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The article titled "Quality assessment for virtual reality technology based on real scene" has been retracted by the Editor-in-Chief and the publisher due to concerns about compromised editorial handling and peer review process, inappropriate references, and not being in line with the journal's scope. The authors have not responded to the publisher's correspondence regarding this retraction. Springer Nature, the publisher, remains neutral regarding jurisdictional claims and institutional affiliations. [Extracted from the article]

This paper introduces a new framework for cooperative games with restricted permutations, focusing on situations where not all possible player permutations occur. The framework allows players within an ordered coalition to exchange positions if it benefits them. To ensure stable connections among players, we introduce the concept of stably connected ordered coalitions, which incorporates the notions of objection and counter-objection. We then define an order-restricted game, a generalized characteristic function game derived from the original game. Additionally, inspired by the Shapley value, we propose an allowable value and provide its axiomatization. Finally, we explore several extensions of this value to further investigate its potential applications. [ABSTRACT FROM AUTHOR]

• Mg-Gd master alloy has a significant modification effect on eutectic silicon of Al-Si alloy. • The mechanism of modification of eutectic Si by Mg-Gd master alloy is twin groove mechanism. • The 1.0wt.%Mg-Gd master alloy can improve the mechanical properties of Al-Si alloy. In this study, the modification of eutectic Si was carried out by adding Mg-Gd master alloy to Al-10Si aluminum alloy. The influence mechanism of Mg-Gd master alloy modification Si on the morphology, size and mechanical properties were studied. The results show that the Mg-Gd master alloy has a remarkable modification effect on eutectic Si, with the average length of eutectic silicon changing from 11.71 μm to 1.95 μm. A large number of twin bands appear in eutectic Si after modification, and the modification mechanism is mainly twin plane reentrant edges. After modification, the mechanical properties are improved significantly and the fracture mode is mainly quasi cleavage fracture. [ABSTRACT FROM AUTHOR]

This study presents an investigation on the influence of loading rate and temperature on mode I interlaminar fracture toughness of unidirectional composite laminates. An analytical model was developed to describe the temperature- and loading rate-dependent fracture toughness, and a loading rate coefficient m was defined to evaluate the rate dependency. Quasi-static and dynamic double cantilever beam (DCB) tests were conducted at various temperatures from −20 to 110 °C. A dual electromagnetic Hopkinson bar was employed to perform dynamic tests under loading rates of 15 and 24 m/s to achieve pure mode I delamination. The experimental results show that the fracture toughness exhibits an obvious positive loading rate sensitivity at all temperatures, whereas the loading rate coefficient m shows two different trends with temperature indicating different loading rate dependency. Fractography observations reveal an obvious transition in the dominant failure mechanism at low temperatures from fiber/matrix interface debonding under quasi-static conditions to brittle fracture of matrix under dynamic conditions. However, both the quasi-static and dynamic delamination surfaces exhibit multiple failure modes at high temperatures. It is reasonable to deduce that the effect of temperature and loading rate can be attributed to the nature of matrix, the bonding between fiber and matrix. [Display omitted] • Dynamic DCB tests under different temperatures are performed by adopting electromagnetic Hopkinson bar. • An analytical model is developed to assess the loading rate and temperature-dependent interlaminar fracture toughness. • Different loading rate dependency of mode I fracture toughness is evaluated at different temperatures. • The effects of temperature and loading rate on failure mechanism in mode I delamination are identified. [ABSTRACT FROM AUTHOR]

In this work, the valence states and optical properties of chromium-doped Mg 2 GeO 4 are investigated via first-principles methods. The formation energies and thermal charge transition levels show that the site occupation and valence states of chromium are strongly related to the growth condition: Cr3+ dominates in the Mg sites under Mg-poor conditions, and Cr4+ dominates in the Ge sites under Ge-poor conditions. With the lithium co-doping, the Fermi-level is pinned below the midgap, and the formation energies of chromium-doped Mg sites become the lowest either Mg-poor or Ge-poor conditions, suggesting that the co-doping of lithium ions promotes the chromium to preferentially occupy Mg sites, in good agreement with experiments. Furthermore, the excitation and emission processes of chromium ions are investigated, and our results recommend that the near-infrared emission is related to the 4T 2 to 4A 2 transition of Cr3+ at the Mg sites and the infrared emission is related to the 3T 2 -3A 2 transition of Cr4+ at the Ge site. Our results help to understand the stability of the valence states of chromium ions doped Mg 2 GeO 4 and the effects of ions co-doping in regulating the chromium valence states, as well as the corresponding optical properties of different types of chromium ions. • The mechanics of valence state regulation of chromium ions is studied from first-principles. • The relationship between the site occupation of chromium ions is investigated. • The Fermi level regulated by lithium co-doping affects the site occupation and valence states of chromium ions. • The relationship between the emission process of chromium ions and the occupied site is discussed. [ABSTRACT FROM AUTHOR]

The southwestern Yangtze Craton hosts more than 400 carbonate‐hosted Pb–Zn deposits, and is well endowed with enormous base metals. The giant Maoping deposit is one of the most representative deposits, and the mineralization mainly occurs in the Devonian to Carboniferous dolomitic rocks. Its metallogenesis has been thoroughly discussed from many perspectives by previous studies, but it remains controversial, especially about the relationship between the structural process and the Pb–Zn mineralization. In this paper, we conducted large‐scale structural mapping and whole‐rock geochemical analysis to investigate the structural process and its control on the mineralization at Maoping. Three stages of deformation have been recognized, including the NE–SW‐striking folds and thrusts (D1), the N–S‐striking transtensional faults (D2), and the NW–SE‐striking transpressional structures (D3). The geochemical analysis shows relatively higher contents of the ore‐related trace elements in the tectonites from the N–S‐striking faults, indicating a close relationship between the N–S‐striking faults and the mineralization. Combined with field evidence and geochemical analysis, we propose that the N–S‐striking transtensional faults are likely the major ore‐conducting structures, and the NE–SW‐striking interlayer fractures serve as the assistant structures at the deposit scale. The regional NE–SW‐striking fold‐and‐thrust belts are suggested to dominate the spatial distribution and location of the Pb–Zn deposits in northeastern Yunnan at the regional scale. Our study enhances the understanding of the metallogenesis at Maoping and provides new insights into the Pb–Zn prospecting at both the regional scale and the deposit scale. [ABSTRACT FROM AUTHOR]

Surveys conducted by radio astronomy observatories, such as SKA, MeerKAT, Very Large Array, and ASKAP, have generated massive astronomical images containing radio galaxies (RGs). This generation of massive RG images has imposed strict requirements on the detection and classification of RGs and makes manual classification and detection increasingly difficult, even impossible. Rapid classification and detection of images of different types of RGs help astronomers make full use of the observed astronomical image data for further processing and analysis. The classification of FRI and FRII is relatively easy, and there are more studies and literature on them at present, but FR0 and FRI are similar, so it is difficult to distinguish them. It poses a greater challenge to image processing. At present, deep learning has made breakthrough progress in the field of image analysis and processing and has preliminary applications in astronomical data processing. Compared with classification algorithms that can only classify galaxies, object detection algorithms that can locate and classify RGs simultaneously are preferred. In target detection algorithms, YOLOv5 has outstanding advantages in the classification and positioning of small targets. Therefore, we propose a deep-learning method based on an improved YOLOv5 object detection model that makes full use of multisource data, combining FIRST radio with SDSS optical image data, and realizes the automatic detection of FR0, FRI, and FRII RGs. The innovation of our work is that on the basis of the original YOLOv5 object detection model, we introduce the SE Net attention mechanism, increase the number of preset anchors, adjust the network structure of the feature pyramid, and modify the network structure, thereby allowing our model to demonstrate galaxy classification and position detection effects. Our improved model produces satisfactory results, as evidenced by experiments. Overall, the mean average precision (mAP@0.5) of our improved model on the test set reaches 89.4%, which can determine the position (R.A. and decl.) and automatically detect and classify FR0s, FRIs, and FRIIs. Our work contributes to astronomy because it allows astronomers to locate FR0, FRI, and FRII galaxies in a relatively short time and can be further combined with other astronomically generated data to study the properties of these galaxies. The target detection model can also help astronomers find FR0s, FRIs, and FRIIs in future surveys and build a large-scale star RG catalog. Moreover, our work is also useful for the detection of other types of galaxies. [ABSTRACT FROM AUTHOR]

This paper investigates an adaptive cooperative fault-tolerant supervisory control problem for nonlinear strict-feedback leader-following systems with unknown control coefficients and actuator faults under the fixed directed graph. Radial basis function neural networks are used to approximate system uncertainties. The Nussbaum gain technique is introduced to address unknown signs of control gains. Then, based on the dynamic surface control method, a distributed adaptive fault-tolerant control scheme is presented to compensate for the actuator faults of followers. For neural networks approximation theory, the unknown smooth function can only be approximated on a compact set due to the approximation errors. By theoretic analysis, the supervisory-based adaptive controllers are proposed to guarantee that system state signals can converge to compact sets and the leader-following systems can achieve the practical output consensus. Finally, the simulation results are provided to show the validity of the proposed consensus scheme. [ABSTRACT FROM AUTHOR]

Graph Convolutional Networks are able to characterize non-Euclidean spaces effectively compared with traditional Convolutional Neural Networks, which can extract the local features of the point cloud using deep neural networks, but it cannot make full use of the global features of the point cloud for semantic segmentation. To solve this problem, this paper proposes a novel network structure called DeepGCNs-Att that enables deep Graph Convolutional Network to aggregate global context features efficiently. Moreover, to speed up the computation, we add an Attention layer after the Graph Convolutional Network Backbone Block to mutually enhance the connection between the distant points of the non-Euclidean space. Our model is tested on the standard benchmark S3DIS. By comparing with other deep Graph Convolutional Networks, our DeepGCNs-Att's mIoU has at least two percent higher than that of all other models and even shows excellent results in space complexity and computational complexity under the same number of Graph Convolutional Network layers. [ABSTRACT FROM AUTHOR]

The third or organismic view of space states that space is neither lifeless nor neutral, but a living structure capable of being more living or less living, thus different fundamentally from the first two mechanistic views of space: Newtonian absolute space and Leibnizian relational space. The living structure is defined as a physical and mathematical structure or simply characterized by the recurring notion (or inherent hierarchy) of far more small substructures than large ones. This paper seeks to lay out a new geography as a science of the Earth's surface founded on the third view of space. The new geography aims not only to better understand geographic forms and processes but also – maybe more importantly – to make geographic space or the Earth's surface to be living or more living. After introducing two fundamental laws of geography: Tobler's law on spatial dependence (or homogeneity) and scaling law on spatial heterogeneity, we argue that these two laws are fundamental laws of living structure that favour statistics over exactitude, because the former (or statistics) tends to make a structure more living than the latter (or exactitude). We present the concept of living structure through some working examples and make it clear how a living structure differs from a non-living structure, under the organismic worldview that was first conceived by the British philosopher Alfred Whitehead (1861–1947). In order to make a structure or space living or more living, we illustrate two design principles – differentiation and adaptation – using two paintings and two city plans. The new geography is a science of living structure, dealing with a wide range of scales, from the smallest scale of ornaments on walls to the scale of the entire Earth's surface. [ABSTRACT FROM AUTHOR]

The railway system is a prime example of a safety-critical system. Predicting the causes of railway accidents holds immense significance in enhancing railway transportation safety. Previous approaches to railway causation analysis have encountered huge challenges regarding data processing and analytical capabilities. To address this concern, this paper proposes an innovative deep model framework based on the Transformer architecture that utilizes historical data on railway equipment accidents to predict the causes behind such incidents. Firstly, this paper proposes the utilization of Convolutional Block Attention in the domain of text processing, serving as a lexical encoder to augment word semantics acquisition in accident texts. Subsequently, in order to address the deficiency of traditional Transformers that lack positional representation information, we propose incorporating a BiGRU (Bidirectional Gated Recurrent Unit) as a contextual positional information encoder to capture contextual positional information in railway accident data effectively. Finally, considering that accident data reports are discrete tabular data, this study suggests employing cue word techniques for preprocessing accident data to alleviate the model's learning burden. We applied the proposed model to the FRA (Federal Railroad Administration) dataset. The results demonstrate that our model surpasses the current state-of-the-art language models, exhibiting superior performance compared to the optimal model with a notable improvement of 3.56%, 0.42%, and 0.76% in Precision, Recall, and F1-score, respectively. Furthermore, our model accurately predicts accident categories prone to misjudgment even when trained on limited data, outperforming existing language models. The study findings will contribute to the prevention and management of railway accidents. [ABSTRACT FROM AUTHOR]

[Display omitted] • Active learning cycle system was designed to explore high-entropy alloys with exceptional hardness. • Screened 30 Al-Co-Cr-Cu-Fe-Ni compositions exhibit a predicted hardness higher than 650 HV. • Four alloys exhibit ultra-high hardness (>740 HV) and low density (<5.9 g/cm3). • Precipitation strengthening of disordered nanoparticles leads to an increase in hardness. High-entropy alloys (HEAs) have attracted considerable attention for their exceptional microstructures and properties. Discovering new HEAs with desirable properties is crucial, but traditional design methods are laborious and time-consuming. Fortunately, the emerging Machine Learning (ML) offers an efficient solution. In this study, composition-microhardness data pairs from various alloy systems were collected and expanded using a Generative Adversarial Network (GAN). These data pairs were converted into empirical parameter-microhardness pairs. Then Active Learning (AL) was employed to screen the Al-Co-Cr-Cu-Fe-Ni system and identify the eXtreme Gradient Boosting (XGBoost) as the optimal ML master model. Millions of data training iterations employing the XGBoost sub-model and accuracy evaluations using the Expected Improvement (EI) algorithm establish the relationship between HEA compositions and microhardness. The proposed sub-model aligns well with experimental data, wherein four Al-rich compositions exhibit ultra-high microhardness (>740 HV, with a maximum of ∼780.3 HV) and low density (<5.9 g/cm3) in the as-cast bulk state. The hardening increment originates from the precipitation of disordered BCC nanoparticles in the ordered AlCo-rich B2 matrix compared to the dilute B2 AlCo intermetallics. This lightweight, high-performance alloy shows potential for engineering applications as thin films or coatings. [ABSTRACT FROM AUTHOR]

• Changes in oil composition are indicated during SSA-B&M. • Acidic compounds increase during biodegradation but crack when Easy%Ro > 0.8 %. • Nitrogen compounds resistant to biodegradation and maturation are characterized. • Two new indices were defined to recover biodegradation and maturity during SSA-B&M. The Tarim and Junggar basins are major petroliferous sedimentary deposits in China. Some oil reservoirs in these basins experienced superimposed secondary alterations including early biodegradation followed by thermal maturation/alteration (SSA-B&M). Heteroatomic polar organic compounds in crude oil are significantly influenced by SSA-B&M, which play a vital role in understanding the evolutionary history of oil reservoir. However, research on such alterations is limited. The present study employed negative and positive ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) to investigate the molecular transformations of heteroatomic organic compounds in crude oils resulting from SSA-B&M. The findings indicate that biodegradation leads to an enrichment of naphthenic acids, while subsequent cyclization, aromatization and thermal cracking reactions enhances the aromaticity of the pyrolysis products of all the oil samples with varying degree of biodegradation. Notably, highest aromaticity was observed for the crude oil that has been most severely altered by biodegradation. During early and moderate stages of biodegradation, the abundances of O2 compounds (molecules contain two oxygen atoms) representing carboxylic acids were continuously increasing. However, at severe biodegradation levels, fatty acids with 1 double bond equivalents (DBE) underwent degradation, while the naphthenic acids were further enriched. Subsequently, during maturation, O2 compounds with 1 to 5 DBE experienced a steady decline in abundance. The naphthenic acids mainly experienced aromatization, while the fatty acids were partly decarboxylized and cracked thereby forming new n-alkanes. Biodegradation led to modification in neutral nitrogen compounds with 3 to 4 condensed rings (DBE = 9–12) and long alkyl side chains, while the impact on basic nitrogen compounds was relatively minimal. After subsequent thermal maturation, both neutral and basic nitrogen compounds with long alkyl side chains underwent cracking, while those with shorter alkyl side chains and higher degrees of condensation tended to remain relatively unchanged. Finally, two new indices were defined and tested to correctly evaluate the maturation and biodegradation level for crude oils that have experienced SSA-B&M. [ABSTRACT FROM AUTHOR]

Bearing skidding is a frequent phenomenon in rotating machinery, which causes equipment motion instability and bearing wear failure. Due to the difficulties in the manufacture of high-speed flexible rotor test rig, measurement of bearing motion parameters and complex structure of angular contact ball bearing (ACBB), which makes the research on double-piece inner ring ACBB skidding challenging. This paper studies the ACBB skidding mechanism from the aspect of rotor characteristics, and first finds the resonance skidding phenomenon. Firstly, a high-speed flexible rotor test rig is designed and built to study the ACBB skidding mechanism, and the influence of foreign matter on the bearing cage slip rate is systematically studied. Then, the bearing cage speed considering the influence of lubricating oil pollution is accurately measured based on the adaptive fractional short-time Fourier transform. Finally, bearing skidding diagnosis under variable working conditions is realized based on the deep meta-transfer learning with feature enhanced generative adversarial network and average deflection power threshold. These proposed strategies systematically solve some problems in the research field of ACBB skidding, which has high practical significance and theoretical guidance value. • The resonance skidding phenomenon is first found by considering flexible rotor characteristics. • Bearing cage speed is accurately measured based on the eddy current sensor. • The influence of foreign matter on ball bearing skidding is first systematically studied. • Bearing skidding diagnosis is realized based on the deep meta-transfer learning. [ABSTRACT FROM AUTHOR]

Developing advanced nanofiltration membranes (NFMs) for inorganic salt ions separation remains a significant challenge in the value-added process of water treatment. Herein, we engineered a highly permeable-selective TA/Fe/Ca/PA-p NFM through a novel strategy for the interfacial polymerization (IP) regulated by the dynamic polyphenol-metal coordination. Interestingly, the dynamic coordination occurred after the substrate surface was first modified with tannic acid (TA) and Fe3+ and then coated with an aqueous phase solution containing piperazine (PIP) and Ca2+. In this process, the coordination competition between Fe3+ and Ca2+ for TA and the conversion of TA/Fe3+ bis-complex into tris-complex were conducive to forming more uniform TA/Fe/Ca complex on the substrate surface. Meanwhile, TA can also perform Michael addition with PIP to control the diffusion of PIP to the organic phase. Following the IP reaction, the nascent TA/Fe/Ca/PA NFM underwent post-treatment in a sodium citrate (SC) solution to dissociate the TA/Fe/Ca complex by further applying the dynamic coordination, resulting in a crumpled and thinner separation layer with desirable surface properties. The optimized TA/Fe2/Ca/PA-p NFM exhibited a pure water permeability of 36.1 L m−2 h−1⋅bar−1, nearly 2.4 times higher than that of the original PA NFM. Correspondingly, the Na 2 SO 4 rejection reached 99.4 % and its Cl−/SO 4 2− separation factor was 118.3. This outstanding permselectivity was mainly attributed to the decreased mass transfer resistance, the expanded effective permeability area, and the increased negative charge on the membrane surface. Additionally, the TA/Fe2/Ca/PA-p NFM was endowed with good operational stability, pressure resistance, and antifouling performance. This eco-friendly and cost-effective approach paves the way for fabricating high-performance NFMs and demonstrates the great potential of dynamic polyphenol-metal coordination in water treatment. [Display omitted] • An advanced PA NFM was regulated by the dynamic polyphenol-metal coordination. • Dynamic coordination includes the competition, conversion and dissociation of complexes. • A crumpled and thinner separation layer with desirable surface properties was constructed. • The NFM exhibited high permeability and high Cl−/SO 4 2− selectivity. [ABSTRACT FROM AUTHOR]

In this article, the issue of distributed sensor fault estimation with resilient property is studied for a class of multi‐agent systems. Based on the relative output information, a novel fault estimation design is presented to estimate sensor fault and state vectors simultaneously. Meanwhile, the variation of observer gain is considered to improve the robustness of fault estimation observer. Furthermore, robust l2−l∞ performance is used to suppress the influence of external interference on sensor fault estimation error. Finally, simulations are provided to present effectiveness of the developed approach. [ABSTRACT FROM AUTHOR]

In this paper, we pioneer a new machine-learning method to search for H ii regions in spectra from The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). H ii regions are emission nebulae created when young and massive stars ionize nearby gas clouds with high-energy ultraviolet radiation. Having more H ii region samples will help us understand the formation and evolution of stars. Machine-learning methods are often applied to search for special celestial bodies such as H ii regions. LAMOST has conducted spectral surveys and provided a wealth of valuable spectra for the research of special and rare celestial bodies. To overcome the problem of sparse positive samples and diversification of negative samples, a novel method called the self-calibrated convolution network is introduced and implemented for spectral processing. A deep network classifier with a structure called a self-calibrated block provides a high precision rate, and the recall rate is improved by adding the strategy of positive-unlabeled bagging. Experimental results show that this method can achieve better performance than other current methods. Eighty-nine spectra are identified as Galactic H ii regions after cross-matching with the WISE Catalog of Galactic H ii Regions, confirming the effectiveness of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

This article presents a fault-tolerant tracking control strategy for Takagi–Sugeno fuzzy model-based nonlinear systems which combines integral sliding mode control with adaptive control technique. Two common actuator faults: 1) loss of effectiveness and 2) increased bias input, are considered simultaneously. The fuzzy tracking control system is first established by incorporating the integral term of the output tracking error. Then, an appropriate fuzzy integral switching surface is designed such that the corresponding sliding motion only suffers from the unamplified unmatched disturbance. The solution of the nominal tracking controller can be transformed into a to convex optimization problem. In particular, an adaptive fuzzy sliding mode tracking controller is synthesized to ensure the accessibility of the sliding motion despite the effect of actuator faults and unknown disturbances. Finally, the proposed tracking strategy is verified by applying it to the dynamic positioning control of unmanned marine vehicles. [ABSTRACT FROM AUTHOR]

This paper proposed an axial multistage compressor aerodynamic design methodology based on dimensional zooming. Two-dimensional design parameters are acquired through the dimensionality reduction of three-dimensional data to avoid dependence on the empirical loss models. The research on the zooming design method is conducted on a self-designed five-stage compressor. The method has considered the three-dimensional end wall viscosity loss and modified the blade profiles and blade stacking. It provided a path on how to improve the blade design based on computational fluid dynamics analysis. The aerodynamic performance, compressor characteristics of the prototype, and the zooming design are investigated and compared. The results show that the zooming design compressor performances are improved than those of the prototype one. [ABSTRACT FROM AUTHOR]

Direct determination of the equilibrium adsorption and spectroscopic observation of adsorbent‐adsorbate interaction is crucial to evaluate the olefin/paraffin separation performance of porous adsorbents. However, the experimental characterization of competitive adsorption of various adsorbates at atomic‐molecular level in the purification of multicomponent gas mixtures is challenging and rarely conducted. Herein, solid‐state NMR spectroscopy is employed to examine the effect of co‐adsorbed guest adsorbates on the separation of ethylene/ethane mixtures on Mg‐MOF‐74, Zn‐MOF‐74 and UTSA‐74. 1H MAS NMR facilitates the determination of equilibrium uptake and adsorption selectivity of ethylene/ethane in ternary mixtures. The co‐adsorption of H2O and CO2 significantly leads to the degradation of ethylene uptake and ethylene/ethane selectivity. The detailed host‐guest and guest‐guest interactions are unraveled by 2D 1H−1H spin diffusion homo‐nuclear correlation and static 25Mg NMR experiments. The experimental results verify H2O coordinated on open metal sites can supply a new adsorption site for ethylene and ethane. The effects of guest adsorbates on the adsorption capacity and adsorption selectivity of ethylene/ethane mixtures are in the following order: H2O>CO2>O2. This work provides a direct approach for exploring the equilibrium adsorption and detailed separation mechanism of multicomponent gas mixtures using MOFs adsorbents. [ABSTRACT FROM AUTHOR]

The fault-tolerant control (FTC) issue for a class of interconnected wave-distributed parameter systems is addressed by using the inclusion principle. Both subsystem faults and coupling faults are considered. First, the original system is expanded into an equivalent decoupled system. The main structure of the expanded system consists of multiple pair-wise subsystems. Second, the pair-wise fault-tolerant controllers are designed to stabilise the pair-wise subsystems, which can compensate for the effects of subsystem faults and major coupling faults. Third, a coordinated fault-tolerant controller with a suitable coordinated compensator for the expanded system is constructed according to the pair-wise fault-tolerant controllers of all subsystems. The coordinated compensator is used to compensate for the effects of other minor interconnections and coupling faults, and the coordinated controller is designed for the expanded system. Furthermore, the fault-tolerant controller is obtained to guarantee asymptotical stability of the faulty interconnected wave system by satisfying the contraction condition. The numerical experiments are presented to illustrate the effectiveness of the FTC method. [ABSTRACT FROM AUTHOR]

To improve the accuracy of warfarin daily dose prediction, we develop an evolutionary synthetic oversampling technique (ESMOTE) with a cocktail ensemble model (CEM) called ESMOTE-CEM. Different from conventional oversampling methods, ESMOTE finds the near-optimal oversampling parameters by evolving the parameter representation based on the pre-predicted warfarin dose and then synthesizes new samples to balance the data. The CEM, which improves the performance of random forest (RF) and boosted regression tree (BRT) models using a hybrid mechanism in the regression calculation, estimates the daily dose of warfarin. We test the ESMOTE-CEM on a dataset of 733 samples collected from the First Affiliated Hospital of Soochow University and the International Warfarin Pharmacogenetics Consortium (IWPC). The results show that ESMOTE outperformed the other oversampling methods by at least 6.98% for R2 and 5.03% for the mean squared error (MSE). In terms of the percentage of patients whose predicted warfarin dose is within 20% of the actual stable therapeutic dose (20%-p value), the ESMOTE-CEM achieves a 20%-p value of 50%. Moreover, compared to RF, BRT and AdaBoost models, the CEM is the most suitable base predictive model for ESMOTE. [ABSTRACT FROM AUTHOR]

Magnesium (Mg) alloys, as one of the lightest structural metallic materials, have attracted considerable attention in the automotive, aerospace, and microelectronic industries. However, wrought Mg alloys are easy to form a strong basal texture with the basal planes of hexagonal close-packed unit cells being parallel to the processing direction during hot processing. This extremely deteriorates the stretch formability of Mg alloy sheets at room temperature (RT) and limits their widespread industrial applications. To overcome this drawback, many studies have been devoted to controlling microstructures including grain sizes, texture characteristics and precipitates to achieve high-performance Mg alloy sheets via alloying and new processing techniques. In this review, we briefly summarize recent advances in enhancing the stretch formability of Mg alloy sheets at RT from two major aspects: (1) by the design of new alloy systems and (2) by the exploitation of advanced processing techniques. Both strategies hold great promise for developing high-performance and low-cost Mg alloy sheets with a superior combination of strength, ductility and stretch formability. Additionally, future research directions for the development of such high-performance Mg alloy sheets are suggested. We hope that this review can provide some insightful information for researchers who are committed to fabricating high-performance Mg alloys for lightweight structural applications in the transportation industry, so as to improve fuel efficiency and reduce climate-changing and health-compromising emissions. [ABSTRACT FROM AUTHOR]

BACKGROUND: α‐lactalbumin (α‐La) is of great interest to the industry as a result of its excellent functional properties and nutritional value. Aqueous two‐phase flotation (ATPF) of thermo‐sensitive polymer poly (ethylene glycol‐ran‐propylene glycol) monobutyl ether (UCON) and KH2PO4 was applied to directly separate and purify α‐La from milk whey, which was purposed to simplify the production process and reduced cost of production. RESULTS: The effect of ATPF composition and operating parameters on the flotation efficiency (E) and purity of α‐La were investigated. The optimal conditions included 2 min of premixing time, 30 mL min−1 flow velocity and 20 min of flotation time, whereas the composition conditions comprised 35.0 mL 0.18 g mL−1 phosphate solution (containing 10% (cow milk whey/salt solution, v/v) cow milk whey, 50 ppm defoamer and 2 g NaCl) and 5.0 mL of 40% (w/w) UCON solution. Under the optimal conditions, E of α‐La was 95.67 ± 1.04% and purity of α‐La was 98.78 ± 1.19%. UCON was recovered by a thermally‐induced phase separation and reused in next ATPF process without reducing E of α‐La. Purified α‐La was characterized by several key technologies. The results indicated that α‐La in cow milk whey could be directly separated and purified by the ATPF and the purity was satisfactory. Moreover, it was suggested there was no obvious structure difference between the α‐La separated by ATPF and the α‐La standard. CONCLUSION: The present study enabled the recycling of UCON, providing an effective, economically viable and environmentally friendly approach for the separation and purification of protein. © 2021 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

This paper develops a fault compensation scheme for a class of Euler–Bernoulli beam-ODE cascade systems to deal with certain boundary input faults, using a model transform-based backstepping control design. A model transformation is introduced to convert the Euler–Bernoulli beam-ODE cascade system to a Schrödinger-ODE cascade system. The FTC law is designed to compensate boundary input faults for the Schrödinger-ODE cascade system by constructing a normal intermediate system and a new exponentially stable target system. The purposes of the two-step backstepping are to bring in a state feedback and to improve the system performance. The performance of the target system, intermediate system, and Schrödinger-ODE cascade system is analysed in the Riesz basis frame. The stability analysis of the original Euler–Bernoulli beam-ODE cascade system is further provided. Simulation results illustrate the effectiveness of the proposed fault compensation scheme. [ABSTRACT FROM AUTHOR]

Due to the time-varying characteristics and the interacted nature of multiple faults in the high-speed train (HST), the fault modeling, isolation, and severity estimation cannot be described accurately using a single model, which may result in poor performance of the conventional fault diagnosis methods. This article introduces the idea of multiple models and second-level adaptation techniques to diagnose multiple faults of the HST traction motor. First, a reduced model description for the multiple faults is given. Then, a multiple fault isolation framework is developed to simplify the time-varying fault parameters space segmentation. Based on the decoupled fault set, a fault estimation scheme with second-level adaptation is used to provide a reliable alarm priority for different fault scenarios. A case study is performed to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper addresses a fault accommodation issue for flexible hypersonic vehicles by the static output feedback. Firstly, a longitudinal dynamics for hypersonic vehicles is established in the ODE-beam cascade form and the distributed fault model is built. Next, a novel fault accommodation scheme is developed to achieve fault accommodation and vibration suppression. Such a control strategy is based on the control separation formulation: one component is for accommodating the distributed fault, another one is for the closed-loop stability. The input-to-state stability of the closed-loop system is analysed by using the direct Lyapunov method and bilinear matrix inequalities technique. Then, a new algorithm is provided to obtain the control gain matrices of the fault-tolerant control law. Finally, the simulation results are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

With the rapid growth in astronomical spectra produced by large sky survey telescopes, traditional manual classification processes can no longer fulfill the requirements of precision and efficiency of spectral classification. There is an urgent need to employ machine learning approaches to conduct automated spectral classification tasks. Feature extraction is a critical step which has a great impact on any classification result. In this paper, a novel gradient-based method together with principal component analysis is proposed for the extraction of partial features of stellar spectra, that is, a feature vector indicating obvious local changes in data, which corresponds to the element line positions in the spectra. Furthermore, a general feature vector is utilized as an additional characteristic centering on the overall tendency of spectra, which can indicate stellar effective temperature. The two feature vectors and raw data are input into three neural networks, respectively, for training and each network votes for a predicted category of spectra. By selecting the class having the maximum votes, different types of spectra can be classified with high accuracy. The experimental results prove that a better performance can be achieved using the partial and general methods in this paper. The method could also be applied to other similar one-dimensional spectra, and the concepts proposed could ultimately expand the scope of machine learning application in astronomical spectral processing. [ABSTRACT FROM AUTHOR]

Methods using salient facial patches (SFPs) play a significant role in research on facial expression recognition. However, most SFP methods use only frontal face images or videos for recognition, and they do not consider head position variations. We contend that SFP can be an effective approach for recognizing facial expressions under different head rotations. Accordingly, we propose an algorithm, called profile salient facial patches (PSFP), to achieve this objective. First, to detect facial landmarks and estimate head poses from profile face images, a tree-structured part model is used for pose-free landmark localization. Second, to obtain the salient facial patches from profile face images, the facial patches are selected using the detected facial landmarks while avoiding their overlap or the transcending of the actual face range. To analyze the PSFP recognition performance, three classical approaches for local feature extraction, specifically the histogram of oriented gradients (HOG), local binary pattern, and Gabor, were applied to extract profile facial expression features. Experimental results on the Radboud Faces Database show that PSFP with HOG features can achieve higher accuracies under most head rotations. [ABSTRACT FROM AUTHOR]

Few studies have investigated the impact of landscapes on humans' mental status while they are moving at high speeds, such as driving on the freeway. This study used a simulation system to measure drivers' mental responses to six different freeway landscapes. Each of the 33 participants completed six different 90-minute simulated driving tasks in a randomly assigned sequence. The six landscape conditions consisted of an identical freeway infrastructure, with different roadside landscapes. Results show significant differences between landscape conditions and drivers' mental responses. Landscape conditions with greater greenness, in general, had a greater positive impact on drivers' mental status. The barren and tree regular landscapes yielded the worst and best results, respectively. Further, higher complexity was associated with a higher level of negative mental status. We argue that the speed of human's active movement should be considered as an essential factor in the Attention Restoration Theory and Stress Reduction Theory. [ABSTRACT FROM AUTHOR]

The Urban Park Act was revised in 2017, in which a new Park-PFI system to select private companies through public offering was introduced. The system is a new park maintenance and management method to improve the quality of urban parks and the convenience of park users while encouraging good investment by the private sector in urban parks and reducing the financial burden on park managers. In this study, we analyzed the case of introducing the private sector's expertise into urban park maintenance projects, clarified the background and contents of the projects, and compared the system with the conventional method of public-private partnership projects for urban parks. Furthermore, we implemented a survey on the actual situation of Senri-Minami Park in Suita City. Based on the survey results, we evaluated and analyzed the direct benefi ts obtained from using the Travel Cost Method. Based on the above, this study examined the feasibility and the requirements of establishing public-private collaboration projects in urban parks through literature review, fact-finding survey, and benefi t analysis. [ABSTRACT FROM AUTHOR]

Background and purpose: Epidemiological data on primary brain tumours (PBTs) are lacking due to the difficulty in case ascertainment among the population. Thus, we aimed to estimate mortality due to PBTs in China nationwide and the detection rate in people with suspected symptoms. Methods: A multistage, complex sampling survey regarding mortality due to PBTs in Chinese individuals was carried out by reviewing all causes of death within a year. The detection rates in people with suspected symptoms were estimated based on PBT symptom screening and neurologist reviews and compared between groups by logistic regression analysis. Results: Weighted mortality due to PBT was 1.6 (0.8–3.3) per 100,000 population in Chinese individuals, 1.8 (0.7–4.6) per 100,000 population in men, and 1.5 (0.5–4.5) per 100,000 population in women. Among 14,990 people with suspected symptoms, the PBT detection rate was 306.9 (95% CI 224.7–409.3) per 100,000 population in the total population, 233.0 (95% CI 135.7–373.1) per 100,000 population in men, and 376.9 (95% CI 252.4–546.3) per 100,000 population in women. People with an unsteady gait (OR 2.46; 95% CI 1.09–5.51; P=0.029), visual anomalies (3.84; 1.88–7.85; P<0.001), and headache (2.06; 1.10–3.86; P=0.023) were more likely to have a brain tumour than those without corresponding symptoms, while people with dizziness/vertigo were less likely to have a brain tumour than those without corresponding symptoms (0.45; 0.23–0.87; P=0.017). Conclusions: Mortality due to PBT in China was low, with a nationwide estimate of 21,215 (10,427–43,165) deaths attributable to PBTs annually. However, the detection rate of PBTs can be greatly improved based on symptom screening in the population. [ABSTRACT FROM AUTHOR]

Aspergillus niger prolyl endopeptidase (An-PEP) has become a research focus because of its advantages in specifically cleaving the C-terminal peptide bond of proline residues, especially it was an industrial food-grade acidic PEP. Aqueous two-phase system (ATPS) was first applied for separating An-PEP from fermentation broth. Via response surface method (RSM) experiment, an effectively separation of An-PEP was achieved by ATPS containing27% (w/w) ethanol and 14.5% (w/w) (NH 4) 2 SO 4 at pH 6.0 with the recovery of 90.29 ± 0.23% and purification coefficient of 15.35 ± 0.30. The purified An-PEP was characterized by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE), fourier transform infrared (FTIR) and fluorescence spectrometry. The optimum temperature and pH of An-PEP were 40 °C and 4.5–5.0, respectively. An-PEP was activated and stabilized by Ca2+ but inhibited by Fe3+. The enzymatic application of purified An-PEP was evaluated by hydrolyzing egg white protein (EWP) to prepare bioactive peptides. The obtained hydrolysates had good scavenging ability of OH and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radicals, angiotensin converting enzyme (ACE) inhibitory activity and anti-gout activity. This research realized a low-cost, high-efficiency and simple separation technology of An-PEP and provided a broader idea for the preparation of bioactive peptides and the application of An-PEP. Unlabelled Image • A neomethod to separate a specific enzymewas developed. • Satisfactory separation efficiency of Aspergillus niger prolyl endopeptidase was achieved by ethanol/ (NH 4) 2 SO 4 ATPS. • Enzyme activity was well maintained during the separation. • Peptides obtained by An-PEP hydrolyzed egg white protein showed biological activities. [ABSTRACT FROM AUTHOR]

[Display omitted] • The 1D/2D NiCo-LDH/ZnIn 2 S 4 S-scheme heterojunction was constructed. • The catalyst showed satisfactory catalytic activity for TC degradation. • The heterojunction promoted carrier separation and accelerated PMS activation. • High catalytic performance was confirmed by work function calculation and DFT. • Possible degradation pathways and toxicity assessments were investigated. The coupling of photocatalysis and peroxymonosulfate (PMS) induced advanced oxidation processes can be realized as an efficient strategy for antibiotics-contaminated water purification. However, developing a suitable catalyst with both visible light photo-response and high PMS activation efficiency remains challenging. Here, we employed the simple hydrothermal process to synthesis CoNi-LDH/ZnIn 2 S 4 S-scheme heterojunction, which combines the benefits of visible photocatalysis and massive generation of active oxygen species generated by activating PMS. The results exhibited that the removal efficiency of optimized heterojunction under Light/PMS system reached 90.1 % within 15 min, which were nearly 8.8 and 1.31 times those of single ZIS and CoNi-LDH, respectively. Mechanistic analysis and density functional theory (DFT) calculation indicated that the satisfactory catalytic activity of heterojunction resulted from the synergistic effect between photocatalysis and PMS activation, which facilitates the separation of photogenerated carriers and accelerates the activation of PMS to generate abundant reactive species. Additionally, CoNi-LDH/ZIS heterojunction possess good ant-interference ability, excellent reusability over four cycles, acceptable adaptability in real water environments. Moreover, the toxicity of intermediates and degradation pathways are also investigated. Overall, this work provides new insights into the fabrication of S-scheme photocatalyst in photocatalytic-PMS activation system, which can realize high-efficient purification of antibiotics wastewater. [ABSTRACT FROM AUTHOR]

The hygrothermal characteristics of building materials significantly impact building energy efficiency. Recently, attention around the world has progressively shifted towards sustainable building materials, including rammed earth. In this paper, the hygrothermal parameters of rammed earth (RE) and modified rammed earth (MRE) materials from northwest Sichuan, China, were measured under different humidity environments. The results indicate that MRE materials mixed with cement, crushed stone, sand, and polypropylene fiber exhibit higher thermal conductivity and specific heat capacity, while these two coefficients of the RE materials show greater sensitivity to variations in moisture content. Additionally, the equilibrium moisture content and water vapor permeability of RE materials are higher in the relative humidity range of 33.07 to 97.59%, suggesting superior humidity regulation capabilities. On-site monitoring of the full-scale comparative experimental building has indicated that the MRE wall demonstrates better attenuation and delay effects on outdoor temperature fluctuations in comparison with the RE wall after newly constructed for approximately one year. Despite this, the average indoor temperature of the MRE building was slightly higher during high temperature conditions. In the early construction phase, the slow moisture dissipation of the MRE wall may negatively impact its durability and indoor air quality, but the indoor humidity levels experience more smoothly. Rammed earth construction poses low risk of condensation in summer months. [ABSTRACT FROM AUTHOR]

Developing separated detection of ethanol and acetone for semiconductor oxides based gas sensors with relative stable gas response under different humidity is of great significance to practical application. Herein, a unique mesoporous SnO 2 -ZnO hierarchical structure has been prepared by a facile one-step hydrothermal method. Several characterizations for SnO 2 -ZnO samples have been carried out and the gas sensing properties of all gas sensors have been systematically investigated and analyzed. The results indicate that the optimal working temperature for ethanol detection will decrease from 275°C to 250°C, while the optimal working temperature for acetone detection will maintain at same temperature of 300°C with Sn2+ doping ratio increasing. For ethanol detection, 10 at% SnO 2 modified ZnO gas sensor has the highest gas response, and the humidity tolerance has been obviously improved compared with those of lower Sn element doping ratios (1 at% and 5 at%) at 250°C. Moreover, the detection limit for ethanol and acetone can reach as low as 200 ppb with high SnO 2 contents (10 at% and 15 at%). The improved gas sensing performance could be mainly attributed to the unique morphology of sensing material and the synergistic effect of SnO 2 and ZnO. • Synthesize SnO 2 -ZnO porous hierarchical structure by a facial and repeatable method. • Gas sensor can be used to detect ethanol and acetone at 250 °C and 300 °C respectively. • Gas sensor can detect 200 ppb ethanol and acetone at 250 °C and 300 °C respectively. • The humidity tolerance to ethanol is optimized by adjusting the Sn2+ doping amount. [ABSTRACT FROM AUTHOR]

The development of mesoporous heterogeneous structure through a facile and repeatable method with high gas sensing performance is always highly desirable in the chemical sensor field. Herein, the mesoporous In 2 O 3 -ZnO heterogeneous structure has been successfully synthesized via a reproducible hydrothermal method. The characterizations of sensing materials demonstrate that the porous heterogeneous structure can be easily constructed. Gas sensing investigation indicates that the gas sensor based on 15 at. % In 2 O 3 -ZnO exhibits the obvious enhanced ethanol gas sensing performances compared with that based on pure ZnO material in our previous work, including lower detection limit (200 ppb), lower base line resistance (∼ 1 Mohm), satisfying long term stability and improved moisture tolerance. The enhanced gas sensing properties can be mainly attributed to the In 2 O 3 -ZnO heterogeneous structure and unique microstructure, which will be deliberately discussed in the sensing mechanism part. • Construct of In 2 O 3 -ZnO porous hierarchical structure by facile hydrothermal method. • Gas sensor has the high selectivity to ethanol and high response of ∼ 35–100 ppm. • Low detection limit for ethanol (200 ppb) and low base line resistance (∼ 1 Mohm). • Gas sensor has satisfying long term stability and improved moisture tolerance. [ABSTRACT FROM AUTHOR]

• The mass transfer process of CO 2 /N 2 mixed gas in a microchannel was investigated. • The mass transfer in the bubble formation stage was investigated under different operating conditions. • The instantaneous mass transfer driving force of the bubble along the channel is calculated. • The mass transfer coefficient of mixed gas in a microchannel is obtained. In the chemical industry, the gas phase is not always pure gas generally. The mass transfer (MT) of mixed gas in a microchannel was investigated by using organic amine aqueous solution to absorb CO 2 /N 2 mixed gas. MT in the bubble formation stage was calculated, and the influence of operating conditions on it was investigated. When the gas contacts the liquid, the CO 2 in the bubble is continuously absorbed. Combined with the reduction of bubble volume, the instantaneous MT driving force of the bubble along the microchannel is calculated. On this basis, the MT coefficient of the mixed gas is obtained. The results show that after mixed gas in a certain concentration enters the microchannel, the instantaneous MT driving force and instantaneous MT coefficient are constantly decreased during the bubble moves along the microchannel. [ABSTRACT FROM AUTHOR]

Fault diagnosis of bearing under variable working conditions is widely required in practice, and the combination of working conditions and fault fluctuations increases the complexity of addressing its related problems. By developing a virtual simulation model, a digital twin (DT) can obtain the same or even more information than the physical object at a lower cost. Furthermore, it has great potential in the application of bearing fault diagnosis. In this paper, the DT model of the bearing test rig is robustly established, and the fault diagnosis bearing between the simulation and physical object is realized using the proposed enhanced meta-transfer learning (EMTL). First, the DT model is established through parameter identification and modal testing, and the modeling accuracy of DT model reaching 95.685%. The bearing simulation and experimental data are then collected under the same conditions using the DT model and bearing test rig, and the simulation data with little deviation from the experimental data is obtained. Finally, an attention mechanism and domain adaptation are introduced into the EMTL, with the average accuracy of fault diagnosis of bearing reaching 95.18% with few-label target domain data. The proposed strategy is both theoretically significant and practically useful. The experiment results demonstrate that our method outperforms a series of state-of-the-art methods on the bearing fault diagnosis across various limited data conditions. The proposed strategy effectively solves the few-shot problem, which is both theoretically significant and practically useful. • The digital twin model of the bearing test rig is established based on multidisciplinary simulation. • The complete-modal decomposition algorithm is used to identify closely-spaced modal parameter. • The enhanced meta-transfer learning is used for bearing fault diagnosis across different domains. [ABSTRACT FROM AUTHOR]

Keywords: Cotton (Gossypium hirsutum); CRISPR/Cas9; fiber development; auxin; auxin responsive factor; gibberellin acid EN Cotton (Gossypium hirsutum) CRISPR/Cas9 fiber development auxin auxin responsive factor gibberellin acid 423 425 3 03/02/22 20220301 NES 220301 Cotton is an important cash crop grown worldwide, (Huang I et al i ., 2021; Ma I et al i ., 2018; Wang I et al i ., 2019), which fibers are regulated by multiple phytohormones (Liu I et al i ., 2020; Shan I et al i ., 2014; Zhang I et al i ., 2011). The results showed that IAA and GA SB 1 sb promoted fiber elongation, N-1-naphthylphthalamic acid (NPA, a polar auxin transport inhibitor), and paclobutrazol (PAC, a GA biosynthesis inhibitor) inhibited fiber development. [Extracted from the article]

To evaluate the effect of stent implantation for vertebrobasilar artery stenosis，by using 3D arterial spin labeling (3D ASL) technique. A retrospective analysis was conducted on the clinical and 3D ASL data of 48 patients who underwent vertebral-basilar artery stenting. Post-labeling delay times (PLD) of 1.5 s and 2.5 s were chosen, and the average regional cerebral blood flow (rCBF) values were measured in nine brain regions of the posterior circulation: bilateral thalamus, bilateral occipital lobes, bilateral cerebellar hemispheres, midbrain, pons, and medulla. The 48 patients were divided into two groups based on the presence or absence of acute ischemic stroke in the posterior cerebral circulation region detected by diffusion-weighted imaging (DWI). The preoperative and postoperative rCBF results were statistically analyzed. In the infarct group, there were significant increases in rCBF values of all nine brain regions at both PLD = 1.5 s and 2.5 s postoperatively compared to preoperatively. At PLD = 1.5 s, statistically significant differences in rCBF values between the preoperative and postoperative periods were found in the right thalamus, left cerebellum, midbrain, and pons regions (P < 0.05). At PLD = 2.5 s, statistically significant differences in rCBF values between the preoperative and postoperative periods were observed in the left occipital lobe, right cerebellum, midbrain, and pons regions (P < 0.05). When analyzing the rCBF values of the brain regions with recent infarcts in the infarct group, there was a significant increase in postoperative rCBF values compared to preoperative values (P < 0.05). After excluding the data from brain regions with recent infarcts, the CBF values in the remaining brain regions were also increased postoperatively, and some brain regions showed statistically significant differences in rCBF values between the preoperative and postoperative periods (P < 0.05). In the non-infarct group, there were no statistically significant differences in the preoperative and postoperative rCBF values in all brain regions at both PLD = 1.5 s and 2.5 s (P > 0.05). The application of 3D ASL technology shows significant value in assessing the surgical efficacy of vertebral-basilar artery stenting, especially in patients with acute posterior circulation infarction. [ABSTRACT FROM AUTHOR]

Objective: To investigate the correlation of plasma and local expressions of Circ CDR1as with disease severity in patients with non-traumatic osteonecrosis of femoral head (ONFH). Methods: Ninety-nine non-traumatic ONFH patients receiving surgery and 99 healthy individuals were enrolled in our study. Plasma and local Circ CDR1as were detected using real-time quantitative PCR (RT-qPCR). Radiographic progression was determined using Association Research Circulation Osseous (ARCO) classification system. Harris hip score (HHS) and visual analogue scale (VAS) were used to assess the clinical severity. Receiver operating characteristic (ROC) curve was carried out to evaluate the diagnostic value of plasma Circ CDR1as with regard to the radiographic severity. Results: Plasma Circ CDR1as expressions were significantly higher in non-traumatic ONFH patients compared with healthy controls. In non-traumatic ONFH patients, there were no significant differences of CircCDR1as expressions between patients with alcohol-induced ONFH and steroid-induced ONFH. CircCDR1as in local necrotic tissue were significantly higher than adjacent non-affected tissue. Plasma and local Circ CDR1as expressions in patients with ARCO phase 4 were markedly upregulated compared with ARCO phase 3; plasma and local Circ CDR1as expressions in patients with ARCO phase 3 were markedly upregulated compared with ARCO phase 1/2. Plasma and local CircCDR1as expressions were positively associated with ARCO classification. In addition, plasma and local Circ CDR1as expressions were positively correlated with VAS and HHS scores. ROC curve analysis indicated that plasma Circ CDR1as may act as a decent marker for radiographic progression in non-traumatic ONFH patients. Conclusions: Both plasma and local expressions of CircRNA CDR1as are linked with disease severity in patients with non-traumatic ONFH. [ABSTRACT FROM AUTHOR]

This paper proposes an interval sliding mode observer (ISMO)-based sliding mode actuator fault accommodation (FA) framework for non-minimum phase linear-parameter-varying (LPV) systems involving online control allocation (CA) problem. Firstly, a specifically designed coordinate transformation is introduced to deal with the non-minimum phase issue. Then, an ISMO is proposed to estimate the set of admissible values for the states of the faulty LPV systems, which combines the interval observer technique and the sliding mode observer technique. A fault-tolerant control (FTC) law with an online CA scheme is subsequently designed by stabilising the ISMO instead of the original faulty LPV system. Finally, a simulation for an inverter used in China Railway High-speed (CRH) is presented to illustrate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

Dynamics of the title reaction is investigated on an ab initio based potential energy surface using a full-dimensional quantum wave packet method within the centrifugal sudden approximation. It is shown that the reaction between H and HCN leads to both the hydrogen exchange and hydrogen abstraction channels. The exchange channel has a lower threshold and larger cross section than the abstraction channel. It also has more oscillations due apparently to quantum resonances. Both channels are affected by long-lived resonances supported by potential wells. Comparison with experimental cross sections indicates underestimation of the abstraction barrier height. [ABSTRACT FROM AUTHOR]

A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resulting in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations. [ABSTRACT FROM AUTHOR]

A simple, general, and rigorous scheme for adapting permutation symmetry in molecular systems is proposed and tested for fitting global potential energy surfaces using neural networks (NNs). The symmetry adaptation is realized by using low-order permutation invariant polynomials (PIPs) as inputs for the NNs. This so-called PIP-NN approach is applied to the H + H2 and Cl + H2 systems and the analytical potential energy surfaces for these two systems were accurately reproduced by PIP-NN. The accuracy of the NN potential energy surfaces was confirmed by quantum scattering calculations. [ABSTRACT FROM AUTHOR]