources. First, a long-term-to-day-ahead coupled scheduling framework is established based on intermittent output duration forecasts (3-day/10-day). By integrating seasonal hydrogen storage and pumped-storage hydroelectric plants, this framework achieves comprehensive coordination among electrochemical storage, thermal power, and other flexible resources. Second, a multi-time-horizon optimization model is developed to simultaneously minimize system operating costs and load curtailment costs. This model dynamically adjusts day-ahead scheduling boundary conditions based on long-term and short-term scheduling results, enabling cross-period resource complementarity during wind and photovoltaic generation troughs. Finally, comparative analysis on an enhanced IEEE 30-bus system demonstrates that compared to traditional day-ahead scheduling, this strategy significantly reduces renewable energy curtailment rates and load curtailment volumes during sustained low-generation periods, fully validating its significant advantages in enhancing power supply reliability and economic benefits. Full article

Although blood transfusion eco-compensation—a metaphorical term in the Chinese eco-compensation literature referring to short-term direct compensation—can balance stakeholder interests in securing ecological flows (e-flows) in water-scarce rivers, it often fails to enhance the productivity of disadvantaged stakeholders or expand long-term development opportunities. To overcome this limitation, this study introduces hematopoiesis eco-compensation, a metaphorical term for capacity-building, longer-term development-oriented compensation that improves irrigation water-use efficiency and agricultural productivity through water-saving infrastructure upgrades, enhanced irrigation technologies, and technical training. Based on this distinction, we developed a hybrid eco-compensation mechanism integrating the two approaches using a cost–expenditure method and applied it to the mainstream section of the Weihe River and the Baojixia Yuanshang Irrigation District in Northwest China under typical hydrological conditions. The main findings are as follows: (1) Compensation standards for both approaches increase with higher ecological flow targets, with average values of 2762 CNY ha⁻¹ and 1386 CNY ha⁻¹, respectively. (2) The two approaches differ in terms of participants, standards, and implementation methods, yet they are complementary and indispensable under current conditions. (3) Hematopoiesis eco-compensation generates positive ecological and economic effects, increasing the annual value of riverine ecosystem services by approximately 126 million CNY and the annual economic benefits of the irrigation district by approximately 467 million CNY. This study provides a theoretical foundation and practical guidance for establishing long-term compensation mechanisms to maintain ecological flows in water-scarce regions. Full article

Delays during turnaround operations are a significant source of operational inefficiency for airlines. They reduce airline profit margins by resulting in rescheduled flights and missed connections for passengers. This research paper presents the findings of an approach developed within the INTACT research project (subsequently called “the INTACT system”). The INTACT system aims to achieve reduced delays during turnaround operations and therefore increase their operational efficiency by introducing new technologies. A simulation study, including 350 simulated days, was conducted to assess the impact of three of INTACT’s abilities: (1) the localization of wheelchairs for passengers, (2) the assessment of what trolleys are onboard and how many trolley items are needed, and (3) visual observations of cabin failures and communication back to the destination airport. Results show that the implementation of these technologies leads to a statistically significant average delay reduction of 3 min per turnaround. Under the modeled schedule constraints in the discrete-event simulation, this reduction shifts the distribution of feasible daily flight counts, resulting in an average increase of 0.11 flights/day (38 additional completed flights over 350 simulated days) relative to the full-delay scenario. In addition, the cost–benefit analysis shows that the INTACT system saves an average of $966.95 in turnaround costs and gains $2714.29 in additional revenue per day and per aircraft. With estimated initial investment costs of around 2 million dollars, the payback period is only 1.5 years. During this study, gross additional revenue was reported as an upper-bound estimate; net operational benefit depends on airline-specific variable operating costs. The INTACT system can help to improve turnaround operation issues while providing positive economic performance for stakeholders in the industry. Full article

Introduction: Women with breast cancer experience psychological distress, and resilience-strengthening psychosocial support may improve their quality of life (QoL). Identifying those at risk of low QoL is challenging. This study evaluated the cost-effectiveness of a machine learning-based QoL predictor to support clinical decision-making regarding psychosocial support (sample size: 660). Methods: A decision tree cost–utility model was developed to compare four decision-making strategies in offering psychosocial support: the clinician alone, the QoL predictor alone, the clinician supported by the predictor, and no prediction with no psychosocial support. QoL after one year was used as a proxy for resilience. Costs, health outcomes, and net monetary benefits (NMBs) were estimated using a one-year time horizon. Incremental cost-effectiveness ratios (ICERs) were calculated and dominance assessed. A societal scenario analysis incorporated productivity losses. A probabilistic sensitivity analysis generated cost-effectiveness acceptability curves. Results: Clinicians supported by the QoL predictor produced the highest NMB (EUR 16,349) and the greatest quality-adjusted life year (QALY) gain (0.759), with an ICER of EUR 22,892 compared with the next least costly strategy. Clinician-only prediction and predictor-only approaches were dominated or extendedly dominated. Under the societal perspective, all strategies produced negative NMB values due to productivity losses, but the overall ranking remained unchanged. The probabilistic sensitivity analysis showed that the combined clinician and predictor strategy had a 69% probability of being cost-effective at a willingness to pay threshold of EUR 30,000. Conclusions: Combining clinician judgement with the machine learning-based QoL predictor improved the targeting of psychosocial support and was the most cost-effective strategy. Further prospective and comparative studies are needed to confirm its long-term effectiveness and cost-effectiveness in clinical practice. Full article

The revised Energy Performance of Buildings Directive (EPBD) has introduced ambitious targets aimed at accelerating the decarbonization of the building sector. In parallel, the forthcoming implementation of the Emission Trading System for buildings and road transport (ETS2) in January 2027 adds a further dimension to the policy landscape. This study investigates three renewable energy retrofit strategies (Scenarios A, B, and C) for a hotel building in northern Italy, assessing their effectiveness in meeting the decarbonization objectives set by the EPBD and ETS2. Scenario A couples photovoltaic generation with an existing gas boiler, Scenario B integrates PV with an electric heat pump for space heating, and Scenario C implements the full electrification of both heating and domestic hot water. The results of the three scenarios are evaluated using selected metrics, such as renewable primary energy consumption (EPren), non-renewable primary energy consumption (EPnren), CO₂ emission (CO₂), carbon avoidance cost (CAC), levelized cost of energy (LCOE), net present value (NPV), and Emission Trading System (ETS)2. The results show that PV deployment alone provides economic benefits but yields limited reductions in CO₂ emissions and non-renewable primary energy consumption due to continued reliance on natural gas. The introduction of a heat pump significantly enhances environmental performance, with reduced fossil fuel consumption, increased renewable energy use, and improved cost-effectiveness of carbon avoidance. The ETS2 has no impact in the case of full electrification, as fossil fuel consumption is completely eliminated. Full electrification achieves the greatest emission reductions and the lowest non-renewable primary energy demand while offering the strongest long-term economic performance. Overall, the analysis demonstrates that combining PV systems with building electrification is essential to achieving deep decarbonization, and that fully electrified configurations present the most robust pathway for compliance with emerging ETS2 policies. Full article

Therapeutic inertia in lipid-lowering treatment remains a striking paradox of modern cardiovascular medicine: at a time when the causal role of LDL-cholesterol in atherosclerotic disease is unequivocal and potent therapies are widely available, a substantial proportion of high- and very-high-risk patients still fail to receive timely treatment intensification. Contemporary European and international data consistently show fewer than one in three patients in secondary prevention achieve guideline-recommended LDL-C targets, revealing a persistent and unacceptable gap between scientific evidence and clinical reality. This narrative review examines therapeutic inertia as a key explanatory framework for this gap, describing its epidemiology, mechanisms, and clinical consequences in secondary cardiovascular prevention. We summarize the main physician-, patient-, and system-level determinants and propose recurrent clinician “phenotypes” of inertia that may help explain why opportunities are missed even in the highest-risk patients. The consequences are profound: therapeutic inertia contributes to what we propose as the conceptual framework of an “avoidable atherosclerotic burden”, the cumulative vascular injury that accrues each period in which LDL-C remains above target, translating into higher rates of avoidable cardiovascular events, and increased healthcare costs. Emerging strategies such as upfront combination therapy, decision-support systems, structured lipid pathways, and the integration of artificial intelligence offer practical tools to shift lipid management from reactive to proactive care. Overcoming therapeutic inertia is therefore not merely a matter of improving process metrics, but a clinical and ethical imperative. Closing the gap between evidence and practice requires transforming optimal lipid management from an exception into a system-level default, ensuring that every patient receives the full benefit of therapies proven to save lives. This work proposes a novel characterization of clinician ‘phenotypes’ and the concept of ‘avoidable atherosclerotic burden’ as a framework to understand and address this gap. Full article