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Lipid oxidation often accompanies the processing and storage of peanuts, which causes a serious waste of peanut resources. To solve the problem of being prone to oxidation in peanut processing, a ternary complex antioxidant based on rosemary extract (RE) was constructed to investigate its effect on the oxidative and thermal stability of peanuts, and the inhibition of peanut oxidation by compound antioxidants was revealed by dynamic Arrhenius formula and complexation theory. The results showed that there was a synergistic effect between RE and Tert‐butyl hydroquinone (TBHQ), and the antioxidant effects of RE and TBHQ were 4.86 and 1.45 times higher when used in combination than when used alone, respectively. In addition, RE‐TBHQ‐CA (citric acid) effectively inhibited primary and secondary oxidation of peanuts with a shelf life 8.7 times longer than that of control peanuts. This study provides a novel antioxidant compounding idea, which has a positive effect on improving the quality of peanut and other nut products, prolonging the shelf life and reducing the waste of resources. Practical Application: Compounding a complex antioxidant that permits its use in peanuts. It was found that rosemary and TBHQ might have synergistic antioxidant effects. Meanwhile, this combination of RE‐TBHQ‐CA effectively inhibited the oxidation of peanut oils and prolonged the shelf life of peanuts. RE‐TBHQ‐CA is a highly efficient complex antioxidant that can reduce the amounts of antioxidants added while maintaining high antioxidant efficiency, which may be useful for the future preservation and storage of nut products as it positively affects the quality and shelf life of the product. [ABSTRACT FROM AUTHOR]

Time series forecasting has a wide range of applications in various fields. To eliminate the need for time series data volume, a meta-learning-based few-shot time series forecasting method is proposed. This method uses a residual stack module as its backbone and connects the residuals forward and backward through a multilayer fully connected network so that the model and the meta-learning framework can be seamlessly combined. The Empirical knowledge of different time-sequence tasks is obtained through meta-training. To enable fast adaptation to new prediction tasks, a small meta-network is introduced to adaptively and dynamically generate the learning rate and weight decay coefficient of each step in the network. This method can use sequences of different data distribution characteristics for cross-task learning, and each training task only needs a small number of time series to achieve sequence prediction for the target task. The results show that compared with the two baselines, the proposed method has improved performance on 67.07% and 58.53% of the evaluated tasks. Thus, this method can effectively alleviate the problems caused by insufficient data during training and has broad application prospects in the field of time series. [ABSTRACT FROM AUTHOR]

• A novel rapid coverage analysis approach of Reentry Vehicles Networking Constellation (RVNC). • We establish the ground coverage model of RVNC and present the coverage criterion of RVNC. • We consider the effect of the earth rotation on the predicted distance during Reentry Vehicle (RV) reentry process to establish a predictive distance model. • Predictive Distance Tracking Algorithm (PDTA) that combines the predictive distance model with a coverage zone based on the reachable domain is proposed. To address the problems of low-precision and time-consuming coverage analysis of Reentry Vehicles Networking Constellation (RVNC), this paper proposes a rapid coverage analysis approach consisting of a coverage model of RVNC and a coverage analysis algorithm. In this approach, we first establish the coverage model of RVNC to obtain a coverage criterion used to judge whether a satellite can cover a target. Then, Predictive Distance Tracking Algorithm (PDTA) is proposed to quickly calculate RVNC coverage performances. The PDTA can adaptively adjust the time tracking step by predicting the distance between a target and a coverage area. Finally, the proposed approach is verified by computational experiments. The results show that the proposed approach is rapid, intuitive, and accurate, which makes it be suitable for RVNC and has wide application prospects. [ABSTRACT FROM AUTHOR]

Based on the Mori–Tanaka method and Eshelby's equivalent inclusions theory, a general analytical expression for the effective magnetostriction of ferromagnetic particles–superconducting matrix composites is deduced under the consideration of residual thermal stress. By calculation, the variation rules of effective magnetostriction and effective thermal expansion coefficient affected by residual thermal stresses are investigated for different inclusions radius ratios, volume fraction ratios, and elastic modulus ratios of the material. The results show that the residual thermal stress has a significant effect on the effective magnetostriction of ferromagnetic particle-superconducting matrix composites. [ABSTRACT FROM AUTHOR]

In this paper, the study investigates the effect of magnetic relaxation on the ac susceptibility in type-II superconductors. To this end, the flux creep equation of ac response is deduced, and the characteristic relaxation time is modified. The relaxation effect is a key feature of flux creep. The results show that the change of the effective relaxation time directly affects the effective potential barrier and the approximate relaxation rate of the superconductor at a certain frequency when the critical current density and critical temperature are fixed, which in turn can cause significant changes in the imaginary part of the AC susceptibility. The results are expected to contribute to a better understanding of the flux dynamics of superconductors from a theoretical perspective. [ABSTRACT FROM AUTHOR]

With the rapid development of smart grids and distributed energy sources, the home energy management system (HEMS) is becoming a hot topic of research as a hub for connecting customers and utilities for energy visualization. Accurate forecasting of future short-term residential electricity demand for each major appliance is a key part of the energy management system. This paper aims to explore the current research status of household-level short-term load forecasting, summarize the advantages and disadvantages of various forecasting methods, and provide research ideas for short-term household load forecasting and household energy management. Firstly, the paper analyzes the latest research results and research trends in deep learning load forecasting methods in terms of network models, feature extraction, and adaptive learning; secondly, it points out the importance of combining probabilistic forecasting methods that take into account load uncertainty with deep learning techniques; and further explores the implications and methods for device-level as well as ultra-short-term load forecasting. In addition, the paper also analyzes the importance of short-term household load forecasting for the scheduling of electricity consumption in household energy management systems. Finally, the paper points out the problems in the current research and proposes suggestions for future development of short-term household load forecasting. [ABSTRACT FROM AUTHOR]

In this paper, a superior compound fault diagnosis method of rolling bearing under a variable speed is proposed, which is based on the generalized demodulation transformation and symplectic geometric mode decomposition. First, generalized demodulation transformation is performed on a time-varying non-stationarity compound fault signal to smooth the fault components by calculating the characteristic frequency, phase function, and theoretical fault frequency point. Then, a new signal decomposition method is applied to extract component signals of different frequencies from the smoothed fault components, and the frequency of each extracted component signal is obtained. Finally, the frequencies of the obtained fault components are compared with theoretical fault frequencies to perform decoupling and diagnosis of compound fault. The simulation and experimental analysis results show that the proposed method can effectively decouple different fault components of compound fault without using the order tracking, providing a superior solution for the diagnosis of compound fault under a time-varying rotational speed. [ABSTRACT FROM AUTHOR]

This paper aims to improve the efficiency of parameter identification of the nonlinear state‐space model (SSM). The commonly used particle Markov chain Monte Carlo (PMCMC) method is time‐consuming. The surrogate model is a useful acceleration strategy, but it is expensive to establish a global high‐precision surrogate model. This paper proposes an efficient algorithm that gradually estimates the unknown parameters in two stages. In the first stage, a reduced region is established based on the latest method. We train a local Gaussian Process regression (GPR) of the likelihood function in the reduced region based on the optimum Latin hypercube design (OLHD). In the second stage, we identify the unknown parameters more accurately based on the MCMC method. When the proposal sample is in the reduced region, we use GPR to estimate the likelihood; otherwise, BPF is used to estimate the likelihood. The reduced region is usually the high probability density region, which is why the algorithm is efficient. It is proved that the acceptance rate of any two samples based on the proposed algorithm is theoretically convergent to that of the PMCMC algorithm. Two examples demonstrate that the proposed method performs well in accuracy and efficiency. [ABSTRACT FROM AUTHOR]

In this paper, the AC susceptibility in superconducting film is studied by the extended exponential critical state model, in which the critical-current density is assumed to be inhomogeneous distributed, namely, space gradient dependent. The results show that it should be noted that existence of the gradient parameter produces a quantitative effect on the form of the dependence of AC susceptibility. The magnetization properties caused by the gradient parameter are also highly nonlinear, which should be useful for the design of thin superconducting film devices. [ABSTRACT FROM AUTHOR]

Optimal transport (OT) methods seek a transformation map (or plan) between two probability measures, such that the transformation has the minimum transportation cost. Such a minimum transport cost, with a certain power transform, is called the Wasserstein distance. Recently, OT methods have drawn great attention in statistics, machine learning, and computer science, especially in deep generative neural networks. Despite its broad applications, the estimation of high‐dimensional Wasserstein distances is a well‐known challenging problem owing to the curse‐of‐dimensionality. There are some cutting‐edge projection‐based techniques that tackle high‐dimensional OT problems. Three major approaches of such techniques are introduced, respectively, the slicing approach, the iterative projection approach, and the projection robust OT approach. Open challenges are discussed at the end of the review. This article is categorized under:Statistical and Graphical Methods of Data Analysis > Dimension ReductionStatistical Learning and Exploratory Methods of the Data Sciences > Manifold Learning [ABSTRACT FROM AUTHOR]

This paper researches the identification problem for the unknown parameters of the multivariate equation-error autoregressive systems. Firstly, the original identification model is decomposed into several sub-identification models according to the number of system outputs. Then, based on the characteristic that the information vector and the parameter vector are common among the sub-identification models, the coupling identification concept is used to propose a partially coupled generalized stochastic gradient algorithm. Furthermore, by expanding the scalar innovation of each subsystem model to the innovation vector, a partially coupled multi-innovation generalized stochastic gradient algorithm is proposed. Finally, the numerical simulations indicate that the proposed algorithms are effective and have good parameter estimation performances. [ABSTRACT FROM AUTHOR]

Objective. We aimed to analyze the correlation between the level of skin advanced glycation end products (AGEs) in type 2 diabetes mellitus (T2DM) patients and the diabetic retinopathy (DR) staging in different traditional Chinese medicine (TCM) syndromes. Methods. 416 T2DM patients were divided into normal group, nonproliferative diabetic retinopathy (NPDR) group (mild, moderate, and severe), and proliferative diabetic retinopathy (PDR) group according to the DR grade. Patients' height, weight, fasting blood glucose (FBG), hemoglobin A1C (HbA1c), blood lipid, renal function, and skin AGEs were measured. According to TCM syndrome differentiation criteria, 230 patients with T2DM and DR were divided into I. qi and yin deficiency, collateral stasis group; II. liver and kidney deficiency, eye collaterals loss group; and III. yin and yang deficiency, blood stasis, and phlegm coagulation group. Results. The skin AGEs levels of different DR staging groups were statistically significant (P < 0.05), and the skin AGEs levels in the mild and moderate NPDR groups were significantly higher (P < 0.05) than those of the normal group. It was significantly higher (P < 0.05) in the severe NPDR group than in the normal group, mild and moderate NPDR groups. The skin AGEs levels of the PDR group were significantly higher (P < 0.05) than the normal group, mild and moderate NPDR groups. It was positively correlated with DR stage, HbA1c, total cholesterol (TC), low-density lipoprotein (LDL), and urine metal analysis (UMA) (r = 0.467, 0.411, 0.413, 0.503, 0.424, P < 0.05). The skin AGEs levels of the qi and yin deficiency and collaterals stasis syndrome group were significantly higher (P < 0.05) than in the liver and kidney deficiency and eye collaterals loss groups. It was also significantly higher (P < 0.05) in yin and yang deficiency, blood stasis, and phlegm coagulation syndrome groups than in qi and yin deficiency and collaterals stasis syndrome groups. Conclusion. There is a positive correlation between skin AGEs and DR staging in T2DM patients. Skin AGEs level is predictive for the risk of DR complications in T2DM patients and is vital in assessing DR degree per TCM syndrome type. [ABSTRACT FROM AUTHOR]

To keep safety of the antenna in wireless capsule endoscopy (WCE) to human body and its use range in different groups of people, seven human abdomen models are established where age, tissue thickness, and organ shape have been considered. On the basis of plane wave propagating theory in lossy multilayered media, each model is composed of simulated skin, subcutaneous fat, muscle, visceral fat, and gastrointestinal organ. Different dielectric constants for the biological tissue component are used. A bendable dual-band antenna is designed for the WCE system, conformed to the capsule shell. An L-shaped branch is used to get better impendence matching. Both the ISM band adopted for data transmission and the WMTS band for midfield wireless power transmission are studied. Fresh pork abdominal tissue samples are used as experiment materials, and it is properly kept consistent with the real human abdominal as far as possible. The experimental results show the performance of antenna stable in the ISM (433 MHz) band. The specific absorption ratio value is checked in different models. The results indicate that dielectric parameters varying with age cannot be ignored, and the antenna must be aimed at middle-aged and elderly population with high incidence of gastrointestinal diseases. [ABSTRACT FROM AUTHOR]

Vacuum-air-shift causes trouble to conventional electron beam evaporation (EBE) coatings. This study compares the protection effect of ion assistance and the ALD (atomic layer deposition) Al 2 O 3 capping layer. The vacuum-air-shift was reproduced on an EBE Ta 2 O 5 single-layer film, a Ta 2 O 5 /SiO 2 double-layer coating, and a high-reflectance mirror. Similar samples were prepared by EBE assisted with ion beam bombardment. Part of the as-deposited coatings were capped by ALD Al 2 O 3 film with a thickness of about 100 nm. The vacuum-air-shift of the samples was tested with an in-situ spectrophotometer. The cross-section of the coatings was imaged by a scanning electron microscope. The ion assistance was found to reduce the vacuum-air-shift to a limit extent, while the ALD capping film was found to eliminate the vacuum-air-shift. The mechanism of the two protection techniques was analyzed, and their usage was compared and discussed. The ALD capping technique may be used in high precision EBE coatings with convenience and low cost. [ABSTRACT FROM AUTHOR]

• Unveiled Tan sheep MB purification and confirmed identity via LC-MS/MS analysis. • NO-induced transformation in MbFeⅢ observed by UV–visible and Raman spectroscopy. • AlphaFold2 and docking simulations reveal stable MbFeⅡNO structure. • DFT highlights chemical stability and role of distal histidine in MbFeⅡNO. • Theoretical and experimental synergy elucidates pigment protein dynamics. Color of meat remains crucial quality attribute that attracts attention of researchers worldwide. Various strategies have been employed to manipulate meat color by generating nitric oxide (NO), which interacts with myoglobin (Mb) to yield the pinkish-red pigment, nitrosomyoglobin (MbFeⅡNO). However, the formation mechanism of MbFeⅡNO warrants further exploration at the molecular-structural level for meat pigmentation. Here, Tan sheep Mb was purified and characterized its primary structure via LC-MS/MS, which found it to be identical to sheep Mb. Circular dichroism spectroscopy revealed 70.05 % α-helix content in the secondary structure of Tan sheep Mb. UV-visible and resonance Raman spectroscopy monitored NO bonding in Tan sheep Mb, revealing that NO displaced H 2 O of MbFeⅢ, forming MbFeⅢNO, which subsequently transformed into low-spin six-coordination MbFeⅡNO. Additionally, three-dimensional structure of Tan sheep Mb was constructed utilizing Alphafold2, and theoretical simulations and calculations were performed through molecular docking and DFT. Results confirmed the synergistic effect of the strong metal-ligand and hydrogen bonding interactions among the NO, heme iron, and distal sites significantly contributed to the stable formation of MbFeⅡNO. Overall, this study offers a novel perspective on the mechanism of NO binding in Mb, potentially guiding the development of innovative strategies to mitigate meat color deterioration. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • A two-step hydrothermal and calcination route was used to prepare NiGa 2 O 4 @C@CeO 2. • The NiGa 2 O 4 @C@CeO 2 sensor exhibits excellent triethylamine gas sensitive property. • The NiGa 2 O 4 @C@CeO 2 sensor also shows terrific selectivity and reusability for TEA. • The superior TEA gas sensing mechanism of the heterostructure was also investigated. Metal oxide heterostructures have been demonstrated excellent candidates acting as novel gas sensors with outstanding sensitivity and selectivity. In this work, a hierarchical NiGa 2 O 4 @C@CeO 2 heterostructure with corn-like NiGa 2 O 4 microcrystals covered by a thin carbon layer and then anchored with numerous amounts of external CeO 2 nanoparticles was prepared through the combination of hydrothermal and a subsequent calcination method. The NiGa 2 O 4 @C@CeO 2 composite demonstrates an excellent selective triethylamine (TEA) detection performance with a response of 11.1 towards 20 ppm TEA and a fast response/recovery time of 81 s/38 s. It also shows terrific selectivity for TEA when mixed with else interfering substances, along with prolonged reusability for at least 15 days. The enhanced TEA sensing performance can be ascribed to the significant improvement of conductivity and effective carrier transfer at the interface. This work provides a feasible method to fabricate metal oxide sensors with improved gas sensing performance. [ABSTRACT FROM AUTHOR]

Rapid and accurate target detection is one of the inevitable requirements of intelligent construction site. To meet the speed requirements and improve detection accuracy, an improved small object detection (ISOD) network is proposed. The network utilizes an efficient channel attention mechanism to extract features in the backbone and combines the proposed extended scale feature pyramid network to simplify calculations and create additional high-resolution pyramid layers to improve the ability of detecting small targets. To verify the effectiveness of ISOD, experiments are conducted using the proposed Reflective Vest Scene Dataset and Tsinghua-Tencent 100K, achieving 0.425 and 0.635 mAP@0.5-\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$-$$\end{document}0.95, respectively, exceeding the SOTA YOLOv7 model, demonstrating its excellent small target detection capability and scalability. [ABSTRACT FROM AUTHOR]

[Display omitted] • Domestication of bacteria by MNBs was proposed for bacteria optimization. • Phenol degraded dramatically from 1000 to 23.84 mg L−1 within 10 h in MNB-AR. • MNB-AR achieved high COD removal efficiency (over 92%) in a high-COD environment. • MNB-AR maintained excellent stability under severe water quality fluctuations. • Functional microbials and genes related to phenol degradation were upregulated. The treatment of coking wastewater with high phenol concentrations has been a challenge for conventional biological treatment technology. In this short communication, phenol-degrading bacteria domesticated by micro and nano bubbles (MNBs) water are used to treat the high- concentration phenol in an MNBs aeration reactor (MNB-AR). The results show that the MNB-AR can greatly improve the removal of phenol and chemical oxygen demand (COD). At a phenol concentration of 1000 mg L−1, the phenol and COD removal rates in the MNB-AR are 55 % and 39 % higher than in the conventional bubble aeration reactor respectively. MNB-AR performs more stably and reaches a higher phenol tolerance under fluctuating high-phenol-concentration loadings. Metagenomic analysis shows that MNBs promote the growth and metabolism of aerobic microorganisms related to phenol degradation, and enhance gene abundance related to carbon metabolism. MNBs aeration combined with microorganisms is an efficient solution for treating coking wastewater. [ABSTRACT FROM AUTHOR]

Atomic-level prediction combined with machine learning (ML) and density functional theory (DFT) is carried out to accelerate the fast discovery of potential photovoltaics from the 2D perovskites. Based on the ML prediction, stability test, optical absorption, and the theoretical power conversion efficiency (PCE) evaluation, two promising photovoltaics, i.e., Sr2VON3 and Ba2VON3, are discovered with PCE as high as 30.35% and 26.03%, respectively. Cu, Ag, C, N, H, and He ion implantation are adopted to improve the photovoltaic performance of the high-efficiency and best stable perovskite Sr2VON3. The time-dependent DFT electronic stopping calculations for energetic ion implanted Sr2VON3 indicate that the excited electrons from the valence band contribute to the electron–phonon coupling, the evolution and formation of the defects, and the photovoltaic performance. This work opens the way to the high-accuracy fast discovery of the high-efficiency and environmentally stable 2D perovskites solar cells and the further engineering improvement in photovoltaic performance by ion implantation. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) was confirmed to be associated with hematopoietic insufficiency, as well as abnormal proliferation, differentiation or survival of myeloid progenitors. Multiple studies reported that microRNA-204 (miR-204) and Hepatocyte growth factor (HGF) played important roles in types of cancers. However, the potential molecular regulatory mechanism between miR-204 and HGF in AML remains to be further defined. Real-time PCR (RT-PCR) was adopted to detect the expression of miR-204 and HG. Relative protein levels were detected by western blot assay. The viability, cell cycle, apoptosis, migration, and invasion were analyzed by MTT, flow cytometry, and transwell assays. Moreover, the target relationship between miR-204 and HGF was predicted by MiRcode website and confirmed by luciferase reporter, RNA pull-down, and western blot assays. Our data suggested that miR-204 was downregulated in AML serum samples and cells. MiR-204 overexpression repressed cell proliferation, migration, invasion, and induced cell apoptosis in AML cells. HGF was upregulated in AML samples and cells, and HGF knockdown inhibited the malignancy of AML cells. In addition, HGF was directly targeted by miR-204. HGF overexpression reversed the effects of miR-204 mimic on AML cell proliferation, apoptosis, migration, and invasion. Besides, miR-204 regulated the c-Met signaling by targeting HGF, thereby regulating the downstream protein levels related to cell proliferation, apoptosis, migration, and invasion in AML cells. In conclusion, miR-204 could regulate AML progression through regulating the HGF/c-Met pathway. [ABSTRACT FROM AUTHOR]

Hydrogen activation, storage properties and associated crystal structures of Ti 1- x Sc x Mn 1.6 V 0.4 (x = 0, 0.05, 0.1, 0.15, 0.2, 0.25) alloys are investigated by hydrogenation and XRD. The unit-cells of alloys and hydrides expand with Sc content and hydrogen concentration. Minor addition of Sc significantly improves hydrogen activation and storage properties. The plateau pressure decreases, whereas the sloping factor and relative partial molar enthalpy for hydrogenation increase with Sc content. The activation properties strongly depend on the particle sizes. The bulk samples can easily be activated by implementing a hydrogen-induced cracking mechanism, which avoids removal of protective oxide films and compensates the lack of metallic B-metal in catalysis of hydrogen dissociation. Samples with smaller particle sizes are difficult to activate. The unusual particle size effect is interpreted by activation kinetics, and attributed to the high oxygen binding ability of B-metals and their contribution to the surface oxide films. • Ti 1- x Sc x Mn 1.6 V 0.4 alloys and hydrides expand with Sc content and H concentration. • Minor addition of Sc in the alloy significantly improves hydrogen storage properties. • Hydrogen activation properties improve with increasing Sc content in the alloy. • Hydrogen activation properties of the alloys deteriorate with smaller particle sizes. • Unusual particle size effect is attribute of high oxygen binding ability of B-metals. [ABSTRACT FROM AUTHOR]

Summary: This article researches the filtering‐based parameter estimation issues for a class of multivariate control systems with colored noise. A filtering‐based recursive generalized extended least squares algorithm is derived, in which the data filtering technique is used for transforming the original system into two subidentification systems and the least squares principle is used for estimating parameters of these two subsystems. Furthermore, in order to improve the parameter estimation accuracy, the multiinnovation theory is added for deducing a filtering‐based multiinnovation recursive generalized extended least squares algorithm. The numerical example confirms that these two proposed algorithms are effective. [ABSTRACT FROM AUTHOR]

3-D digital city vividly presents a real-world city and has been widely needed for many application domains. Numerous pole-like objects (PLOs), including trees, street lamps, and traffic signs, are an indispensable part of 3-D digital city. The point cloud data of mobile laser scanning (MLS) systems can capture both the geometric shape and geospatial coordinates of the PLOs while moving along the roads. This article is motivated to accurately extract and efficiently model PLOs from the point cloud data. The main contributions of this article are as follows: 1) a divergence-incorporated clustering algorithm is proposed to extract trunks accurately from the pole-like 3-D distribution perspective of point cloud; 2) an adaptive growing strategy of alternately extending and updating 3-D neighbors is proposed to get the complete canopy points of various shapes and density; and 3) the part-based modeling is proposed to synthesize the point cloud of PLOs with meaningful 3-D shapes, providing a way to model objects for the 3-D digital city vividly and efficiently. The proposed method is tested on three data sets with different interference, shape of the canopy, and point density. Experimental results demonstrate that the proposed method can extract and model the PLOs effectively and efficiently for 3-D digital city. The precision of trunk extraction is 98.45%, 98.08%, and 92.39%, the completeness of canopy extraction is 80.54%, 89.84%, and 89.29%, and the modeling time for a PLO is 0.011, 0.038, and 0.063 s in three data sets. [ABSTRACT FROM AUTHOR]

Reliability-based design optimization (RBDO) has been widely used to search for the optimal design under the presence of parameter uncertainty in the engineering application. Unlike traditional deterministic optimization, RBDO problem takes the uncertainty of design variables and probabilistic reliability constraints into consideration. In the context of RBDO, a large number of model evaluations are required in the reliability analysis to estimate the failure probability. However, the intensive computation of reliability analysis makes it infeasible to address complex and expensive problems. In order to relieve the computational burden, an efficient polynomial chaos-enhanced radial basis function (PCE-RBF) approach is proposed. In this approach, RBF combined with sparse PC method is constructed to enhance predictive accuracy of metamodel. To refine the metamodel, local variation with minimum distance sampling criterion is proposed to select the sample points sequentially. Then, the refined PCE-RBF metamodel with acceptable accuracy is used to perform gradient-based optimization for solving RBDO problem. The performance of the proposed method is validated by four benchmark examples and truss structure issue. [ABSTRACT FROM AUTHOR]

Based on the weighted Laguerre polynomials (WLPs) and artificial anisotropic (AA) parameters, a 3‐D unconditionally stable finite‐difference time‐domain (FDTD) electromagnetic simulation approach is proposed. The implementation of WLPs in time domain effectively eliminates the time step and AA parameters in spatial difference, resulting in suppressed numerical dispersion error. The monochromatic wave is employed as an example to obtain the numerical dispersion relationship of 3‐D AA‐WLP‐FDTD under AA parameter, in which reduced numerical dispersion error is observed. Compared with the conventional WLP‐FDTD technique, this approach demonstrates smaller numerical dispersion error under similar calculation cost. [ABSTRACT FROM AUTHOR]

Voluntary counseling and testing (VCT) service plays an essential part in the prevention of human immunodeficiency virus (HIV) infection. The purpose of this study was to investigate the characteristics of participants and analyze the major factors of HIV infection in VCT in Nantong, China. This study was conducted between January 2010 and December 2015, based on the responses to questionnaires and blood test results retrieved from the Chinese National HIV/AIDS Comprehensive Control Information System (CNHCCIS). Multivariate logistic regression analyses were used to identify factors related to HIV infection. Differences between first-time testers and repeat testers were assessed using the chi-squared or Fisher test. Over six years, a total of 11,560 VCT participants were included, and 420 cases were confirmed to be HIV-positive. Overall, the annual number of participants was relatively stable with a mean of 1927, while there was a rapid increase in the HIV detection rate (from 1.03% in 2010 to 7.52% in 2015). In multivariate analysis, referral counseling and having a HIV-positive spouse/fixed sex partners were found to be significantly associated with HIV infection among all participants, while being unmarried or divorced, having commercial heterosexual behaviors, and male-male sexual behaviors are additional HIV-related factors for males. Compared to first-time testers, repeat testers were more willing to engage in high-risk sexual behaviors and had higher HIV detection rates (P < 0.001). In conclusion, the HIV epidemic in Nantong is still not controlled. Therefore, in the future, it is critical to expand VCT services to increase the detection rate of HIV, which can prevent the transmission of HIV effectively. [ABSTRACT FROM AUTHOR]

We have rationally designed and successfully synthesized FeOOH nanosheet arrays supported on alkali-treated nickel foam. The FeOOH NSAs/ATNF material showed superior catalytic performances for OER in charge transfer, mass transport and reaction kinetics than FeOOH powder. The adverse effects caused by global climate warming continue to be a great impetus to develop electrocatalytic water splitting technology for hydrogen source production. However, there is an urgent necessity but it is still a significant challenge to explore electrocatalysts with excellent performance, low cost, and environmental benignity for expediting the oxygen evolution reaction (OER) owing to the sluggish reaction kinetics. Fe-based materials, especially FeOOH, have great potential as OER electrocatalysts but suffers from poor electrical conductivity. Herein, we rationally designed and successfully synthesized FeOOH nanosheet arrays supported on alkali-treated nickel foam (FeOOH NSAs/ATNF) and applied it as an electrocatalyst toward OER. The FeOOH NSAs/ATNF catalyst exhibited outstanding performance with small overpotential, fast kinetics and superior stability in alkaline medium. Our research opens up a facile and effective approach to develop cost-effective and high-performance electrocatalysts for energy conversion, especially for these Fe-based materials with poor electrical conductivity. [ABSTRACT FROM AUTHOR]

Multivariate output sensitivity analysis has gained much attention when the output of the computational model is a vector. A preferable strategy to deal with the multivariate output issue is the covariance decomposition approach based on the polynomial chaos expansion (PCE) metamodel. However, since the PCE construction depends on the quality of experimental design to some extent, the selection of design points is significant in determining the accuracy of the sensitivity estimator. In this article, a PCE-based sequential experimental design is proposed to estimate the multivariate output sensitivity index. In this method, the optimal design point is sequentially selected to minimize the determinant of covariance matrix of the sensitivity estimator. To validate the performance of the proposed method, several numerical examples are presented, which show that the sequential design approach performs better than other prevalent methods in terms of accuracy and robustness. [ABSTRACT FROM AUTHOR]

Objective. To establish a porcine eye model for manual sub-Bowman layer photorefractive keratomileusis (SBPRK), which is a reformed surface ablation refractive surgery that results in preserving the corneal Bowman layer (BL). Methods. The SBPRK group consisted of eleven eyes of 8 healthy pigs with BL flaps by mechanical technique followed by laser ablation. Regarding the remaining 5 eyes, 3 random eyes had transepithelium photorefractive keratectomy (TransPRK) (the TransPRK group), while the other 2 eyes were untreated (the blank control group). All the pigs were followed up for 8 weeks. Slit-lamp biomicroscopy and optical coherence tomography (OCT) were examined before the surgeries and at 1 week, 4 weeks, and 8 weeks after the surgeries. Results. In a few days after the surgery, 3 eyes of the SBPRK group were excluded from the study because of poor healing of the corneal flaps. At the 1st postoperative week, one eye had an irregular defect of about 3 mm in the central corneal epithelium area; the cornea of the other 7 eyes had just light edema with intact epithelium just like the cornea of the TransPRK group. At the 4th week, in the SBPRK group, the cornea was slightly hazy (haze stage 1). While in the TransPRK group, the cornea was hazier (haze stage 2). At the 8th week, in the SBPRK group, both corneas were almost transparent, and the edges of the BL flaps could not be clearly seen. Meanwhile, in the TransPRK group, the corneal haze became lighter and thinner. OCT showed that, in the SBPRK group, there was high reflection in the BL layer, and it was obvious at 1 week postoperation, decreased at 4 weeks, and calmed down at 8 weeks. However, in the TransPRK group, the high reflection diffused in the anterior corneal stroma at 1 week postoperation, enhanced at 4 weeks, and weakened at 8 weeks. Conclusions. Preserving the BL while conducting surface refractive surgery may result in less haze than TransPRK. However, further study is still needed, and this technique still requires refining until it becomes a standard clinical procedure. [ABSTRACT FROM AUTHOR]

The nanosize confined effect is believed to contribute to improving the resistance drift in nanophase change devices. However, the smaller dimension of device designs is limited by plane lithography techniques. Phase change memory with a confined thickness of ultrathin GeTe layers is fabricated to overcome the limit of current plane lithography. Those memory cells composed of two-dimensional materials present a suppressed resistance drift in their amorphous phase. The drift exponent ν is reduced to 0.05 for 3 nm GeTe layers. Combined with Raman spectroscopy and ab initio molecular dynamics simulations, the structural relaxation process is described as the decay of tetrahedral-bonded sites. Tetrahedrons in ultrathin films are more stable than those in bulk materials. The local motifs of amorphous GeTe ultrathin films are covalently bonded and highly ordered in a short range. The majority of highly ordered tetrahedral clusters prevents spontaneous structural relaxation and leads to high stability in amorphous states, which helps to stop intrinsic fluctuations in physical properties of SET and RESET states, without an extra processing cost. [ABSTRACT FROM AUTHOR]

Nonalcoholic fatty liver disease (NAFLD) is one of the prevalent and typical chronic liver diseases. In this study, we extracted a novel Angelica sinensis polysaccharide (ASP) with low molecular weight (MW) of 3.2 kDa through optimized "one‐step" purification process. The major monosaccharide components of ASP were mannose, rhamnose, glucuronic acid, galactose, arabinose, and xylose with weight ratio of 0.23:0.17:14.41:0.39:1.68:0.87, respectively. Herein, "small" ASP could serve as an effective therapeutic option for NAFLD both in free fatty acid‐induced L02 models and in high‐fat diet‐induced mice models. Results revealed that low MW ASP dose‐dependently decreased TG, TC in vitro and TG, TC, ALT, HDL‐C, and LDL‐C in vivo. Oil Red O‐positive area and Nile red fluorescence intensity decreased in ASP treatment groups both in vitro and in vivo which suggested ASP could reduce lipid accumulation and fatty regeneration. Hematoxylin–eosin staining results shown a decrease in hepatocytes ballooning indicating that ASP could ameliorate liver lipid degeneration. Briefly, a novel polysaccharide with low MW was successfully obtained which can prospectively act as NAFLD therapy. [ABSTRACT FROM AUTHOR]

Low Foxp3+ regulatory T‐cell (Treg) presence in the tumor‐infiltrating lymphocytes (TILs) is considered favorable in breast cancer, and numerous CD25‐targeting agents have been applied in the attempt to remove Foxp3+ Treg cells, which typically present CD4+CD25+/hi surface phenotype. However, CD25 is not Treg‐exclusive and can be upregulated by effector T cells. Hence, CD25 depletion may cause the elimination of activated T cells that are responding to tumor‐specific antigens. In this study, the composition and function of CD4+CD25+ cells inside the microenvironment of triple‐negative breast carcinoma (TNBC) were investigated. Directly ex vivo, the Foxp3+ Treg cells represented a minor subset in total CD4+CD25+ TILs. Significant differences were observed in the expression of Treg‐associated molecules between CD4+CD25+Foxp3+ TILs and CD4+CD25+Foxp3− TILs. While both the CD4+CD25+Foxp3+ and the CD4+CD25+Foxp3− TILs could express CTLA‐4 and LAG‐3, the expression levels were significantly higher in CD4+CD25+Foxp3+ TILs than in CD4+CD25+Foxp3− TILs. Upon TCR stimulation, the expression of TGF‐beta was significantly higher in CD4+CD25+Foxp3+ TILs, while the expression of IL‐10 was significantly higher in CD4+CD25+Foxp3− TILs. These differences were conserved in the blood counterparts of these cells. Interestingly, the level of CD25+Foxp3+ cells in circulating CD4+ T cells was positively correlated with the level of CD25+Foxp3+ cells in CD4+ TILs, but the level of CD25+Foxp3− cells in circulating CD4+ T cells was not associated with the level of CD25+Foxp3‐ cells in CD4+ TILs. Th17‐polarizing medium could readily remodel CD4+CD25+Foxp3−, but not CD4+CD25+Foxp3+, T cells into RORgammat and IL‐17‐expressing T cells, demonstrating stronger plasticity of the former subset. Together, these data demonstrated that the CD4+CD25+ TILs were composed of distinctive Foxp3− and Foxp3+ cells, with the former representing the major subset. The antigen specificity and effector molecule expression of the CD4+CD25+Foxp3− thus require further analyses. [ABSTRACT FROM AUTHOR]

Racial differences have been observed in the rate of bacterial infection and disease progression in HIV. Here, we evaluate racial differences in seasonal influenza vaccine responses. 16 healthy controls (9 Caucasians (CC) and 7 African Americans (AA)) and 26 antiretroviral therapy (ART)-treated aviremic HIV+ subjects (11 CC and 15 AA) were enrolled in the current study. Blood was collected at pre-vaccination (D0) and day 14 (D14) following seasonal influenza vaccination. Serologic responses were characterized in plasma by ELISA. B and T cells were assessed by flow cytometry ex vivo. The absolute counts of CD4+ CD3+ T cells and CD19+ B cells were similar in healthy controls and HIV-infected individuals, and similar in CC and AA in the two study groups. However, the percentage of peripheral T follicular helper (pTfh) cells was decreased in HIV+ AA compared to HIV+ CC. There were no racial differences in IgG antibody responses against vaccination in the two study groups. However, the ratio of anti-influenza-specific IgG versus IgM induction following vaccination was decreased in HIV+ AA compared to HIV+ CC, which was directly correlated with the percentages of pTfh cells. This racial difference and correlation were not demonstrable in healthy controls. Here we report that HIV + AA has decreased fold induction of IgG versus IgM after influenza vaccination, which may suggest impaired class-switching from IgM to IgG in AA HIV-infected individuals. [ABSTRACT FROM AUTHOR]

Because of its hydrophobicity and persistence, dichlorodiphenyltrichloroethane (DDT) is ubiquitous in sediments and poses significant risk to benthic organisms. Therefore, it is imperative to evaluate the long‐term toxicity of DDT. However, limited information is available on its chronic toxicity to benthic invertebrates. Full–life cycle toxicity of sediment‐bound DDT to Chironomus dilutus was assessed. Median lethal concentrations (with 95% confidence limits) of DDT and its degradation products (DDX) to C. dilutus were 334 (165–568), 21.4 (11.2–34.3), and 7.50 (4.61–10.6) nmol/g organic carbon after 10‐, 20‐, and 63‐d exposure, respectively. In addition, median effect concentrations of DDX were 20.0 (15.0–25.3), 7.13 (4.10–10.5), and 8.92 (3.32–15.1) nmol/g organic carbon for growth, emergence, and reproduction, respectively. A toxicity spectrum was established to visually summarize chronic effects of DDX to midges. In addition, DDT degraded to dichlorodiphenyldichloroethane (DDD) and dichlorodiphenyldichloroethylene (DDE) during sediment aging, and their toxicity differed from that of the parent compound. Predicted toxic units of DDX in porewater were utilized to distinguish between toxicity from DDT and that of DDD and DDE. The results showed that DDD was the main contributor to the toxicity in C. dilutus. To improve the accuracy of sediment risk assessment of DDT, the composition of DDX should be considered. Environ Toxicol Chem 2019;38:2698–2707. © 2019 SETAC [ABSTRACT FROM AUTHOR]

This study concentrates on the parameter estimation of multivariate pseudo‐linear autoregressive moving average systems by means of the multi‐innovation identification theory and data filtering technique. A multi‐innovation stochastic gradient algorithm is derived by introducing the innovation length in the stochastic gradient algorithm. Then, the original system is transformed into two subsystems by using a filter. A filtering‐based multi‐innovation stochastic gradient algorithm is presented, whose parameter estimation accuracy is higher than the multi‐innovation stochastic gradient algorithm. The simulation results confirm that these two algorithms are effective. [ABSTRACT FROM AUTHOR]

Firing accuracy is a critical quantity of interest in the performance analysis of electromagnetic railgun (EMRG) exterior ballistics. Since the simulation technique is always used to simulate the complex physical system at a low cost, it is employed to evaluate the firing accuracy of railgun projectile with uncertainty in this paper. An exterior ballistics simulation model of the railgun, including 3-DOF flight mechanical model, relative kinematic model, and guidance law model, is developed to simulate the ballistics behavior in the missile target intercept mission. The firing accuracy is studied in this paper to compare the capability of EMRG with different ranges and muzzle velocities. In order to explore the firing accuracy of the guided projectile, the guidance precision analysis and ballistics uncertainty quantification are studied. In the guidance precision analysis, the shot range and efficiency are used to make a comparison. In addition, the sensitivity analysis and firing accuracy analysis are also performed in terms of uncertainty quantification. The simulation results illustrate that the simulation of the guided projectile can give some practical guide to the projectile design of EMRG. [ABSTRACT FROM AUTHOR]

A finite‐difference time‐domain method is proposed to reduce the numerical dispersion error induced by the non‐uniform meshing of multiscale configurations utilizing weighted Laguerre polynomials. The update functions of two‐dimensional TEz waves are obtained with the introduction of the artificial anisotropic parameters in the derivation procedure. The theoretical analysis of utilizing artificial anisotropic weighted Laguerre polynomial finite‐difference time‐domain for the suppression of numerical dispersion error is also presented. To verify the validation of the proposed method, the propagation of plane waves in a two‐dimensional cavity filled with the dielectric material is modelled. Compared with the existing approaches, the proposed method achieves low numerical dispersion error and improved accuracy without increasing computational cost. [ABSTRACT FROM AUTHOR]

Highlights • An individual-based model was coupled with a machine learning model to explore the variability of both the slope and intercept of the self-thinning line. • Different modes of both competition and facilitation were modelled simultaneously. • A comprehensive evaluation of the role and importance of biotic and abiotic factors in altering the self-thinning line. • The joint application of individual-based modelling and machine learning can strengthen ecology. Abstract The generality and variability of the self-thinning rule in plant populations have been intensively debated in the past decades. Recent studies on self-thinning focus on understanding how the variability arises and are dedicated to a broader theory, with different biotic and abiotic factors suggested to explain the variability of the self-thinning line. However, the relative role and importance of different factors in altering the self-thinning line are still unclear. Using a generic individual-based model which simultaneously implements different modes (symmetric versus asymmetric) of both competition and facilitation among individual plants, we explored the variability of the self-thinning line in simulated plant populations. We employed a machine learning approach (Random Forests) to evaluate the potential effect and importance of seven biotic and abiotic factors (i.e. mode of competition, mode of facilitation, abiotic stress level, initial density, initial spatial distribution pattern, threshold of death and method used for fitting self-thinning lines) on simulated self-thinning lines. Simulations of the individual-based model demonstrated a significant variation in self-thinning lines. Our Random Forests models were able to explain and predict more than 98% of the variation in both the slope and intercept of the self-thinning line. These models identified mode of competition as being the most important factor that alters both the slope and intercept of the self-thinning line. For the variation of slope, other factors were much less important than competition. Most of the factors were more important in altering the intercept rather than the slope of self-thinning line. Changes of the slope and intercept in response to different factors indicated their divergent roles and partial effects on self-thinning mechanisms. Our study demonstrates that different biotic and abiotic factors have distinct effects and importance in altering the self-thinning rule, implying context dependent outcomes and consequences. We highlight that individual-based models and machine learning approaches are powerful tools to evaluate driving factors and to understand hidden mechanisms underlying complex patterns. The joint application of the two powerful tools will help to extend the framework of self-thinning and foster other research in ecology. [ABSTRACT FROM AUTHOR]

Highlights • A strategy is proposed to detect the early fault signals of bearings. • Frequency band extraction method extracts the signal within a resonant frequency band. • Particle swarm optimization optimizes factors of tunable Q-factor wavelet transform. • The strategy can effectively detect early fault signals compares with other methods. Abstract Early fault signals of bearings feature a wide frequency band and strong background noise, which contain both an oscillation component and a periodic impact component. Given its excellent signal decomposition performance, an improved tunable Q-factor wavelet transform (ITQWT) method is applied to separate a measured bearing fault signal into a high-Q-factor oscillation component and a low-Q-factor periodic impact component. In ITQWT, the Q-factors of TQWT are selected by particle swarm optimization to ensure the accuracy of its decomposition. Due to the weak fault symptoms and heavy noise of early fault signals, ITQWT is difficult to apply directly for early fault detection. Thus, a strategy based on frequency band extraction and ITQWT for early fault diagnosis in bearings is proposed. Frequency band extraction based on frequency slice wavelet transform (FSWT) shows significant advantage on observed frequency band selection, which could be highly suitable to extract early fault transient signals within a resonant frequency band. The improved performance of the proposed strategy is tested in simulated and experimental signals. Relative to other methods such as: TQWT and two spectral kurtosis-based methods, the proposed strategy is suitable and reliable for the weak fault feature detection of bearings at the early fault stage. [ABSTRACT FROM AUTHOR]

Abstract Leukemia is the most frequent malignancy in children with acute myeloid leukemia (AML) as the second commonest type. Long non-coding RNA zinc finger antisense 1 (ZFAS1) has been widely reported as an oncogenic factor in multiple malignancies including AML. However, the roles and molecular mechanisms of ZFAS1 in the tumorigenesis of AML are poor defined till now. In the present study, RT-qPCR assay showed that ZFAS1 was highly expressed in bone marrow of acute leukemia patients and AML cell lines. Loss-of-function analyses revealed that ZFAS1 knockdown inhibited proliferation and promoted apoptosis in AML cells and curbed AML xenograft growth in vivo. Bioinformatics analysis and luciferase reporter assay unveiled that microRNA-150 (miR-150) could interact with ZFAS1, Myb 3′ UTR and Sp1 3′ UTR. Moreover, ZFAS1 acted as a molecular sponge of miR-150, giving rise to the downregulation of miR-150 level and upregulation of Myb and Sp1 levels. Moreover, miR-150 overexpression resulted in the reduction of AML cell proliferative ability and the increase of cell apoptotic rate. Additionally, the inhibition of miR-150 abrogated ZFAS1 loss-mediated anti-leukemia effects. In summary, our data demonstrated that ZFAS1 knockdown hampered AML progression by regulating miR-150/Myb and miR-150/Sp1 pathways, providing some potential biomarkers or targets for the diagnosis and treatment of leukemia. [ABSTRACT FROM AUTHOR]

Purpose Early fault detection of bearing plays an increasingly important role in the operation of rotating machinery. Based on the properties of early fault signal of bearing, this paper aims to describe a novel hybrid early fault detection method of bearings.Design/methodology/approach In adaptive variational mode decomposition (AVMD), an adaptive strategy is proposed to select the optimal decomposition level K of variational mode decomposition. Then, a criterion based on envelope entropy is applied to select the optimal intrinsic mode functions (OIMF), which contains most useful fault information. Afterwards, local tangent space alignment (LTSA) is used to denoising of OIMF. The envelope spectrum of the OIMF is used to analyze the fault frequency, thereby detecting the fault. Experiments are conducted in a simulated signal and two experimental vibration signals of bearings to verify the effect of the new method.Findings The results show that the proposed method yields a good capability of detecting bearing fault at an early stage. The new method can extract more useful information and can reduce noise, which can provide better detection accuracy compared with the other two methods.Originality/value An adaptive strategy based on center frequency is proposed to select the optimal decomposition level of variational mode decomposition. Envelope entropy is used to fault feature selection. Combining the advantage of the AVMD-envelope entropy and LTSA, which suits the nature of the early fault signal. So, the proposed method has better detection accuracy, which provides a good alternative for early fault detection of bearings. [ABSTRACT FROM AUTHOR]

Band selection is an important data dimensionality reduction tool in hyperspectral images (HSIs). To identify the most informative subset band from the hundreds of highly corrected bands in HSIs, a novel hyperspectral band selection method using a crossover‐based gravitational search algorithm (CGSA) is presented in this study. In this method, the discriminative capability of each band subset is evaluated by a combined optimisation criterion, which is constructed based on the overall classification accuracy and the size of the band subset. As the evolution of the criterion, the subset is updated using the V‐shaped transfer function‐based CGSA. Ultimately, the band subset with the best fitness value is selected. Experiments on two public hyperspectral datasets, i.e. the Indian Pines dataset and the Pavia University dataset, have been conducted to test the performance of the proposed method. Comparing experimental results against the basic GSA and the PSOGSA (hybrid PSO and GSA) revealed that all of the three GSA variants can considerably reduce the band dimensionality of HSIs without damaging their classification accuracy. Moreover, the CGSA shows superiority on both the effectiveness and efficiency compared to the other two GSA variants. [ABSTRACT FROM AUTHOR]

Abstract The distribution of defect weak absorption and nanosecond pulse laser induced damage characteristics of HfO 2 /SiO 2 multilayers were investigated. A combination of in-situ measurements of defect weak absorption distribution and laser induced damage threshold (LIDT) map was proposed, whereby the evolution of defect weak absorption and the laser induced damage morphology under laser irradiation was studied. During the laser irradiation, some nodular and scalded defects can be removed or passivated by the low flux laser, and the absorption of these defect types was reduced accordingly. Besides, catastrophic destruction defects with enhanced absorption after laser irradiation would develop into catastrophic damage. Further, two-dimensional scanning of the sample surface was used to study the relationship between defects weak absorption and the LIDT. The results indicated that the correlation of defects weak absorption intensity distribution and LIDT map depended on defect evaluation properties during the laser irradiation. Highlights • In-situ measurement linking absorption and laser induced damage threshold (LIDT). • Evolution of weak absorption and damage morphology was observed by 2D scanning. • Correlation between weak absorption and LIDT was established. [ABSTRACT FROM AUTHOR]

Many scientific studies collect data where the response and predictor variables are both functions of time, location, or some other covariate. Understanding the relationship between these functional variables is a common goal in these studies. Motivated from two real-life examples, we present in this article a function-on-function regression model that can be used to analyze such kind of functional data. Our estimator of the 2D coefficient function is the optimizer of a form of penalized least squares where the penalty enforces a certain level of smoothness on the estimator. Our first result is the representer theorem which states that the exact optimizer of the penalized least squares actually resides in a data-adaptive finite-dimensional subspace although the optimization problem is defined on a function space of infinite dimensions. This theorem then allows us an easy incorporation of the Gaussian quadrature into the optimization of the penalized least squares, which can be carried out through standard numerical procedures. We also show that our estimator achieves the minimax convergence rate in mean prediction under the framework of function-on-function regression. Extensive simulation studies demonstrate the numerical advantages of our method over the existing ones, where a sparse functional data extension is also introduced. The proposed method is then applied to our motivating examples of the benchmark Canadian weather data and a histone regulation study. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

[Display omitted] • Two different methods were used for the modification of porous maize starch. • Thermal stability of curcumin was improved by curcumin-starch microspheres. • Different modifications enhanced the antioxidant capacity of curcumin in microspheres. • The crosslinked porous starch increased the sustained-release capacity of curcumin. Maize porous starch-curcumin microspheres were prepared by encapsulating curcumin into cross-linked porous starch and oxidized porous starch to investigate the effect of modified porous starch in embedding and protecting curcumin. The morphology and physicochemical properties of microspheres were analyzed using scanning electron microscopy, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction, Zeta/DLS, Thermal stability, and antioxidant activity; the release of curcumin was evaluated with a simulated gastric-intestine model. The FT-IR results revealed that curcumin was amorphously encapsulated in the composite and hydrogen bond formation between starch and curcumin was one of the major driving forces for encapsulation. Microspheres increased the initial decomposition temperature of curcumin, which has a protective effect on curcumin. Modification improved the encapsulation efficiency and the scavenging free radical ability of porous starch. The release mechanism of curcumin from microspheres fits first-order and Higuchi models well in gastric and intestinal models, respectively, indicating that encapsulation of curcumin within different porous starches microspheres enables controlled release of curcumin. To recapitulate, two different modified porous starch microspheres improved the drug loading, slow release and free radical scavenging effects of curcumin. Among them, the cross-linked porous starch microspheres had higher encapsulation and slow release ability for curcumin than the oxidized porous starch microspheres. It provides theoretical significance and data basis for the encapsulation of active substances by modified porous starch. [ABSTRACT FROM AUTHOR]

Sijunzi Decoction (SJZD) is a renowned formula for the treatment of spleen deficiency syndrome (SDS) in traditional Chinese medicine (TCM). Its non-polysaccharides (NPS) component, dominated by various compounds of SJZD, has shown the remarkable efficacy in SDS, especially in gastrointestinal injury. However, the principle of compatibility of SJZD and the micro-mechanism of effect on SDS are still unclear. To elucidate the scientific implications of SJZD compatibility and its micro-mechanism in the treatment of SDS-induced intestinal injury. First, the chemical composition of NPS in SJZD and incomplete SJZD (iSJZD, including SJZD-R, SJZD-A, SJZD-P, SJZD-G) were comprehensively analyzed by UPLC-QTOF-MS, and comparing their chemical composition by multivariate statistical analysis to reveal the effect of a single herb on SJZD compatibility. Second, network pharmacology and molecular docking were used to uncover the micro-mechanisms of potential active compounds in SJZD for the treatment of SDS, and develop an active component combination (ACC) by accurate quantification. Subsequently, the action of the potential active compounds and ACC was verified through in vivo and in vitro. A total of 112, 77, 93, 87, and 67 compounds were detected in NPS of SJZD, SJZD-R, SJZD-A, SJZD-P, and SJZD-G, respectively. Changes in the chemical components of SJZD_NPS and iSJZD_NPS revealed that RG and RAM, as well as RAM and Poria significantly affected the dissolution of each other's chemical components, and the co-decoction of four herbs promoted the dissolution of the active compounds and inhibited toxic compounds. Furthermore, network pharmacology showed that 274 compounds of 15 categories in SJZD_NPS acted on the 186 key targets to treat SDS by inhibiting inflammation, enhancing immunity, and regulating gastrointestinal function and metabolism. Finally, through in vitro experiments, six compounds among 18 potential compounds were verified to markedly repair intestinal epithelium injury by modulating the FAK/PI3K/Akt or LCK/Ras/PI3K/Akt signaling pathway. It is worth mentioning that ACC, composed of 11 compounds accurately quantified, demonstrated significant in vivo treatment effects on intestinal damage with SDS similar to NPS or SJZD. This study elucidates the scientific evidence of the " Jun-Chen-Zuo-Shi " and "detoxification and synergistic" in the decocting process of SJZD. An ACC, the active component of SJZD, ameliorate SDS-induced intestinal injury by the FAK/PI3K/Akt signaling pathway, which provides a strategy for screening alternatives to effective combinations of TCMs. [Display omitted] • Uncovering the principle of "Jun-Chen-Zuo-Shi" and "detoxification and synergistic" of four herbs in SJZD. • Various types of compounds in SJZD_NPS treat SDS through inhibiting inflammation, enhancing immunity, and regulating metabolism and gastrointestinal function. • Six potential active compounds and active component combination repaired the SDS with intestinal injury via modulating FAK/PI3K/Akt signaling pathway. [ABSTRACT FROM AUTHOR]

Credit scoring systems have seen revolutionary development in recent decades, with many classification algorithms being proposed. However, with the increase in the data volume, the performance of traditional algorithms tends to encounter bottlenecks. Although deep learning methods have advantages in handling big data, they are not commonly applied in credit scoring. As one of the most frequently used methods in deep learning, convolutional neural network (CNN) use convolutional kernels as feature extraction tools and has been very successful in tasks related to images or text. This is because image and text data naturally have a structural characteristic called spatial local correlation, which means that the pixels or tokens covered by the same convolutional kernel are highly correlated, and they can be jointly processed to extract meaningful feature representations. However, the tabular data used for credit scoring do not naturally have such a characteristic. The main contribution of this paper is to propose a novel end-to-end soft reordering one-dimensional CNN (SR-1D-CNN), which can adaptively reorganize the original tabular data and make them more conducive to CNN learning. Several real-world credit scoring datasets of different sizes are used for a comprehensive comparison with traditional machine learning classifiers and other deep learning methods. The experimental results demonstrate that the soft reordering mechanism can effectively improve the classification effect of the CNN for tabular data. With the increase in the data scale, the proposed approach obtains superior results to those of other benchmark models. [ABSTRACT FROM AUTHOR]