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An accurate and nondestructive prediction method of lime acidity was established based on near infrared (NIR) spectroscopy and ensemble learning strategy. Dual-band spectra were obtained nondestructively with a single scan using a desk-top Fourier transform spectrometer and a grating portable spectrometer. Spectral preprocessing methods were used to eliminate the interferences in the spectra. The quantification models of available acidity (pH and 10−pH) and total acidity (TA) were developed with the ensemble learning strategy compared with partial least squares (PLS) and variable selection methods. The results indicated that due to the high-energy light source, the models of the grating portable spectrometer were much better than those of the Fourier transform spectrometer. Short-wave NIR (SWNIR) was more suitable for quantitative analysis of available acidity, while long-wave NIR (LWNIR) was more effective for quantitative analysis of TA. Besides, the models of available acidity were ahead of those of TA. Compared with PLS and variables selection methods, the ensemble learning strategy can produce models with higher prediction accuracy and better robustness. In the optimized models, the correlation coefficients of pH, 10−pH and TA for the prediction set were 0.84, 0.82 and 0.66, respectively. The experiment results show that accurate and nondestructive prediction of lime acidity can be achieved with the grating portable NIR spectrometer and ensemble learning strategy. [Display omitted] • Simultaneous and nondestructive detection of pH and TA in lime was achieved. • Dual-band spectra were obtained with a single scan using two spectrometers. • Models of the grating portable spectrometer can satisfy practical application. • Ensemble learning strategy can produce models with higher prediction accuracy. • SWNIR was more suitable for pH, while LWNIR was more effective for TA. [ABSTRACT FROM AUTHOR]

In this paper, the penetration ability of near infrared (NIR) diffuse reflectance light to peel was studied with grating NIR spectrometer. 15 kinds of fruit, including 3 kinds of thin-peel non-citrus fruit, 9 kinds of medium-peel citrus and 3 kinds of thick-peel citrus were investigated. A new strategy to evaluate the NIR penetration ability was developed with a designed penetration experiment and chemometric methods. The penetration abilities of different integration time, peel thickness and wavelength bands were compared. The results show that NIR light can easily penetrate the peel of thin-peel fruit, while it is not easy to penetrate the peel of citrus due to the thick peel. Both the thickness and composition of the peel have relationship with the penetration ability. Increase of integration time can improve the penetration ability to some extent. However, as the integration time lengthens, noise interference and spectral distortion may appear in long wave near infrared (LWNIR) region. The optimal integration time is 65 ms for citrus. Besides, the penetration ability of short wave near infrared (SWNIR) light is better than that of LWNIR light, and the absorption peaks of peel are mainly located in LWNIR region, indicating that SWNIR is more suitable for fruit internal quality detection. [Display omitted] • A new method to evaluate the NIR penetration ability of peel was developed. • Penetrability of integration time, peel thickness and wavelength was compared. • It is not easy for NIR light to penetrate peel of citrus due to the thick peel. • Increase of integration time can improve NIR penetration ability to some extent. • Penetration ability of SWNIR light is better than those of LWNIR light. [ABSTRACT FROM AUTHOR]

To test whether sonographically determined fecal width (SDFW) correlates with symptom improvement in a population of children with bladder and bowel dysfunction (BBD) managed with standard urotherapy (SU), even for those patients lacking initial bowel complaints. We retrospectively analyzed 200 pediatric BBD patients managed with SU for at least 3 months. Self-reported symptom improvement (complete, partial, no response) following International Children's Continence Society guidelines was tabulated. Patients with complex urologic diagnoses other than vesicoureteral reflux (VUR) were excluded. Pharmacotherapy choice, physical therapy (PT), urinary tract infection (UTI) occurrence, and VUR status were tabulated. SDFW was recorded. Non-parametric analysis of variants (ANOVA) and parametric/non-parametric t testing were used for analysis. Patients had a mean age of 9.5 years (4-12). Forty-eight patients had no gastrointestinal complaints at presentation. Urotherapy yielded complete, partial, and no responses in 14% (n = 27), 33% (n = 67), and 53% (n = 106) of patients, respectively. The average SDFW for those patients with complete response (2.6 cm) was smaller than the SDFW of those with a partial response (3.1 cm) or no response (3.3 cm) (P =.0001). Non-compliance led to greater SDFW compared to compliant patients (3.7 cm and 3.1 cm, respectively, P =.0001). Fecal width was unaffected by VUR, UTI, PT, or pharmacotherapy. SDFW correlates well with symptom improvement in pediatric patients managed for BBD, confirming our hypothesis. SDFW is reasonable as single objective parameter to identify successful management in patients with BBD, extending to those without bowel complaints at presentation. [ABSTRACT FROM AUTHOR]

Vehicle Load Monitoring (VLM) on entire long-span bridge decks presents significant challenges due to the spatial and temporal randomness of vehicles. Existing VLM systems often suffer from limited viewing coverage and poor continuity of multi-vehicle tracking methods. This paper proposes a VLM system consisting of multi-vision image pre-processing, modified YOLO-v4 model, kinematics-enhanced vehicle tracking algorithm, and data fusion method between vision and Weigh-In-Motion sub-systems. The system was tested on a long-span bridge using six cameras, achieving vehicle monitoring of entire deck. The precision of multi-vehicle tracking achieved 99.28% built upon YOLO-v4 model with 96.2% mean Average Precision (mAP). Comparative results demonstrate that the modified YOLO-v4 model outperforms state-of-the-art approaches, and our proposed tracking method surpasses other methods. Our proposed system offers a comprehensive solution for VLM on entire bridge deck, overcoming the limitations of existing methods. Future work could extend the system's capability to include complex traffic patterns. [Display omitted] • Multi-view video data are seamlessly integrated to broaden limited monitoring field. • Original YOLO-v4 is modified, achieving SOTA performance in vehicle detection. • Kinematics-based strategies are exploited to achieve high-precision vehicle tracking. • Intersection principle is proposed, fusing vision-WIM data accurately. [ABSTRACT FROM AUTHOR]

Cable replacement has been commonly implemented to avoid its insufficient bearing capacity after long-term service. To guide better the cable maintenance and life assessment, the experimental studies on replaced cables are significant. As the fundamental step of replaced cable assessment, the corrosion examination of steel wires is required. The existing methods and systems mainly focus on the qualitative estimation and localization of corrosion, which is hard to fulfill the requirement of precise analyses. In this paper, a multi-vision scanning system is proposed to detect and represent the real corrosion and its distribution on the surface of a steel wire. Applied with a novel high-definition image scanning hardware and advanced panoramic image stitching processing algorithms, the surface 2D texture of a single steel wire can be scanned automatically. Afterward, by using the deep learning methods, the corrosion is precisely identified. Furthermore, non-uniformity indicators are proposed for the description of the apparent corrosion. The system has been verified and utilized in the inspection and evaluation of several steel wires from a replaced suspender. Due to it is effective and economical, the system is promising and serves as an instrument for both corrosion researches and structural assessment. [Display omitted] • Design and develop a novel flexibly extensible multi-vision system for visual examination of steel wires. • Deduct and accomplish the image processing algorithms for standard panoramic image acquisition of steel wires. • Propose the evaluation indicators reflecting the non-uniformity of corrosion by image identification of the panoramic image of steel wires. [ABSTRACT FROM AUTHOR]

An accurate and nondestructive detection method of hidden mold infection in citrus was established based on portable near infrared diffuse reflectance spectroscopy and chemometric methods. [Display omitted] • Nondestructive detection of hidden mold infection in citrus was achieved. • NIRDRS light was demonstrated to penetrate the citrus peel. • Models were validated by the validation and external validation sets. • Identification models of LWNIR were much better than those of SWNIR. • Identification accuracy of LWNIR-DT-PLS-DA model was 100%. An accurate and nondestructive detection method of hidden mold infection in citrus was established based on portable near infrared diffuse reflectance spectroscopy (NIRDRS) and chemometric methods. Penetrability of NIRDRS light on the peel of Chunjian hybrid citrus was studied. The results show that NIRDRS light can penetrate the peel to a certain extent, while the penetrability of short-wave near infrared (SWNIR) was better than that of long-wave near infrared (LWNIR). The identification models of hidden mold infection were established with five pattern recognition methods combined with different wavelength bands. The results show that the identification models of LWNIR were much better than those of SWNIR. 100% identification accuracies of LWNIR were obtained with soft independent pattern classification (SIMCA), support vector machine (SVM), partial least squares discriminant analysis (PLS-DA) and the optimized pretreatment methods. In addition, the developed models were further validated by the external validation set collected one month later. [ABSTRACT FROM AUTHOR]