Underwater motion scene image restoration based on an improved U-Net network.

Active underwater polarization imaging is a common underwater imaging method, which uses the polarization difference between the reflected light and the scattered light in the underwater scene to suppress the scattered light, so as to improve the imaging quality of the underwater scene. However, the implementation often requires the acquisition of multiple polarization images, which is not suitable for the restoration of images of underwater motion scenes. To address the problem, a U-AD-Net deep learning network model based on a single polarized image is proposed, taking the polarization information of the single polarized image as the feature input, based on the classic U-Net network model, and introducing Dense-Net and spatial attention module. The learning ability and generalization ability of the proposed model for deep features are enhanced, and the polarization information that is most helpful to the image restoration is extracted, so as to restore the scene image more comprehensively. IE, AG, UCIQE, and SSIM are selected as evaluation metrics to assess the quality of the restored images. Experimental results show that the images restored through this proposed method contain richer detail information, having an obvious advantage to the existing network models. Since only a single polarized image is needed for restoration, this method has dynamic adaptability to underwater moving scene restoration.

Static and dynamic diffuse wave inspection of delaminations in carbon fiber reinforced composites.

This paper aims to realize a self-reference delamination inspection in CFRPs with diffuse ultrasonic waves. The static experiments are first conducted on samples with a machined defect of 0.5 mm in height which simulates an opening state delamination. The diffusivity decreases with delamination diameter (pristine, 6 mm, 12 mm) at a constant depth and increases with delamination depth (0.25 mm, 0.75 mm) at a given diameter. However, no clear pattern can be found for the dissipation coefficient because of the intrinsic absorption and manufacturing uncertainties. Both coefficients are insensitive to the delamination height under loading. In contrast, the corresponding maximum cross-correlation coefficient from coda wave interferometry shows a variation of 2.4-7 % in different samples. A sharp transition can be found due to the clapping effect when the delamination is fully closed. After then, the static loading is replaced by acoustic stressing pulse from PZT in a closed delamination sample. The low frequency pulse induced reverberation field is sampled by a high frequency diffuse wave semi-synchronously, which mimics a cyclic and low amplitude loading during service. All the dynamic cross-correlation coefficient curves present an ascending trend during voltage ramp-up due to the viscoelastic effect, no matter in the intact zone or delamination zone. When the voltage threshold of 250 V is reached, the clapping effect can be triggered. A descending trend has been found not only when the excitation is right above but also near the delamination. This can be applied as an indicator of the delamination existence regionally without scanning. Such nonlinear measurement system can be expanded to passive imaging and other deficiency inspection in CFRPs with less demanding facilities.

Autofocus methods based on laser illumination.

Autofocusing system plays an important role in microscopic measurement. However, natural-image-based autofocus methods encounter difficulties in improving focusing accuracy and robustness due to the diversity of detection objects. In this paper, a high-precision autofocus method with laser illumination was proposed, termed laser split-image autofocus (LSA), which actively endows the detection scene with image features. The common non-learning-based and learning-based methods for LSA were quantitatively analyzed and evaluated. Furthermore, a lightweight comparative framework model for LSA, termed split-image comparison model (SCM), was proposed to further improve the focusing accuracy and robustness, and a realistic split-image dataset of sufficient size was made to train all models. The experiment showed LSA has better focusing performance than natural-image-based method. In addition, SCM has a great improvement in accuracy and robustness compared with previous learning and non-learning methods, with a mean focusing error of 0.317µm in complex scenes. Therefore, SCM is more suitable for industrial measurement.

Influence of α-amylase, xylanase and cellulase on the rheological properties of bread dough enriched with oat bran.

A better understanding of dough rheology during processing is crucial in the bakery industry, since quality attributes of the final product are influenced by those properties. In this study, we investigated the effects of xylanase, α-amylase and cellulase on the rheological properties of bread dough enriched in oat bran. A DoughLAB was used to measure the mixing characteristics of dough. According to the results, adding a single enzyme did not significantly affect the water absorption, development time, or stability of oat bran dough. In contrast, when blended enzymes were used at high concentrations (10, 120, and 60 ppm), the water absorption, development time, and stability of the oat bran dough were significantly reduced compared to using the single enzyme (62.1%, 7.1 and 6.6 min). It was found that combining α-amylase, xylanase and cellulase resulted in better extensibility and stickiness (16.5 mm and 60.8 g) of oat bran dough than using these enzymes individually. As a result, α-amylase, xylanase and cellulase complemented each other in determining the rheology of bread dough.

Effect of Enyzmes on the Quality and Predicting Glycaemic Response of Chinese Steamed Bread.

The present study investigates the individual and interactional effects of α-amylase (6 and 10 ppm), xylanase (70 and 120 ppm) and cellulase (35 and 60 ppm) on the physicochemical characteristics and nutritional quality of Chinese steamed bread (CSB) incorporated with 15% oat bran. As a result, the single enzyme can significantly improve the specific volume and texture of CSB. Compared to the single enzyme, the combined enzymes improved the specific volume of CSB up to the highest value (2.51 mL/g) and decreased the hardness to the minimum value (233.61 g) when the concentration was 6, 70 and 35 ppm. With respect to chemical and nutritional properties, the addition of single enzyme had no great changes, while the combined enzymes (6, 70 and 35 ppm) significantly (p < 0.05) decreased the total starch from 37.52 to 34.11% and hence increased the area under the reducing sugar release curve during 2 h in vitro digestion (AUC) from 344.61 to 371.26. Consequently, enzymes combination can significantly improve the quality of oat bran CSB whereas reduce the nutritional value of oat bran CSB.

High-precision microscopic autofocus with a single natural image.

In industrial microscopic detection, learning-based autofocus methods have empowered operators to acquire high-quality images quickly. However, there are two parts of errors in Learning-based methods: the fitting error of the network model and the making error of the prior dataset, which limits the potential for further improvements in focusing accuracy. In this paper, a high-precision autofocus pipeline was introduced, which predicts the defocus distance from a single natural image. A new method for making datasets was proposed, which overcomes the limitations of the sharpness metric itself and improves the overall accuracy of the dataset. Furthermore, a lightweight regression network was built, namely Natural-image Defocus Prediction Model (NDPM), to improve the focusing accuracy. A realistic dataset of sufficient size was made to train all models. The experiment shows NDPM has better focusing performance compared with other models, with a mean focusing error of 0.422µm.

Phase measurement deflectometry with refraction model and its calibration.

The phase measurement deflectometry considering the refraction effect is presented to measure the mirror surface in this paper. In the context of the conventional phase measurement deflectometry, the biplanar structure of the system constructed by spatial multiplexing of a screen or a half mirror with two screens is a compromise of traditional display technology, while they suffer from complex calibration process and low accuracy. To improve the system compactness and efficiency, a novel measurement model consisting of a transparent screen and an ordinary screen is used to determine the incident light. To compensate for the measurement errors caused by transparent screen refraction, the refraction of the transparent screen is characterized by two physical parameters, which can be calibrated thanks to the multi-stereo vision technique. Then, the improved mirror calibration method with the refraction model is proposed to determine the posed relationship of the system. After that, the three-dimensional (3D) information of mirror surface is restored by the radial basis function interpolation with the optimized refraction parameters and posed relationships from the gradient data which is transformed from the normal information. Higher measurement efficiency, higher measurement accuracy and more compactness of the proposed measurement method are verified by the experimental results.

A screening method of oil-soluble synthetic dyes in chilli products based on multi-wavelength chromatographic fingerprints comparison.

A multi-wavelength HPLC fingerprint comparison method was proposed for the screening of oil-soluble synthetic dyes in chilli products. The screening was based on the fingerprint differences of normal unadulterated chilli sample with tested chilli samples. The samples were extracted with acetone and fingerprinted by HPLC under four visible light wavelengths (450 nm, 490 nm, 520 nm, and 620 nm). It was found that the fingerprints of different chilli product samples had a relatively fixed number of peaks and stable retention time. When 16 kinds of known synthetic dyes were used as model analytes to assess the screening efficiency, 14 of them could be screened using fingerprint comparison method, with LOD of 0.40-2.41 mg/kg. The new screening method was simple and had the possibility of finding existence of the adulterated dyes which could not be identified using known standard analytes as control.

Simultaneous determination of 14 oil-soluble synthetic dyes in chilli products by high performance liquid chromatography with a gel permeation chromatography clean-up procedure.

A method was developed for the simultaneous determination of 14 fat-soluble dyes in chilli products. The samples were extracted with hexane/acetone. The cleanup was performed with gel permeation chromatography (GPC) cleanup system. A HPLC separation was performed using variable wavelength detector and a gradient elution with 0.1% formic acid and methanol-acetonitrile (1:1, v/v) as the mobile phases. Good linearity (R² ≥ 0.995) was observed between 0.1 and 5.0 µg/mL. Detection limits of the investigated dyes, which were evaluated at signal to noise ratio of 3, were in the ranges of 11-71 µg/kg. The recoveries of the 14 synthetic colourants in three matrices ranged from 73.4% to 103.5%. Relative standard deviations ranged from 3.7% to 12.3%. The method has been successfully used for the determination of banned dyes in real samples.

Generic nonsinusoidal fringe model and gamma calibration in phase measuring profilometry.

Gamma distortion is a dominant error source of phase measuring profilometry. It makes a single frequency for the ideal sinusoidal waveform an infinite width of spectrum. Besides, the defocus of the projector-camera system, like a spatial low-pass filter, attenuates the amplitudes of the high-frequency harmonics. In this paper, a generic distorted fringe model is proposed, which is expressed as a Fourier series. The mathematical model of the harmonic coefficients is derived. Based on the proposed model, a robust gamma calibration method is introduced. It employs the multifrequency phase-shifting method to eliminate the effect of defocus and preserve the influence of gamma distortion. Then, a gamma correction method is proposed to correct the gamma distortion with the calibrated gamma value. The proposed correction method has the advantage of high signal-to-noise ratio. The proposed model is verified through experiments. The results confirm that the phase error is dependent on the defocus and the pitch. The proposed gamma calibration method is compared with the state of the art and proves to be more robust to pitch and defocus variations. After adopting the proposed gamma correction method, the phase precision is much enhanced with higher quality in the measured surfaces.

Hypoglycemic and hypocholesterolemic effects of Coptis chinensis franch inflorescence.

Hypocholesterolemic and hypoglycemic activities of Coptis chinensis franch inflorescence (Coptis inflorescence) were studied using animal models. Serum total and LDL cholesterol of rats fed a diet containing 1% cholesterol and 0.5% cholic acid increased, as compared with those of rats fed a normal diet. The level of total and LDL cholesterol were reduced markedly in a dose dependent manner, in rats given Coptis inflorescence extract orally at doses of 0.25, 0.5 g/kg.day for 4 weeks. In diabetic rats induced by alloxan, Coptis inflorescence extract showed a significant (p < 0.05) blood sugar lowering activity at all experimented doses (0.125, 0.25 and 0.5 g/kg.day). The highest reduction of blood sugar was about 58% when the rats were given Coptis inflorescence extract orally at a dose of 0.5 g/kg.day for 3 weeks. The 100 g dried water extract of Coptis inflorescence contained 8.11 g total alkaloid, 3.34 g berberin, 1.08 g palmatine and 0.66 g jatrorrhizine, which had long been identified as active compounds in Coptis chinensis franch root (Coptis root). Thus, the results suggest that Coptis inflorescence would be effective in the prevention and management of coronary artery disease by lowering serum cholesterol and blood sugar.