Search Results (3,165)

In ultrafast science, the strong-field approximation (SFA) provides a powerful framework to describe high-order harmonic generation (HHG) and related phenomena. Meanwhile, within the current ab initio theoretical framework, the use of nonlocal potentials in calculating multi-electron molecular wave functions is almost unavoidable. We find that when such wave functions are directly applied to compute transition dipole moments for correcting SFA, it introduces a fundamental gauge transformation problem. Specifically, the nonlocal potential contributes an additional gauge-dependent phase function to the dipole operator, which directly modifies the phase of the transition dipole. As a consequence, the saddle-point equations acquire an entirely different structure compared to the standard SFA, leading to a splitting of the conventional short and long classical trajectories in HHG into multiple distinct quantum trajectories. Here, ‘‘complex molecules’’ refers to multi-center molecular systems whose nonlocal electronic structure leads to gauge-dependent strong-field responses. Our analysis highlights that the validity of gauge in-variation cannot be assumed universally in SFA framework. Our approach combines the molecular strong-field approximation with gauge transformation analysis, incorporating nonlocal pseudopotentials, saddle-point equations, and multi-center recombination effects. Full article

It is recognized that a ship’s performance, speed, fuel consumption, and resistance are impacted by the marine environment. The magnitude of this effect, which can be altered by ship design and operational conditions, necessitates added resistance calculations for optimizing these phases. Ship designers can generate efficient hull forms and operators can make sound navigational decisions to reduce emissions within the service zone. For this research, air and wave resistances were calculated using the KCS hull form with a superstructure during a simulated voyage in the North Pacific Ocean. To verify the results, data from towing tank tests available in the literature were used, along with calm water resistance calculations obtained from a computational fluid dynamics (CFD) analysis conducted for this study. When transporting 3600 loaded containers, sea conditions at model-scale impact the ship’s power requirements, leading to air resistance from the superstructure (aerodynamic) and hull resistance from head waves. This research compares the increased wave and air resistance with calm water resistance to provide important insights into the main engine power requirements when traveling in this region. Cruising between 14 and 18 knots generates 8–11% added resistance when encountering head waves at Sea State 5. Full article

Background/Objectives: Accurate intraocular lens (IOL) power calculation is vital for achieving the desired postoperative spherical equivalent (SE) in cataract surgery. Generative Artificial-Intelligence (AI) systems are increasingly being used in ophthalmology to refine diagnostic and surgical planning. However, it is still unknown whether a low-cost, easily accessible generative AI model like DeepSeek can match the accuracy of conventional biometric formulas. To evaluate the accuracy of DeepSeek, an open-source generative artificial intelligence (AI), in predicting postoperative refractive spherical equivalent compared to the Barrett Universal II formula in uncomplicated cataract surgeries. Methods: This study analyzed biometric data from 50 eyes of 50 patients who underwent cataract surgery between July 2024 and January 2025 at Humanitas Research Hospital in Milan, Italy. Only uncomplicated cases of emmetropia with Alcon AcrySof^® SA60WF IOL implantation were included. 30–40 days postoperative subjective refraction was measured with a calibrated trial-frame and 6 m logMAR chart by an experienced optometrist. Prediction error (PE), median absolute error (MedAE), standard deviation (SD), and cumulative frequency of PE diopters range were calculated. A Wilcoxon signed-rank test was performed to assess statistical significance. Results: Barrett showed MedAE 0.36 D [0.16–0.64] and MAE 0.43 D (95% CI, 0.34–0.52) while DeepSeek-R1 showed MedAE 0.76 D [0.52–1.01] and MAE 0.77 D (95% CI, 0.67–0.87). Cumulative accuracy (AE threshold) at ±0.25/±0.50/±0.75/±1.00/±1.25/±1.50/±1.75 D was 37.7/71.7/81.1/92.5/100.0/100.0/100.0% for Barrett Universal II and 11.1/25.9/50.0/74.1/88.9/96.3/100.0% for DeepSeek-R1 (McNemar p < 0.01 at each threshold). The paired comparison of per-eye absolute errors favored Barrett (Wilcoxon signed-rank test, p < 0.0001). Conclusions: In this cohort, Barrett Universal II outperformed DeepSeek-R1 across MedAE/MAE and cumulative accuracy thresholds, with a significant paired difference. A general-purpose generative model used off-the-shelf (fixed A-constant, no ophthalmology-specific tuning) did not match the accuracy of a validated vergence-based formula; established formulas remain the reference standard for clinical IOL power calculation. Full article

Building energy consumption accounts for a significant portion of total society energy use, and photovoltaic technology is being rapidly deployed across the construction sector. In order to improve the efficiency with which photovoltaic shading devices capture solar energy, a numerical calculation model for the ideal tilt angle of these devices is constructed in this study. This model is based on clear-sky solar radiation calculation algorithms and solar radiation resources across different latitudes. In order to maximize solar radiation collection, an ideal control strategy for photovoltaic shading devices on buildings with varied orientations at different latitudes and in different months is derived through numerical simulations. The findings demonstrate that the building’s orientation has a significant role in determining how well photovoltaic shading systems use solar energy. In winter, the ideal tilt angle for south-facing facades increases by 10° for every 10° increase in latitude. And for every 25° rise in latitude, the ideal tilt angle increases by only around 10° in summer. By applying optimal regulatory strategies, solar radiation consumption efficiency of roughly 65% can be attained, providing a reference basis for boosting power generating efficiency and building energy saving. Full article

This study presents the development, purification, and performance evaluation of a biogas-powered electricity generation system designed for medium-scale swine farms. A conventional Hino V-22C diesel engine was modified to operate in spark-ignition mode using purified biogas with methane content ranging from 65 to 70%, obtained through a PSA upgrading system. The compression ratio was reduced from 18.5:1 to 14.7:1 to accommodate the lower heating value and combustion characteristics of biogas. An oxygen-sensor-based emergency fuel supply (EFS) system was integrated, activating when λ > 19.0 and deactivating when λ < 17.0, to enhance combustion stability under high-load operation. The corrected higher heating value (HHV ≈ 20–21 MJ/kg) and consistent fuel mass flow rate (0.036 kg/s) were used for revised thermodynamic calculations. Field testing over 524 operating hours demonstrated stable power generation between 80 and 120 kW. The EFS system increased thermal efficiency by approximately 22.7%, achieving a peak efficiency of 11.66% at 100 kW. A techno-economic assessment, including sensitivity analysis (±20% biogas yield and ±10% electricity price), confirmed economic viability with a breakeven period of 15.79 months. The system offers a reliable and scalable renewable energy solution for agricultural applications, contributing to methane mitigation and improved waste-to-energy utilization. Full article

This article evaluates and develops a thermodynamic steady-state model, analyzing the thermodynamic properties of ammonia–ionic liquid (NH₃–IL) working pairs for use in high-temperature (>100 °C) absorption heat pumps. Given the increasing need for energy savings and reductions in greenhouse gas emissions, this is becoming an important consideration in the context of industrial facilities. Prior work on ammonia–ionic liquid (IL) pairs has largely focused on lower supply temperatures and offers no quantitative criteria connecting IL properties to high-temperature (>100 °C) cycle design. This article presents calculations based on correlations in the literature to determine the vapor pressures of pure ionic liquids using a modified Redlich–Kwong equation of state; the vapor–liquid equilibrium (VLE) of NH₃/[emim][SCN] and NH₃/H₂O mixtures in the NRTL model; the specific heats of pure ionic liquids (ILs); the specific heat capacities of NH₃–IL and NH₃–H₂O mixtures; and the excess enthalpy (HE) for NH₃/[emim][SCN] and NH₃/[emim][EtSO₄] as a function of temperature and composition, using a combination of NRTL + Gibbs–Helmholtz and Redlich–Kister polynomials. The calculations confirm the practically zero volatility of ionic liquids in the generator. This preserves the high purity of the ammonia vapor above the NH₃/[emim][SCN] solution (y₁ ≥ 0.997 over a wide range of temperatures and concentrations) and enables the rectification process in the generator to be omitted. The specific heat capacity of pure ionic liquids (ILs) has been shown to be 52–63% lower than that of water. Mixtures of ammonia (NH₃) and ILs with a mass fraction of 0.5/0.5 have a specific heat at 120 °C that is 34–37.5% lower than that of the ammonia–water (NH₃–H₂O) solution. This directly translates into a reduction in the power required in the generator. Excess enthalpy results show moderate or strongly negative values within the useful temperature and concentration range, indicating the exothermic nature of the mixture. At the same time, the NH₃/[emim][EtSO₄] mixture is characterized by a decrease in enthalpy with increasing temperature, suggesting that benefits for the COP of the system can be obtained. Based on these calculations, criteria for selecting ionic liquids for use in high-temperature absorption pumps were formulated: negligible volatility, a low specific heat capacity for the mixture, and a strongly negative excess enthalpy, which decreases with temperature, at the operating temperatures of the absorber and generator. Full article

Domestic dogs can sense the geomagnetic field (GMF), spontaneously aligning their bodies along its axis, altering the alignment’s pattern during geomagnetic disturbances. Whether anthropogenic magnetic fields (MF) from high-voltage power lines (PL) influence this behavior remains unclear. We investigated the effects of alternating MF generated by PL on spontaneous magnetic alignment in 36 dogs. Behavior was recorded under north–south (NS) and east–west (EW) oriented PL and compared with control conditions lacking anthropogenic MF. Each dog’s mean alignment angle relative to magnetic north was calculated from >50 measurements per condition, and Grand Means (GMs) were derived. Under control geomagnetically calm conditions, alignment was bimodal (GM = 23°/203°), while geomagnetic storms caused significant shifts and increased angular dispersion. Under NS-oriented PL, alignment remained bimodal (GM = 5°/185°), but under EW-oriented PL it became trimodal (Likelihood ratio test for multimodality: nodes = 3, p = 0.042; GM = 103°/283°). These differences were statistically significant (LME for linearized angles: p < 0.001 for control vs. NS PL and control vs. EW PL). Our results demonstrate that dogs maintain directional alignment under PL exposure, with orientation patterns corresponding to the direction of both MF and PL, which suggests a potentially complex impact involving non-magnetic cues. Full article

Scientific planning and optimal development of multi-type power sources are critical prerequisites for supporting the robust evolution of emerging power systems. However, existing techno-economic evaluation methods often face challenges such as higher-order uncertainty and weight conflicts, making it difficult to provide reliable support for comparing and selecting power source schemes. To address this, this paper proposes an improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on Fermatean Fuzzy Sets (FFS) for techno-economic evaluation of multi-type power sources. First, building on the traditional TOPSIS framework, we introduce Fermatean Fuzzy Sets to construct a FF Hybrid Weighted Distance (FFHWD) measure. This measure simultaneously captures the subjective importance of evaluation indicators and decision-makers’ risk preferences. Second, we design a subjective-objective coupled weighting strategy integrating Fuzzy Analytic Hierarchy Process (FAHP) and Entropy Weight Method (EWM) to achieve dynamic weight balancing, effectively mitigating biases caused by single weighting approaches. Finally, the FFHWD is integrated into the improved TOPSIS framework by defining FF positive and negative ideal solutions. The comprehensive closeness coefficients of each power source scheme are calculated to enable robust ranking and optimal selection of multi-type power source alternatives. Empirical analysis of five representative power generation technologies—thermal power, hydropower, wind power, photovoltaics (PV), and energy storage—demonstrates the following comprehensive techno-economic ranking: hydropower > photovoltaics > thermal power > wind power > energy storage. Hydropower achieves the highest closeness coefficient (−0.4198), whereas energy storage yields the lowest value (−2.8704), effectively illustrating their respective advantages and limitations within the evaluation framework. This research provides scientific decision-making support and methodological references for optimizing multi-type power source configurations and planning new power systems. Full article

Traditionally, the development and optimisation of photocatalytic materials have relied on experimental approaches and density functional theory (DFT) calculations. Although these methods have driven significant scientific progress, they are increasingly constrained by high computational costs, lengthy development cycles, and limited scalability. In recent years, machine learning (ML) has emerged as a powerful and sustainable alternative, offering a data-driven framework that accelerates materials discovery through rapid and accurate property prediction. This review highlights the essential components of the ML workflow data collection, feature engineering, model selection, and validation while exploring its application in predicting photocatalytic properties. It further discusses recent advances in forecasting key characteristics such as band edge positions, charge carrier mobility, and surface reactivity using both supervised and unsupervised ML techniques. Persistent challenges, including data scarcity, model interpretability, and generalisability, are also addressed, alongside potential strategies to improve the robustness and reliability of ML-driven materials design. By combining high prediction accuracy with superior computational efficiency, ML holds the potential to revolutionise high-throughput screening and guide the systematic development of next-generation photocatalysts. Full article

In this study, the operation features of a transformerless voltage divider, with transistor–diode commutation of switchable capacitors, designed to operate as a part of low-power autonomous electronic systems with reduced output voltage are studied both theoretically and experimentally. The analysis is carried out for a divider operation with a constantly or periodically connected voltage source V₀ with unlimited power. It is found that the divider’s efficiency during operation with a constantly connected primary voltage source V₀ with unlimited power is very low. However, the efficiency can reach 60% during the divider’s operation using a periodically connected voltage source V₀ with unlimited power. It has been shown that the efficiency can only reach 40% in the case of using a voltage source with limited power connected to the divider periodically. It has been established that for circuits with transistor–diode commutation of the capacitors, the stabilization effect is much stronger than for circuits with diode commutation of the capacitors. Therefore, an excess of the maximum load voltage relative to the expected value V₀/N is significantly lower for transistor–diode commutation in comparison with diode commutation (N is the number of divider stages). Based on the ideas developed regarding the divider operation, analytical expressions are obtained, enabling us to calculate the parameters of the studied divider circuits in a wide range. The good agreement between the analytical estimations and experimental data suggests that these calculations adequately describe the operation of the dividers, and that the derived analytical expressions can be successfully used during the preliminary design stage. In general, the analysis carried out herein and the developed approach make it possible to significantly narrow the range of search for the necessary system parameters when designing voltage dividers. Full article

The Former General Electric Utility in Japan is a major participant in the electricity market. The integrated operational capabilities of these power companies have significant impacts on the stable development and sustainability of the power industry. This study evaluates the comprehensive operational capabilities of these power companies from 2003 to 2015 and analyzes the indicators that may affect their operational capabilities. Establishing an evaluation index system comprising five subsystems, namely profitability, management, solvency, growth, and scale, and optimizing it using principal component analysis. The Technique for Order of Preference by Similarity to Ideal Solution was utilized to calculate the relative closeness of each company, with a score representing the integrated operational capabilities. Furthermore, coupling coordination and grey correlation analyses were conducted to assess the internal coordination among subsystems and to identify critical drivers of sustainable performance. The results show that (1) the Kyushu Electric Power Company and Tohoku Electric Power Company have strong integrated operational capabilities. (2) The five evaluation subsystems of integrated operational capability during the period of 2003–2015, fluctuated between moderate and high levels. (3) The top 5 indicators with the highest average grey correlation are as follows: “Hydropower capacity factor”, “Operating cash flow to current liabilities ratio”, “Operating profit growth rate”, “Net profit growth rate”, “Total capital utilization”. This study contributes to the sustainable management of the electricity industry by providing a systematic and data-driven assessment framework. The findings offer practical insights for optimizing corporate governance, enhancing energy efficiency, and formulating policy measures that support the long-term sustainability and competitiveness of Japan’s power utilities. Full article

To determine the optimal arrangement of vertical-axis wind turbines (VAWTs) within wind farms, we previously developed a technique (method-1) that constructs a flow field based on two-dimensional (2D) velocity data derived from computational fluid dynamics (CFD) simulations. In this study, we introduce an improved approach (method-2), which follows the same fundamental concept as method-1 but incorporates a more efficient algorithm for generating the flow field. Comparative analyses confirmed that method-2 produces results equivalent to those of method-1 while significantly reducing computational time and cost. Method-2 reduces the computation time of method-1 by approximately 50% for parallel layouts (θ = 0°) and up to 60% for slanted layouts (θ = ±45°). Using method-2, we further investigated the performance of a wind farm composed of eight VAWT rotors arranged in a linear configuration under the assumption of a 2D flow. The results highlighted two important aspects. First, the predicted power output is unaffected by the order in which the flow fields are superimposed during calculation; second, the method exhibits high sensitivity to even small variations in rotor placement within the layout when the spacings between rotors are short. Additionally, we examined how rotor spacing affects the distribution of power generation across the rotor array. These findings of this study validate the efficiency of method-2 and offer practical insights for designing optimized VAWT layouts. Full article

Accurate trend prediction of valve internal leakage is crucial for the safe and economical operation of thermal power units. To address the issues of prediction lag and insufficient accuracy in existing methods when dealing with the dynamic changes in internal leakage, this paper proposed an Improved Autoregressive Integrated Moving Average–Generalized Autoregressive Conditional Heteroskedasticity (IARIMA-GARCH) method that integrated Multi-Time-Scale Decomposition, an Improved ARIMA (IARIMA) model, and an Improved GARCH (IGARCH) model for accurate prediction of drain valve internal leakage. First, using a Multi-Time-Scale Decomposition method based on sampling at different time intervals, the original valve internal leakage time series were reconstructed into three characteristic subsequences—short-term, medium-term, and long-term—to capture the evolutionary features at various time scales. Then, an IARIMA model, employing the Huber loss function for robust parameter estimation, was constructed as the leakage prediction model to effectively suppress the interference of outliers. Simultaneously, an IGARCH model was built as the leakage volatility prediction model by introducing the previous moment’s volatility to correct the current residual, establishing a feedback mechanism between the mean and volatility equations, thereby enhancing the characterization of volatility clustering. Finally, using a weight coefficient dynamic calculation method based on RMSE, the Multi-Time-Scale prediction results of each subsequence were fused to obtain the final predicted valve internal leakage. Taking the main steam drain valve of a thermal power plant as the research object, and using Mean Absolute Error (MAE), Root-Mean-Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and symmetric Mean Absolute Percentage Error (sMAPE) as evaluation metrics, a case study on trend prediction of drain valve internal leakage was conducted, comparing the proposed method with ARIMA, Long Short-Term Memory networks (LSTM) and eXtreme Gradient Boosting (XGBoost) methods. The results showed that compared to ARIMA, LSTM and XGBoost, the proposed IARIMA-GARCH method achieved the lowest values on error metrics such as Mean Absolute Error (MAE), Root-Mean-Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and symmetric Mean Absolute Percentage Error (sMAPE), and its Coefficient of Determination (R²) is closest to 1. The standardized residual sequence most closely resembled a white noise sequence with zero mean and unit variance, and its distribution was the closest to a normal distribution. This proved that the IARIMA-GARCH method possessed higher prediction accuracy, stronger dynamic adaptability, and superior statistical robustness, providing an effective solution for valve condition prediction and predictive maintenance. Full article

A proactive power compensation strategy applicable to achieving transient ride-through of ship microgrid (SM) under pulsed load is presented in this paper. The essence of this strategy can be summarized as the generator enters a transient process when a large portion of the pulsed load is connected to the islanded microgrid. Next, the pulsed load power is calculated and predicted over a 20 ms time scale based on the changes in stator current, stator voltage, excitation current and excitation voltage during the process. As a result, the predicted power is used as the control desired value of the compensation device to ensure that the microgrid recovers the power balance and achieves transient ride-through. Finally, the proposed control strategy not only replaces the one machine infinite bus (OMIB) with the transient model of the SG but also utilizes the energy storage device to actively guide the generator to output the differential power in the microgrid. The power response time of the compensation system is in the range of 6–20 ms, which is able to realize the transient ride-through of the SG within one cycle. Full article

China’s expressways generate substantial carbon emissions annually. To mitigate these emissions, this study explores the deployment of photovoltaic (PV) modules in the available areas of expressway service areas. As critical energy consumption nodes along the expressway network, service areas offer notable advantages for PV deployment compared to other highway segments, including ease of management, cost-effectiveness, and reduced transmission losses. However, the scattered distribution of service areas—many of which are located in mountainous and complex terrains—poses significant challenges to accurately assessing their PV potential. To address this issue, this study develops a spatiotemporal model to evaluate the solar photovoltaic power generation potential of expressway service areas across China. First, national service area coverage is determined using highway network data. Second, digital elevation model (DEM) data are used to estimate hourly shadow areas caused by surrounding terrain; solar radiation within these shadowed regions is assumed to be zero. Finally, by integrating ground-based solar radiation data with a radiation estimation model, the PV potential of service areas in each province is calculated. The model integrates expressway service area data, high-resolution digital elevation models, and ground-based solar radiation datasets to simulate spatially and temporally resolved irradiance conditions, enabling accurate estimation of photovoltaic potential at the provincial and national scales. Based on data from approximately 3225 expressway service areas as of the end of 2022, the results indicate an annual photovoltaic potential of 1400.72 TW, with an estimated installable capacity of 51.85 GW, yielding an annual electricity generation of 66.37 TWh. The southeastern regions, particularly Guangdong Province, exhibit greater PV potential due to their higher density of service areas, compared to the northwestern regions. Nationwide adoption of PV systems in expressway service areas is projected to reduce carbon emissions by 48.85 million tons. This study provides a valuable reference for regional planning and suitability assessment of PV expressway infrastructure development in China. Moreover, this study provides a novel spatiotemporal assessment framework and the first national-scale case study of PV potential in expressway service areas, offering valuable guidance for highway energy planning and low-carbon infrastructure development in China. Full article