Search Results (806)

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

This paper presents a novel design for precise vertical landing of drones based on the detection of three phase shifts in the range of ±180°. The design has three inputs to which the signal transmitted from an oscillator located at the landing point arrives with different delays. The circuit increases the aerial tracking volume relative to that achieved by detectors with theoretical unambiguous detection ranges of ±90°. The phase shift measurement circuit uses an analog phase detector (mixer), detecting a maximum range of ±90°and a double multiplication of the input signals, in phase and phase-shifted, without the need to fulfill the quadrature condition. The calibration procedure, phase detector curve modeling, and calculation of the input signal phase shift are significantly simplified by the use of an automatic gain control on each branch, dwhich keeps input amplitudes to the analog phase detectors constant. A simple program to determine phase shifts and guidance instructions is proposed, which could be integrated into the same flight control platform, thus avoiding the need to add additional processing components. A prototype has been manufactured in C band to explain the details of the procedure design. The circuit uses commercial circuits and microstrip technology, avoiding the crossing of lines by means of switches, which allows the design topology to be extrapolated to much higher frequencies. Calibration and measurements at 5.3 GHz show a dynamic range greater than 50 dB and a non-ambiguous detection range of ±180°. These specifications would allow one to track the drone during the landing maneuver in an inverted cone formed by a surface with an 11 m radius at 10 m high and the landing point, when 4 cm between RF inputs is considered. The errors of the phase shifts used in the landing maneuver are less than ±3°, which translates into 1.7% losses over the detector theoretical range in the worst case. The circuit has a frequency bandwidth of 4.8 GHz to 5.6 GHz, considering a 3 dB variation in the input power when the AGC is limiting the output signal to 0 dBm at the circuit reference point of each branch. In addition, the evolution of phases in the landing maneuver is shown by means of a small simulation program in which the drone trajectory is inside and outside the tracking range of ±180°. Full article

The non-uniform thermal distribution in the active neutral-point clamped (ANPC) topology causes significant thermal gradients during high-power operation, restricting its use in large-capacity power conversion systems like variable-speed pumped storage. This study introduces a novel hybrid fundamental frequency modulation strategy. Through a dynamic allocation mechanism based on a reference signal, this strategy alternates inner and outer power switches at the fundamental frequency, ensuring balanced switching frequency across devices. Consequently, it effectively mitigates the inherent loss imbalance in conventional ANPC topologies. Quantitative analysis using a power device loss model shows that, compared to conventional carrier phase-shift modulation, the proposed method reduces total system losses by 39.98% and improves the loss-balancing index by 18.27% over inner-switch fundamental frequency modulation. A multidimensional validation framework, including an MW-level hardware platform, numerical simulations, and test data, was established. The results confirm the proposed strategy’s effectiveness in improving power device thermal balance. Full article

This paper presents a complete workflow for the evaluation of GaN transistors in voltage source inverters. With the associated high switching speed of transistors based on GaN, it is important to consider some critical points in the design phase as well as in the measurement setup in order to be able to utilise and verify the advantages of GaN properly. For this reason, the presented circuit board’s design focuses on a minimised power loop inductance. Simulation models, an analytical approach and measurement results with the aim of determining this inductance are compared with each other. A good compliance results between the presented methods. Additionally, the description of a test bench is given, which enables the performance of the opposition method. This setup allows the measurement of the designed H-bridge’s arising losses and the GaN-transistor’s switching behaviour. In comparison to the conventional double pulse method, this approach enables results that are more accurate for determining losses. Full article

This paper presents an accurate analysis of the power losses of an interior permanent magnet synchronous motor fed by a cascaded H-bridge multilevel inverter. The main goal of this study is to investigate the impact of the cascaded h-bridge inverter, multicarrier PWM strategies, and inverter switching frequency on the synchronous motor power losses. With this aim in mind, a detailed frequency domain power analysis was carried out on motor power losses at different operating points in the frequency–torque plane. Motor power losses were further categorized into fundamental and harmonic power losses. This evaluation involved driving the power converter using six distinct multicarrier PWM strategies at four different switching frequencies. Additionally, a comparison was conducted with a conventional two-level PWM inverter to quantify the reduction in motor power losses. The experimental results show that the cascaded h-bridge inverter guarantees a notable increase in the motor efficiency, up to 7%, and losses in segregation at the fundamental frequency, if compared to the standard two-level PWM inverter, especially at low speed and with partial-load conditions. Such results mark out the cascaded H-bridge inverter as a valuable choice, also with regard to low-voltage drive applications. Full article

Analyzing and measuring the similarity between two signals is a common task in many vibration-based structural health monitoring applications. Coherence between input and response signals serves as a convenient indicator of damage, based on the premise that nonlinearity due to damage in a linear system manifests as a loss of coherence in specific frequency bands. Because input excitations in civil structures are difficult to measure, damage indicators based on the coherence between two response signals have been developed. These indicators have shown promise in detecting nonlinear behavior in structures that were initially linear. This paper proposes a new damage indicator based on Mutual Information, a nonlinear extension of the squared correlation coefficient, to quantify the similarity between two signals without making assumptions about the nature of their interactions or the underlying dynamics of the system. Mutual Information is distinguished from other nonlinear similarity metrics due to its ability to capture all types of nonlinear dependencies, its high computational efficiency, and its invariance to invertible transformations, such as scaling. The proposed approach is demonstrated using a standard dataset containing experimental data from a three-story aluminum frame structure under 17 different damage states. The results show that the proposed metric can detect deviations from the baseline state due to changes in mass, stiffness, or newly induced nonlinear behavior, suggesting its potential for monitoring changes in the structural system. Full article

Monitoring the peak junction hotspot temperature in IGBT modules is critical for ensuring the reliability of high-power industrial multilevel inverters, particularly when operating under extreme thermal conditions, such as in traction applications. This study presents a comprehensive chip-level analytical loss and thermal model for estimation of the peak junction hotspot temperature in a three-level T-type neutral-point-clamped (TNPC) IGBT module. The developed model includes a detailed analytical assessment of conduction and switching losses, along with transient thermal network modeling, based on the actual electrical and thermal characteristics of the IGBT module. Additionally, a hybrid thermal–electrical stress experimental setup, designed to replicate real operating conditions, was implemented for a balanced three-phase inverter circuit utilizing a Semikron three-level IGBT module, with testing currents reaching 100 A and a critical case temperature of 125 °C. The analytically estimated module losses and peak junction hotspot temperatures were validated through direct experimental measurements. Furthermore, thermal simulations were conducted with Semikron’s SemiSel benchmark tool to cross-validate the accuracy of the thermo-electrical model. The outcomes show a relative estimation error of less than 1% when compared to experimental data and approximately 1.15% for the analytical model. These findings confirm the model’s accuracy and enhance the reliability evaluation of TNPC-IGBT modules in extreme thermal environments. Full article

In recent years, the rapid spread of electric vehicles (EVs) has intensified the competition to develop power units for EVs. In particular, improving the driving range of EVs has become a major topic, and in order to achieve this, many studies have been conducted on improving the efficiency of EV power units. In this study, we propose a multiple-inverter-drive permanent magnet synchronous motor based on an 8-pole, 48-slot structure, which is commonly used as an EV motor. The proposed motor is composed of two completely independent parallel inverters and windings, and intermittent operation is possible; that is, only one inverter and one parallel winding is used depending on the situation. In the proposed motor, we compare losses including stator iron loss, rotor iron loss, and magnet eddy current loss by PWM voltage inputs for some stator winding topologies, we show that the one-side winding arrangement is the most efficient during intermittent operation, and that it is more efficient than normal operation especially in the low-speed, low-torque range. Finally, through a vehicle-driving simulation considering the efficiency map including motor loss and inverter loss, we show that the intentional use of intermittent operation can improve electrical energy consumption. Full article

Sugarcane is mostly planted in rows, and the accurate identification of crop rows is important for the autonomous navigation of agricultural machines. Especially in the elongation period of sugarcane, accurate row identification helps in weed control and the removal of ineffective tillers in the field. However, sugarcane leaves and stalks intertwine and overlap at this stage. They can form a complex occlusion structure, which poses a greater challenge to target detection. To address this challenge, this paper proposes an improved target detection method, SugarRow-YOLO, based on the YOLOv11n model. The method aims to achieve accurate sugarcane identification and provide basic support for subsequent sugarcane row detection. This model introduces the WTConv convolutional modules to expand the sensory field and improve computational efficiency, adopts the iRMB inverted residual block attention mechanism to enhance the modeling capability of crop spatial structure, and uses the UIOU loss function to effectively mitigate the misdetection and omission problem in the region of dense and overlapping targets. The experimental results show that SugarRow-YOLO performs well in the sugarcane target detection task, with a precision of 83%, recall of 87.8%, and mAP₅₀ and mAP_50-95 of 90.2% and 69.2%. In addition to addressing the problem of large variability in row spacing and plant spacing of sugarcane, this paper introduces the DBSCAN clustering algorithm and combines it with a smooth spline curve to fit the crop rows in order to realize the accurate extraction of crop rows. This method achieved 96.6% in the task, with high precision in sugarcane target detection and demonstrates excellent accuracy in sugarcane row fitting, offering robust technical support for the automation and intelligent advancement of agricultural operations. Full article

This work explored an electrochemical approach for synthesizing lanthanum-modified nickel oxide (NiO_x:La) as a hole transport layer (HTL) in inverted perovskite solar cells (IPSCs). By varying the La³⁺ concentration, the chemical, charge transport, structural, and morphological properties of the NiO_x:La film and the HTL/PVK interface were evaluated to enhance photovoltaic performance. X-ray photoelectron spectroscopy (XPS) confirmed La³⁺ incorporation, a higher Ni³⁺/Ni³⁺ ratio, and a valence band shift, improving p-type conductivity. Electrochemical impedance spectroscopy and Mott–Schottky analyses indicated that NiO_x:La 0.5% exhibited the lowest resistance and the highest carrier density, correlating with higher recombination resistance. The NiO_x:La 0.5% based cell achieved a PCE of 20.08%. XRD and SEM confirmed no significant changes in PVK structure, while photoluminescence extinction demonstrated improved charge extraction. After 50 days, this cell retained 80% of its initial PCE, whereas a pristine NiO_x device retained 75%. Hyperspectral imaging revealed lower optical absorption loss and better homogeneity. These results highlight NiO_x:La as a promising HTL for efficient and stable IPSCs. Full article

Printed circuit board (PCB) defect detection faces challenges like small target feature loss and severe background interference. To address these issues, this paper proposes PCES-YOLO, an enhanced YOLOv11-based model. First, a developed Pre-convolution Receptive Field Enhancement (PRFE) module replaces C3k in the C3k2 module. The ConvNeXtBlock with inverted bottleneck is introduced in the P4 layer, greatly improving small-target feature capture and semantic understanding. The second key innovation lies in the creation of the Efficient Feature Fusion and Aggregation Network (EFAN), which integrates a lightweight Spatial-Channel Decoupled Downsampling (SCDown) module and three innovative fusion pathways. This achieves substantial parameter reduction while effectively integrating shallow detail features with deep semantic features, preserving critical defect information across different feature levels. Finally, the Shape-IoU loss function is incorporated, focusing on bounding box shape and scale for more accurate regression and enhanced defect localization precision. Experiments on the enhanced Peking University PCB defect dataset show that PCES-YOLO achieves a mAP50 of 97.3% and a mAP50–95 of 77.2%. Compared to YOLOv11n, it shows improvements of 3.6% in mAP50 and 15.2% in mAP50–95. When compared to YOLOv11s, it increases mAP50 by 1.0% and mAP50–95 by 5.6% while also significantly reducing the model parameters. The performance of PCES-YOLO is also evaluated against mainstream object detection algorithms, including Faster R-CNN, SSD, YOLOv8n, etc. These results indicate that PCES-YOLO outperforms these algorithms in terms of detection accuracy and efficiency, making it a promising high-precision and efficient solution for PCB defect detection in industrial settings. Full article

Recently, active impedance inverters based on non-Foster negative capacitors have been proposed for applications in widely tunable filters. These designs use a traditional Linvill’s topology of the negative capacitor. Unfortunately, the range of external loads needed for the stable operation of such active inverters is rather limited. However, there is also the negative capacitor based on a recently proposed loss-compensated passive structure. This novel design promises stability-robust behavior for an extremely wide range of external loads. In this study, we compare the stability properties of both approaches and show that the design based on the loss-compensated passive structure is more robust. Full article

This paper presents a compact, high-efficiency electromagnetic transmitter for Controlled-source Audio-frequency Magnetotelluric (CSAMT) applications, operating in the 10–100 kHz range. A novel bipolar square-wave inverter topology is proposed, which directly modulates the transformer’s secondary-side AC output, eliminating conventional rectification and filtering stages. This design reduces system losses (simulated efficiency > 90%) and achieves an approximately 40% reduction in both volume and weight. The power stage uses a full-bridge bipolar inverter topology with SiC-MOSFETs, combined with a high-frequency transformer for voltage gain. Simulation, laboratory testing, and EMI evaluation confirm stable square-wave generation and full compliance with EN55032 Class A standards. Field validation with a CSAMT receiver demonstrates effective signal transmission and high-resolution subsurface imaging, thereby improving the efficiency and portability of urban geophysical exploration. Full article

In the last decade, countries have experienced increased solar radiation, leading to an increase in the use of solar photovoltaic (PV) systems to boost renewable energy generation. However, the high solar penetration into these systems can disrupt the normal operation of the distribution grid. Thus, a major concern is the impact of these units on power quality indices. To improve these units, one approach is to design more efficient power inverters. This study introduces a pulse width modulation (PWM) technique for multilevel power inverters, employing a sine wave as the carrier wave and an amplitude over-modulated triangular wave as the modulator (PSTM-PWM). The proposed technique improves the waveform quality and increases the AC voltage output of the multilevel inverter compared with that from conventional PWM techniques. In addition, it ensures compliance with the EN50160 standard. These improvements are achieved with a lower modulation order than that used in traditional techniques, resulting in reduced losses in multilevel power inverters. The proposed approach is then implemented using a five-level cascaded H-bridge inverter. In addition, a comparative analysis of the efficiency of multilevel power inverters was performed, contrasting classical modulation techniques with the proposed approach for various modulation orders. The results demonstrate a significant improvement in both total harmonic distortion (THD) and power inverter efficiency. Full article

This study focuses on estimating the unknown parameters and the reliability function of the inverted-Weibull distribution, using an improved adaptive progressive Type-II censoring scheme under a competing risks model. Both classical and Bayesian estimation approaches are explored to offer a thorough analysis. Under the classical approach, maximum likelihood estimators are obtained for the unknown parameters and the reliability function. Approximate confidence intervals are also constructed to assess the uncertainty in the estimates. From a Bayesian standpoint, symmetric Bayes estimates and highest posterior density credible intervals are computed using Markov Chain Monte Carlo sampling, assuming a symmetric squared error loss function. An extensive simulation study is carried out to assess how well the proposed methods perform under different experimental conditions, showing promising accuracy. To demonstrate the practical use of these methods, a real dataset is analyzed, consisting of the survival times of male mice aged 35 to 42 days after being exposed to 300 roentgens of X-ray radiation. The analysis demonstrated that the inverted Weibull distribution is well-suited for modeling the given dataset. Furthermore, the Bayesian estimation method, considering both point estimates and interval estimates, was found to be more effective than the classical approach in estimating the model parameters as well as the reliability function. Full article