Black soybean hull, as main by-production in black bean processing, has significant biological activity. In this study, the polysaccharide from black soybean hull (BSPS-H) was obtained by enzymatic ...hydrolysis, the yield was 5.3%, and its chemical composition and structural composition were further studied. The results shown that BSPS-H was mainly composed of Mannose, Galactose, and Glucose (molar ratio = 48.1: 29.7: 15.8), and might be existed in the form of pyran ring in α/β-linkage type. The anti-oxidant activity shown that BSPS-H had a certain capacity of anti-oxidation in a concentration-dependent manner. Among them, it has the best scavenging effect on DPPH free radicals. When the polysaccharide concentration was 10 mg/ml, the scavenging rate reached 94.37%. The results of anti-fatigue effect indicated that BSPS-H could prolong the duration of exhaustive swimming in mice, increased the contents of liver glycogen, reduced the content of blood urea nitrogen (BUN), enhanced the activity of lactate dehydrogenase (LDH) and reduced the accumulation of lactic acid (LA). This study provides a fundamental basis for the development and use of BSPS-H in medicine and functional foods.
Three β-glucosidases from
ATCC15703, namely, BaBgl1A, BaBgl3A, and BaBgl3B, were overexpressed in
. The recombinant β-glucosidases were sufficiently purified using Ni
affinity chromatography, and ...BaBgl1A exhibited the best purification efficiency with a purification factor of 2.3-fold and specific activity of 71.2 U/mg. Three recombinant β-glucosidases acted on
-nitrophenyl-β-glucopyranoside (
NPβGlc) at around pH 7.0 and 30-50°C. The results of the substrate specificity assay suggested that BaBgl1A acted exclusively as β-1,2-glucosidase, while BaBgl3A and BaBgl3B acted mostly as β-1,3-glucosidase and β-1,4-glucosidase, respectively. The substrate specificity of the three recombinant enzymes was further studied using the ginsenosides Rb1 and Rd as substrates. The results of thin-layer chromatography and high-performance liquid chromatography analyses showed that BaBgl1A exhibited the highest bioconversion ability on Rb1 and Rd, where it hydrolyzed the outer C-3 glucose moieties of Rb1 and Rd into the rare ginsenosides Gypenoside XVII and F
; BaBgl3A exhibited medium bioconversion ability on Rb1, where it hydrolyzed both the outer C-3 and C-20 glucose moieties of Rb1 into Gyp XVII and Rd; and BaBgl3B was not active on Rb1 and Rd. These β-glucosidases will act as new biocatalytic tools for transforming ginsenosides and preparing active glycosides and aglycone.
The ionosphere is a vitally dynamic charged particle region in the Earth's upper atmosphere, playing a crucial role in applications such as radio communication and satellite navigation. The slant ...total electron contents (STECs) are an important parameter for characterizing wave propagation, representing the integrated electron density along the ray of radio signals passing through the ionosphere. The accurate prediction of STEC is essential for mitigating the ionospheric impact particularly on Global Navigation Satellite Systems (GNSS). In this work, we propose a high-precision STEC prediction model named deep neural operator network (DeepONet)-STEC, which learns nonlinear operators to predict the 4-D temporal-spatial integrated parameter for the specified satellite-ground station ray path globally. As a demonstration, we validate the performance of the model based on GNSS observation data for global and US Continuously Operating Reference Stations (CORS) regimes under ionospheric quiet and storm conditions. The DeepONet-STEC model results show that the three-day 72 h prediction in quiet periods could achieve high accuracy using observation data by the precise point positioning (PPP) with temporal resolution <inline-formula> <tex-math notation="LaTeX">30~\rm {s} </tex-math></inline-formula>. Under active solar magnetic storm periods, the DeepONet-STEC also demonstrated its robustness and superiority than traditional deep learning methods. This work presents a neural operator regression architecture for predicting the 4-D spatiotemporal ionospheric state for satellite navigation system performance, which may be further extended for various space applications and beyond.
Triphenylamine (TPA)‐based polyimides (PIs) have excellent discoloration characteristics and widely used as functional films. However, these PIs usually exhibit lower mechanical and thermal ...properties, and TPA units as the electron donor also weaken the optical transmittance of PIs. Utilized blending with diaminodiphenyl ether (ODA)‐based PIs, we successfully prepared the blend polyimide (BPI) films containing ODA/TPA units, to realize complementary advantages of excellent mechanical, thermal, optical, and electrochemical properties. Among them, the tensile strength of BPI‐53 film (mole ratio of TPA/ODA = 5:3) is reached up to 105.5 MPa, which is 641.9% much higher than 14.22 MPa of TPA‐PI film. Moreover, the thermal stability of BPI‐53 film is also significantly improved. T5 (temperature of 5% weight loss) can be increased to 548.26°C for BPI‐53 film, and the weight residual rate at 800°C in N2 atmosphere is increased by an addition of 4%. Besides, BPI‐53 film also has good transmittance property in district of 400–700 nm, and the variation range of transmittance under 1.0 V positive bias voltage is of 36.61%. For the electrochromics, the discoloration properties of blend polyamide acid (BPAA) dry film can be well maintained.
In this study, WO3 nanorods are directly blended with polyamic acid (PAA) solutions to improve the electrochromic capacity of WO3/PAA composite films. Specifically, the hexagonal WO3 nanorods are ...prepared as inorganic reinforcements using a hydrothermal method and modified by γ‐aminopropyl triethoxysilane. After curing at 300 °C, the WO3 nanorods/polyimide (PI) composite films demonstrate excellent mechanical and thermal properties. The tensile strength of the 1 wt% WO3/PI composite film is ≈110.27 MPa. The thermal stability of the 5 wt% WO3/PI composite film is better than that of the others, and the T5 (5% thermal weight loss temperature) value is ≈560.05 °C. Moreover, the WO3/PAA composite films demonstrate electrochromic behaviors. The electrochromic range of the 5 wt% WO3/PAA composite film exceeds to 68%. For the WO3/PAA samples, the oxidation peak of the WO3 nanorods is evident in the cyclic voltammetry curves. The color contrast of WO3/PI nanocomposites can be enhanced owing to the significant synergistic effects of the electron donor–acceptor system.
This work utilizes the new synergistic effects of the electron donor–acceptor system to enhance the main performance of WO3 nanorods/polyimide (PI) nanocomposites. The electrochromic capacity of WO3/PI nanocomposites can be improved by direct blending and interface modification. Such WO3/PI nanocomposites demonstrate excellent mechanical and thermal properties. There are potentially applied in capacitors, solar cells, energy storage, and display devices.
Abstract
In this study, WO
3
nanorods are directly blended with polyamic acid (PAA) solutions to improve the electrochromic capacity of WO
3
/PAA composite films. Specifically, the hexagonal WO
3
...nanorods are prepared as inorganic reinforcements using a hydrothermal method and modified by
γ
‐aminopropyl triethoxysilane. After curing at 300 °C, the WO
3
nanorods/polyimide (PI) composite films demonstrate excellent mechanical and thermal properties. The tensile strength of the 1 wt% WO
3
/PI composite film is ≈110.27 MPa. The thermal stability of the 5 wt% WO
3
/PI composite film is better than that of the others, and the
T
5
(5% thermal weight loss temperature) value is ≈560.05 °C. Moreover, the WO
3
/PAA composite films demonstrate electrochromic behaviors. The electrochromic range of the 5 wt% WO
3
/PAA composite film exceeds to 68%. For the WO
3
/PAA samples, the oxidation peak of the WO
3
nanorods is evident in the cyclic voltammetry curves. The color contrast of WO
3
/PI nanocomposites can be enhanced owing to the significant synergistic effects of the electron donor–acceptor system.
Ionospheric structure is important for estimating ionospheric delay for user stations in Global Navigation Satellite System (GNSS). However, most existing parameter estimation methods suffer from ...challenges due to data inaccuracy and unavailability of limited and sparse scattered data at ground reference stations. The high variability of active low latitude or disturbed ionosphere leads to GNSS signal scintillation. It is critical to capture ionospheric random structure and estimate ionospheric parameter using data of disperse receivers to improve accuracy. This paper proposes a unifying method named Ionosphere Kernel Estimation Algorithm (IKEA) to retrieve the information of ionospheric spatial structure. The proposed model utilities the semi-parametric representation theorem to incorporate prior information and constraints. The multiple kernel technique is adopted firstly to include physical correlations. Additionally, a learning approach is deployed to determine model parameters. The IKEA model has been verified based on simulated and experimental data at active low latitudes from a network of ground GNSS reference stations from all visible GPS and GALILEO satellites. The IKEA model reduces approximately 19.5% and 24.2% of differential Slant Total Electron Content (dSTEC) in the root mean square error with respect to Inverse Distance Weighting (IDW) and the Kriging model during high ionospheric activities. The IKEA architecture has been demonstrated effective to make robust ionospheric estimation, which may be further extended for various GNSS applications and beyond.
A neutral polysaccharide (SSPS‐N) and an acidic polysaccharide (SSPS‐A) were isolated from Okara by anion‐exchange chromatography. The physical and chemical properties of polysaccharides were studied ...by HPLC, FT‐IR, and SEM. The results showed that SSPS‐N might be a galactomannans with a lamella‐like structure, and SSPS‐A might be an arabinogalactan with a complete porous structure. Furthermore, a new neutral soybean soluble polysaccharide (SSPS‐N‐b) with a molecular weight of 8.6 kDa was isolated from SSPS‐N, and its fine structure was analyzed by GC–MS, enzymatic analysis, and NMR. The results showed that SSPS‐N‐b was a mixture of β‐1,4‐galactan and glucomannan, which (1→4)‐β‐d‐linked mannose and (1→4)‐β‐d‐linked glucose were connected alternately, and it was in parallel with β‐1,4‐galactan. The antioxidant activity results showed that β‐1,4‐Galactan in SSPS‐N‐b was identified as the main activity domain. This result will be utilized for the development of SSPS as novel functional foods and medicine.
Practical applications
Soluble soybean polysaccharide is considered to be a functional component in food because of their biological activities. The physical and chemical properties and antioxidant activity of polysaccharides from Okara show potential applications in novel functional foods and medicine.
The four hydraulic cylinders pressing equipment is commonly used in superplastic forming equipment and other similar applications. But it hardly to arrange the reaction force in the geometry center ...of four cylinder which makes the depress equipment unbalance and very harmful for these equipment. In this paper the coupling between four cylinders is considered and the linear model of four-cylinders pressing system is built by the form of state-equation. Based on this model, the balanced force control strategy is studied. This paper propose a control strategy which is based on detecting the displacement of the four cylinders to amend the force commands of four cylinder. The simulation results shows that it can achieve load control precisely and the tilt angle of loading platform is small.
To predict global ionospheric total electron content (TEC), this paper applies Singular Spectrum Analysis (SSA) for the extraction of trend, periodic, and irregular components form Spherical Harmonic ...(SH) coefficients. It further employs Convolutional Long Short-Term Memory (ConvLSTM)-based machine learning models to construct an encoder-decoder neural network for short-term prediction of TEC. The training set, ranging from March 2017 to October 2018, includes the trend, periodic, and irregular components form the SH coefficients, ap indices, DST indices, days of the year, and hours of the day. For testing set 1, which spans from November 2016 to February 2017, the root mean squared error (RMSE) is 0.72 TECU and 1.20 TECU for the first- and second-hour predictions, respectively {(1 T E C U}=10^{16} \text{el} / \mathrm{m}^2) . For testing set 2, covering the period from November 2018 to February 2019, the RMSE of the prediction results is 0.55 TECU and 0.90 TECU.
