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As tower cranes (TC) getting more use in the construction process, a reliable TC energy consumption calculation model is increasingly required for construction management. This paper proposed a semi-empirical model, which is based on the division of TC work cycle. For fitting the coefficients, Partial Least Squares Regression (PLSR) was adopted. To simplify the model, variables with weak regression significance to energy consumption were deleted in turn. The best suitable version achieves a Mean Absolute Percentage Error of 25.55%, a Root Mean Square Error (RMSE) of 1036.19 kJ, and a Coefficient of Determination (R 2 ) of 0.83, with just one independent variable. A comparative analysis showed the proposed model had the highest accuracy and fitting degree among all the models for TC energy consumption calculation. Through physical transformation of the proposed model, several key engineering parameters (i.e., load mass, number of work cycles, and hoisting height) affecting TC energy consumption were extracted. The innovation of this empirical study lies in confirming the feasibility of the stage-based calculation model and the small sample fitting strategy, providing new ideas of constructing and optimizing energy consumption models for other construction machinery. At the same time, the proposed model lays a foundation for research related to TC energy consumption to be more reliable.

Purpose To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy. Methods Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non‐small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th‐percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R‐squared values were used to determine the best metric. Results Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites. Conclusion Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.

Purpose. To elaborate the customized principle of determining the actual zone of the corneal astigmatism based on keratotopographic data and compare the accuracy of calculating the toric IOL according to the actual zone and conventional keratometry. Material and methods. The study included 48 patients (48 eyes) who underwent toric IOL implantation. 3–6 months (5.1±0.6) after surgery, all patients were measured the residual refractive astigmatism. The toric IOL was retrospectively calculated according to the data of the actual keratotopographic zone determined by the proposed method (1st group) and according to conventional keratometry (2nd group). Vector and centroid analyses were used to estimate the error in calculating the IOL toricity. Results. The principles of determining the actual zone are based on the assumption that maximum visual acuity and visual quality can be achieved when the regularity of astigmatism in the central parts of the cornea corresponds to the regularity of toric IOL. The mean diameter of the selected actual zone was 2.93±0.61 (from 2.0 to 4.3 mm respectively). The average vector error of toricity calculation in 1st group was 0.30±0.31, in 2nd group – 0.42±0.30 (p=0.006). Centroid analysis showed similar values of centroid error in 1st group and 2nd group (0.09 and 0.08), while the dispersion was higher in 2nd group (0.42 and 0.51, respectively). Conclusion. The customized principle of selecting the actual zone according to topographic maps of the cornea showed a more accurate calculation of the IOL toricity compared with the use of conventional keratometry data. Key words: toric IOL, corneal astigmatism, IOL calculation accuracy, keratometry, keratotopography

The roll deformation model of the six-high rolling mill is one of the core models of the strip shape control theory. The influence function method (IFM) is a numerical method applied to solve the roll deformation problem. This study aims to address the problems of slow calculation speed and insufficient calculation accuracy of IFM in calculating the roll deformation of the six-high rolling mill. Three optimization measures are proposed, namely, optimizing the iterative calculation order of the roll deformation to improve the calculation efficiency; introducing the Adam (Adaptive Moment Estimation) gradient descent optimization algorithm to enhance the stability of the iterative process; and introducing a high-precision rolling force model based on the XGBoost (eXtreme Gradient Boosting) algorithm to improve the calculation accuracy of flatness in the IFM. Parallel experimental results show that by applying the three optimization measures simultaneously, improving the iterative calculation order of the roll deformation can improve the calculation speed by about 7.64 times; introducing the Adam algorithm can reduce the oscillation range of roll contact pressure by an average of 50.4%, increasing the stability of the calculation process; and introducing a high-precision rolling force model based on the XGBoost algorithm can improve the flatness calculation accuracy by about 39.1%. This study provides an effective method to improve the calculation speed and accuracy of the roll deformation in a six-high rolling mill, which has important academic application value.

Background and purpose The AAPM TG‐43 formalism has long served as the clinical standard for brachytherapy dose calculation but assumes a homogeneous water equivalent medium, overlooking limited scattering conditions and tissue heterogeneities. Model‐based dose‐calculation algorithms (MBDCAs), including Monte Carlo (MC) simulations overcome these limitations by accounting for real tissue composition, scatter, and applicator attenuation. This systematic review evaluates TG‐43, MBDCAs/MC methods in terms of dosimetric accuracy, validation strategies, computational feasibility, clinical implementation barriers, and emerging innovations. Methods A PRISMA‐guided literature search was conducted using the Scopus database, identifying 284 records, of which 42 full‐text studies met inclusion criteria. Eligible studies compared at least two of the three dose‐calculation approaches (TG‐43, MBDCAs and MCs) in pelvic, breast, or head‐and‐neck brachytherapy. Extracted data encompassed dosimetric discrepancies, validation approaches, computational performance, workflow integration, and enabling technologies. Results Across anatomical sites, TG‑43 showed no consistent bias. Its differences from heterogeneity‑aware models depended on tissue composition, scatter conditions, and source geometry. In soft‑tissue regions with minimal heterogeneity, TG‑43 generally overestimated target coverage by about 0.5%–5%. Near low‑density interfaces or in reduced‑scatter configurations, TG‑43 could instead yield lower doses than Monte Carlo or MBDCAs. For OARs, discrepancies were site‑specific: skin dose was often overestimated, while other organs showed smaller or opposite variations. Overall, MBDCAs and Monte Carlo agreed with experimental or benchmark data within roughly 3% and produced more reliable biological metrics. GPU‑accelerated and deep‑learning engines reduced computation times from hours to seconds, shifting remaining challenges toward standardization, commissioning, and QA. Successful clinical adoption relied on TG‑186–aligned validation, staff training, and integrated automated workflows. Conclusion Evidence from the systematic review supports a clinical transition toward TG‐186–compliant, heterogeneity‐aware dose‐calculation frameworks. MBDCAs/MC algorithms provide superior dosimetric and radiobiological accuracy and are increasingly compatible with adaptive and biologically guided planning. Broad implementation is now supported by established QA standards and benchmarking datasets, which connects dosimetric precision with patient outcomes. The transition beyond TG‐43 marks a pivotal step toward precision, safety, and personalization in modern brachytherapy.

The whale optimization algorithm (WOA) is a swarm intelligence optimization algorithm developed by Mirjalili and Lewis in 2016 based on the foraging behavior of whales. Because of its simplicity and high efficiency, scholars have adopted this algorithm to address various problems in different disciplines. However, standard WOA has the problems of slow convergence speed, insufficient search accuracy, and limited ability to solve complex problems. In order to solve these problems, this paper proposes a multi-strategy hybrid whale algorithm (MHWOA). Firstly, the calculation speed is accelerated by modifying the parameters; then, the accuracy of the algorithm is improved by incorporating the scatter search strategy; finally, the simulated annealing algorithm is integrated to improve its ability to solve complex problems. The performance differences between MHWOA, the baseline algorithm, and the improved WOA algorithm are compared using the CEC2017 test suite and three real-world engineering problems. In the comparison of processing results of various problems, the calculation accuracy of MHWOA is improved by no less than 1.96%, the calculation error is reduced by no less than 1.83%, and the execution time is improved by no less than 5.6%. In the CNN-MHWOA-based time series electricity load forecasting problem, MHWOA shows the advantages of reduced error and improved fitting degree with the true value compared with the standard WOA.

Background We evaluated whether 16-bit CT reconstruction with explicit CT-to-electron-density (CT-to-ED) calibration improves dose-calculation accuracy versus conventional 12-bit reconstruction in the presence of metallic implants, and whether geometric metrics can identify cases that benefit most. Methods CT-to-ED tables were built for both bit depths. In Solid Water, dose profiles and absolute dose were compared against EBT4 film and TG-51 ion-chamber measurements. Eight clinical IMRT plans were optimized and cross-recalculated between bit-depth domains with segments and monitor units fixed. A beam–metal interaction metric, η metal (monitor-unit–weighted beam’s-eye-view overlap), and the volumetric overlap ratio (VOR) between metal and PTV were computed. Gamma passing rate (GPR, 3 mm/3%), mean gamma, profile error, and absolute-dose deviation were evaluated. Results In the phantom, 16-bit improved agreement over 12-bit, yielding higher GPR, profile differences ≤ 2%, and absolute-dose errors ≤ 1.0%; 12-bit showed profile errors up to 5.4% (stainless steel) and 3.0% (titanium) and absolute-dose errors of 2.3% and 1.7%. In patients, η metal  > 35% was associated with GPR < 90% when 12-bit plans were recalculated on 16-bit, whereas low η metal maintained ≥ 90%. η metal correlated positively with VOR and negatively with GPR, supporting pre-treatment triage via VOR. Conclusions Extended-bit reconstruction mitigates HU saturation, improves RED assignment, and yields better agreement with measurements and calculation. These findings support adopting 16-bit CT with CT-to-ED calibration as the default for planning and verification in patients with metallic implants, with VOR or η metal flagging cases where benefit is greatest.

The objective of this study is to evaluate the applicability of the most widely used closed-form ground-return impedance formulas in short-circuit analyses of distribution systems and to identify the critical network configurations in which the choice of impedance model significantly affects the short-circuit results. The methodology adopted in this research is organized into three stages. First, an algorithm was developed to implement and compare several closed-form Earth-return impedance formulations, and its performance was validated using benchmark data reported in the literature. Second, a short-circuit analysis algorithm was designed and verified against reference results published by the IEEE Power and Energy Society. Finally, multiple short-circuit studies were performed on several IEEE distribution test feeders. The findings reveal that most closed-form Earth-return impedance models provide adequate accuracy for both balanced and unbalanced short-circuit analyses. However, for single-phase line-to-ground faults, the choice of closed-form impedance formulation is critical to obtaining accurate short-circuit results. El objetivo de este estudio es evaluar la aplicabilidad de las principales fórmulas cerradas de impedancia de retorno por tierra en el análisis de cortocircuito de sistemas de distribución, así como identificar las configuraciones críticas en las cuales la elección del modelo de impedancia puede influir significativamente en los resultados del cortocircuito. La metodología adoptada en esta investigación se estructura en tres etapas. Primero, se desarrolló un algoritmo para implementar y comparar las formulaciones cerradas de impedancia de retorno por tierra, el cual fue validado con datos de referencia disponibles en la literatura. Segundo, se diseñó un algoritmo de análisis de cortocircuito que fue verificado con resultados publicados por la IEEE Power and Energy Society. Finalmente, se realizaron múltiples estudios de cortocircuito en varios alimentadores de prueba de distribución del IEEE. Los resultados muestran que la mayoría de las formulaciones cerradas de impedancia de retorno por tierra son adecuadas tanto para análisis de cortocircuito balanceados como desbalanceados, y que, en fallas monofásicas a tierra, la elección de la fórmula cerrada de impedancia resulta un factor crítico para obtener resultados precisos.

This study evaluated the calculation accuracy of the stopping power ratio (SPR) using dual-energy computed tomography with fast kilovoltage switching (FKSCT) for particle therapy. A tissue characterization phantom with various reference materials was scanned to obtain single-energy computed tomography (SECT) images and generate virtual monochromatic images at 77 keV (VMI ) and 140 keV (VMI ), water density (WD) images, and effective Z (Z ) images. For SECT, VMI and VMI lookup tables were generated to convert the measured Hounsfield value into the theoretical SPR for a normal phantom size. Subsequently, the reference materials were scanned in small and large phantoms. The SPR was calculated using the lookup tables of SECT (SPR ) images, VMI (SPR ), and VMI (SPR ), and it was derived from the WD and Z (SPR ). In the normal-sized phantom, the overall mean difference between SPR and theoretical SPR was -0.3%, and remained below 2% for most reference materials. For the large phantom, the overall mean absolute difference for SPR (3.0%, p=0.006) and SPR (3.2%, p=0.002) for the reference materials was significantly lower than that for SPR (5.9%). For the small phantom, a significant reduction in the mean difference in the SPR calculation was observed in SPR (1.0%, p=0.001) and SPR (1.1%, p=0.013) compared with SPR (2.2%). VMI generated using FKSCT significantly improves the estimation accuracy of SPR compared with SECT. Thus, FKSCT may be used to improve the dose calculation accuracy for treatment planning of particle therapy.

Numerical simulation is becoming an important research method in the field of supersonic flow. Its accuracy and reliability have always been the key to its further application and the focus of current researches. In this study, a series of numerical simulations of transverse supersonic jet in supersonic free flow are carried out based on Reynolds averaged (RANS) solver. Firstly, the flow field structure obtained by different calculation cases is studied, and the mechanism of the difference of flow field structure is described. Furthermore, by changing the accuracy of difference scheme for the convection term and the turbulence model, the different simulation results are compared with the experimental data. The deviation from numerical simulation compared with the experiment is further analyzed to clarify the critical factors affecting the calculation reliability. The results show that improving the accuracy of the scheme cannot effectively improve the calculation results, while choosing an appropriate turbulence model can be helpful to improve the calculation accuracy. When the numerical simulation of jet flow mixing in supersonic flow field is carried out, the conclusions of this study can provide a support for determining the numerical model method and error analysis.