Search Results (333)

Under the background of “dual-carbon” strategy and global energy transition, the metallurgical industry, which accounts for 15–20% of industrial energy consumption, urgently needs to reduce the energy consumption and emission of DC power supply of electric furnaces. Aiming at the existing 400–800 V/≥3000 A industrial-frequency transformer-rectifier system with low efficiency, large volume, heat dissipation difficulties and other bottlenecks, this thesis proposes and realizes a high-frequency integrated DC power supply scheme for high-power electric furnaces: high-frequency transformer core and rectifier circuit are deeply integrated, which breaks through and reduces the volume of the system by more than 40%, and significantly reduces the iron consumption; multiple cores and three windings in parallel are used for the system. The topology of multiple cores and three windings in parallel enables several independent secondary stages to share the large current of 3000 A level uniformly, eliminating the local overheating and current imbalance; the combination of high-frequency rectification and phase-shift control strategy enhances the input power factor to more than 0.95 and cuts down the grid-side harmonics remarkably. The authors have completed the design of 100 kW prototype, magneto-electric joint simulation, thermal structure coupling analysis, control algorithm development and field comparison test, and the results show that the program compared with the traditional industrial-frequency system efficiency increased by 12–15%, the system temperature rise reduced by 20 K, electrode voltage increased by 10–15%, the input power of furnace increased by 12%, and the harmonic index meets the requirements of the traditional industrial-frequency system. The results show that the efficiency of this scheme is 12–15% higher than the traditional IF system, the temperature rise in the system is 20 K lower, the voltage at the electrode end is 10–15% higher, the input power of the furnace is increased by 12%, and the harmonic indexes meet the requirements of GB/T 14549, which verifies the value of the scheme for realizing high efficiency, miniaturization, and reliable DC power supply in metallurgy. Full article

This study evaluates the performance and energy trade-offs of three popular data processing libraries—Pandas, PySpark, and Polars—applied to GreenNav, a CO₂ emission prediction pipeline for urban traffic. GreenNav is an eco-friendly navigation app designed to predict CO₂ emissions and determine low-carbon routes using a hybrid CNN-LSTM model integrated into a complete pipeline for the ingestion and processing of large, heterogeneous geospatial and road data. Our study quantifies the end-to-end execution time, cumulative CPU load, and maximum RAM consumption for each library when applied to the GreenNav pipeline; it then converts these metrics into energy consumption and CO₂ equivalents. Experiments conducted on datasets ranging from 100 MB to 8 GB demonstrate that Polars in lazy mode offers substantial gains, reducing the processing time by a factor of more than twenty, memory consumption by about two-thirds, and energy consumption by about 60%, while maintaining the predictive accuracy of the model (R² ≈ 0.91). These results clearly show that the careful selection of data processing libraries can reconcile high computing performance and environmental sustainability in large-scale machine learning applications. Full article

Molecular dynamics (MD) simulations have been performed on the energetics, mechanical properties, and irradiation response of seventy-three 3C-SiC symmetric tilt grain boundaries (STGBs) with three tilt axes (<100>, <110> and <111>). The effect of GB characteristics on the STGB properties has been investigated. The GB energy is positively and linearly correlated with the excess volume, but the linearity in SiC is not as good as in metals, which stems from the inhomogeneous structural relaxation near GBs induced by orientation-sensitive covalent bonding. For <110>STGBs, the shear strength exhibits symmetry with respect to the misorientation angle of 90°, which is consistent with ab initio calculations for Al in similar shear orientations. Cascades are performed with 8 keV silicon as the primary knock-on atom (PKA). No direct correlation is found between the sink efficiency of GBs for defects and GB characteristics, which comes from the complexity of the diatomic system during the recovery phase. For GBs with smaller values of Σ, the GBs exhibit a weaker blocking effect on the penetration of irradiated defects, resulting in a lower number of defects in GBs and a higher number of total surviving defects. In particular, it is seen that the percentage decrease in tensile strength after irradiation is positively correlated with the Σ value. Taken together, these results help to elucidate the impact of GB behavior on the mechanical properties of as well as the primary irradiation damage in SiC and provide a reference for creating improved materials through GB engineering. Full article

Encryption and decryption are essential components in signal processing and optical communication systems, providing data confidentiality, integrity, and secure high-speed transmission. We present a novel design and simulation of an all-optical encryption and decryption system operating at 120 Gb/s using carrier reservoir semiconductor optical amplifiers (CR-SOAs) embedded in Mach–Zehnder interferometers (MZIs). The architecture relies on two consecutive exclusive-OR (XOR) logic gates, implemented through phase-sensitive interference in the CR-SOA-MZI structure. The first XOR gate performs encryption by combining the input data signal with a secure optical key, while the second gate decrypts the encoded signal using the same key. The fast gain recovery and efficient carrier dynamics of CR-SOAs enable a high-speed, low-latency operation suitable for modern photonic networks. The system is modeled and simulated using Mathematica Wolfram, and the output quality factors of the encrypted and decrypted signals are found to be 28.57 and 14.48, respectively, confirming excellent signal integrity and logic performance. The influence of key operating parameters, including the impact of amplified spontaneous emission noise, on system behavior is also examined. This work highlights the potential of CR-SOA-MZI-based designs for scalable, ultrafast, and energy-efficient all-optical security applications. Full article

The core objective of racehorse breeding is to enhance the speed and endurance of the horses. The Grassland-Thoroughbred is an emerging horse breed developed in northern China in recent years, characterized by excellent speed performance, enduring stamina, and strong environmental adaptability. However, research on the genetic characteristics within this breed and the genes associated with athletic performance remains relatively limited. We conducted whole-genome resequencing of Grassland-Thoroughbred F1, F2, F3, and the crossbred population (CY) and obtained a total of 4056.23 Gb of high-quality data after quality control. The single nucleotide polymorphisms (SNPs) were primarily distributed in intergenic regions, followed by intronic regions. Principal component analysis (PCA) and STRUCTURE revealed clear distinctions among the generations, with a notable overlap between CY and F3. Using the SNP dataset, we analyzed the number and length distribution patterns of runs of homozygosity (ROHs) in the genomes of different generational groups of Grassland-Thoroughbreds. Short ROHs ranging from 0.5 to 2 Mb were the most abundant, with the following distribution: F1 (85.15%) > F2 (82.92%) > CY (78.75%) > F3 (77.51%). Medium-length ROHs (2–8 Mb) and long ROHs (>8 Mb) together exhibited a similar but opposite trend. The average length of ROHs was 1.57 Mb. The inbreeding coefficients (F_ROH) among different generational groups of Grassland-Thoroughbreds were as follows: F1 (0.0942) < F2 (0.1197) < CY (0.1435) < F3 (0.1497). Through ROH island analysis, 10 high-frequency ROH regions were identified and annotated with 120 genes. Genomic regions and candidate genes associated with athletic traits—ACAD8, OPCML, PRDX2, NTM, NDUFB7, SCL25A15, FOXO1, and SLC4A10—were identified. These genes may play important roles in regulating muscle performance, mitochondrial energy supply, and learning and memory processes in horses and are closely associated with the athletic ability of the Grassland-Thoroughbred population. This study is the first to systematically characterize the genomic diversity and inbreeding dynamics of the Grassland-Thoroughbred during the breeding process. It identifies candidate genes that may influence athletic performance, thereby providing an important molecular foundation and theoretical basis for the genetic improvement and performance-based selection of this emerging breed. Full article

Forecasting future solar power plant production is essential to continue the development of photovoltaic energy and increase its share in the energy mix for a more sustainable future. Accurate solar radiation forecasting greatly improves the balance maintenance between energy supply and demand and grid management performance. This study assesses the influence of input selection on short-term global horizontal irradiance (GHI) forecasting across two contrasting Algerian climates: arid Ghardaïa and coastal Algiers. Eight feature selection methods (Pearson, Spearman, Mutual Information (MI), LASSO, SHAP (GB and RF), and RFE (GB and RF)) are evaluated using a Gradient Boosting model over horizons from one to six hours ahead. Input relevance depends on both the location and forecast horizon. At t+1, MI achieves the best results in Ghardaïa (nMAE = 6.44%), while LASSO performs best in Algiers (nMAE = 10.82%). At t+6, SHAP- and RFE-based methods yield the lowest errors in Ghardaïa (nMAE = 17.17%), and RFE-GB leads in Algiers (nMAE = 28.13%). Although performance gaps between methods remain moderate, relative improvements reach up to 30.28% in Ghardaïa and 12.86% in Algiers. These findings confirm that feature selection significantly enhances accuracy (especially at extended horizons) and suggest that simpler methods such as MI or LASSO can remain effective, depending on the climate context and forecast horizon. Full article

The research reviews and contrasts two studies based on the gas-phase reaction OH + D₂(v, j). In these studies, Quasi-Classical Trajectory (QCT) calculations and the Gaussian Binning (GB) technique were used on the Wu–Schatz–Lendvay–Fang–Harding (WSLFH) potential energy surface. Large sample sizes allow for precise energy state distribution analysis across translational, vibrational, and rotational components in the products. A key observation is the influence of the vibrational and rotational excitation of D₂ on the total angular momentum (J′) of the HOD* product. This study reveals that increasing the vibrational level, vD₂, significantly shifts P(J′) distributions toward higher values, broadening them due to increased isotropy. In contrast, increasing the rotational level, jD₂, results in a smaller shift but introduces greater anisotropy, leading to a more selective distribution of J′ values. The dual Gaussian Binning selection—Vibrational-GB followed by Rotational-GB—further highlights a preference for either odd or even J′ values, depending on the specific excitation conditions. These findings have implications for the development of chemical lasers, as the excitation and emission properties of HOD* can be leveraged in the laser design. Future research aims to extend this study to a broader range of initial conditions, refining the understanding of reaction dynamics in controlled gas-phase environments. Full article

This study explores the application of machine learning (ML) techniques—gradient boosting (GB), ridge regression (RR), and support vector regression (SVR)—for estimating the consumption of energy (CE) and Blaine fineness (BF) in cement clinker grinding. This study utilizes key clinker grinding parameters, such as maximum ball size, ball filling ratio, clinker mass, rotation speed, and number of revolutions, as input features. Through comprehensive preprocessing, feature selection methods (mutual info regression (MIR), lasso regression (LR), and sequential backward selection (SBS)) were employed to identify the most significant variables for predicting CE and BF. The performance of the models was optimized using a grid search for hyperparameter tuning and validated using k-fold cross-validation (k = 10). The results show that all ML methods effectively estimated the target parameters, with SVR demonstrating superior accuracy in both CE and BF predictions, as evidenced by its higher R² and lower error metrics (MAE, MAPE, and RMSE). This research highlights the potential of ML models in optimizing cement grinding processes, offering a novel approach to parameter estimation that can reduce experimental effort and enhance production efficiency. The findings underscore the advantages of SVR, making it the most reliable method for predicting energy consumption and Blaine fineness in clinker grinding. Full article

Reduced Beam Sections (RBS) are used in steel design to promote ductile behavior by shifting inelastic deformation away from critical joints, enhancing seismic performance through controlled energy dissipation. While current design guidelines assist in detailing RBS connections, moment–rotation curves—essential for understanding energy dissipation—require extensive testing and/or modeling. Machine learning (ML) offers a promising alternative for predicting these curves, yet few studies have explored ML-based approaches, and none, to the best of the authors’ knowledge, have applied Explainable Artificial Intelligence (XAI) to interpret model predictions. This study presents an ML framework using Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machines (SVM), Gradient Boosting (GB), and Ridge Regression (RR) trained on 500 numerical models to predict the moment–rotation backbone curve of RBS connections under cyclic loading. Among all the models applied, the ANN obtained the highest R² value of 99.964%, resulting in superior accuracy. Additionally, Shapley values from XAI are employed to evaluate the influence of input parameters on model predictions. The average SHAP values provide important insights into the performance of RBS connections, revealing that cross-sectional characteristics significantly influence moment capacity. In particular, flange thickness (t_f), flange width (b_f), and the parameter “c” are critical factors, as the flanges contribute the most substantially to resisting bending moments. Full article

Commercial herbal compounds are a main attractive target to explore for a novel drug for the treatment of HSV. This study investigated the anti-HSV infectivity of extracts derived from the Thai commercial herbals Kerra^TM, KS^TM, and Minoza^TM. Wild-type HSV-1 KOS, HSV-2, and drug-resistant HSV-1 dxpIII were used to investigate any inhibitory effects of these extracts. A plaque formation assay was performed to investigate the effects of all extracts. The viral ICP4, UL30, gD, and gB and cellular IL1β, IL6, STAT3, and NFKB1 expression levels were evaluated. The Kerra^TM, KS^TM, and Minoza^TM extracts at 50–200 μg/mL significantly inhibited HSV-1 KOS and dxpIII infection in the post-entry step, whereas only Minoza^TM could not reduce plaque formation of HSV-2. In addition, ICP4, UL30, and gD mRNAs and gB protein were significantly decreased in Kerra^TM- and KS^TM-treated cells. Furthermore, IL1B, IL6, STAT3, and NFKB1 expression was upregulated in Kerra^TM- and KS^TM-treated cells. Kerra^TM and KS^TM could be agents against HSV infection, especially the HSV acyclovir (ACV)-resistant strain. From the docking result and drug-likeness prediction, 2-Methoxy-9H-xanthen-9-one, piperine, and sargassopenilline D found in Kerra^TM, KS^TM, and Minoza^TM show high binding energy closely resembling ACV, and are desirable as drug-like characteristics. Full article

Precision air conditioning (PAC) systems are prone to various types of failures, leading to inefficiencies, increased energy consumption, and possible reductions in equipment performance. This study proposes an automatic real-time fault detection and diagnosis system. It classifies events as either faulty or normal by analyzing key status signals such as pressure, temperature, current, and voltage. This research is based on data-driven models and machine learning, where a specific strategy is proposed for five types of system failures. The work was carried out on a Rittal PAC, model SK3328.500 (cooling unit), installing capacitive pressure sensors, Hall effect current sensors, electromagnetic induction voltage sensors, infrared temperature sensors, and thermocouple-type sensors. For the implementation of the system, a dataset of PAC status signals was obtained, initially consisting of 31,057 samples after a preprocessing step using the Random Under-Sampler (RUS) module. A database with 20,000 samples was obtained, which includes normal and failed operating events generated in the PAC. The selection of the models is based on accuracy criteria, evaluated by testing in both offline (database) and real-time conditions. The Support Vector Machine (SVM) model achieved 93%, Decision Tree (DT) 93%, Gradient Boosting (GB) 91%, K-Nearest Neighbors (KNN) 83%, and Naive Bayes (NB) 77%, while the Random Forest (RF) model stood out, having an accuracy of 96% in deferred tests and 95.28% in real-time. Finally, a validation test was performed with the best-selected model in real time, simulating a real environment for the PAC system, achieving an accuracy rate of 93.49%. Full article

Based on the resource conservation requirements of GB/T 50378-2019 “Green Building Evaluation Standard”, this study constructed a BIM–Ecotect collaborative analysis model and proposed a “four-dimensional integration” green performance optimization method. Taking a high-rise office building in Wuhan as an example, a LOD 300-level Revit building information model was established, and a multidisciplinary collaborative analysis was achieved through gbXML data interaction. The lighting simulation results show that the average natural lighting coefficient of the office area facing south is 2.4 (the standard 85%), while in the meeting room area, due to the optimized design of the curtain wall, the average natural lighting coefficient has increased to 2.6 (the standard 92%). In terms of energy-saving renovation, a three-dimensional collaborative design strategy was adopted. Through the optimization of the envelope structure, the cooling load of the air conditioning system was reduced by 25.3%, and the heat load was reduced by 23.6% (the u value of the exterior wall was reduced by 56.3%, the SHGC of the exterior windows was reduced by 42.9%, and the thermal resistance of the roof was increased by 150%). The ventilation optimization adopts the CFD flow field reverse design, adjusting the window opening rate of the exterior windows from 15% to 20% to form a turbulent diffusion effect. Therefore, the air change rate in the office area reached 2.5 times per hour, and the CO₂ concentration decreased by up to 27.1% at most. The innovative adoption of the “composite sound insulation curtain wall” technology in acoustic environment control has increased the indoor noise compliance rate by 27 percentage points (from 65% to 92%). The above research data indicate that digital collaborative design can achieve an overall energy-saving rate of over 20% for buildings, providing a replicable technical path for enhancing the performance of green buildings. Full article

Ti-6Al-4V (Ti64) is widely used in the additive manufacturing (AM) industry for its superior mechanical properties; however, severe anisotropy is inevitable. In this work, a Ti64 sample fabricated using laser-directed energy deposition is used for fundamental investigations into the anisotropy of its microstructure, mechanical properties, and fracture behaviors. The microstructure of martensite α and prior β-Ti grains are characterized in both the XOY and XOZ planes. The tensile/compressive properties and microhardness along the building direction (BD) and scanning direction (SD) are tested, and it is found that the sample along the SD has better comprehensive mechanical properties. Due to grain boundary α (GB-α), different fracture behaviors and crack propagation paths are found along the BD and SD. When tensile force is parallel to the growth orientation of GB-α, a much higher density of microcracks caused by fractured GB-α is found to contribute to a prolonged elongation and the weakening of strength. While stretching along the SD, the cracks would propagate along the GB-α easily and straightly, which might lead to lower elongation. Full article

It is anticipated that by 2028 there will be a significant increase in the use of HWHP systems in Great Britain (GB). Such systems are considered a better, energy-efficient alternative to fossil fuel-based burners and furnaces, as they use electricity. There are concerns that these systems are susceptible to microbial contamination because they hold water at lower temperatures. In particular, the concern is regarding Legionella contamination, as it can potentially cause disease in the general public and those who are maintaining and replacing these systems. Therefore, this review was focused on understanding the potential risk posed by their increased use and maintenance requirements. This review was approached systematically but was not a full systematic review. There were 61 papers that were considered potentially relevant to the research questions. Of these, 40 papers were considered relevant to the topic of Legionella in HWHP and underwent full article assessment and data extraction. The remaining papers were considered useful for background information. The scope of this review established that Legionella are a known risk in hot water systems that can be carried over to HWHP systems, yet there is minimal evidence to suggest that the current control measures are being appropriately applied to reduce the risk of exposure. When considering countrywide legislation and guidance, it appears that the risk is considered lower in single- or multi-family homes that do not require a centralised system. This review included the assessment of information regarding the safety of working with HWHP systems with regards to maintenance and replacement. The authors found a lack of information regarding these safety concerns. This review is among the first to systematically evaluate the risks of Legionella contamination in HWHP systems. Full article

An energy- and area-efficient non-return-to-zero (NRZ) transmitter with feedforward equalization (FFE) is proposed for an extra-short-reach (XSR) data interface in chiplet-based system in packages (SiPs) and multi-chip modules (MCMs). At the system level, the final-stage 2:1 multiplexer (MUX) in the transmitter is combined with the driver to reduce the hardware and power consumption; at the circuit level, charge-steering-based moderate-swing signal processing further reduces the circuit power consumption and inter-symbol interference. Fabricated in a 28 nm CMOS process with a core area of 0.032 mm², the prototype NRZ transmitter demonstrates an energy efficiency of 0.42 pJ/b at a data rate of 50 Gb/s with an insertion loss of 10 dB, which makes it a promising candidate for XSR die-to-die (D2D) interfaces. Full article