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Underdetermined blind source separation has received increasing attention in recent years as an effective method for speech-signal processing. Hence, a self-organizing mapping-density peak clustering and compressed sensing approach, which is a two-step approach, is proposed herein to improve the accuracy of underdetermined blind source separation. The approach features the following two aspects: (1) A mixing matrix estimation method based on self-organizing mapping and density peak clustering, which can intuitively determine the number of source signals, remove outliers, and determine the column vector of the mixing matrix based on local density; (2) a compressed sensing-based source signal reconstruction method, which can exploit the sparsity of signals in the frequency domain and use a hierarchical coupling method to reconstruct the source signal accurately and efficiently under the premise that the prior knowledge of the signal is unknown. The proposed method does not require the number of source signals and exhibits excellent performance under different noise conditions. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.

Bastnaesite is an important rare earth mineral and is usually beneficiated by flotation. Sodium silicate is commonly used to depress calcium-bearing gangue minerals, however it can also depress bastnaesite when Ca2+ ions exist in the pulp. In this study, the effect of Ca2+ ions and sodium silicate individually or in combination on bastnaesite flotation was studied through micro-flotation, zeta potential, fluorescence spectroscopy and X-ray photoelectron spectroscopy (XPS) measurements. Micro-flotation results show that the combination of Ca2+ ions and sodium silicate depresses bastnaesite more severely due to their synergistic effect. Zeta potential results show that the combination renders the surface potential of bastnaesite negatively shifted more significantly. Fluorescence spectroscopy shows that the combination decreases the surface hydrophobicity of bastnaesite more severely. XPS shows that the combination increases the adsorption of sodium silicate on bastnaesite by forming hydrophilic Ca-SiO3 precipitate, which causes more serious depression on bastnaesite flotation.

The optical properties of the Eu3+-doped Y2O3-stabilized ZrO2 crystals demonstrate potential for various applications based on their intense emission of orange light.

The growth, structure and optical properties of (ZrO2)92(Y2O3)8−x(Nd2O3)x single crystals were reported. The maximum intensity of the emission spectra was with 0.75 mol% Nd2O3, indicating this sample has potential for near-UV up-conversion luminescence and laser output.

Depth estimation using monocular sensors is an important and basic task in computer vision. It has a wide range of applications in robot navigation, autonomous driving, etc., and has received extensive attention from researchers in recent years. For a long time before, monocular depth estimation was based on convolutional neural networks, but its inherent convolution operation showed limitations in modeling large-scale dependence. Using Transformers instead of convolutional neural networks to perform monocular depth estimation provides a good idea, but there is a problem that the calculation complexity is too high and the number of parameters is too large. In response to these problems, we proposed Swin-Depth, which is a Transformer-based monocular depth estimation method that uses hierarchical representation learning with linear complexity for images. In addition, there is an attention module based on multi-scale fusion in Swin-Depth to strengthen the network’s ability to capture global information. Our proposed method effectively reduces the excessive parameters in the monocular depth estimation using transformer, and a large number of research experiments show that Swin-Depth has achieved state-of-the-art in challenging datasets of indoor and outdoor scenes.

Geotechnical investigation and design show that when evaluating the settlement of ground with soft soil ground, the use of a single stress path results in a larger error than in the case of a multistress path. To understand the influence of a multistress path on the deformation properties and microstructure characteristics of soil, a two-stage stress path (corresponding to three stress states: the in situ state, unloading-loading state, and grouting pressure state) of soil was examined by analytical solution. Then, a series of triaxial tests was conducted to analyze macroscopic deformation properties considering four influencing factors, i.e., the relative distance between the soil and tunnel, stress paths, type of silty clay, and drainage conditions. The results show that axial strain of silty clay caused by the two-stage stress path increases by 31.6% with the relative distance decreasing from 1.67R (R means tunnel radius) to 1.25R on tunnel side, while the volume strain increases by 80% with the relative distance decreasing from 1.21R to 1.06R on tunnel bottom. In addition, the deformation caused by the two-stage stress path (or reconstituted soil or undrained condition) is larger than that caused by the one-stage stress path (or undisturbed soil or drained condition). Finally, through scanning electron microscopy and mercury intrusion porosimetry, the pore size, distribution, shape, and arrangement of silty clay on the bottom and sides of the tunnel were investigated. The research shows that under the two-stage stress path, the number of large pores decrease and that of small pores increase. The probability entropy of pore orientation ranges from 0.834 to 0.971 when silty clay is subjected to a two-stage stress path. This illustrates that the pore order of the soil on tunnel side is better than that on the tunnel bottom.

The upward shield method in horizontal tunnels has the advantages of small ground space occupation, low construction cost, and short construction period, which expresses substantial economic benefits. The special segments of horizontal shield tunnels corresponding to the upward shield method construction area have special design requirements, and different internal force calculations and analyses should be carried out. To determine the mechanical behavior of the special segment structure of horizontal shield tunnels during the construction of upward shield tunnels, the theoretical calculation formula of the internal force of the special segment structure is deduced based on the average uniform rigidity ring method. Moreover, the bending moment and axial force of special segments are numerically simulated and analyzed using Midas GTS NX software. Finally, the theoretical formula and finite element calculation results are compared and analyzed. The results show that the internal force values of the open segment ring and the adjacent segment ring of the special segment are quite different during upward shield tunnel construction. Furthermore, compared with the arch crown and arch bottom of the segment ring, the stress at the arch waist of the segment ring is the most unfavorable. The stress difference between the open segment ring and the adjacent segment ring may cause unbalanced deformation, leading to damage to the segment ring radial joint. In the design and construction, attention should be given to the shear strength of the segment ring radial joint and the bending stiffness of the ring joint at the arch waist.

Background and Aims Studies verify that intercropping influence the soil aggregates and arbuscular mycorrhizal fungi (AMF), but the characteristics and relationships of AMF communities and soil aggregates at different soil depths have not been fully understood. Methods A long term positioning experiment starting in 2017, including two-factor experiment of N application level and cultivation. The N application level including N0 (0 kg·hm−2) and N2 (240 kg·hm−2 and 80 kg·hm−2 for maize and soybean, respectively). The cultivation, including monoculture maize, monoculture soybean, and maize/soybean intercropping (intercropping maize, intercropping soybean). Soil aggregates and AMF were collected and analyzed from the difference depths soil. Results Results showed that intercropping can improve the macro-aggregate (>5 mm) content of maize soil at 0-15 cm and 15-30 cm depth under N0 level. Also, the intercropping can only improve the macro-aggregate content of soybean soil at 0-15 cm depth. Likewise, the results also proved that increasing the N fertilizer application rate can significantly decrease the macro-aggregates in intercropping soil at 0-15 cm and 15-30 cm depths. Moreover, intercropping treatment can significantly improve the AMF diversity of maize and soybean soil at different depths, while the application of N fertilizer significantly reduced the AMF diversity of soil at different depths. Conclusion The Structural equation modeling indicated that the intercropping system could influence and participate in the formation of soil aggregates by changing the soil AMF community and relative abundance, thereby contributing the soil stability. These results reveal the mechanisms of improvement of soil quality through diversity planting patterns.

Target identification of small molecules is an important and still changeling work in the area of drug discovery, especially for botanical drug development. Indistinct understanding of the relationships of ligand–protein interactions is one of the main obstacles for drug repurposing and identification of off-targets. In this study, we collected 9063 crystal structures of ligand-binding proteins released from January, 1995 to April, 2021 in PDB bank, and split the complexes into 5133 interaction pairs of ligand atoms and protein fragments (covalently linked three heavy atoms) with interatomic distance ≤5 Å. The interaction pairs were grouped into ligand atoms with the same SYBYL atom type surrounding each type of protein fragment, which were further clustered via Bayesian Gaussian Mixture Model (BGMM). Gaussian distributions with ligand atoms ≥20 were identified as significant interaction patterns. Reliability of the significant interaction patterns was validated by comparing the difference of number of significant interaction patterns between the docked poses with higher and lower similarity to the native crystal structures. Fifty-one candidate targets of brucine, strychnine and icajine involved in Semen Strychni (Mǎ Qián Zǐ) and eight candidate targets of astragaloside-IV, formononetin and calycosin-7-glucoside involved in Astragalus (Huáng Qí) were predicted by the significant interaction patterns, in combination with docking, which were consistent with the therapeutic effects of Semen Strychni and Astragalus for cancer and chronic pain. The new strategy in this study improves the accuracy of target identification for small molecules, which will facilitate discovery of botanical drugs.

A modular wireless power transmission (WPT) Photovoltaic (PV) subpanel system is proposed. The PV system may contain multiple PV subpanels, and each subpanel is integrated with an individual DC/DC converter connected to a full bridge inverter and to a WPT LC resonant tank. The PV units can be placed on a wireless charging mat, and each WPT unit can be independently designed without affecting other units’ performance. However, because of the rugged outdoor environment, it is difficult to precisely know various circuit parameters, airgaps, or other influential variables that need to be matched or optimized for the WPT. Therefore, two separate power point tracking algorithms are implemented. The first (traditional) maximum power point tracking (MPPT) is used to maintain the solar panel at its highest efficiency point. The second frequency power point tracker is used to adjust the operating frequency of the inverter to match the resonant frequency of the WPT system to ensure the maximum efficiency transfer. Preliminary experimental results are provided to verify the robustness of the WPT system features and the control strategies.

Gallium oxide (Ga2O3) has drawn remarkable attention for next generation power electronics applications. However, the development of Ga2O3 power devices is seriously restricted due to its inefficient p-type dopants and low thermal conductivity. In this article, a novel Ga2O3 superjunction (SJ) LDMOS (laterally-diffused metal-oxide semiconductor) device with introduction of a p-type diamond layer in the drift region is proposed and numerical investigated. The drift region of the proposed Ga2O3 device consists of n-type Ga2O3, Al2O3 and p-type diamond, which is not only increases the breakdown voltage (BV) and reduces the specific on-resistance (R on,sp), but also improves thermal performance of the device. The simulation results show that the BV and R on,sp of the proposed device are 23.22 mΩ·cm2 and 7000 V, which are improved by more than 82.3% and 133% compared with those the conventional gate-connected filed-plate Ga2O3 lDMOS with a R on,sp of 131.43 mΩ·cm2 and a BV of 3000 V, respectively. Moreover, the thermal performance of the proposed Ga2O3 SJ LDMOS is also improved dramatically, although the power density of the proposed device is about 5.7 times higher than that of the conventional device.

With twice the number of cancer’s deaths, cardiovascular diseases have become the leading cause of death worldwide. Atherosclerosis, in particular, is a progressive, chronic inflammatory cardiovascular disease caused by persistent damage to blood vessels due to elevated cholesterol levels and hyperlipidemia. This condition is characterized by an increase in serum cholesterol, triglycerides, and low-density lipoprotein, and a decrease in high-density lipoprotein. Although existing therapies with hypolipidemic effects can improve the living standards of patients with cardiovascular diseases, the drugs currently used in clinical practice have certain side effects, which insists on the need for the development of new types of drugs with lipid-lowering effects. Some marine-derived substances have proven hypolipidemic activities with fewer side effects and stand as a good alternative for drug development. Recently, there have been thousands of studies on substances with lipid-lowering properties of marine origin, and some are already implemented in clinical practice. Here, we summarize the active components of marine-derived products having a hypolipidemic effect. These active constituents according to their source are divided into algal, animal, plant and microbial and contribute to the development and utilization of marine medicinal products with hypolipidemic effects.

Osteoporosis is a polygenic disorder and has been demonstrated to be associated with ~30 candidate genes, the majority of which have also been implicated in the regulation of bone mineral density (BMD). Vitamin D receptor (VDR) is the candidate gene that has been most extensively studied. Certain studies have reported that the VDR single nucleotide polymorphism ApaI is associated with the risk of osteoporosis in Caucasian and African women. However, this association has not yet been studied in postmenopausal Han Chinese women in the Xinjiang area. In the present study, ApaI polymorphisms of VDR were defined by polymerase chain reaction-restriction fragment length polymorphism, in order to analyze the distribution of ApaI polymorphisms in postmenopausal Han Chinese women from Xinjiang. BMD was measured by dual energy X-ray absorptiometry at the lumbar spine (L2-4), Ward's triangle, great trochanter and femoral shaft. A total of 336 women were included in this study. The genotype distribution of ApaI was consistent with the Hardy-Weinberg equilibrium (all P>0.05). There were no significant differences in ApaI genotype frequencies between the 90 cases in the osteoporosis group and 246 cases in the non-osteoporosis group (P=0.946). Meanwhile, it was identified that BMD values of the tested locations were negatively correlated with age (P0.05). In conclusion, the present study identified no significant association of the common VDR polymorphism ApaI with BMD at several skeletal sites in postmenopausal Han Chinese women in the Xinjiang area. Age was negatively correlated with BMD at different sites and identified as a risk factor; while BMI was positively correlated with BMD and identified as a protective factor.

Parisite (CaCe2(CO3)3F2) and bastnaesite (CeCO3F), important rare earth minerals, have different elemental compositions and crystal structures. Their flotation behavioral differences under commonly used sodium silicate (SS) depressant and hydroxamate collector are important for rare earth ore beneficiation, which is still unknown. In this study, the effect of sodium silicate on bastnaesite and parisite flotation with octyl hydroxamic acid (OHA) as collector was comparatively investigated through microflotation, zeta potential measurements, X-ray photoelectron spectroscopy (XPS), and mineral crystal computational analysis. The results indicated that the inhibition effect of SS on parisite was significantly stronger than that on bastnaesite. SS had little effect on the adsorption of OHA on bastnaesite surface, rendering a slight inhibition on bastnaesite flotation. However, SS strongly hindered the adsorption of OHA on parisite surface, rendering the heavy inhibition on parisite flotation. The inhibition mechanism of SS on parisite was due to the reaction of the calcium species with silicate, thereby forming Ca-SiO3 hydrophilic complex on parisite surfaces. This hydrophilic complex hindered the adsorption of OHA and increased the hydrophilicity on parisite surface, thus, causing significant inhibition on parisite flotation.

Knowledge Tracing (KT), namely tracking the knowledge conditions of each student across time, has always been challenging due to the latent and time-varying characteristics of knowledge states. Traditional psychometrical frameworks lack the ability to extract rich representations of exercises or examinees. Deep learning KT models have shown comparable performances, but uninterpretable model parameters have limited their applications. Furthermore, existing frameworks usually cannot handle temporal factors appropriately, as most of them simply apply stochastic processes to simulate fluctuations on knowledge states over time. In this paper, we propose a new framework named Time-and-Concept Enhanced Deep Multidimensional Item Response Theory (TC-MIRT) that integrates the parameters of a Multidimensional Item Response Theory into an improved recurrent neural network. Specifically, two enhanced components are constructed to empower our model with the ability to perform trend forecasting and to generate explainable parameters in each specific domain of knowledge. Experiments implemented on two real-world datasets show that our framework outperforms state-of-the-art KT approaches on performance prediction tasks. Moreover, extensive case analyses also demonstrate that the interpretable parameters of TC-MIRT can be used to evaluate the strengths and weaknesses of students.