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Abstract Background Accurately redirecting reconstructed Positron emission tomography (PET) images into short-axis (SA) images shows great significance for subsequent clinical diagnosis. We developed a system for automatic redirection and quantitative analysis of myocardial PET images. Methods A total of 128 patients were enrolled for 18 F-FDG PET/CT myocardial metabolic images (MMIs), including 3 image classifications: without defects, with defects, and excess uptake. The automatic reorientation system includes five modules: regional division, myocardial segmentation, ellipsoid fitting, image rotation and quantitative analysis. First, the left ventricular geometry-based canny edge detection (LVG-CED) was developed and compared with the other 5 common region segmentation algorithms, the optimized partitioning was determined based on partition success rate. Then, 9 myocardial segmentation methods and 4 ellipsoid fitting methods were combined to derive 36 cross combinations for diagnostic performance in terms of Pearson correlation coefficient (PCC), Kendall correlation coefficient (KCC), Spearman correlation coefficient (SCC), and determination coefficient. Finally, the deflection angles were computed by ellipsoid fitting and the SA images were derived by affine transformation. Furthermore, the polar maps were used for quantitative analysis of SA images, and the redirection effects of 3 different image classifications were analyzed using correlation coefficients. Results On the dataset, LVG-CED outperformed other methods in the regional division module with a 100% success rate. In 36 cross combinations, PSO-FCM and LLS-SVD performed the best in terms of correlation coefficient. The linear results indicate that our algorithm (LVG-CED, PSO-FCM, and LLS-SVD) has good consistency with the reference manual method. In quantitative analysis, the similarities between our method and the reference manual method were higher than 96% at 17 segments. Moreover, our method demonstrated excellent performance in all 3 image classifications. Conclusion Our algorithm system could realize accurate automatic reorientation and quantitative analysis of PET MMIs, which is also effective for images suffering from interference.

Background: Accurately redirecting reconstructed Positron emission tomography (PET) images into short-axis (SA) images shows great significance for subsequent clinical diagnosis. We developed a system for automatic redirection and quantitative analysis of myocardial PET images. Methods: A total of 128 patients were enrolled for 18 F-FDG PET/CT myocardial metabolic images (MMIs), including 3 image classifications: without defects, with defects, and excess uptake. The automatic reorientation system includes five modules: regional division, myocardial segmentation, ellipsoid fitting, image rotation and quantitative analysis. First, the left ventricular geometry-based canny edge detection (LVG-CED) was developed and compared with the other 5 common region segmentation algorithms, the optimized partitioning was determined based on partition success rate. Then, 9 myocardial segmentation methods and 4 ellipsoid fitting methods were combined to derive 36 cross combinations for diagnostic performance in terms of Pearson correlation coefficient (PCC), Kendall correlation coefficient (KCC), Spearman correlation coefficient (SCC), and determination coefficient. Finally, the deflection angles were computed by ellipsoid fitting and the SA images were derived by affine transformation. Furthermore, the polar maps were used for quantitative analysis of SA images, and the redirection effects of 3 different image classifications were analyzed using correlation coefficients. Results: On the dataset, LVG-CED outperformed other methods in the regional division module with a 100% success rate. In 36 cross combinations, PSO-FCM and LLS-SVD performed the best in terms of correlation coefficient. The linear results indicate that our algorithm (LVG-CED, PSO-FCM, and LLS-SVD) has good consistency with the reference manual method. In quantitative analysis, the similarities between our method and the reference manual method were higher than 96% at 17 segments. Moreover, our method demonstrated excellent performance in all 3 image classifications. Conclusion: Our algorithm system could realize accurate automatic reorientation and quantitative analysis of PET MMIs, which is also effective for images suffering from interference. [ABSTRACT FROM AUTHOR]

Precise navigation in agricultural applications necessitates accurate guidance from the seedling belt, which the Global Positioning System (GPS) alone cannot provide. The overlapping leaves of Chinese cabbage (Brassica pekinensis Rupr.) present significant challenges for seedling belt fitting due to difficulties in plant identification. This study aims to address these challenges by improving the You Only Look Once (YOLO) v7 model with a novel approach that decouples its network head deriving from the Faster-Regions with Convolutional Neural Network (Faster R-CNN) architecture. Additionally, this study introduced a BiFormer attention mechanism to accurately identify the centers of overlapping Chinese cabbages. Using these identified centers and pixel distance verification, this study achieved precise fitting of the Chinese cabbage seedling belt (CCSB). Our experimental results demonstrated a significant improvement in performance metrics, with our improved model achieving a 2.5% increase in mean average precision compared to the original YOLO v7. Furthermore, our approach attained a 94.2% accuracy in CCSB fitting and a 91.3% Chinese cabbage identification rate. Compared to traditional methods such as the Hough transform and linear regression, our method showed an 18.6% increase in the CCSB identification rate and a 17.6% improvement in angle accuracy. The novelty of this study lies in the innovative combination of the YOLO v7 model with a decoupled head and the BiFormer attention mechanism, which together advance the identification and fitting of overlapping leafy vegetables. This advancement supports intelligent weeding, reduces the reliance on chemical herbicides, and promotes safer, more sustainable agricultural practices. Our research not only improves the accuracy of overlapping vegetable identification, but also provides a robust framework for enhancing precision agriculture. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During the operation of the power transmission line tower foundation, uneven settlement and horizontal sliding were formed due to the damage of the local environment or external force. It is the most direct and effective way to realize the transformation from “passive response” to “active prevention and control” by real-time and long-term monitoring of the tower foundation and providing automatic early warning. In this paper, based on FBG (fiber Bragg grating) sensing technology, a FBG flexible sensor with temperature self-compensation characteristic was developed, which can be used for real-time monitoring of three-dimensional deformation field of tower foundation. Based on the strain information measured by the sensor, a coordinate transformation fitting algorithm was applied to reconstruct the deformation field of the tower foundation. To improve the displacement sensing precision of the flexible sensor, the influence of the length of the cemented layer and the groove radius on the strain transfer coefficient was analyzed, and the orthogonal curvature obtained by the sensing point was corrected by cubic spline interpolation. In the displacement sensing experiment, the mean absolute errors along the x-axis direction after interpolation correction were 1.84 mm (Type 1), 1.52 mm (Type 2) and 1.96 mm (Type 3), respectively; the mean absolute errors along the y-axis direction were 1.64 mm (Type 1), 2.34 mm (Type 2) and 1.21 mm (Type 3), respectively. After interpolation correction, the maximum absolute error percentages of the measuring points along the x-axis were 9.62% (Type 1), 9.01% (Type2) and 10.23% (Type 3); the maximum absolute error percentages along the y-axis were 10.44% (Type 1), 9.53% (Type2) and 9.43% (Type 3). Therefore, the designed FBG flexible sensor can be competent for the task of monitoring the three-dimensional deformation field of the tower foundation, which has important significance and application promotion value.

With the development of near-eye display technology, optical distortion is often introduced into the design of near-eye optical system to meet people's requirements for high definition and large field of view. However, the larger the field of view, the greater the distortion of the projected image. In order to correct distorted images, this paper proposes an image pre-distortion algorithm based on nonlinear fitting and forward mapping interpolation. The radial basis function fitting algorithm is used to get a more precise mapping relationship between the original image and the pre-distorted image. The compactly supported radial basis function (CSRBF) interpolation algorithm based on forward mapping is used for image gray reconstruction to obtain better correction effect of image distortion. The experimental results show that the fitting error of the radial basis function fitting algorithm can be reduced to less than 1 pixel, reaching sub-pixel level. The pre-distortion algorithm has a good correction effect on the non-rotational symmetry distortion produced by the near-eye optical system, which makes the display image clear and complete. [ABSTRACT FROM AUTHOR]

Copyright of China Rubber Industry is the property of Editorial Office of China Rubber Industry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Large-scale measurements of soil moisture play a critical role in many fields, such as agriculture, hydrology, and engineering. The distributed temperature sensing (DTS) technology, based on a dual-probe heat pulse (DPHP), is a novel approach to realizing large-scale soil moisture estimation. However, the application of the method is limited by the complex optical cable layout, calculation algorithm, and lack of standardized heating strategy. In this paper, an improved DPHP-DTS method considering the soil bulk density was proposed. The measurement accuracy of the DPHP-DTS method under different heating strategies was studied in laboratory experiments, and its long-term stability in regard to the monitoring of soil moisture during natural evaporation in different soils was tested. The results show that the improved DPHP-DTS method can accurately measure the soil moisture, and the fitting algorithm can reduce the error caused by the accuracy of the DTS temperature measurement under the low-power heating strategy. Its measurement accuracy increases with the increase in the heating strength and duration. In addition, the improved DPHP-DTS method can describe soil evaporation in both sand and loess with good reliability and stability. [ABSTRACT FROM AUTHOR]

The import of the majority of soluble peroxisomal proteins is initiated by the interaction between type-1 peroxisomal targeting signals (PTS1) and their receptor PEX5. PTS1 motifs reside at the extreme C-terminus of proteins and consist of a characteristic tripeptide and a modulatory upstream region. Various PTS1-PEX5 interactions have been studied by biophysical methods using isolated proteins or in heterologous systems such as two-hybrid assays, but a recently established approach based on Försters resonance energy transfer (FRET) allows a quantifying investigation in living cells. FRET is the radiation-free energy transfer between two fluorophores in close proximity and can be used to estimate the fraction of acceptor molecules bound to a donor molecule. For PTS1-PEX5 this method relies on the measurement of FRET-efficiency between the PTS1-binding TPR-domain of PEX5 tagged with mCherry and EGFP fused to a PTS1 peptide. However, this method is less suitable for binding partners with low affinity and protein complexes involving large proteins such as the interaction between full-length PTS1-carrying cargo proteins and PEX5. To overcome this limitation, we introduce a life-cell competition assay based on the same FRET approach but including a fusion protein of Cerulean with the protein of interest as a competitor. After implementing the mathematical description of competitive binding experiments into a fitting algorithm, we demonstrate the functionality of this approach using known interaction partners, its ability to circumvent previous limitations of FRET-measurements and its ability to study the interaction between PEX5 and its full-length cargo proteins. We find that some proteins (SCP2 and AGXT) bind PEX5 with higher affinity than their PTS1-peptides alone, but other proteins (ACOX3, DAO, PerCR-SRL) bind with lower but reasonable affinity, whereas GSTK1 binds with very low affinity. This binding strength was not increased upon elongating the PEX5 TPR-domain at its N-terminus, PEX5(N-TPR), although it interacts specifically with the N-terminal domain of PEX14. Finally, we demonstrate that the latter reduces the interaction strength between PEX5(N-TPR) and PTS1 by a dose-dependent but apparently non-competitive mechanism. Altogether, this demonstrates the power of this novel FRET-based competition approach for studying cargo recognition by PEX5 and protein complexes including large proteins in general.

A multi-surface phase demodulation algorithm is proposed to measure surfaces of the transparent plate simultaneously. A non-linear least-squares method based on the trust region is utilized to fit the window function derived from the characteristic polynomials. The fitted window function requires fewer parameters and has a flexible form, which means the window length can be stretched freely and used flexibly. Then, a multi-surface phase demodulation technique combining the discrete Fourier principle and the fitted window function is investigated, allowing simultaneous reconstruction of the measured front surface, rear surface, and thickness variation. During the implementation of our algorithm, the processing time for the interferograms with 850×850 pixels is around 5.1s. Measurement errors caused by several factors are analyzed, including wavelength-tuning error, frequency order error, cavity length error, and average thickness error. The experimental result on a rectangular transparent plate further verifies the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]

Large-scale measurements of soil moisture play a critical role in many fields, such as agriculture, hydrology, and engineering. The distributed temperature sensing (DTS) technology, based on a dual-probe heat pulse (DPHP), is a novel approach to realizing large-scale soil moisture estimation. However, the application of the method is limited by the complex optical cable layout, calculation algorithm, and lack of standardized heating strategy. In this paper, an improved DPHP-DTS method considering the soil bulk density was proposed. The measurement accuracy of the DPHP-DTS method under different heating strategies was studied in laboratory experiments, and its long-term stability in regard to the monitoring of soil moisture during natural evaporation in different soils was tested. The results show that the improved DPHP-DTS method can accurately measure the soil moisture, and the fitting algorithm can reduce the error caused by the accuracy of the DTS temperature measurement under the low-power heating strategy. Its measurement accuracy increases with the increase in the heating strength and duration. In addition, the improved DPHP-DTS method can describe soil evaporation in both sand and loess with good reliability and stability.

Underground target detection technology has been widely used in urban construction and resource exploration. With the development of industrial modernization, the demand for underground target detection is becoming more specific, such as the material and shape of underground targets. Therefore, it is necessary to classify the properties of underground targets. In this paper, sensitivity analysis was performed on the spheroid model and the approximate forward model at first, and the influence of the target properties on the model output is obtained. Secondly, we utilized the fitting algorithm to obtain the model parameters of the simulation data (model response of targets with varying shapes and materials), and analyzed the influence of the fitting algorithm on the classification results at different SNR. Finally, eight machine learning algorithms: support vector machine(SVM), neural network(NN), quadratic discriminant analysis (QDA), Gaussian process (GP), decision tree (DT), random forest (RF) and AdaBoost were used in this study to compare the obtained results. From the above analysis, we found that the shape (radius) have a greater influence on the model than the material (permeability) in the spheroid model. According to the approximate forward model, we found that it is not feasible to classify targets when the orientation is unknown. The influence of the fitting algorithm on the classification performances is related to the noise level. The obtained results using neural network demonstrated that the proposed method outperformed in material-based classification and shape-based classification. In the material-based classification, the classifier generally has a weaker ability to distinguish between permeable materials.

We consider random changepoint segmented regression models to analyse data from a study conducted to verify whether treatment with stem cells may delay the onset of a symptom of amyotrophic lateral sclerosis in genetically modified mice. The proposed models capture the biological aspects of the data, accommodating a smooth transition between the periods with and without symptoms. An additional changepoint is considered to avoid negative predicted responses. Given the nonlinear nature of the model, we propose an algorithm to estimate the fixed parameters and to predict the random effects by fitting linear mixed models iteratively via standard software. We compare the variances obtained in the final step with bootstrapped and robust ones. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The BeiDou Navigation Satellite System (BDS) provides wide area differential service (WADS) for users in China territory by broadcasting equivalent satellite clock, orbit correction, ionospheric grid information and zone correction through Geostationary Earth Orbit (GEO) satellites. By using WADS corrections correctly, users with code observations can get meter-level positioning accuracy while carrier phase users can get decimeter-level result. However, the imperfection and discontinuity of zone correction bring a negative influence upon positioning. Aiming at solving the precision deterioration and positioning reconvergence caused by the discontinuity of zone correction, a fitting algorithm is proposed for zone correction generation and user’s positioning. The fitting algorithm is established on the basis of the stability of double-differenced zone corrections. By fixing the zone correction of one reference satellite and the dou⁃ ble-differenced bias between multiple zones and satellites, the correction gap can be filled up successfully. Then, the validity of the algorithm and the performance of fitting zone correction was evaluated by differential positioning experiments using observations from six Multi-GNSS Experiment (MGEX) stations within zone correction service range under kinematic PPP mode. Experiment results show that although the positioning precision of fitting zone corrections, which is 0.20 m and 0.44 m for horizontal and vertical components respectively, is slightly inferior to the result derived by using the original corrections. In the discontinuous periods of zone correction, the positioning results are much more stable and continuous, and without posi⁃ tioning re-convergence. With no additional information used in correction fitting, the algorithm can be used for the zone correction generation period and position, which will improve the service integrity and positioning reliability. [ABSTRACT FROM AUTHOR]

The acquisition of the oil film pressure and forces on the bearing pads through experimentation is crucial to understanding the characteristics of journal bearing. Lots of efforts had been taken in film pressure measurement, and the pressure was obtained at specified position on the bearing pads. However, due to the space and structure constraint, merely very limited number of the point pressure can be obtained with traditional sensors and acquiring the detail pressure field on whole bearing pad surface is still an open challenge. In this paper, a method based on thin-film sensors technique is proposed and employed to measure the pressure distribution and oil film forces of journal bearings. The measurement is conducted on a cylindrical journal bearing with two axial grooves, and ElectroMechanical Film sensor arrays are designed and laid on the surface of the bearing pads. The oil film pressure is acquired at up to 32 measurement points in total along the bearing pads in both circumference and axial directions. The pressure distribution in a wide rotation speed range is obtained successfully by using fitting algorithm. Furthermore, the oil film forces on horizon and vertical direction are obtained through the integration of the measured pressure filed. The test results prove that it is feasible to measure the oil pressure filed of journal bearings using ElectroMechanical Film piezo-film sensor array. [ABSTRACT FROM AUTHOR]

Purpose: Multileaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and pelvic motion during radiotherapy. The purpose of this work was to characterize the performance of two MLC leaf‐fitting algorithms, direct optimization and piecewise optimization, for real‐time motion compensation with different plan complexity and tumor trajectories. Methods: To test the algorithms, both in silico and phantom experiments were performed. The phantom experiments were performed on a Trilogy Varian linac and a HexaMotion programmable motion platform. High and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient‐measured organ‐specific trajectories. For both MLC leaf‐fitting algorithms, the plans were run with their corresponding patient trajectories. To compare algorithms, the average exposure errors, i.e., the difference in shape between ideal and fitted MLC leaves by the algorithm, plan complexity and system latency of each experiment were calculated. Results: Comparison of exposure errors for the in silico and phantom experiments showed minor differences between the two algorithms. The average exposure errors for in silico experiments with low/high plan complexity were 0.66/0.88 cm2 for direct optimization and 0.66/0.88 cm2 for piecewise optimization, respectively. The average exposure errors for the phantom experiments with low/high plan complexity were 0.73/1.02 cm2 for direct and 0.73/1.02 cm2 for piecewise optimization, respectively. The measured latency for the direct optimization was 226 ± 10 ms and for the piecewise algorithm was 228 ± 10 ms. In silico and phantom exposure errors quantified for each treatment plan demonstrated that the exposure errors from the high plan complexity (0.96 cm2 mean, 2.88 cm2 95% percentile) were all significantly different from the low plan complexity (0.70 cm2 mean, 2.18 cm2 95% percentile) (P < 0.001, two‐tailed, Mann–Whitney statistical test). Conclusions: The comparison between the two leaf‐fitting algorithms demonstrated no significant differences in exposure errors, neither in silico nor with phantom experiments. This study revealed that plan complexity impacts the overall exposure errors significantly more than the difference between the algorithms. [ABSTRACT FROM AUTHOR]

The present study introduces a novel curve-fitting algorithm for surface plasmon resonance (SPR) curves using a self-constructed, wedge-shaped beam type angular interrogation SPR spectroscopy technique. Previous fitting approaches such as asymmetric and polynomial equations are still unsatisfactory for analyzing full SPR curves and their use is limited to determining the resonance angle. In the present study, we developed a sigmoid-asymmetric equation that provides excellent curve-fitting for the whole SPR curve over a range of incident angles, including regions of the critical angle and resonance angle. Regardless of the bulk fluid type (i.e., water and air), the present sigmoid-asymmetric fitting exhibited nearly perfect matching with a full SPR curve, whereas the asymmetric and polynomial curve fitting methods did not. Because the present curve-fitting sigmoid-asymmetric equation can determine the critical angle as well as the resonance angle, the undesired effect caused by the bulk fluid refractive index was excluded by subtracting the critical angle from the resonance angle in real time. In conclusion, the proposed sigmoid-asymmetric curve-fitting algorithm for SPR curves is widely applicable to various SPR measurements, while excluding the effect of bulk fluids on the sensing layer.

Aim: Low signal-to-noise ratio (SNR) images of lung-like (low-density [LD]) gel dosimeters, compared to unit-density (UD) gels, necessitate the use of different quantification methods. Setting and Design: In this study, a new method is introduced based on noise correction and exponential (NCEXP) fitting. The feasibility of NCEXP method for quantifying dose absorption in LD gels is evaluated. Materials and Methods: Sensitivity, dose resolution, detectable dynamic range, and correlation of the calibration curve for both UD and LD gel dosimeters are the parameters, which we analyze to investigate the consequences of new method. Results of NCEXP method are compared to maximum likelihood estimation of rician distribution (MLE-R) and variable echo number (VAREC) quantification methods. Results: Dose response of LD gel dosimeter shows wider detectable dynamic range as compared to UD gel. Using NCEXP method for both LD and UD dosimeter gels, a more sensitive calibration curve with a superior dose resolution is obtained. The advantage of new quantification method is more significant for LD dosimeter gel analysis, where SNR decreases as a result of higher absorbed doses (≥10 Gy). Despite the inverse effect of the VAREC method on detectable dose range of UD gel, no specific changes are observed in dynamic dose range of LD gel dosimeter with different quantification methods. The correlations obtained with different methods were approximately of the same order for UD and LD gels. Conclusion: NCEXP method seems to be more effective than the MLE-R and VAREC methods for quantification of LD dosimeter gel, especially where high-dose absorption and steep-dose gradients exist such as those in intensity-modulated radiation therapy and stereotactic radiosurgery. [ABSTRACT FROM AUTHOR]

Based on the measurement progress of straight through pinholes, the measuring for angular is challenging because the probe is inconvenient to stretch into the pinhole exactly. In the paper, an adjustable five-dimensional system, which is mainly composed of a three-coordinate measuring machine (CMM), a turntable, a visual sensor and a capacitive probe, is employed to accomplish the measurement for a circular workpiece with angular multi-pinholes. The CMM traces the coordinates while the capacitive probe moves, a precise turntable turns the workpiece at desired angle to guarantee the pinhole and the probe in the same orientation. A binocular visual sensor and a capacitive probe is for alignment and measuring, respectively. A comprehensive algorithm of combining projection and the least-squares fitting is put forward for fitting spatial axis equation of 3-D pinholes. Finally, a reliable and entire measurement system is set up and the optimal equation of the spatial axis is obtained. [ABSTRACT FROM AUTHOR]