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The finding of new integrable coupling systems has become an important area of research in mathematical physics and their study will aid in the classification of multi-component integrable systems. A basic method for generating integrable coupling systems is algebraic expansion, for example, the Frobenius algebra, the Lie algebra, the superalgebra, and so on. In this paper, we introduce a Frobenius Boussinesq equation based on the Frobenius algebra, and then we present a Lax pair of it. It follows that we give a Bäcklund transformation of the Frobenius Boussinesq equation. Furthermore, the lattice equation of the Frobenius Boussinesq equation is presented by using three Bäcklund transformations, and then obtain the exact solutions. Additionally, we obtain the conservation laws of the Frobenius Boussinesq equation via the Bäcklund transformation. Strongly coupled and weakly coupled systems physically represent strong and weak interactions, respectively. In this paper, we introduce a weakly coupled Degasperis–Procesi (DP) equation, and construct a Lax pair of it. In addition, the Bäcklund transformation and superposition principle are applied to investigate the weakly coupled DP equation. We also obtain the conservation laws of the weakly coupled DP equation. Then, we introduce a strongly coupled DP equation, and use the same method to study the strongly coupled DP equation. The exact solutions of these two equations are obtained. Moreover, we introduce a Z n -DP equation. Considering the superposition principle, we obtain the solution of an associated Z n -DP equation by using Bäcklund transformations. These new multi-component integrable systems can enrich the existing integrable models and possibly describe new nonlinear phenomena. [ABSTRACT FROM AUTHOR]

Objective: Artificial hip arthroplasty (AHA) is widely accepted in elderly patients with femoral neck fractures, but it is associated with high risk of death and various postoperative complications due to old age and accompanying chronic diseases. Therefore, this study aimed to explore the risk factors for death in elderly patients with femoral neck fractures after AHA and to establish a nomogram risk prediction model, which is expected to reveal high‐risk patients and improve the postoperative quality of life and survival rate of patients. Methods: Elderly patients who underwent AHA for femoral neck fractures in our hospital from September 2014 to May 2021were retrospectively analyzed. These patients were divided into a survival group and a death group according to their clinical outcomes. The following clinical data were recorded for the patients in the two groups: sex, age, underlying diseases, smoking and drinking history, preoperative nutritional risk score (NRS) and American Society of Anesthesiologists (ASA) score, as well as relevant indicators about the operation. These data were subject to univariate analysis and then logistic analysis to determine the risk factors of death. Subsequently, a nomogram risk prediction model was established and further validated with the receiver operating characteristic curve (ROC) and the Hosmer–Lemeshow test. Finally, the effects of predictive risk factors were analyzed using the Kaplan–Meier survival curve. Results: Follow‐up was completed by 260 patients, including 206 patients in the survival group and 54 patients in the death group; the overall death rate was 20.77%, and the follow‐up time, age, postoperative 1, 3 and 5‐year death rates were 3.47 ± 1.93 years, 75.32 ± 9.12 years, 5.77%, 12.51%, and 25.61%, respectively. The top three causes of death in 54 patients were respiratory disease, cerebrocardiovascular disease, and digestive disease, respectively. The logistic analysis indicated that elderly patients with femoral neck fractures, the risk factors for death after AHA were age ≥ 80 years, preoperative NRS ≥ 4, HB ≤ 90 g/L, CR ≥ 110 umol/L, and ASA score ≥ 3, as well as postoperative albumin ≤ 35 g/L, the nomogram was established, and then its predictive performance was successfully validated using the ROC curve (AUC = 0.814, 95% confidence interval = 0.749–0.879) and the Hosmer–Lemeshow test (p = 0.840). Furthermore, Kaplan–Meier survival curve analysis revealed that the abovementioned six indicators were correlated with the post‐AHA survival time of elderly patients with femoral neck fractures (pLog Rank < 0.05). Conclusion: Old age, preoperatively high NRS and ASA score, anemia, poor renal function, and postoperative hypoproteinemia are the major risk factors for death in elderly patients with femoral neck fractures after AHA; they are also associated with postoperative survival. Early identification and effective interventions for optimization of modifiable risk factors are recommended to improve the postoperative quality of life and survival rates. [ABSTRACT FROM AUTHOR]

Loss of ARID1A, a subunit of the SWI/SNF chromatin remodeling complex, contributes to malignant progression in multiple cancers including non-small cell lung cancer (NSCLC). In the search for key genes mediating the aggressive phenotype caused by ARID1A loss, we analyzed 3 Gene Expression Omnibus (GEO) datasets that contain RNA sequencing data from ARID1A-depleted cancer cells. PLAU was identified as a common gene that was induced in different cancer cells upon ARID1A depletion. Overexpression of PLAU positively modulated NSCLC cell growth, colony formation, cisplatin resistance, and survival under serum deprivation. Moreover, enforced expression of PLAU enhanced tumorigenesis of NSCLC cells in nude mice. Mechanistically, PLAU interacted with TM4SF1 to promote the activation of Akt signaling. TM4SF1-overexpressing NSCLC cells resembled those with PLAU overepxression. Knockdown of TM4SF1 inhibited the growth and survival and increased cisplatin sensitivity in NSCLC cells. The interaction between PLAU and TM4SF1 led to the activation of Akt signaling that endowed ARID1A-depleted NSCLC cells with aggressive properties. In addition, treatment with anti-TM4SF1 neutralizing antibody reduced the growth, cisplatin resistance, and tumorigenesis of ARID1A-depleted NSCLC cells. Taken together, PLAU serves as a target gene of ARID1A and promotes NSCLC growth, survival, and cisplatin resistance by stabilizing TM4SF1. Targeting TM4SF1 may be a promising therapeutic strategy for ARID1A-mutated NSCLC. [ABSTRACT FROM AUTHOR]

In this paper, we performed Lie symmetry analysis and applied G ′ / G expansion method on the nonlinear dissipative–dispersive equation. The purpose of this research is to find the vector fields and transform the nonlinear dissipative–dispersive equation into simpler forms. The Maple software was used to obtain the vector field and similarity reductions for nonlinear dissipative–dispersive equations. In addition, we obtained exact solutions based on the G ′ / G expansion method and power series method, including the hyperbolic functions, the trigonometric functions and the rational functions. The method we used is direct, concise, elementary and effective, and can be used for many other nonlinear evolution equations. Furthermore, the invariant subspaces of the nonlinear dissipative–dispersive equation were identified using the refined invariant subspaces method. The invariant subspaces of solutions to linear ordinary differential equations were used to prove that nonlinear dissipative–dispersive equation admits subspaces. The exact solutions were obtained by using generalized separated variables. [ABSTRACT FROM AUTHOR]

We generalize the constrained modified KP (mKP) hierarchy to the multi-component version whose tau function can be expressed as the vacuum expectation value of Clifford operators using free fermions. Meanwhile, we extend the relevant theory of the Boson–Fermion correspondence in single component constrained mKP hierarchy to the multi-component version. This leads us to obtain the rational and soliton solutions of the multi-component constrained mKP hierarchy utilizing the Boson–Fermion correspondence. Furthermore, we give five sets of differential Fay identities and two sets of difference Fay identities of the multi-component mKP hierarchy. [ABSTRACT FROM AUTHOR]

Surrogate models have been used to emulate mathematical simulators of physical or biological processes for computational efficiency. High‐speed simulation is crucial for conducting uncertainty quantification (UQ) when the simulation must repeat over many randomly sampled input points (aka the Monte Carlo method). A simulator can be so computationally intensive that UQ is only feasible with a surrogate model. Recently, deep neural network (DNN) surrogate models have gained popularity for their state‐of‐the‐art emulation accuracy. However, it is well‐known that DNN is prone to severe errors when input data are perturbed in particular ways, the very phenomenon which has inspired great interest in adversarial training. In the case of surrogate models, the concern is less about a deliberate attack exploiting the vulnerability of a DNN but more of the high sensitivity of its accuracy to input directions, an issue largely ignored by researchers using emulation models. In this paper, we show the severity of this issue through empirical studies and hypothesis testing. Furthermore, we adopt methods in adversarial training to enhance the robustness of DNN surrogate models. Experiments demonstrate that our approaches significantly improve the robustness of the surrogate models without compromising emulation accuracy. [ABSTRACT FROM AUTHOR]

Multi-view data can be generated from diverse sources, by different technologies, and in multiple modalities. In various fields, integrating information from multi-view data has pushed the frontier of discovery. In this paper, we develop a new approach for multi-view clustering, which overcomes the limitations of existing methods such as the need of pooling data across views, restrictions on the clustering algorithms allowed within each view, and the disregard for complementary information between views. Our new method, called CPS-merge analysis, merges clusters formed by the Cartesian product of single-view cluster labels, guided by the principle of maximizing clustering stability as evaluated by CPS analysis. In addition, we introduce measures to quantify the contribution of each view to the formation of any cluster. CPS-merge analysis can be easily incorporated into an existing clustering pipeline because it only requires single-view cluster labels instead of the original data. We can thus readily apply advanced single-view clustering algorithms. Importantly, our approach accounts for both consensus and complementary effects between different views, whereas existing ensemble methods focus on finding a consensus for multiple clustering results, implying that results from different views are variations of one clustering structure. Through experiments on single-cell datasets, we demonstrate that our approach frequently outperforms other state-of-the-art methods. Author summary: Advances in single-cell profiling technologies have made it possible to measure various types of features from a single cell. In this new type of data, known as multimodal single-cell data, each cell has numerical measurements from multiple views. Analyzing multimodal data has opened up new horizons for single-cell genomics, where clustering is a fundamental analysis for validating existing hypotheses or discovering insights when little prior knowledge is available. Existing clustering methods either combine data from different modalities for simultaneous processing or use integration algorithms to aggregate clustering results from multiple views. In this paper, we propose a new approach called CPS-merge analysis, which considers both consensus and complementary effects among clustering results across views and provides a quantified contribution of each view. The approach operates on single-view cluster labels, enabling the use of advanced clustering algorithms in any individual view. Furthermore, since CPS-merge analysis does not require pooling the original data, it can be applied to distributed sources or data with sharing concerns. This new approach tackles the problem of multi-view clustering from a novel combinatorial perspective and has the potential to become a widely used and effective tool. [ABSTRACT FROM AUTHOR]

[2.2]-Paracyclophane derivatives have been promising platforms for applications in biology and materials science. To access pure derivatives thereof, a safe and non-toxic synthetic method for 4- n -propyl-[2.2]-paracyclophane is developed via a microwave-assisted and NH2NH2/KOH reduction route. We introduce microwave-assisted acylation for a synthesis that successfully improves the yield and reduces the reaction time. Notably, an exploration of the length and number of the alkyl chains on the [2.2]-paracyclophane ring did not significantly affect the outcome of this reaction. We synthesized 4- n -butyl-[2.2]-paracyclophane and 4,12-dipropyl-[2.2]-paracyclophane via our protocol with high yields. The regioselectivity of the second electrophilic substitution on 4- n -propyl-[2.2]-paracyclophane occurs at the para position of the less substituted phenyl ring. [ABSTRACT FROM AUTHOR]

The properties of the support have profound effects on the catalytic performance of the supported catalyst. A series of NiMo bimetallic catalysts supported on niobium phosphate supports with different structures via the impregnation method was prepared. The effect of the acidity and porosity of the support on the dispersity and valence state of metal components and the synergistic interaction between Ni and Mo were investigated using XRD, N2-physisorption, NH3-TPD, XPS, H2-TPR, and TEM. The catalytic performance of the catalysts was evaluated in the hydrodeoxygenation of oleic acid (OA). The results demonstrate that the stronger acidity of the support leads to better dispersion of the metal Ni and it is more difficult to reduce the metal Ni. It was shown that the synergistic interaction between Ni and Mo, which could increase the concentration of oxygen vacancies (Ov) in the catalyst and the charge density on the surface of Ni atoms, is the main reason for the catalyst showing high selectivity to n-octadecane (C18). The reaction results showed that the highest selectivity to C18 (91.3%) could be achieved with 98.4% conversion of oleic acid over the Ni2Mo/NbP-3 catalyst under the condition of reaction temperature of 260 °C, 3 MPa initial H2 pressure, and reaction time of 7 h. [ABSTRACT FROM AUTHOR]

Rural revitalization aims to consolidate the achievements of poverty alleviation. Furthermore, enhancing the sustainable poverty alleviation ability of farmers in poverty-stricken areas is a critical concern. Using samples of farmers in four regions of the Yunnan province in China, multidimensional poverty and sustainable poverty alleviation ability indexes were constructed. Furthermore, a multidimensional poverty double boundary method (A–F method) was used to identify multidimensional poverty, and binary logistic function in SPSS was used to perform a regression analysis between multidimensional poverty and sustainable poverty alleviation ability. Results showed that as the poverty dimension increased, poverty incidence rate in the four regions decreased, with middle poverty incidence rate being the highest. Ability poverty was then identified as the major type of poverty in the sample, with the group of poor farmers with a high dimension of poverty being the most affected. Therefore, based on the ability structure of sustainable farmers out of poverty, we analyze the prominent problem of the ability construction of sustainable poverty reduction and propose a path for promoting sustainable poverty reduction ability. Hence, we will effectively link poverty alleviation with rural vitalization. [ABSTRACT FROM AUTHOR]

Trajectory prediction technology uses the trajectory data of historical ships to predict future ship trajectory, which has significant application value in the field of ship driving and ship management. With the popularization of Automatic Identification System (AIS) equipment in-stalled on ships, many ship trajectory data are collected and stored, providing a data basis for ship trajectory prediction. Currently, most of the ship trajectory prediction methods do not fully consider the influence of ship density in different sea areas, leading to a large difference in the prediction effect in different sea areas. This paper proposes a hybrid trajectory prediction model based on K-Nearest Neighbor (KNN) and Long Short-Term Memory (LSTM) methods. In this model, different methods are used to predict trajectory based on trajectory density. For offshore waters with a high density of trajectory, an optimized K-Nearest Neighbor algorithm is used for prediction. For open sea waters with low density of trajectory, the Long Short-Term Memory model is used for prediction. To further improve the prediction effect, the spatio-temporal characteristics of the trajectory are fully considered in the prediction process of the model. The experimental results for the dataset of historical data show that the mean square error of the proposed method is less than 2.92 × 10−9. Compared to the prediction methods based on the Kalman filter, the mean square error decreases by two orders of magnitude. Compared to the prediction methods based on recurrent neural network, the mean square error decreases by 82%. The advantage of the proposed model is that it can always obtain a better prediction result under different conditions of trajectory density available for different sea areas. [ABSTRACT FROM AUTHOR]

Reinforcement learning-based methods have addressed production scheduling problems with flexible processing constraints. However, delayed rewards arise due to the dynamic arrival of jobs and transportation constraints between two successive operations. The flow time of operations can only be determined after processing due to the possibility that the solution for job sequencing may change if new operations are inserted in dynamic environments. Job sequencing is often overlooked in single-agent-based scheduling methods. The lack of information sharing between multiple agents necessitates that researchers manually design reward functions to fit the relationship between optimization objectives and rewards, thereby reducing the accuracy of the learned policies. Thus, this paper proposes a multi-agent-based scheduling optimization framework that facilitates collaboration between the agents of both machines and jobs to address dynamic flexible job-shop scheduling problems (DFJSP) with transportation time constraints. Then, this paper formulates the Partial Observation Markov Decision Process and constructs a reward-sharing mechanism to tackle the delayed reward issue and facilitate policy learning. Finally, we develop an improved multi-agent dueling double deep Q network algorithm to optimize scheduling policy during long-term training. The results show that, compared with the state-of-the-art methods, the proposed method efficiently shortens the weighted flow time under the trained and unseen scenarios. Additionally, the case study results demonstrate its efficiency and responsiveness. It indicates that the proposed method efficiently addresses production scheduling problems with complex constraints, including the insertion of jobs, transportation time constraints, and flexible processing routes. [ABSTRACT FROM AUTHOR]

The study addresses path planning problems for autonomous mobile robots (AMRs), considering their kinematics, where performance and responsiveness are often incompatible. This study proposes a multi-agent policy learning-based method to tackle this challenge in dynamic environments. The proposed method features a centralized learning and decentralized execution-based path planning framework designed to meet performance and responsiveness requirements. The problem is modeled as a partial observation Markov Decision Process for policy learning while considering the kinematics using conventional neural networks. Then, an improved proximal policy optimization algorithm is developed with highlight experience replay that corrects failed experiences to speed up the learning processes. The experimental results show that the proposed method outperforms the baselines in both static and dynamic environments. The proposed method shortens the movement distance and time in static environments by about 29.1% and 5.7%, as well as in dynamic environments by about 21.1% and 20.4%, respectively. The runtime is maintained in milliseconds across various environments, taking only 0.07 s. Overall, the proposed method is valid and efficient in ensuring the performance and responsiveness of AMRs when dealing with complex and dynamic path planning problems. [ABSTRACT FROM AUTHOR]

Multi-agent reinforcement learning algorithms have achieved satisfactory performances in various scenarios, but many of them encounter difficulties in partially observable environments. In partially observable environments, the inability to perceive environment states results in unsteadiness and misconvergence, especially in large-scale multi-agent environments. To improve interactions among homogeneous agents in a partially observable environment, we propose a novel multi-agent actor-critic model with a visual attention interface to solve this problem. First, a recurrent visual attention interface is used to extract a latent state from each agent's partial observation. These latent states allow agents to focus on several local environments, in which each agent has a complete perception of a local environment and the intricate multi-agent environment is teased out by the interaction among several agents in the same local environment. The proposed method trains multi-agent systems with a centralized training and decentralized execution mechanism. The joint action of agents is approximated by the mean-field theory because the number of agents in a local environment is uncertain. Experimental results on the simulation platform suggest that our model performs better when training large-scale multi-agent systems in partially observable environments than baselines. [ABSTRACT FROM AUTHOR]

The architectures of many neural networks rely heavily on the underlying grid associated with the variables, for instance, the lattice of pixels in an image. For general biomedical data without a grid structure, the multi‐layer perceptron (MLP) and deep belief network (DBN) are often used. However, in these networks, variables are treated homogeneously in the sense of network structure; and it is difficult to assess their individual importance. In this paper, we propose a novel neural network called Variable‐block tree Net (VtNet) whose architecture is determined by an underlying tree with each node corresponding to a subset of variables. The tree is learned from the data to best capture the causal relationships among the variables. VtNet contains a long short‐term memory (LSTM)‐like cell for every tree node. The input and forget gates of each cell control the information flow through the node, and they are used to define a significance score for the variables. To validate the defined significance score, VtNet is trained using smaller trees with variables of low scores removed. Hypothesis tests are conducted to show that variables of higher scores influence classification more strongly. Comparison is made with the variable importance score defined in Random Forest from the aspect of variable selection. Our experiments demonstrate that VtNet is highly competitive in classification accuracy and can often improve accuracy by removing variables with low significance scores. [ABSTRACT FROM AUTHOR]

Recently, the sequential recommendation has become a hot spot. Previous works combined user long-term and short-term behavior to achieve the next item recommendation, but the previous works typically processed the user long-term sequential behavior in left-to-right order and some useful information may be overlooked in such a particular way. Moreover, these methods ignored that every user has his/her own attention on the different items. In this paper, we propose a novel hybrid model called Attentive Hybrid Recurrent Neural Networks to resolve these problems. The first module is the bidirectional long- and short-term memory network (Bi-LSTM), and the second is the GRU module, both of which are equipped with user-based attention mechanism. The hybrid model aims to grasp the user general preference as well as to capture the user latest intent. Experiment results on two public datasets suggest that our hybrid model has better performance on the next item recommendation task compared with previously reported baseline algorithm. [ABSTRACT FROM AUTHOR]

2101 duplex stainless steel with low Ni content is developed to replace austenitic stainless steel in many corrosive environments. Herein, the effects of Ce addition on the microstructure and corrosion resistance of 2101 duplex stainless steel are studied. The electrochemical corrosion behavior of 2101 duplex stainless steel with Ce contents of 0, 0.005, and 0.020 wt% is studied in 3.5 wt% NaCl solution and 0.05 mol L−1 H2SO4 + 0.05 mol L−1 KSCN solution at 25 °C. The situation is evaluated in 6 wt% FeCl3 solution at 35 °C. The results show that with increasing Ce content, the proportion of α phase in 2101 duplex stainless steel decreases, whereas the proportion of γ phase increases. At 0.005 wt% Ce, the two‐phase ratio is close to 1:1. Moreover, the partition coefficient (K) of elements gradually approaches 1 with increasing Ce, indicating a more uniform element distribution between the two phases. The electrochemical experiments in simulated seawater and acidic environments show that Ce addition gradually increases the corrosion potential and pitting resistance, leading to the formation of more stable passivation film. [ABSTRACT FROM AUTHOR]

Quercetin is one of the main flavonoids in the human diet and mainly found in different plant tissues, including seeds, flowers, leaves, stems, and roots. However, its biological function in plant tissues, especially in seeds, is unknown. In this study, the seed germination and subsequent seedling growth of Apocynum pictum and A. venetum under osmotic stress (400 mmol L−1 mannitol) supplemented with 5 μmol L−1 quercetin were evaluated after 7, 14, and 21 days of germination. Results showed that quercetin improved the germination percentage and seed vigor, as indicated by the higher germination energy, shoot length, root length, dry weight, fresh weight, and chlorophyll content in A. pictum and A. venetum seedlings under the mannitol compared with those under the mannitol alone. Quercetin decreased H 2 O 2 and O 2 − production and cell membrane damage, and mostly increased the gene expression of superoxide dismutase, peroxidase, catalase, chalcone synthase and flavonol synthase in A. pictum and A. venetum seedlings under the mannitol compared with those under the mannitol alone. In addition, the germination energy of A. pictum was 21.57% higher than that of A. venetum , and the gene expression of key enzymes in quercetin biosynthesis in A. pictum was mostly higher than that in A. venetum after 1 and 7 days of germination. These results indicated that quercetin was an effective anti-osmotic agent that alleviated the adverse effect of mannitol-induced osmotic stress on seed germination and seed vigor, and A. pictum seeds were more osmotic resistant than A. venetum seeds. Quercetin supplement alleviated the adverse impact of osmotic stress on seed germination and seed vigor in A. pictum and A. venetum by decreasing ROS production and cell membrane damage, and enhancing antioxidant enzyme activity, photosynthesis, and quercetin biosynthesis. Image 1 • Quercetin enhanced the seed germination and seed vigor under osmotic stress. • A. pictum seeds were more osmotic resistant than A. venetum seeds. [ABSTRACT FROM AUTHOR]

[Display omitted] • CoS 2 /CdS with 0D/1D heterostructure was fabricated by growing CoS 2 QDs on CdS NWs. • CoS 2 QDs and CdS NWs separately act as chlorpyrifos-recognition probe and PEC sensitizer. • A visible-light-driven PEC sensor was developed for the analysis of chlorpyrifos. • The PEC sensor can detect chlorpyrifos with concentrations down to 0.010 ppb. A visible-light-responsive photoelectrochemical (PEC) sensor was proposed for the sensitive and selective analysis of chlorpyrifos (CPF) by synergistically using CoS 2 quantum dots (QDs) and CdS nanowires (NWs). The CdS NWs were first prepared by the solvothermal method and subsequently combined with CoS 2 QDs to produce CoS 2 /CdS product with 0D/1D heterostructure. It turned out that the so-obtained nanocomposites with 0D/1D heterostructure could greatly suppress the recombination of photoinduced electrons and holes, and the electrode modified with this composite could exhibit preferable PEC performance and photocurrent signal compared to the one with CdS or CoS 2. After the addition of CPF, the photocurrent signal of the proposed PEC sensor was found to be selectively decreased because of the specific chelation between the cobalt sites of CoS 2 /CdS and the sulfur, nitrogen-atoms of CPF, which might block the electrons transferring process. The proposed PEC sensor could detect CPF in concentrations that linearly span from 0.030 to 100 ppb with an ideal detection limit of 0.010 ppb, which performances are much better than those of currently used analytical methods. Furthermore, this work may establish a framework for the development of various PEC sensing platforms with 0D/1D heterostructure for the quantitative assay of environmental pollutants like CPF. [ABSTRACT FROM AUTHOR]

Motivation Cluster analysis is widely used to identify interesting subgroups in biomedical data. Since true class labels are unknown in the unsupervised setting, it is challenging to validate any cluster obtained computationally, an important problem barely addressed by the research community. Results We have developed a toolkit called covering point set (CPS) analysis to quantify uncertainty at the levels of individual clusters and overall partitions. Functions have been developed to effectively visualize the inherent variation in any cluster for data of high dimension, and provide more comprehensive view on potentially interesting subgroups in the data. Applying to three usage scenarios for biomedical data, we demonstrate that CPS analysis is more effective for evaluating uncertainty of clusters comparing to state-of-the-art measurements. We also showcase how to use CPS analysis to select data generation technologies or visualization methods. Availability and implementation The method is implemented in an R package called OTclust, available on CRAN. Contact lzz46@psu.edu or jiali@psu.edu Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Abstract Subsurface damage (SSD) induced by silicon wafer grinding process is an unavoidable problem in semiconductor manufacturing. Although experimental attempts have been made on investigation of the influential factors on the SSD depth, however, few theoretical studies have been conducted to obtain SSD depth through grinding parameters. To fill the gap, an analytical model is developed to predict the SSD depth in silicon wafer due to self-rotating grinding process, which can reveal the relationship among SSD depth and the grinding parameters, the size of the abrasive grains and the radial distance from the wafer center. The establishment of the proposed model is based on scratch theory and fracture mechanics of isotropic brittle materials, and we further consider the effects of elastic recovery, cleavage plane and crystalline orientation on SSD formation. To validate the applicability of the proposed predictive model, grinding experiments with varied grinding parameters are performed and the depths of SSD along the <110> and <100> crystal directions are also measured and analyzed. The results given by the proposed model present reasonable accuracy of less than 20% deviation with experimental results. Effects of grinding parameters, wafer radial distance, crystalline orientation, and abrasive grain size on SSD depth are discussed in detail. Graphical abstract Image 1 Highlights • Predictive model of subsurface damage (SSD) depth of silicon wafer. • The cutting depth is considered elastic recovery effect and crystal orientation. • Nine sets of grinding experiments validate the predictive model of SSD depth. [ABSTRACT FROM AUTHOR]

Photocatalytic oxidation removal of elemental mercury (Hg 0 ) by Ag@AgCl/Ag 2 CO 3 hybrids was carried out in a wet scrubbing reactor under fluorescent light. The photocatalysts synthesized via a modified coprecipitation method were characterized by using SEM-EDS, HRTEM, N 2 adsorption-desorption, XRD, XPS, DRS, and ESR. Effects of operational parameters on Hg 0 removal, including AgCl content, fluorescent light (FSL) irradiation, pH value, reaction temperature, and flue gas components (O 2 , SO 2 and NO) were studied in detail. Furthermore, simultaneous removal of Hg 0 and SO 2 was investigated and the possible mechanism of highly enhanced Hg 0 removal efficiency was proposed. The results showed that AgCl amount, fluorescent light irradiation, reaction temperature, SO 2 and NO had notable impact on Hg 0 removal efficiency. Simultaneous removal efficiencies of 98% for SO 2 and 80% for Hg 0 were obtained by coupling Ag@AgCl(0.3)/Ag 2 CO 3 with Ca(OH) 2 under FSL. The trapping studies of reactive radicals exhibited that holes (h + ) were one of the main reactive species for Hg 0 removal. [ABSTRACT FROM AUTHOR]

A series of ternary Ag/AgI-Ag 2 CO 3 photocatalysts synthesized using a facile coprecipitation method were employed to investigate their performances of Hg 0 removal in a wet scrubbing reactor. The hybrids were characterized by N 2 adsorption-desorption, XRD, SEM-EDS, HRTEM, XPS, DRS and ESR. The photocatalytic activities of Hg 0 removal were evaluated under fluorescent light. The results showed that AgI content, fluorescent light irradiation, reaction temperature all showed significant influences on Hg 0 removal. NO exhibited significant effect on Hg 0 removal in comparison to SO 2 . Among these ternary Ag/AgI-Ag 2 CO 3 hybrids, Ag/AgI(0.1)-Ag 2 CO 3 showed the highest Hg 0 removal efficiency, which could be ascribed to the effective separation of photogenerated electron-hole pairs between AgI and Ag 2 CO 3 and the surface plasmon resonance (SPR) effect in the visible region by metallic silver nanoparticles (Ag 0 NPs). The trapping studies of reactive radicals showed that the superoxide radicals ( O 2 − ) may play a key role in Hg 0 removal under fluorescent light. According to the experimental and characterization results, a possible photocatalytic oxidation mechanism for enhanced Hg 0 removal over Ag/AgI(0.1)-Ag 2 CO 3 hybrid under fluorescent light was proposed. [ABSTRACT FROM AUTHOR]

In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d.), zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method) with genetic algorithm (GA) and constituted the hybrid genetic algorithm (HGA). Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system. [ABSTRACT FROM AUTHOR]

A novel technique for photocatalytic removal of elemental mercury (Hg 0 ) using visible-light-driven Ag/AgBr-Ag 2 CO 3 hybrids was proposed. The ternary Ag/AgBr-Ag 2 CO 3 hybrids were synthesized by a simple modified co-precipitation method and characterized by N 2 adsorption-desorption, scanning electron microscope (SEM), X-ray diffraction (XRD), UV–vis diffused reflectance spectroscopy (DRS), X-ray photoelectron spectroscopy (XPS) and electron spin resonance (ESR) techniques. The effects of AgBr content, fluorescent lamp (FSL) irradiation, solution temperature, SO 2 and NO on Hg 0 removal were investigated in detail. Furthermore, a possible reaction mechanism for higher Hg 0 removal was proposed, and the simultaneous removal of Hg 0 , SO 2 and NO was studied. The results showed that a high efficiency of Hg 0 removal was obtained by using Ag/AgBr-Ag 2 CO 3 hybrids under fluorescent lamp irradiation. The AgBr content, FSL irradiation, solution temperature, and SO 2 all exhibited significant effects on Hg 0 removal, while NO had slight effect on Hg 0 removal. The addition of Ca(OH) 2 demonstrated a little impact on Hg 0 removal and could significantly improve the SO 2 -resistance performance of Ag/AgBr(0.7)-Ag 2 CO 3 hybrid. The characterization results exhibited that hydroxyl radical ( OH), superoxide radical ( O 2 − ), hole (h + ), and Br 0 , were reactive species responsible for removing Hg 0 , and the h + played a key role in Hg 0 removal. [ABSTRACT FROM AUTHOR]

Numerous cretaceous sandstone grottoes in Longdong area have been suffering from serious weathering, and the weathering is proceeding at a considerable rate, resulting in severe challenges for conservation practice. However, relatively little is known about the weathering behavior and mechanism of cretaceous sandstone in Longdong Area. In this study, cretaceous sandstone in North Grotto Temple was selected as a typical case, and the weathering characteristics from the surface to the interior in real environment were studied by field investigation and laboratory analysis (particle and pore size distribution, soluble salt content, microstructure, mineral and chemical composition). Cretaceous sandstones are mainly litharenite and feldspathic litharenite at the North Grotto Temple (NGT). Efflorescence and subflorescence were confirmed as the main weathering forms for litharenite and feldspathic litharenite, respectively. Sodium sulfate and sodium chloride observed from the SEM images were the most active soluble salts tend to accumulate at the certain depth below the surface (1 cm for litharenite and 3 cm for feldspathic litharenite). The salts migration kinetics inside the cliff were concluded based on the distribution of salts. The K-feldspar increased from the surface to the interior with the kaolinite, illite decreasing, indicating the corresponding alteration of K-feldspar in the surface layer. The weathering indexes indicated that the weathering degree along the depth was nonlinear, whereas the weathering degree was firstly increased and then decreased from the surface to the interior. The experimental results in this study can provide a better understanding for the weathering mechanisms of cretaceous sandstone in Longdong Area. • The weathering mechanism of Cretaceous sandstone from the surface to the interior was investigated; • Nonlinear deterioration pattern of Cretaceous sandstone from the surface to the interior is obtained; • The salts migration kinetics inside the vertical cliff were concluded. [ABSTRACT FROM AUTHOR]

A nanozyme with 2D/1D heterostructure has been fabricated by the in-situ growth of molybdenum disulfide nanosheets (MoS 2 NSs) onto single-walled carbon nanotubes (SWCNTs). It was discovered that the so-obtained SWCNTs@MoS 2 nanozyme could exhibit greatly improved peroxidase-like catalysis, due to that the formed 2D/1D interfacial coupling in the heterostructure might provide more active sites and exhibit enhanced charge transferring during the catalytic reactions, as confirmed by the X-ray photoelectron spectroscopy, photoluminescence, electrochemical impedance spectra and radical capturing experiments. Furthermore, the catalysis of the developed nanozyme could be selectively inhibited by glutathione (GSH) through the competitive consumption of hydroxyl radicals with enzyme substrate in the catalytic reaction system. A SWCNTs@MoS 2 catalysis-based colorimetric strategy was further proposed for the quantitative analysis of GSH with the concentrations linearly ranging from 0.01 to 1000.0 μM. Besides, the feasibility of the developed colorimetric method was evaluated by monitoring GSH separately in the extractions from hela cells and human serum, promising the extensive applications for monitoring various biological species like GSH in the clinical laboratory. Importantly, such a fabrication route for nanozyme with 2D/1D heterostructure may pave the way towards the wide applications for designing various nanzymes with improved catalysis. [Display omitted] • A nanozyme with 2D/1D heterostructure was synthesized by in-situ growing MoS 2 nanosheets on SWCNTs forming SWCNTs@MoS 2. • The SWCNTs@MoS 2 can exhibit greatly improved catalysis performances due to the formed 2D/1D interfacial coupling in the heterostructure. • SWCNTs@MoS 2 with 2D/1D heterostructure may possess enhanced charge transfer and more active sites during the catalytic reaction on the improved catalysis. • The competing reaction between GSH and chromogenic substrate triggered by the hydroxyl radical could be revealed toward the highly selective detection of GSH. • The SWCNTs@MoS 2 catalysis-based colorimetric strategy enables the evaluation of GSH in the extractions of hela and human serum with pretty high sensitivity and selectivity. [ABSTRACT FROM AUTHOR]

[Display omitted] • ZnS/CdS was fabricated with type-II heterostructure by growing ZnS QDs on CdS NWs. • Low-bandgap CdS NWs and wide-bandgap ZnS QDs act separately as photosensitizer and Hg2+ probe. • A selective PEC sensor was developed for the analysis of Hg2+ with "turn-on" signal output. • Hg2+ induces the in-situ formation of HgS/ZnS/CdS with double type-II heterostructure. • The PEC sensor can detect Hg2+ with concentrations down to about 0.40 pM. An ultrasensitive and selective photoelectrochemical (PEC) platform has been developed for determining Hg2+ with "turn-on" signal output by synergistically using CdS nanowires (NWs) and ZnS quantum dots (QDs). CdS NWs was first prepared and then deposited with ZnS QDs to yield ZnS/CdS nanocomposite with type-II heterostructure. It was found that the as-constructed ZnS/CdS heterostructure can exhibit excellent photoelectrochemical characteristics by separately employing CdS NWs and ZnS QDs as the photosensitizer and Hg2+-recognition probe. What's more, the constructed analysis platform could display specifically enhanced photocurrent responses to Hg2+ under the visible light via the selective ion-exchange reaction. The in-situ formation of ternary HgS/ZnS/CdS could be thus expected with double type-II heterostructures so as to further enhance the transferring and separation of charges. A linear response can be achieved for Hg2+ in the concentration range from 0.0010 to 5.0 nM, with a detection limit of 0.40 pM. Moreover, the application feasibility of the developed sensor with ZnS/CdS heterostructure could be testified by detecting Hg2+ ions in environmental waters. Such a route of in-situ formation of double type-II heterostructure might promise the wide applications for designing different visible light-driven PEC sensors for probing heavy metals like Hg2+ with the "turn-on" signal output. [ABSTRACT FROM AUTHOR]

C@MoS 2 nanocomposites with hollow nanotube structures were synthesized through the hydrothermal sulfuration of molybdenum precursor along with the carbonization of glucose. Interestingly, it was found that the so-obtained C@MoS 2 nanzymes could specifically exhibit much enhanced oxidase-like catalysis after the addition of Hg2+. Herein, carbon might not only play a role in accelerating charge transfer, but also conduct the synergistic effects with MoS 2 to provide more catalytic active sites of nanzymes as compared with pristine MoS 2. Especially, the introduction of Hg2+ could induce C@MoS 2 nanozyme to produce more quantities of highly oxidative superoxide radicals through the strong Hg-S chelation in the catalysis reactions, as confirmed by the electron spin-resonance spectroscopy, X-ray photoelectron spectroscopy, photoluminescence spectra, and radical capturing experiments. A catalysis-based colorimetric platform with C@MoS 2 nanozyme was thereby constructed for the quantitative analysis of Hg2+ ions, showing linear responses to Hg2+ in the range of 0.010–100 μM with the detection limit of 2.7 nM, which is lower than those of current analysis methods. More importantly, the proposed colorimetric assay could be applied for detecting Hg2+ in environmental wastewater with the satisfactory detection recoveries, showing great potential applications for environmental monitoring, biomedical sensing, and food detection fields. [Display omitted] • Hollow C@MoS 2 nanotubes with Hg2+-enhanced oxidase-like activity were synthesized. • Carbon might conduct the synergistic effects with MoS 2 yielding more active sites of C@MoS 2. • Hg2+ could endow C@MoS 2 nanozyme with more superoxide radicals by the Hg-S chelation. • An effective C@MoS 2 -based colorimetric assay is established for the analysis of Hg2+ ions. • The developed strategy enables the evaluation of Hg2+ ions in the wastewater. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fe-doped MoS 2 nanosheets are prepared via one-pot hydrothermal route. • Nanozymes can exhibit controllable catalysis depending on Mo-to-Fe molar ratios. • Doped Fe atoms and Mo-S sites may conduct synergistic effects on the improved catalysis. • Two different catalytic pathways are proposed for Fe-MoS 2 nanozyme by kinetic studies. • Bi-catalysts-based colorimetric platform is developed for probing glucose in blood. MoS 2 nanosheets were doped with Fe elements simply via the one-pot hydrothermal route resulting in the peroxidase-like nanozymes with dramatically enhanced catalysis. It was discovered that the resulted Fe-MoS 2 could display controllable catalysis activities depending on the Mo-to-Fe molar ratios, among which the highest one was achieved at 3/1 with catalysis efficiency over three folds higher than that of pristine MoS 2. The greatly improved catalysis performances of Fe-MoS 2 nanozyme are thought to be resulted from the synergistic effects of the doped Fe atom and Mo-S sites. On the one hand, herein, the Fe sites might serve as the electron transferring mediators to facilitate the peroxidase-like catalytic reactions, as confirmed by the cytochrome C -based electron transportation experiments. On the other hand, the Mo-S sites might conduct the catalytic behavior of Fenton-like reactions, as revealed by the hydroxyl radicals-capturing experiments. Furthermore, the feasibility of practical applications for the developed Fe-MoS 2 nanozyme based colorimetric methods was demonstrated for glucose in blood sample. Importantly, an insight can be thereby obtained into the design of different nanozymes with enhanced catalysis designed by doping heteroatoms like Fe, promising for the catalysis-based applications in the biomedical analysis, food safety, and environmental monitoring fields. [ABSTRACT FROM AUTHOR]

Smoothing analysis process of distributive red-black Jacobi relaxation in multigrid method for solving 2D Stokes flow is mainly investigated on the nonstaggered grid by using local Fourier analysis (LFA). For multigrid relaxation, the nonstaggered discretizing scheme of Stokes flow is generally stabilized by adding an artificial pressure term. Therefore, an important problem is how to determine the zone of parameter in adding artificial pressure term in order to make stabilization of the algorithm for multigrid relaxation. To end that, a distributive red-black Jacobi relaxation technique for the 2D Stokes flow is established. According to the 2h-harmonics invariant subspaces in LFA, the Fourier representation of the distributive red-black Jacobi relaxation for discretizing Stokes flow is given by the form of square matrix, whose eigenvalues are meanwhile analytically computed. Based on optimal one-stage relaxation, a mathematical relation of the parameter in artificial pressure term between the optimal relaxation parameter and related smoothing factor is well yielded. The analysis results show that the numerical schemes for solving 2D Stokes flow by multigrid method on the distributive red-black Jacobi relaxation have a specified convergence parameter zone of the added artificial pressure term. [ABSTRACT FROM AUTHOR]

A highly sensitive and visible-light-driven photoelectrochemical (PEC) sensor has been constructed for the quantitative assay of organophosphorus pesticides like chlorpyrifos (Chlo) using hollow Co 9 S 8 @CdS heterostructures. The Co 9 S 8 @CdS heterostructures were created by growing CdS onto Co 9 S 8 surface via one-step oil-bath route, of which Co 9 S 8 was fabricated with hollow tubular structures through the Co(CO 3) 0.35 Cl 0.2 (OH) 1.1 -templated solvothermal method. It was discovered that the so-obtained Co 9 S 8 @CdS with direct Z-scheme heterojunctions could exhibit larger photocurrents than the Co 9 S 8 or CdS because of the greatly enhanced separation efficiency of photo-generated carriers. What's more, the photocurrent signal of Co 9 S 8 @CdS-based PEC sensor could be selectively inhibited with the addition of Chlo through the specific chelation between the N and S atoms of Chlo with C N and P S groups and Co sites of Co 9 S 8 @CdS so as to suppress the carriers transferring. The developed PEC sensor could exhibit a linear response for Chlo ranging from 0.050 to 1000 ppb, with the detection limit value down to 0.015 ppb, which was far below than those of currently reported PEC sensors. Besides, the proposed routes may provide guidelines for designing various direct Z-scheme heterojunction-based PEC analysis platforms for determining environmental pollutants like Chlo. [Display omitted] • A visible-light-driven photoelectrochemical sensor was developed for probing chlorpyrifos. • Hollow Co 9 S 8 @CdS heterostructures were constructed via one-pot oil-bath route. • Co 9 S 8 and CdS were separately utilized as chlorpyrifos-recognition probe and sensitizer. • The sensor can facilitate the detection of chlorpyrifos with concentration down to 0.015 ppb. [ABSTRACT FROM AUTHOR]

• Static coarsening behavior was controlled by termination migration and Ostwald ripening mechanism. • The average diameter of Ti 2 Cu phase increased with thermal exposure time. • The loss of ductility is mainly attributed to the coarsening of Ti 2 Cu phase. [Display omitted] The static coarsening behavior of a Ti-14Cu alloy relative to the Ti 2 Cu phase after long-term isothermal thermal exposure was comprehensively investigated. The growth of the precipitated phase is shown to be controlled by the diffusion mechanism characterized by morphological variation during thermal exposure. The static coarsening process is composed of a rapid coarsening stage and stable coarsening stage, and it is primarily governed by volume diffusion of the Lifshitz-Slyozov-Wagner (LSW) model. The rapid coarsening stage is mainly dominated by the terminal migration mechanism, while the stable coarsening stage is governed by the Ostwald ripening mechanism. The rapid coarsening of the Ti 2 Cu phase enhances the effects of precipitation strengthening significantly and simultaneously improves the plasticity of the alloy. However, with stable coarsening, the presence of the high-volume Ti 2 Cu phase in a Ti-14Cu alloy increases the effective slip length during deformation and reduces plasticity. [ABSTRACT FROM AUTHOR]

The chaotic behavior of a carbon nanotube with waviness along its axis is investigated. The equation of motion involves a quadratic and cubic terms due to the curved geometry and the mid-plane stretching. Melnikov method is applied for the system, and Melnikov criterion for global homoclinic bifurcations is obtained analytically. The numerical solution of the system using a fourth-order-Runge-Kutta method confirms the analytical predictions and shows that the transition from regular to chaotic motion is often associated with increasing the energy of an oscillator. Moreover, a detailed numerical study of the periodic attractor in the period window is also carried out. [ABSTRACT FROM AUTHOR]

Designated as a world heritage site by UNESCO in 1987, the Mogao Grottoes is famous for its cultural relics, in particular, the superb murals and painted sculptures. Moisture has been confirmed as the most active factor that could result in mural diseases. Therefore, ascertaining the moisture distribution of the cliff is of great significance for preventing the deterioration of murals and painted sculptures. In this study, a multi-electrode resistivity survey is applied atop the cliff of Mogao Grottoes. By deploying survey lines in two main study areas, the moisture distribution of the cliff is reflected by the resistivity profiles qualitatively. The results show that there is a mutually verifying relationship between the resistivity profiles and the water content of the exploratory well. In general, the resistivity of the cliff body is low in the distribution range of 1–300 Ω·m. It shows that the moisture content of these gullies atop the cliff is even lower. Besides, four potential danger areas are determined on the cliff face. Murals in these caves, which are excavated in these areas, will suffer more serious deterioration due to the moisture migration. The result also ascertains that the resistivity of the cliff could determine the moisture distribution inside the cliff. Moreover, this study can provide a firm scientific basis for protecting the valuable murals and painted sculptures in the caves. [ABSTRACT FROM AUTHOR]

Abstract: An analytically nonlocal Euler–Bernoulli beam model for the wave propagation in fluid-filled single-walled carbon nanotube (SWCNT) is established. The governing equations with the nonlocal effects are derived on the variational principle, and used in the wave propagation analysis of the SWCNT beam. Compared with the partially nonlocal Euler–Bernoulli beam models used previously, the analytically nonlocal model presented in the present study predicts well the effects of the stiffness enhancement and the wave damping at the high wavenumber or the strong nonlocal effects area for the fluid-filled SWCNT beam. Though the analytical model is less sensitive than the partially nonlocal model when the moving velocity of the internal fluid is high enough, it simulates more of the high-order nonlocal effecting information than the partially nonlocal model does in many cases. [Copyright &y& Elsevier]

Abstract: This paper is concerned with the characteristics of wave propagation in double-walled carbon nanotubes (DWCNTs). The DWCNTs is simulated with a Timoshenko beam model based on the nonlocal continuum elasticity theory, referred to as an analytically nonlocal Timoshenko-beam (ANT) model. The governing equations of the DWCNTs beam consist of a set of four equations that are derived from the variational principle of the beam with high-order boundary conditions at the both ends, in which the effects of the nano-scale nonlocality and the van der Waals interaction between inner and outer tubes are inclusive. The characteristics of the wave propagation in the DWCNTs beam were analyzed with the new ANT model proposed and the comparisons with the partially nonlocal Timoshenko-beam (PNT) models in publication were made in details. The results show that the nonlocal effects of the ANT model proposed in the present study on the wave propagations are more significant because it is in stronger stiffness enhancement to the DWCNTs beam. [Copyright &y& Elsevier]

An innovative computational model is presented for the large eddy simulation (LES) of multidimensional unsteady turbulent flow problems in complex geometries. The main objectives of this research are to know more about the structure of turbulent flows, to identify their three-dimensional characteristic, and to study physical effects due to complex fluid flow. The filtered Navier-Stokes equations are used to simulate large scales; however, they are supplemented by dynamic subgrid-scale (DSGS) models to simulate the energy transfer from large scales toward subgrid-scales, where this energy will be dissipated by molecular viscosity. Based on the Taylor-Galerkin schemes for the convection-diffusion problems, this model is implemented in a three-dimensional finite element code using a three-step finite element method (FEM). Turbulent channel flow and flow over a backward-facing step are considered as a benchmark for validating the methodology by comparing with the direct numerical simulation (DNS) results or experimental data. Also, qualitative and quantitative aspects of three-dimensional complex turbulent flow in a strong 3D blade passage of a Francis turbine are analyzed. [ABSTRACT FROM AUTHOR]

Abstract: The traveling wave solutions of the magma equation are studied by using the approach of dynamical systems and the theory of bifurcations. With the aid of Maple, all bifurcations and phase portraits in the parametric space are obtained. Under different regions of parametric space, various sufficient conditions to guarantee the existence of solitary wave, periodic wave and breaking wave solutions are given. Moreover, the reason for appearance of breaking waves is explained. [ABSTRACT FROM AUTHOR]

[Display omitted] • Doping nitrogen into CoS x polyhedron via N 2 plasma treatment to yield N-CoS x. • CdS was controllably loaded on N-CoS x forming CdS/N-CoS x photocatalyst. • Surface wettability, conductivity and Fermi level of CoS x were tuned by plasma treatment. • Visible-light photocatalysis for Cr(VI) reduction was achieved with efficiency up to 100%. • A photocatalytic mechanism of direct Z-scheme heterojunction was proposed. A direct Z-scheme heterojunction has been constructed by loading cadmium sulfide (CdS) on cobalt sulfide doped with nitrogen (N-CoS x) by N 2 plasma treatment for efficient photocatalytic Cr(VI) reduction under visible light. It was discovered that the resulting CdS/N-CoS x nanocomposites could present different photocatalytic performances controllably depending on the plasma treatment time and CdS-to-N-CoS x ratios. Especially, the one with 5-min plasma treatment and 8/1 M ratio could exhibit the highest Cr(VI) photoreduction efficiency, which is over four and two folds higher than those of pristine N-CoS x and CdS, respectively. Herein, the plasma-assisted N doping could not only increase the surface wettability and conductivity of CoS x but also decrease its Fermi level for improving the photocatalytic Cr(VI) reduction. More importantly, a direct Z-scheme heterojunction could be constructed by the combination of CdS and N-CoS x with suitable band structures, which could further booster the charge separation and transferring, without sacrificing the redox capacity of photogenerated carriers. The enhanced photocatalytic activity and stability of CdS/N-CoS x nanocomposites could thereby be expected for Cr(VI) reduction, with the efficiency up to 100% within 25 min. Such a direct Z-scheme heterojunction created by the plasma treatment route may promise for the large-scale applications for the removal of various toxic pollutants in the environmental remediation field. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, large-scale porous NiTi shape memory alloy (SMA) sintered by self-propagating high-temperature synthesis (SHS) has been investigated numerically. The SHS reaction process could be divided into three steps: preheating, ignition and sintering. The mathematical model about ignition and sintering were constructed to investigate the effect of the preheating temperature and the initial degree of conversion on the combustion. The results showed that the SHS reaction could not be completed for large initial degree of conversion. The critical preheating temperature for completed combustion was also obtained for different initial degree of conversion. It needed at least 573K to complete the combustion for the initial degree of conversion 0.215, and 873K for the initial degree of conversion 0.56. The mean wave velocity increased with the increase of preheating temperature and decreased with the increase of the initial degree of conversion. [Copyright &y& Elsevier]

Abstract: In this paper, the porous NiTi shape memory alloy (SMA) fabricated by self-propagating high-temperature synthesis (SHS) has been investigated experimentally and numerically. The mathematical models about the ignition and the sintering were constructed to investigate the effect of the preheating temperature and the coil temperature on the combustion. The results showed that the temperature difference between the ignition face and the bottom face was large due to low heat transfer conductivity. The ignition time would increase with the decrease of the coil temperature and the preheating temperature. The temperatures for different locations showed a strong dependence on the combustion time for lower preheating temperature, for the preheating temperature 1173K, this mode of the combustion has transferred from SHS to thermal explosion. The transient partial molten phenomenon occurred during the process of combustion, which was more homogenous for preheating temperature 873K. The mean velocity of the combustion wave was investigated systematically. An experiment was also carried out to investigate the ignition and SHS reaction for porous NiTi alloy in this paper. It was found that the results of experiment and numerical simulation were shown in good consistence. [Copyright &y& Elsevier]

Results from combined laboratory experimental and turbulent numerical modeling studies are presented to investigate the effects of bed roughness (discrete square strips) and slope on the flow over a free overfall in a rectangular channel. A broad range of model parameters such as the bed roughness, channel slope, and incoming upstream Froude number is investigated. The water surface profiles upstream of the brink of the channel, the velocity fields in cavity between two strips, and end depth (water depth at the brink of the channel) are simulated, measured, and discussed for various input conditions. The results show that for a given dimension of bed roughness the relative spacing of roughness (defined as the ratio of the center to center distance to the height of the strip) has a significant effect on the flow. The computational results are in good agreement with the experimental measurements. [ABSTRACT FROM AUTHOR]

In this paper, the experimental and numerical study has been carried out to investigate the water jet impingement on a convex hemispherical surface. The pressure and skin friction coefficient distributions on the impingement surface were analyzed numerically. A great deal of attention was paid to analyze the effects of the jet impingement exit velocity and the nozzle-to-surface distance on the heat transfer characteristics. A comparison of the heat transfer coefficient was performed between the jet impingement on the convex surface and the flat plate. The results show that the Nusselt number for the convex surface is higher than that for the flat surface. The local Nusselt number is decreased monotonically from its maximum value at the stagnation point for lower Reynolds numbers. A secondary maxima occurs for higher Reynolds numbers. The experiment and simulation were performed with the following parameters: the jet impingement Reynolds number of Re = 1947-19478, and the nozzle-to-surface distance of L/D = 2.5-25. [ABSTRACT FROM AUTHOR]

Abstract: A numerical simulation scheme of 3D incompressible viscous fluid in a box flow passage is developed to solve Navier–Stokes (N–S) equations by firstly taking fluid–structure interaction (FSI) into account. This numerical scheme with FSI is based on the polynomial differential quadrature (PDQ) approximation technique, in which motions of both the fluid and the solid boundary structures are well described. The flow passage investigated consists of four rectangular plates, of which two are rigid, while another two are elastic. In the simulation the elastic plates are allowed to vibrate subjected to excitation of the time-dependent dynamical pressure induced by the unsteady flow in the passage. Meanwhile, the vibrating plates change the flow pattern by producing many transient sources and sinks on the plates. The effects of FSI on the flow are evaluated by running numerical examples with the incoming flow’s Reynolds numbers of 3000, 7000 and 10,000, respectively. Numerical computations show that FSI has significant influence on both the velocity and pressure fields, and the DQ method developed here is effective for modelling 3D incompressible viscous fluid with FSI. [Copyright &y& Elsevier]

The turbulent flow in a reacting hydro turbine was simulated with large eddy simulation (LES) to investigate the spatial and temporal distributions of the turbulence in a 3D skew blade passage. The simulations show that the intrinsic features are quite complicated. LES can capture the details of the structures, and the results are generally agreeable with those by direct numerical simulation. [ABSTRACT FROM AUTHOR]

A constitutive relationship for high strength concrete in triaxial monotonic and cyclic compressions is developed based on the continuum damage mechanics. The bounding surface concept is employed in the formulation of the theoretical model. An experimental program was undertaken in order to establish databases for high strength concrete under triaxial monotonic and cyclic compressions. The stress-strain responses of high strength concrete subjected to triaxial monotonic and cyclic compressions were acquired through an experimental program. Comparison of the stress strain results indicates good agreement between the theoretical model and the experimental data. [Copyright &y& Elsevier]

• A wireless grinding force measurement module for wafer grinding machine is developed. • The variations of grinding force during the whole grinding process are revealed real-timely. • Effect of process parameter on grinding force, and parameter optimization are investigated. Grinding force is a crucial factor that affects the machining accuracy, wheel wear and the material removal efficiency for precision machining of semiconductor materials under nanometer accuracy. However, due to the complex rotational motion of both the grinding wheel and wafer workpiece, in situ measurement of the grinding force in wafer self-rotating grinding is still a big challenge. In this paper, a novel grinding force measurement method in silicon wafer grinding process is developed. The method is achieved by embedding four thin film force sensors into a self-designed force measurement device and real-time monitoring through wireless signal transmission. Based on this method, the grinding force under 5 groups of process parameters are measured. For the first time, the variations of grinding force during the whole grinding process are revealed real-timely. Effects of process parameters, i.e. spindle rotational speed and feed rate, on grinding force are investigated, and the parameters are also optimized based on the theory of specific grinding energy. The test results show that the force measurement method has the advantages of high precision, reliable and convenient implementation. [ABSTRACT FROM AUTHOR]

• A near-infrared-light-driven photoelectrochemical sensor is developed for probing Hg2+. • Bead chain-like Ag@Ag 2 S composites are prepared via one-step oil-bath route followed by photoreduction. • Ag 2 S and metallic Ag separately act as the sensitizer and Hg2+-recognition probe. • This PEC sensor can facilitate the detection of Hg2+ with concentrations down to 0.50 pM. A near-infrared (NIR) light-driven photoelectrochemical (PEC) sensing platform was established for the quantitative assay of Hg2+ using Ag@Ag 2 S nanocomposites. Ag 2 S quantum dots (QDs) with the bead-chain-like nanostructure were fabricated simply via one-step oil-bath route to be further deposited with metallic Ag through the photo-reduction method to yield Ag@Ag 2 S nanocomposites. It was found that Ag@Ag 2 S-based sensor could present more than twice larger PEC responses than the Ag 2 S-based one, due to the synergetic combination of metallic Ag with the surface plasmon resonance (SPR) effects and Ag 2 S QDs with the NIR-light-irradiated PEC properties. More importantly, the developed PEC sensor could display the photocurrent responses that are selectively inhibited in the presence of Hg2+ by forming Ag-Hg amalgam to accelerate the recombination of photo-induced electron-hole pairs. Under NIR light, it can detect Hg2+ in the concentrations linearly ranging from 0.0010 to 5.0 nM, with a limit of detection of about 0.50 pM. This work may guide a promising combination of Ag 2 S of NIR QDs with metallic Ag of SPR effects for designing various PEC sensing platforms for the complex environmental monitoring of different heavy-metal ions like Hg2+. [ABSTRACT FROM AUTHOR]