Search Results (185)

An easy approach is described for the preparation of ZrO₂-coated Y₂O₃ nanopowder from a solution of zirconium nitrate with commercial Y₂O₃ nanopowder. The evolution process of the ZrO₂ coating layer upon calcination, such as the phase and microstructure of the particles’ surface, was studied. Calcination of the powder at 700 °C resulted in ZrO₂-coated Y₂O₃ nanopowder. The rheological properties of the suspensions of ZrO₂-coated Y₂O₃ powders were studied. A well-dispersed suspension with a solid loading of 35.0 vol% using ZrO₂-coated Y₂O₃ nanopowder was obtained. The consolidated green body obtained by the centrifugal casting method showed improved homogeneity with a relative density of 50.2%. Transparent ceramic with high transparency and an average grain size of 1.7 µm was obtained by presintering at 1500 °C for 16 h in air, followed by post-HIP at 1550 °C for 2 h under 200 MPa pressure. The in-line transmittance at the wavelength of 1100 nm (1.0 mm thick) reached 81.4%, close to the theoretical transmittance of Y₂O₃ crystal. Full article

Data are a strategic resource for industrial production, and an efficient data-mining process will increase productivity. However, there exist many missing values in data collected in real life due to various problems. Because the missing data may reduce productivity, missing value imputation is an important research topic in data mining. At present, most studies mainly focus on imputation methods for continuous missing data, while a few concentrate on discrete missing data. In this paper, a discrete missing value imputation method based on a multilayer perceptron (MLP) is proposed, which employs a momentum gradient descent algorithm, and some prefilling strategies are utilized to improve the convergence speed of the MLP. To verify the effectiveness of the method, experiments are conducted to compare the classification accuracy with eight common imputation methods, such as the mode, random, hot-deck, KNN, autoencoder, and MLP, under different missing mechanisms and missing proportions. Experimental results verify that the improved MLP model (IMLP) can effectively impute discrete missing values in most situations under three missing patterns. Full article

As a typical tight oil reservoir in a lake basin, the Permian Lucaogou Formation of the Jimsar Sag in the Junggar Basin has great potential for exploration and development. However, at present, there are few studies on the identification of the diagenetic facies of tight oil reservoir logging in the study area, and the control effect of diagenesis on tight oil reservoirs is not clear. The present work investigates the diagenesis and diagenetic facies logging of the study area, making full use of core data, thin sections, and logs, among other data, in order to understand the reservoir characteristics of the Permian Lucaogou Formation in the Jimsar Sag. The results show that the Lucaogou Formation has undergone diagenetic activity such as compaction, carbonate cementation, quartz cementation, and clay mineral infilling and dissolution. The diagenetic facies are classified according to mineral and diagenetic type, namely, tightly compacted facies, carbonate-cemented facies, clay mineral-filling facies, quartz-cemented facies, and dissolution facies. The GR, RT, AC, DEN, and CNL logging curves were selected, among others, and the convolutional neural network was introduced to construct a diagenetic facies logging recognition model. The diagenetic facies of a single well was divided and identified, and the predicted diagenetic facies types were compared with thin sections and SEM images of the corresponding depths. Prediction results had a high coincidence rate, which indicates that the model is of a certain significance to accurately identify the diagenetic facies of tight oil reservoirs. Assessing the physical properties of the studied reservoirs, dissolution facies are the dominant diagenetic facies in the study area and are also the preferred sequence for exploration—to find dominant reservoirs in the following stage. Full article

Conventional building energy models (BEM) for heating and cooling energy-consumption prediction without calibration are not accurate, and the commonly used manual calibration method requires the high expertise of modelers. Bayesian calibration (BC) is a novel method with great potential in BEM, and there are many successful applications for unknown-parameters calibrating and retrofitting analysis. However, there is still a lack of study on prediction model calibration. There are two main challenges in developing a calibrated prediction model: (1) poor generalization ability; (2) lack of data availability. To tackle these challenges and create an energy prediction model for office buildings in Guangdong, China, this paper characterizes and validates the BC method to calibrate a quasi-dynamic BEM with a comprehensive database including geometry information for various office buildings. Then, a case study analyzes the effectiveness and performance of the calibrated prediction model. The results show that BC effectively and accurately calibrates quasi-dynamic BEM for prediction purposes. The calibrated model accuracy (monthly CV(RMSE) of 0.59% and hourly CV(RMSE) of 19.35%) meets the requirement of ASHRAE Guideline 14. With the calibrated prediction model, this paper provides a new way to improve the data quality and integrity of existing building energy databases and will further benefit usability. Full article

From the dried vines of Aspidopterys obcordata Hemsl, five new polyoxypregnane glycosides, named obcordatas J–N (1–5), were obtained. Their structures were fully elucidated and characterized by HRESIMS and extensive spectroscopic data. In addition, all of the new compounds were screened for their antinephrolithiasis activity in vitro. The results showed that compounds 1–3 have prominent protective effects on calcium oxalate crystal-induced human kidney 2 (HK-2) cells, with EC₅₀ values ranging from 6.72 to 14.00 μM, which is consistent with the application value of A. obcordata in folk medicine for kidney stones. Full article

Halauxifen-methyl is a new auxin herbicide developed by Corteva Agriscience (Wilmington, DE, USA). It has been suggested that ABF5 may be the target of halauxifen-methyl, as AFB5 mutants of Arabidopsis thaliana are resistant to halauxifen-methyl, which preferentially binds to AFB5. However, the mode of action of halauxifen-methyl has not yet been reported. Therefore, the aim of the present study was to reveal the mode of action of halauxifen-methyl by exploring its influence on indole-3-acetic acid (IAA) homeostasis and the biosynthesis of ethylene and Abscisic Acid (ABA) in Galium aparine. The results showed that halauxifen-methyl could disrupt the homeostasis of IAA and stimulate the overproduction of ethylene and ABA by inducing the overexpression of the 1-aminocyclopropane-1-carboxylate synthase (ACS) and 9-cis-epoxycarotenoid dioxygenase (NCED) genes involved in ethylene and ABA biosynthesis, finally leading to senescence and plant death. Full article

Wind erosion is a typical issue for stone carvings in northwest China caves, and windbreaks such as shelterbelts have proven to be effective in mitigating wind erosion. This study has the main purpose of examining the effect of shelterbelts on alleviating the wind erosion degree of stone carvings. The applicability of the canopy model for reproducing the aerodynamic effects based on the realizable k–ε and LES model was examined by using a validation metric. The shelterbelt structure has been discussed with the goal of finding the optimum canopy structure to provide a guideline for designing shelterbelts. Compared with the LES model, the realizable k–ε model was adopted in this study based on its comprehensive performance. The results show that a canopy with porosity of φ = 30% and a width of 0.3 to 0.5 H has better sheltering efficiency. Compared to the case with no shelterbelt, the wind speed amplification coefficient decreased by 43%, and the significant decrease in the value of the wind speed amplification coefficient in the primary-harm wind direction demonstrates the effectiveness of the shelterbelt. By exploring preventive protection technology in the context of historical stone carving, this study can promote the practice of scientific and technological protection of cultural relics. Full article

Orbital angular momentum (OAM) with mutually orthogonal advantage attribute to break through the high capacity and long-reach transmission limited in the classical passive optical network (PON). Employing Laguerre Gaussian (LG) mode as the orthogonal OAM excitation, a more dimensional multiplexing PON system is proposed to creatively hybridize OAM division multiplexing (OAM-DM) based on wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM). By utilizing the compatibility of OAM-DM and WDM, data of $40$ Gbit/s OFDM signals is successfully transmitted in 80 km multimode fiber (MMF) with low crosstalk. Within this hybrid system, the effects of different wavelengths and different modes on the bit error rate (BER) are discussed at varying transmission distances. Moreover, the performance of several subsystems carrying quadrature phase-shift keying (QPSK), on-off keying (OOK), and OFDM modulation signals is also compared at a BER less than $3.8\times {10}^{-3}$. It is observed that the proposed OAM-DM-WDM-OFDM-PON system has favorable performance, which is a reasonable solution for large-capacity PON architecture. Full article

High-risk human papillomavirus (HPV) infection is an important cause of cervical cancer formation; therefore, being able to detect high-risk HPV (e.g., HPV-16) is important for the early treatment and prevention of cervical cancer. In this study, a combination of a 3-aminopropyltriethoxysilane (APTES) modified gold electrode and a super sandwich structure was creatively developed, resulting in the development of a biosensor that is both sensitive and stable for the detection of HPV-16. The electrochemical biosensor possesses a lower detection limit compared with previous studies with an LOD of 5.475 × 10⁻¹⁶ mol/L and it possesses a wide linear range from 1.0 × 10⁻¹³ mol/L to 1.0 × 10⁻⁶ mol/L (R² = 0.9923) for the target DNA. The experimental data show that the sensor has good stability, and there is no significant decrease in the current response value after 7 days in the low-temperature environment. In addition, the sensor proved to be a powerful clinical tool for disease diagnosis because it showed good interference resistance in complex human serum samples. Full article

Under a changing environment, the effect of climate change and human activities on maize yield is vital for ensuring food security and efficient socio-economic development. The time series of maize yield is generally non-stationary and contains different frequency components, such as long- and short-term oscillations. Nevertheless, there is no adequate understanding of the relative importance of climate change. In addition, human activities on maize yield at multiple timescales remain unclear, which help in further improving maize yield prediction. Based on the ensemble empirical mode decomposition method (EEMD), the method of dependent variable variance decomposition (DVVD) and the Sen-slope method, the effect of climate change including growing-season precipitation and temperature (i.e., GSP, GEP, CDD, GST, GSMAT, and GSMT) and human activities including effective irrigation area (EIA) and the consumption of chemical fertilizers (CCF) on maize yield were explored at multiple timescales during 1979–2015. The Heilongjiang Province, a highly important maize production area in China, was selected as a case study. The results of this work indicate the following: (1) The original maize yield series was divided into 3.1-, 7.4-, 18.5-, and 37-year timescale oscillations and a residual series with an increasing trend, where the 3.1-year timescale (IMF1), the 18.5-year timescale (IMF3), and the increasing trend (R) were dominant; (2) the original sequence was mainly affected by human activities; (3) climate change and human activities had different effects on maize yield at different timescales: The short-term oscillation (IMF1) of maize yield was primarily affected by climate change. However, human activities dominated the mid- and long-term oscillations (IMF3 and R) of maize yield. This study sheds new insight into multiple timescale analysis of the role of climate and human activities on maize yield dynamics. Full article

Two new A-ring contracted triterpenoids, madengaisu A and madengaisu B, and one undescribed ent-kaurane diterpenoid, madengaisu C, along with 20 known compounds were isolated from the roots of Potentilla freyniana Bornm. The structures were elucidated using extensive spectroscopic techniques, including 1D and 2D-NMR, HR-ESI-MS, ECD spectra, IR, and UV analysis. Moreover, all isolated constituents were evaluated for their anti-proliferative activity against RA-FLS cells and cytotoxic activities against the human cancer cell lines Hep-G2, HCT-116, BGC-823, and MCF-7. Ursolic acid and pomolic acid displayed moderate inhibitory activity in RA-FLS cells with IC₅₀ values of 24.63 ± 1.96 and 25.12 ± 1.97 μM, respectively. Hyptadienic acid and 2α,3β-dihydroxyolean-12-en-28-oic acid 28-O-β-d-glucopyranoside exhibited good cytotoxicity against Hep-G2 cells with IC₅₀ values of 25.16 ± 2.55 and 17.66 ± 1.82 μM, respectively. In addition, 2α,3β-dihydroxyolean-13(18)-en-28-oic acid and alphitolic acid were observed to inhibit HCT-116 cells (13.25 ± 1.65 and 21.62 ± 0.33 μM, respectively), while madengaisu B and 2α,3β-dihydroxyolean-13(18)-en-28-oic acid showed cytotoxic activities against BGC-823 cells with IC₅₀ values of 24.76 ± 0.94 and 26.83 ± 2.52 μM, respectively, which demonstrated that triterpenes from P. freyniana may serve as therapeutic agents for RA and cancer treatment. Full article

Objectives: Patients with occlusal disharmony (OD) may be susceptible to depression. The hypothalamus–pituitary–adrenal axis, 5-HT and 5HT_2AR in the prefrontal cortex (PFC), amygdala, and hippocampus are involved in the modulation of emotion and depression. This study investigated whether OD affects the HPA axis and 5-HT system and, subsequently, produces depression-like behaviors in rats. Materials and methods: OD was produced by removing 0.5 and 0.25 mm of hard tissue from the cusps of the maxillary molars in randomly selected sides of Sprague–Dawley rats. CUS involved exposure to 2 different stressors per day for 35 days. OD-, CUS-, and OD + CUS-treated groups and an untreated control group were compared in terms of behavior, endocrine status and brain histology. Results: There were significant differences among the four groups in the behavior tests (p < 0.05), especially in the sucrose preference test, where there was a significant decrease in the OD group compared to the control group. ACTH and CORT concentrations were significantly higher in the OD + CUS group than the control group (p < 0.05). Expression of GR and 5-HT_2AR in the PFC, amygdala and hippocampal CA1 was significantly higher in the OD, CUS and OD + CUS groups than the control group (p < 0.05). Conclusion: OD promotes depression-like behaviors through peripheral and central pathways via the HPA axis, GR and 5-HT system. Full article

This paper proposed a hybrid intelligent process model, based on a hybrid model combining the two-temperature model (TTM) and molecular dynamics simulation (MDS) (TTM-MDS). Combined atomistic-continuum modeling of short-pulse laser melting and disintegration of metal films [Physical Review B, 68, (064114):1–22.], and Gaussian process regression (GPR), for micro-electrical discharge machining (micro-EDM) were also used. A model of single-spark micro-EDM process has been constructed based on TTM-MDS model to predict the removed depth (RD) and material removal rate (MRR). Then, a GPR model was proposed to establish the relationship between input process parameters (energy area density and pulse-on duration) and the process responses (RD and MRR) for micro-EDM machining. The GPR model was trained, tested, and tuned using the data generated from the numerical simulations. Through the GPR model, it was found that micro-EDM process responses can be accurately predicted for the chosen process conditions. Therefore, the hybrid intelligent model proposed in this paper can be used for a micro-EDM process to predict the performance. Full article

Evanescent wave absorption-based mid-infrared chalcogenide fiber sensors have prominent advantages in multicomponent liquid and gas detection. In this work, a new approach of tapered-fiber geometry optimization was proposed, and the evanescent efficiency was also theoretically calculated to evaluate sensing performance. The influence of fiber geometry (waist radius (R_w), taper length (L_t), waist deformation) on the mode distribution, light transmittance (T), evanescent proportion (T_O) and evanescent efficiency (τ) is discussed. Remarkably, the calculated results show that the evanescent efficiency can be over 10% via optimizing the waist radius and taper length. Generally, a better sensing performance based on tapered fiber can be achieved if the proportion of the LP₁₁-like mode becomes higher or R_w becomes smaller. Furthermore, the radius of the waist boundary (R_L) was introduced to analyze the waist deformation. Mode proportion is almost unchanged as the R_L increases, while τ is halved. In addition, the larger the micro taper is, the easier the taper process is. Herein, a longer waist can be obtained, resulting in larger sensing area which increases sensitivity greatly. Full article

The health of the landing gear retraction/extension(R/E) hydraulic system may be assessed using fuzzy comprehensive evaluation (FCE), however the traditional FCE method depends solely on human assessment by specialists, which is excessively subjective. To address the issue of excessive human subjective variables in the assessment, an improved FCE model based on enhanced risk coefficient is provided, which includes four consideration indexes: failure probability, failure severity, failure detection difficulty, and failure repair difficulty. To reduce subjective human judgment errors entirely due to expert experience, the improved FCE takes into account the likelihood of failure using a statistical method, the severity of failure using a fault simulation analysis based on the LMS Imagine.Lab AMESim simulation platform, and the difficulty of fault detection and repair using the aircraft manufacturer’s professional maintenance information. As part of the evaluation model, the range of health assessment values and accompanying treatment methods are included, making it easier to implement on a daily basis in aircraft maintenance. As a final step, the simulation is evaluated, and the simulated faults are calculated. Full article