Active vibration control of support sting in wind tunnel by using adaptive method

The low-frequency and large-amplitude coupled vibration of the support sting in wind tunnel affects the accuracy of the wind tunnel test’s data. An active vibration control system of support sting in wind tunnel is demonstrated using adaptive control method in this paper. Following the establishment of the finite element model, and the extraction of parameter matrix, the original model is reduced to lower-mode model which contains first two pitching modes based on DC gain ranking method. The active control model is proposed based on model reference adaptive control method (RACM) to control the low-frequency vibration of supporting sting in wind tunnel. Research results have justified the effectiveness of the controlled system and provided insight into the practical application of the proposed method

User behavior prediction via heterogeneous information preserving network embedding

© 2018 Elsevier B.V. User behavior prediction with low-dimensional vectors generated by user network embedding models has been verified to be efficient and reliable in real applications. However, most user network embedding models utilize homogeneous properties to represent users, such as attributes or user network structure. Though some works try to combine two kinds of properties, the existing works are still not enough to leverage the rich semantics of users. In this paper, we propose a novel heterogeneous information preserving user network embedding model, which is named HINE, for user behavior classification in user network. HINE applies attributes, user network connection, user network structure, and user behavior label information for user representation in user network embedding. The embedded vectors considering these multi-type properties of users contribute to better user behavior classification performances. Experiments verified the superior performances of the proposed approach on real-world complex user network dataset

Geo6D: Geometric Constraints Learning for 6D Pose Estimation

Numerous 6D pose estimation methods have been proposed that employ end-to-end regression to directly estimate the target pose parameters. Since the visible features of objects are implicitly influenced by their poses, the network allows inferring the pose by analyzing the differences in features in the visible region. However, due to the unpredictable and unrestricted range of pose variations, the implicitly learned visible feature-pose constraints are insufficiently covered by the training samples, making the network vulnerable to unseen object poses. To tackle these challenges, we proposed a novel geometric constraints learning approach called Geo6D for direct regression 6D pose estimation methods. It introduces a pose transformation formula expressed in relative offset representation, which is leveraged as geometric constraints to reconstruct the input and output targets of the network. These reconstructed data enable the network to estimate the pose based on explicit geometric constraints and relative offset representation mitigates the issue of the pose distribution gap. Extensive experimental results show that when equipped with Geo6D, the direct 6D methods achieve state-of-the-art performance on multiple datasets and demonstrate significant effectiveness, even with only 10% amount of data

A comprehensive review of wheat phytochemicals: From farm to fork and beyond

The health benefits of whole wheat consumption can be partially attributed to wheat's phytochemicals, including phenolic acids, flavonoids, alkylresorcinols, carotenoids, phytosterols, tocopherols, and tocotrienols. It is of increasing interest to produce whole wheat products that are rich in bioactive phytochemicals. This review provides the fundamentals of the chemistry, extraction, and occurrence of wheat phytochemicals and includes critical discussion of several long-lasting issues: (1) the commonly used nomenclature on distribution of wheat phenolic acids, namely, soluble-free, soluble-conjugated, and insoluble-bound phenolic acids; (2) different extraction protocols for wheat phytochemicals; and (3) the chemistry and application of in vitro antioxidant assays. This review further discusses recent advances on the effects of genotypes, environments, field management, and processing techniques including ultrafine grinding, germination, fermentation, enzymatic treatments, thermal treatments, and food processing. These results need to be interpreted with care due to varied sample preparation protocols and limitations of in vitro assays. The bioaccessibility, bioavailability, metabolism, and potential health benefits of wheat phytochemicals are also reviewed. This comprehensive and critical review will benefit scientific researchers in the field of bioactive compounds of cereal grains and also those in the cereal food industry to produce high-quality functional foods

RP-HPLC DETERMINATION OF GINSENOSIDES RG1 AND RB1 IN PANAX GINSENG FRUITS

Background: At present, there has been a lot of research at home and abroad on the roots, stems and leaves of Panax Ginseng as well as their extracts, but the fruits of Panax Ginseng have been relatively little studied. Materials and Methods: To establish a method for determination of ginsenosides Rg1 and Rb1 in Panax Ginseng fruits. RP-HPLC method is adopted, column used is a ZOBAX SB-C18 column (4.6 mm × 250 mnl, 5 μm), mobile phase A is water, and B is acetonitrile, gradient elution conditions are: 0~20 min (A:B 20:80), 20~60 min (A:B 20~35: 80~65); and detection wavelength 203 nm. Results: Ginsenosides Rgl and Rb1 have good linear relationships within the ranges of 1.04~10.40 μg and 0.50~5.00 μg, respectively, and r is 0.9998 and 0.9997; reproducibility and recovery of the method are both in line with requirements. Conclusion: The method established is simple, accurate and fast, which is suitable for the simultaneous determination of ginsenosides Rg1 and Rb1 in Panax Ginseng fruits

Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE)

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave radiative transfer modeling system. This new system improves the modeling of brightness temperature in both horizontal and vertical polarization. (3) A multiyear (2001–2018) monthly terrestrial actual evapotranspiration and its spatial distribution on the Tibetan Plateau is generated using the surface energy balance system (SEBS) forced by a combination of meteorological and satellite data. (4) A comparison of four large scale soil moisture products to in situ measurements is presented. (5) The trajectory of water vapor transport in the canyon area of Southeast Tibet in different seasons is analyzed, and (6) the vertical water vapor exchange between the upper troposphere and the lower stratosphere in different seasons is presented

Rapid detection of micronutrient components in infant formula milk powder using near-infrared spectroscopy

In order to achieve rapid detection of galactooligosaccharides (GOS), fructooligosaccharides (FOS), calcium (Ca), and vitamin C (Vc), four micronutrient components in infant formula milk powder, this study employed four methods, namely Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), Normalization (Nor), and Savitzky–Golay Smoothing (SG), to preprocess the acquired original spectra of the milk powder. Then, the Competitive Adaptive Reweighted Sampling (CARS) algorithm and Random Frog (RF) algorithm were used to extract representative characteristic wavelengths. Furthermore, Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) models were established to predict the contents of GOS, FOS, Ca, and Vc in infant formula milk powder. The results indicated that after SNV preprocessing, the original spectra of GOS and FOS could effectively extract feature wavelengths using the CARS algorithm, leading to favorable predictive results through the CARS-SVR model. Similarly, after MSC preprocessing, the original spectra of Ca and Vc could efficiently extract feature wavelengths using the CARS algorithm, resulting in optimal predictive outcomes via the CARS-SVR model. This study provides insights for the realization of online nutritional component detection and optimization control in the production process of infant formula

HYDRODYNAMIC STUDY OF HEAVE COMPENSATED LANDING SYSTEM

With the limitation of lowering capacity, traditional lowering systems cannot meet the challenge to lower emerging ultra-large subsea equipment to the seabed. One source affecting the lowering capability of a lowering system is disturbance on the lifting line. In this work, a lowering system, called Heave Compensated Landing System, has been proposed for reducing disturbance on the lifting line by enhancing its heave compensation. However, its hydrodynamic and heave compensated characteristic are poorly understood. To analyze its hydrodynamic characteristic, especially to evaluate its heave compensated performance, this research conducts a case study of this system to lower a 450t manifold. The hydrodynamic characteristic of the Heave Compensated Landing System is investigated using both non-coupled model and fully coupled model and analyzed both in frequency domain and time domain

A tuning method of active disturbance rejection control for a class of high-order processes

This paper aims to propose a quantitative tuning method for active disturbance rejection control (ADRC) that controls the K/(Ts+1)n-type high-order processes. An asymptote in the Nyquist curve has been observed for the first time and its mathematical expression has been deduced. An asymptote condtion is provided in order to derive a parameter tuning rule under the sensitivity constraint. Although this proposed tuning rule is originally designed for a certain type of high-order processes, it can be extended to other types processes that can be approximated into the form of K/(Ts+1)n. Comparisons with different PID control strategies have been conducted for a range of cases to demonstrate the efficiency of the proposed tuning method. Finally, the effectiveness of the proposed tuning rule is experimentally verified on water tank system that exhibits high-order dynamics. Field tests on the superheater steam temperature control of a circulating fluidized bed (CFB) power plant further demonstrate its potential for applications in complex industrial processes