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The Indian Ocean Dipole (IOD) plays a crucial role in shaping local and global environments, yet its effects on interannual variability of the Arabian Sea oxygen minimum zone (ASOMZ) remains poorly understood. Here, we used a coupled physical‐biogeochemical model to investigate the dynamical response of the ASOMZ to extreme negative (2016) and positive (2019) IOD events. Our findings revealed that the suboxic area of the ASOMZ reduced (expanded) by ∼27% (∼28%) after the negative (positive) IOD event. Compared to the 2019 pIOD event, approximately 2.5 times more oxygen‐rich water was delivered into the Arabian Sea during the 2016 nIOD event, replenishing dissolved oxygen (DO) consumed by intensified upwelling‐induced enhanced remineralization of particulate organic matter (POM), thereby increasing the DO concentration in the Gulf of Aden. Conversely, more POM from the western Arabian Sea was transported to the central Arabian Sea, leading to a subsequent decrease in DO concentration there. Plain Language Summary: The Indian Ocean Dipole (IOD) is a climate phenomenon that sea surface temperature in the western Indian Ocean becomes alternately warmer (positive phase) and then colder (negative phase) than the eastern Indian Ocean south of Indonesia. This variability significantly impacts global atmospheric circulation and environments. The Arabian Sea oxygen minimum zone (ASOMZ) is an area in the Arabian Sea characterized by low dissolved oxygen (DO) levels, which can have adverse effects on marine life. We used a model to examine how extreme IOD events influence the ASOMZ. The results suggested that during the negative IOD event in 2016, the suboxic area of the ASOMZ decreased by approximately 27%, while it expanded by approximately 28% during the positive IOD event in 2019. The response of the ASOMZ to IOD events in the Gulf of Aden was primarily modulated by physical factors, such as the Somali Coastal Current and local upwelling. On the other hand, the ASOMZ in the central Arabian Sea was regulated by a combination of biological and physical processes. These findings contributed to our understanding of the ASOMZ's response to IOD events, which is essential for studying the Arabian Sea's marine ecosystem. Key Points: The response of the Arabian Sea oxygen minimum zone to the Indian Ocean Dipole events in the Gulf of Aden was modulated by physical factorsThe Arabian Sea oxygen minimum zone in the central Arabian Sea was regulated by both biological and physical processesThe upper edge of the Arabian Sea oxygen minimum zone invaded the lower euphotic zone (100–200 m) under the impact of Indian Ocean Dipole events [ABSTRACT FROM AUTHOR]

To effectively control CaCO3 scaling in oilfield-produced water, terpolymer scale inhibitor P(IA-AA-SHP) was synthesized by aqueous solution polymerization using itaconic acid (IA), acrylic acid (AA) and sodium hypophosphite (SHP) as raw materials and ammonium persulfate as an initiator. The optimal monomer ratio, initiator dosage, reaction temperature, and time for copolymer synthesis were determined by the controlled variable method. According to the static scale inhibition performance test method in the oilfield, the copolymer dose reached 95.8% inhibition efficiency of CaCO3 at 30 mg L−1. A study of the inhibitory efficiency of copolymer on the CaCO3 scale at different Ca2+ concentrations, CO32− concentrations, and temperatures was also carried out, and the excellent scale inhibition efficiency was maintained despite a change in the water quality conditions. The structure of copolymer P(IA-AA-SHP) was characterized by FTIR, UV, 1H-NMR, and 13C-NMR. Since the molecular weight (Mw) has a great influence on the scale inhibition performance, the relationship between the molecular weight of the polymer and the scale inhibition performance was discussed using gel permeation chromatography (GPC) to detect the molecular weight of the product. The copolymers were shown to have excellent thermal stability using thermogravimetric (TGA) analysis. The effect of copolymers on the morphological structure of CaCO3 crystals was analyzed by SEM and XRD, and the mechanism of scale inhibition was discussed. [ABSTRACT FROM AUTHOR]

CO2 hydrogenation to formic acid is full of challenges due to the high stability of both H2 and CO2. For a long time, unrecyclable bases had been widely used in CO2 hydrogenation to shift the reaction equilibrium by the formation of formate, while a low turnover number (TON) was obtained in the absence of a base. Herein, an efficient method of hydrogenation of CO2 to formic acid in water without consumption of a base is realized. The base can be easily regenerated by the transformation between imidazolium bicarbonate ionic liquid and imidazolium formate in the presence of CO2. A TON of up to 364 249could be achieved in the CO2 hydrogenation performed in an aqueous solution. Formic acid is isolatable with a separation yield of up to 86.8%. The catalyst and base could be recycled simultaneously and their activities remained quite well preserved in a five-cycle experiment. [ABSTRACT FROM AUTHOR]

The dielectric elastomer (DE) has attracted significant attention due to its desired features, including large deformation, fast response, and high energy density. However, for a DE actuator (DEA) utilizing a snap-through deformation mode, most existing theoretical models fail to predict its deformation path. This paper develops a new finite element method (FEM) based on the three-parameter Gent-Gent model suitable for capturing strain-stiffening behaviors. The simulation results are verified by experiments, indicating that the FEM can accurately characterize the snap-through path of a DE. The method proposed in this paper provides theoretical guidance and inspiration for designing and applying DEs and bistable electroactive actuators. [ABSTRACT FROM AUTHOR]

Multiple upwelling systems develop in the Indian Ocean during the summer monsoon. The Sri Lanka dome (SLD), which occurs in the open ocean off the east coast of Sri Lanka from June to September, is distinct from those near the coast. The SLD is characterized by uplifted thermocline and increased chlorophyll concentration. Mechanisms of the upwelling and its biogeochemical response are not well understood. Here, we explored the dynamics of the chlorophyll and sea-to-air CO2 flux in the SLD using ocean color and altimetry remote sensing data, together with other reanalysis products. We found that the occurrence of high chlorophyll concentration and sea-to-air CO2 flux happens along the pathway of the southwest monsoon current (SMC). The annual cycle of chlorophyll in the SLD has a one-month lag relative to that in the southern coast of Sri Lanka. The positive wind stress curl that forms in the SLD during the summer does not fully explain the seasonal chlorophyll maximum. Transport of the SMC, eddy activity, and associated frontal processes also play an important role in regulating the variability in chlorophyll. In the SLD, upwelled subsurface water has excess dissolved inorganic carbon (DIC) relative to the conventional Redfield ratio between DIC and nutrients; thus, upwelling and sub-mesoscale processes determine this region to be a net carbon source to the atmosphere. [ABSTRACT FROM AUTHOR]

Accurate photovoltaic (PV) power forecasting is indispensable to enhancing the stability of the power grid and expanding the absorptive photoelectric capacity of the power grid. As an excellent nonlinear regression model, the relevance vector machine (RVM) can be employed to forecast PV power. However, the optimization of the free parameters is still a key problem for improving the performance of the RVM. Taking advantage of the strong global search capability, good stability, and fast convergence rate of the sparrow search algorithm (SSA), this paper optimizes the parameters of the RVM by using the SSA to develop an excellent RVM (called SSA-RVM). Consequently, a novel hybrid PV power forecasting model via the SSA-RVM is proposed to perform ultra-short-term (4 h ahead) prediction. In addition, the effects of seasonal distribution and weather type on PV power are fully considered, and different seasonal prediction models are established separately to improve the prediction capability. The benchmark is used to verify the accuracy of the SSA-RVM-based forecasting model under various conditions, and the experiment results demonstrate that the proposed SSA-RMV method outperforms the traditional RVM and support vector machine models, and it even shows a better prediction effect than the RVM models with other optimization approaches. [ABSTRACT FROM AUTHOR]

Damage detection technology based on wavelet packet energy has been widely applied to structural health monitoring, especially for one-dimensional structures. With more complex vibration characteristics than one-dimensional structure, two-dimensional structure is common in ship structure. It is a challenge for using wavelet packet energy methods to detect damage in two-dimensional structures. In this study, based on the wavelet packet energy eigenvector, a novel concept of detection index ratio (DIR) is defined to characterize the damage location ability of the excitation force. Based on the above research, a multi-excitation method of damage location in plate-like structures is proposed. In this method, a series of half-sine pulse excitation forces with different frequencies are applied to the structure, and wavelet packet transform (WPT) is used to decompose the vibration response of the intact structure and the damaged structure. The energy ratio changes in frequency bands on all measuring points are taken as the preliminary damage detection index, and the final detection index is obtained by synthesizing the preliminary indexes under various excitation. Moreover, to verify the effect of the proposed method, several tested damage cases are presented. The results show that the proposed method can locate single and multiple damage more accurately and has better noise robustness than the traditional detection method under single excitation. [ABSTRACT FROM AUTHOR]

The South China Sea (SCS) is the largest semi-enclosed marginal sea in the western Pacific. The alternation of East Asian monsoon causes a significant seasonal pattern of chlorophyll, primary productivity, and export flux of sinking particles. However, the source and sink of dissolved organic carbon (DOC) pools with different bioavailability are less studied. Here we evaluated the seasonal production of DOC in labile, semi-labile and refractory forms using a coupled physical-biogeochemical model. This study aims to understand the dynamics and budgets of organic matters in the SCS. Model results show that the production of labile, semi-labile and refractory DOC is highly correlated with the net primary productivity (NPP) which is higher in winter and lower in summer, reflecting a dependence of DOC on the NPP. The seasonal variation in Pearl River discharge dominates the DOC production in the northern coastal region. In the northeast, the Kuroshio intrusion associated frontal system is attributed to cause high winter production. The DOC production in the southwest is controlled by both winter mixing and summer upwelling. The production of refractory DOC with the least bioavailability favors carbon sequestration. Its annual mean production is 1.8±0.5 mg C m−2 d−1, equivalent to 26% of the export flux of particulate organic carbon at 1000 m. [ABSTRACT FROM AUTHOR]

In this study, a bidirectional fluid-structure interaction (FSI) method was proposed based on dynamic mesh technology to calculate the erosion defects of pipe bends under high pressure. In calculating the erosion rate of pipe bends, a stress erosion model was adopted, and the displacement and stress of the inner wall of pipe bend under high external pressure were considered. The influence of different parameters on the calculation results of erosion depth was discussed, and the buckling pressure and collapse mode of pipe bend under the erosion defect of liquid-solid flow were also studied. The proposed method can be used for predicting pipeline erosion defects under high pressure and evaluating the remaining limit load of pipelines with such erosion defects. • A bidirectional fluid structure interaction method was proposed to calculate the erosion of pipe bend under high pressure. • The deformation and stress of pipe bend under high pressure were considered in the fluid domain calculation. • A displacement field transfer method was proposed to update the solid mesh automatically based on erosion results. • The influence of erosion defects on pipe bend buckling was analyzed on the basis of erosion analysis. [ABSTRACT FROM AUTHOR]

Accurate cluster photovoltaic power prediction (CPPP) is crucial for the operation and control of renewable energy grid-connected power systems. The traditional modeling strategies for CPPP such as direct aggregation (DA) and statistical upscaling (SU) have limitations such as error accumulation and upscaling factor uncertainty. To address these issues, this paper proposed a novel hybrid approach for CPPP by combining machine learning models with an improved SU technique. Firstly, a robust broad learning system (BLS) model, in which the Generalized Maximum Correntropy Criterion (GMCC) is used to replace the original mean square error (MSE) loss in BLS, is proposed to solve the problem of multiple outliers affecting the prediction accuracy of regional cluster stations, and it is called GBLS. Then, the Relevance Vector Machine (RVM) as an effective nonlinear regression model is further utilized to compensate for the prediction errors obtained by the GBLS to form the hybrid prediction model, namely GBLS-RVM. Moreover, to mitigate the uncertainty associated with scaling factors in traditional SU strategy, a new SU strategy is developed to refine the relationship between the reference station and the cluster sub-region, enabling direct modeling for regional power prediction. Finally, data from two PV clusters in different regions of China are used to validate the effectiveness of the proposed model, and the results show that under the improved SU strategy, the GBLS-RVM model, reduced RMSE by approximately 33.7% compared to the traditional BLS model, and the RMSE decreased by 12.89% and 30.2% when compared to traditional DA and traditional SU strategies. • A novel hybrid method for CPPP is developed by combining ML and improved SU technique. • A BLS with GMCC (GMCC-BLS) as a prediction model is developed to handle the outliers in measurement data. • An innovative error correction strategy based on RVM is proposed to improve prediction reliability. • A new SU technique is used to establish direct relationships between reference stations and subregions. [ABSTRACT FROM AUTHOR]

Highly-branched cyclic dextrin (HBCD) is a novel dextrin with promising applications in functional foods. In this study, the influence of HBCD on physiochemical properties of κ-carrageenan (KC) gels was determined by rheological measurements, thermal analysis, spectral analysis, micromorphology observation, and freeze-thaw cycle test. The results revealed that the addition of HBCD at a concentration of 2% (w/v) significantly enhanced the storage modulus and freeze-thaw stability of KC gels. During the gelation, HBCD prompted the uniform distribution of KC chains and facilitated the aggregation of KC helixes to form a compact network, enhancing the mechanical properties of KC gels. Meanwhile, the small pores within the compact network contributed to reduced water loss from the KC gels. Comparatively, the syneresis of KC gels with 2% HBCD was 19.80% after the first freeze-thaw cycle and 46.51% after complete cycles (five times), much lower than that observed in pure KC gels (66.50% after the first cycle and 68.15% after the fifth cycle). Furthermore, the attachment of HBCD to the network wall strengthened hydrogen-bonding interactions, thereby enhancing the thermal reversibility of KC gels. Overall, this research provides valuable insights and a theoretical foundation for the potential applications of HBCD in KC gels. [Display omitted] • HBCD was originally applied in KC gels. • HBCD ameliorated the mechanical properties of KC gels. • The freeze-thaw stability of KC gels was significantly perfected by HBCD. [ABSTRACT FROM AUTHOR]

Human action recognition (HAR) is one of the most challenging tasks in the field of computer vision due to complex backgrounds and ambiguity action, etc. To tackle these issues, we propose a novel action recognition framework called Semantic Feature and High-order Physical Feature Fusion (SF-HPFF). Concretely, we first calculate attention pooling module with a low-rank approximation to remove the information of irrelevant complex backgrounds and thus capture the interested target motion region. On this basis, motion features based on the physical characteristics of flow field and semantic features based on word embedding are developed to distinguish ambiguity behaviors. These features are of low dimension and high discrimination, which help to reduce computation burden significantly while maintaining an excellent recognition performance. Finally, cascaded convolutional fusion network is adopted to fuse features and accomplish classification. Multiple experiment results validate that the proposed SF-HPFF outperforms the state-of-art action recognition methods. [ABSTRACT FROM AUTHOR]

Optical flow is widely used in human action recognition. However, the influence of complex background on optical flow often leads to low recognition efficiency. To deal with this issue, an optical flow-based physical feature-driven action recognition framework is proposed in this paper. We first calculate the original dense optical flow field. Then, for reducing computational burden, joint action relevance that can eliminate the pseudo-optical flow in complex background is developed. After that, a more state flow field is obtained by local spatial–temporal thermal diffusion processing. On this basis, we design a feature descriptor that takes the divergence, curl and gradient features of flow field into consideration. Finally, we adopt Fisher vector to encode descriptors for classification. Experimental on HMDB51, KTH and UCF101 datasets proves that actions in complex background can be recognized accurately by the proposed framework, which outperforms the already developed methods. [ABSTRACT FROM AUTHOR]

[Display omitted] • A polygonal MDF and preferred ion lists were used for progressive data acquisition. • Deep learning-assisted MDF combined with GNPS for compound identification. • 116 compounds containing 86 alkaloids were identified in PCC. Advanced analytical methods are often required for detailed and comprehensive interpretation of the complex traditional Chinese medicine system. Phellodendri Chinensis Cortex (PCC) is a common herb involving alkaloids as its main active constituent. The systemic characterization of alkaloids in PCC was carried out by an intelligent process combining polygonal mass defect filtering (p-MDF) with preferred ion lists based on high-resolution mass spectrometry. Firstly, the combination of p-MDF and preferred ion lists was used for data acquisition. Secondly, the mass spectrometry data sets were classified by the deep learning-assisted MDF method for manual annotation, including alkaloids and other components. The characteristic diagnosis ions and neutral loss fragments were also used to assist the manual annotation. Subsequently, the Global Natural Product Social platform was employed for automated annotation. A total of 116 compounds from PCC were identified, containing 86 alkaloids, 1 amino acid, 9 phenylpropanoids, 2 triterpenoids, 13 fatty acids and 5 others. The established strategy provided a powerful guide for the chemical characterization of complex herbal substrates. [ABSTRACT FROM AUTHOR]

Accurate estimation of the state of health (SOH) is crucial for the safe and stable operation of lithium-ion batteries. However, since the labeled values may contain non-Gaussian noise which may lead to a decrease in the effectiveness of traditional data-driven based estimation methods. Therefore, a novel robust stacking integrated learning model (ILM) is proposed to enable accurate SOH estimation under non-Gaussian noises (or outliers) conditions. The mixture correntropy loss (MCL) is used in original extreme learning machine (ELM) and the gated recurrent unit (GRU) frameworks to develop novel robust learning models, i.e MCL-ELM and MCL-GRU, and they are used as the sub-models of the proposed ILM, which takes into account the generalization performance of the model and the overall trend of SOH over the time series. In addition, the entropy weighting method that can well reflect the differences between the sub-models is utilized to reduce the complexity of the stacked ILM. Furthermore, the local tangent space alignment is used to capture the local relationships between different loops to enhance the effectiveness of the extracted health features. Several numerical experiments are performed under different cases to validate the estimation effect of the proposed model by using two publicly available datasets, and the experimental results demonstrate that the maximum RMSE, MAE, and MAPE values of the proposed model are 1.391%, 0.932%, and 1.480%, respectively, under non-Gaussian noises conditions. • Robust ELM and GRU models using MCL are developed. • Novel robust stacking ILM via the combination of the MCL-ELM and MCL-GRU is proposed for SOH estimation. • The EWM is used to obtain the output results of multiple base learners in the proposed ILM. [ABSTRACT FROM AUTHOR]

When solving compressible multi-material flow problems, an unresolved challenge is the computation of advective fluxes across material interfaces that separate drastically different thermodynamic states and relations. A popular idea in this regard is to locally construct bimaterial Riemann problems, and to apply their exact solutions in flux computation. For general equations of state, however, finding the exact solution of a Riemann problem is expensive as it requires nested loops. Multiplied by the large number of Riemann problems constructed during a simulation, the computational cost often becomes prohibitive. The work presented in this paper aims to accelerate the solution of bimaterial Riemann problems without introducing approximations or offline precomputation tasks. The basic idea is to exploit some special properties of the Riemann problem equations, and to recycle previous solutions as much as possible. Following this idea, four acceleration methods are developed, including (1) a change of integration variable through rarefaction fans, (2) storing and reusing integration trajectory data, (3) step size adaptation, and (4) constructing an R-tree on the fly to generate initial guesses. The performance of these acceleration methods is assessed using four example problems in underwater explosion, laser-induced cavitation, and hypervelocity impact. These problems exhibit strong shock waves, large interface deformation, contact of multiple (>2) interfaces, and interaction between gases and condensed matters. For all the problems, the acceleration methods are able to significantly reduce the computational cost without affecting solver robustness or solution accuracy. In different cases, the solution of bimaterial Riemann problems is accelerated by 37 to 87 times. As a result, the total cost of advective flux computation, which includes the exact Riemann problem solution at material interfaces and the numerical flux calculation over the entire computational domain, is accelerated by 18 to 81 times. • Bimaterial Riemann problems can be constructed to compute interfacial fluxes. • Computational cost is often prohibitive, if complex equations of state are involved. • An efficient exact Riemann solver is proposed, with four algorithmic improvements. • Significant cost reduction (37-87X) is achieved for four challenging examples. • Does not introduce approximations or require offline precomputation. [ABSTRACT FROM AUTHOR]

Increasing the carotenoid content of nectarine (Prunus persica var. nucipersica) is of great significance for improving its quality and economic value. A two years study was carried out on 'Shuguang' nectarine to evaluate the effect of calcium chloride (Cl–Ca) and L-aspartic acid nano calcium [Ca (L-asp) - NPs] (nano-Ca) on carotenoid accumulation. The results show that both Cl–Ca and nano-Ca could increase the carotenoid content of nectarine fruit flesh, but the effect of nano-Ca was more significant. Nano-Ca is more easily absorbed by nectarine leaves and fruits, which improves the calmodulin activity of leaves, peel and flesh, and up-regulates the expression of carotenoid synthesis-related genes PpPSY , PpPDS , PpZDS , PpLCY-B , PpCHY-B and PpZEP. Nano-Ca also significantly up-regulated the expression of sucrose synthesis related genes PpSUS1 and PpSUS3 in leaves and sucrose transport related genes PpSUT2 and PpSUT4 in stem phloem, promoting the transport of more photosynthetic products to fruits, providing raw materials for carotenoid synthesis, and increasing the content of total sugars and ascorbic acid (Vc). In addition, nano-Ca can also up-regulate the expression levels of PpMYB10.1 and PpUFGT and promote total anthocyanins accumulation in peel. The results of our study will be useful for clarifying how nano-fertilizer improve the fruit quality of nectarine. • Nano-Ca treatment increase the calmodulin activities. • Nano-Ca up-regulates the expression levels of carotenoid biosynthesis-related genes. • Nano-Ca up-regulates the expression levels of anthocyanin biosynthesis-related genes. • Nano-Ca up-regulates the expression levels of PpSUS1 , PpSUS3 , PpSUT2 and PpSUT4. [ABSTRACT FROM AUTHOR]

How homochirality concerning biopolymers (DNA/RNA/proteins) could have originally occurred (i.e., arisen from a non-life chemical world, which tended to be chirality-symmetric) is a long-standing scientific puzzle. For many years, people have focused on exploring plausible physic-chemical mechanisms that may have led to prebiotic environments biased to one chiral type of monomers (e.g., D-nucleotides against L-nucleotides; L-amino-acids against D-amino-acids)–which should have then assembled into corresponding polymers with homochirality, but as yet have achieved no convincing advance. Here we show, by computer simulation–with a model based on the RNA world scenario, that the biased-chirality may have been established at polymer level instead, just deriving from a racemic mixture of monomers (i.e., equally with the two chiral types). In other words, the results suggest that the homochirality may have originated along with the advent of biopolymers during the origin of life, rather than somehow at the level of monomers before the origin of life. Author summary: People have long been curious about the fact that central molecules in the living world (biopolymers), i.e., nucleic acids and proteins, are asymmetric in chirality (handedness), but as the relevant background, the chemical world is symmetric in chirality. Now that life should have originated from a prebiotic non-life background, how could this dissymmetry have occurred? Previous studies in this area focused their efforts on how the chirality-symmetry may have been broken at the monomer level (i.e., nucleotides or amino acids), but have achieved little advance over decades of years. Here we demonstrate, by in silico simulation, that instead, the required chirality-deviation may have been established along with the emergence of biopolymers at the beginning stage in the origin of life–just deriving from a chirality-symmetric monomer pool. The process is actually not only an issue of chemistry but also an issue involving evolution–thus previously difficult to reveal by pure lab work in this area. By modelling the evolutionary process, the present computer simulation study provides significant clues for experiments in future. [ABSTRACT FROM AUTHOR]

• A novel two-level nesting smoothed meshfree method (NSMM) is proposed. • The NSMM is applied for structural dynamic analysis. • The NSMM is directly extended to solving dynamic fracture problems. • The NSMM is efficient, accurate and stable. This paper presents a novel two-level nesting smoothed meshfree method (NSMM), which significantly improves the computational efficiency of the meshfree Galerkin methods without losing their accuracy, thus facilitates the employment of meshfree methods in applications where background integration cells would be prohibitively expensive. In the NSMM, the system stiffness matrix is calculated using the general smoothing strain technique over the two-level nesting smoothing sub-domains where fewer integration points are used and the costly derivative computation of meshfree shape functions is avoided. The accuracy, efficiency and stability of the present method are assessed by virtue of several numerical examples for problems involving free and forced vibration analysis of the linear elastic continua and dynamic crack response of elastic solid. The results reveal that the NSMM stands out and achieves better performance compared to other existing approaches in the literature. [ABSTRACT FROM AUTHOR]

The High-degree Cubature Kalman Filter (HCKF) is proposed as a novel methodology based on the arbitrary degree spherical rule, which can achieve better performance than the traditional Kalman filter. However, it also has a large calculation burden when used in a high-dimension and high-degree of accuracy estimation system. The number of sampling points of an HCKF increases polynomially with increasing state-space dimensions, which further increases the calculation burden. The reduction of the number of the state-space dimensions is the main contribution of this study. A strategy for HCKF based on the partitioning of the state-space and orthogonal principle is introduced, referred to as the Multiple Robust HCKF (MRHCKF). It is shown that this technique can effectively reduce the calculation burden for the high-dimension system with robust performance. Numerical simulations are performed for the example of high-dimension relative position and attitude estimation to show that the proposed method can obtain nearly the same performance as the HCKF, while drastically reducing computational complexity. [ABSTRACT FROM AUTHOR]

A bias‐compensated normalised least mean square (BCNLMS) algorithm with variable step size (denoted as BCVNLMS) is developed in this work to improve the accuracy and convergence speed for the three‐phase power system (TPPS) frequency estimation in circumstance of the noise and harmonic interference. Taking into account the problem of bias estimation caused by the mixed noises in the acquisition signal of the TPPS, the NLMS algorithm with an unbiased criterion (called BCNLMS) was employed to compensate the bias and improve the estimate accuracy. Furthermore, an adaptive variable step scheme is also incorporated into the BCNLMS algorithm to improve the convergence speed and stability during the process of adaptively frequency estimation. The experimental results show that the proposed BCVNLMS algorithm outperforms other well‐known methods for frequency estimation of the TPPS in several scenarios such as severe noise pollution, harmonic interference and frequency mutation. [ABSTRACT FROM AUTHOR]

The South China Sea (SCS) is strongly influenced by the East Asian monsoon system with seasonal reversal. Measurements from a 7-year continuous sediment trap located in the central SCS showed a clear seasonal pattern. The particulate organic carbon (POC) export flux at the depth of 1200 m was considerably higher in monsoon seasons. The driving dynamics leading to this seasonal variability of POC export, however, remains inadequately understood. Here, a one-dimensional physical-biogeochemical coupled model was developed to simulate the temporal variability of a lower-trophic planktonic ecosystem. The modeled POC export flux compared reasonably well with the 7-year time series from moored sediment trap. Model results showed that the POC export flux at 1200 m is highly correlated with the 0–100 m integrated primary productivity and with the export flux at 100 m, implying that the seasonal variability of sediment trap data could be induced by changes in phytoplankton production and its vertical export. Further model analysis suggested that the annual mean export ratio (e-ratio) at 100 m and transfer efficiency at 1200 m in the central SCS were 0.19 and 0.07, respectively, which are lower than those in high latitudes. The winter monsoon favors not only surface carbon fixation but also export to the deep ocean. The heat flux is the dominant factor regulating the seasonal cycle of mixed layer depth, nutrient supply, and the growth of phytoplankton in this region. The wind-driven mixing can further facilitate upward nutrient transport to the surface and amplify the seasonal amplitude of the POC export flux. [ABSTRACT FROM AUTHOR]

Previous theoretical and computational studies on hypervelocity impact have mainly focused on the dynamic response of the solid materials that constitute the projectile and the target, while the surrounding environment is often assumed to be a vacuum. In this paper, we consider impact events that occur in a fluid (e.g., gas) medium, and present a computational model that includes the dynamics, thermodynamics, and ionization of the surrounding fluid material. The model couples the compressible Navier–Stokes equations with the Saha equations to predict the onset and extent of ionization in the surrounding fluid. An extended level set method with two signed distance functions is employed to track the three material interfaces between the projectile, the target, and the ambient fluid. This method accommodates the large deformation, contact, and separation of the interfaces, while avoiding spurious overlapping of different material subdomains. The advective fluxes across material interfaces are computed by constructing and solving bimaterial Riemann problems, thereby taking into account the discontinuities in both state variables (e.g., density) and thermodynamic relations. The computational model is first verified for an infinite ideal plasma and a one-dimensional three-material impact problem. Next, the model is employed to analyze the impact of a tantalum rod projectile onto a soda lime glass (SLG) target in an argon gas environment. In different analyses, the impact velocity is varied between 3 and 6 km / s , and the radius of the projectile is varied between 2.5 and 10 mm. Each analysis starts with a steady-state fluid dynamics simulation that generates the shock-dominated hypersonic flow around the projectile. This flow field is then used as an initial condition to start the fluid–solid coupled impact simulation. The predicted maximum temperature and pressure within the SLG target agree reasonably well with published experimental data for a similar material (fused quartz). Within the ambient gas, the impact-generated shock wave is found to be stronger than the initial bow shock in front of the projectile. Behind this shock wave, a region of high pressure and temperature forms in the early stage of the impact, mainly due to the hypersonic compression of the fluid between the projectile and the target. The temperature within this region is significantly higher than the peak temperature in the solid materials. For impact velocities higher than 4 km / s , ionization is predicted. This finding indicates that the ambient gas may be a nontrivial contributor to the plasma formed in terrestrial and atmospheric hypervelocity impact events. • A fluid–solid coupled computational model of hypervelocity impact. • Three material interfaces tracked implicitly by solving two level set equations. • Ionization in the surrounding fluid predicted by the Saha equations. • Impact simulations for tantalum – soda lime glass – argon gas, 3–6 km/s. • Significant ionization detected for impact velocities higher than 4 km/s. [ABSTRACT FROM AUTHOR]

In this work, biopolymer nanomaterials were prepared by electrostatic complexation and thermal treatment using the medicinal and edible homologous polysaccharides from Lentinus edodes (LEP) and bovine serum albumin (BSA). The hydrodynamic radius, PDI and zeta potential of the LEP-BSA nanocarriers (NCs) were 125.3 ± 1.2 nm, 0.206 ± 0.007 and − 25.3 ± 0.7 mV, respectively. SEM images of LEP-BSA NCs further demonstrated their uniform morphology. UV–vis, fluorescence and FTIR spectra revealed that LEP interacted successfully with BSA. And the presence of LEP caused the conformational change of BSA, which was confirmed by FTIR spectroscopy. The LEP-BSA NCs maintained good stability in long-term storage at different temperatures and kept integrity at neutral or slightly higher pH conditions. In vitro hemolysis and cytotoxicity experiments were performed to verify the biocompatibility of the LEP-BSA NCs. Furthermore, the ability of LEP-BSA NCs to encapsulate bioactive compounds was proved by the successful encapsulation of resveratrol and the photoprotection of resveratrol. This work will be applied to other polysaccharide-protein systems with unique activities to prepare multi-functional stimuli-responsive nanomaterials for better applications in food production and biopharmaceuticals. [Display omitted] • The nanocarriers were smaller than 130 nm. • Conformation changes of the protein were confirmed by spectroscopy methods. • The nanocarriers remained stable for 90 days at room temperature. • Photoprotection of encapsulated resveratrol under UV irradiation. [ABSTRACT FROM AUTHOR]

Highlights • Greatly improving the efficiency of the meshfree method by transforming background cell integral into boundary integration. • Directly imposing the boundary condition without any effort. • Completely avoiding the derivation of meshfree shape functions. • Improving the accuracy of the stress field in the vicinity of the crack tips. Abstract A smoothed enriched meshfree Galerkin method with two-level nesting triangular sub-domains (NSEMM) is presented for linear elastic fracture mechanics. In the present method, displacement fields are constructed by using the linear MLS approximation in linear region away from the crack tip and the enriched MLS approximation in enriched region around the crack tip respectively. To overcome the discontinuous problem of the coupling approximations and accelerate meshfree computations, two-level nesting triangular sub-domains based on the triangular background integration cells are designed and used to construct the smoothing strain. Each two-level nesting sub-domains includes the triangular background cell itself and four equal-area triangular sub-cells. The discretized system equations are created by the Generalized smoothed Galerkin (GS-Garlerkin) weak form and Richardson extrapolation method. The values of SIFs are evaluated by using the domain form of interaction integral. Numerical examples have been simulated to demonstrate the effectiveness and robustness of the present method for crack problems with complicated configurations, and very satisfactory results have been obtained. The NSEMM takes advantages of both EFGM and generalized strain smoothing technique such as lower computational cost, high accurate and easy to implementation. [ABSTRACT FROM AUTHOR]

Abstract A series of emission color tunable Ce3+, Tb3+, and Eu3+ co-doped La 2 Si 2 O 7 (LSO) phosphors have been prepared via a solid state reaction. The crystal structure, luminescence properties, and thermal stability of the phosphors were studied in this paper. There exists two kinds of energy transfer (ET) modes under UV excitation, namely, electric dipole-dipole interaction for Ce3+→Tb3+ and terbium bridge model [Ce3+→(Tb3+) n →Eu3+] for LSO:Ce3+,Tb3+,Eu3+ system. The emitting color of the phosphors can be tuned from green to yellow and eventually to orange-red through the Ce3+→Tb3+→Eu3+ energy transfer. Although codoping Tb3+ and Eu3+ into La 2 Si 2 O 7 :Ce3+ leads to the reduction of thermal stability, it still remains 80% for LSO:0.05Ce3+,0.8 Tb3+,0.02Eu3+ at 150 °C when compared to that at room temperature. The absolute quantum yield (QY) increases from 71.04% (LSO:0.05Ce3+) to 95.60% (LSO:0.05Ce3+, 0.6 Tb3+), while those of LSO:0.05Ce3+, y Tb3+,0.02Eu3+ samples remain more than 70%. These results indicate that the phosphors can be candidates for application in phosphor-converted white light-emitting diodes (pc-WLEDs). Graphical abstract Image 1 Highlights • La 2 Si 2 O 7 :Ce3+,Tb3+,Eu3+ has been prepared by a high-temperature solid state reaction. • The emitting color can be tuned from green to yellow and then to orange-red. • [Ce3+→(Tb3+) n →Eu3+] bridge is responsible for the enhancement of Eu3+ emission. • The quantum efficiency of 0.05Ce3+, y Tb3+,0.02Eu3+ codoped samples is more than 70%. • The phosphors exhibit good thermal stability. [ABSTRACT FROM AUTHOR]

Summary: Two novel adaptive filtering algorithms based on the mixed square/fourth error criterion are proposed for solving sparse system identification problems. Motivated by the fact that the proportionate update scheme can enhance the tracking ability of the system, we develop a proportionate least mean square/fourth (PLMS/F) algorithm in this paper. Combining the proportionate update scheme and the LMS/F algorithm, the proposed PLMS/F algorithm shows superiority for non‐Gaussian noise environments. Moreover, to further improve the performance of the PLMS/F algorithm in the noisy input cases, a bias‐compensated PLMS/F algorithm is developed by incorporating an unbiased criterion to compensate the bias caused by input noises. Simulation results in the context of the sparse system identification framework demonstrate that the proposed PLMS/F and bias‐compensated PLMS/F algorithms can achieve excellent identification performance in terms of steady‐state misalignment and convergence speed under noisy input and non‐Gaussian output noise environments. [ABSTRACT FROM AUTHOR]

Highlights • We propose a bias-compensated normalized MCC algorithm which is efficient for the noisy input and impulsive output noise cases. • We use the unbiasedness criterion to derive the bias compensated term for the proposed algorithm. • The proposed BCNMCC algorithm performs better than the original NMCC algorithm in noisy input environment. Abstract This paper proposes a bias-compensated normalized maximum correntropy criterion (BCNMCC) algorithm charactered by its low steady-state misalignment for system identification with noisy input in an impulsive output noise environment. The normalized maximum correntropy criterion (NMCC) is derived from a correntropy based cost function, which is rather robust with respect to impulsive noises. To deal with the noisy input, we introduce a bias-compensated vector to the NMCC algorithm, and then an unbiasedness criterion and some reasonable assumptions are used to compute the bias-compensated vector. Taking advantage of the bias-compensated vector, the bias caused by the input noise can be effectively suppressed. System identification simulation results demonstrate that the proposed BCNMCC algorithm can outperform other related algorithms with noisy input especially in an impulsive output noise environment. [ABSTRACT FROM AUTHOR]

Ce 3+ single-doped Ca 3 (SiO 3 ) 3 phosphors were synthesized by a traditional solid-state reaction at elevated temperature. The phase impurities of phosphors prepared at different conditions were characterized and analyzed and an optimal one was obtained. The synthesis and luminescent properties of the phosphors were studied in detail. As a result, two different emission bands can be observed under excitations at 330 and 360 nm, which peak at 380 and ∼400 nm, respectively. Further analyses of emission spectra reveal that there should exist four different emission bands originating from four Ce 3+ luminescence centers on different Ca 2+ sites. The phosphor with optimal Ce 3+ content [Ca 2.82 (SiO 3 ) 3 :0.18Ce 3+ ] exhibits high absolute quantum efficiencies up to 90.1% and 79.5% for emission bands at 380 and 400 nm, respectively. Moreover, the emission intensity of Ca 2.82 (SiO 3 ) 3 :0.18Ce 3+ at 150 °C remains ∼65% of that at room temperature. The phosphor deserves further investigation for the purpose of application in pc-WLEDs. [ABSTRACT FROM AUTHOR]

In this paper, we present a multiple-scale higher order polynomial collocation method for the numerical solution of 2D and 3D elliptic partial differential equations (PDEs) with variable coefficients. The collocation method with higher order polynomial approximation is very simple for solving PDEs, but it has not become the mainstream method. The main reason is that its resultant algebraic equations have highly ill-conditioned behavior. In our scheme, the multiple-scale coefficients are introduced in the polynomial approximation to overcome the ill-conditioned problem. Based on the concept of the equilibrate matrix, the multiple scales are automatically determined by the collocation points. We find these scales can largely reduce the condition number of the coefficient matrix. Numerical results confirm the accuracy, effectiveness and stability of the present method for smoothed and near-singular 2D and 3D elliptic problems on various irregular domains. [ABSTRACT FROM AUTHOR]

• The UKF with EKRSL is developed by using the fixed-point iteration; • An enhanced EKRSL-UKF is proposed via an exponential function of innovation; • The proposed EnEKRSL-UKF is used for robust DSE. The traditional unscented Kalman filter (UKF) with mean square error (MSE) criterion for dynamic state estimation (DSE) is sensitive for unknown non-Gaussian noise and outliers. Leading to biased state estimates. This paper proposes a novel robust UKF with extended kernel risk-sensitive loss (EKRSL) for DSE considering unknown non-Gaussian process and measurement noises. Instead of MSE criterion, a novel robust EKRSL via the generalized Gaussian density is defined in KRSL framework, and we further develop a new robust UKF using the EnKRSL(called EKRSL-UKF). To obtain the recursive form of EKRSL-UKF, the statistical linear regression model is used and the fixed-point iteration is further utilized to iteratively get the optimal state estimate. An error constrained method is also introduced to restrict the error to address the numerical instability problem caused by large outliers. Furthermore, an enhanced EKRSL-UKF is established by using an exponential function of innovation to improve the estimation accuracy in the presence of noise uncertainties. Numerical results carried out on the IEEE 39-bus test system demonstrate that the proposed method can achieve desired robustness without loss of estimation accuracy under various conditions. [ABSTRACT FROM AUTHOR]

Marine primary producers are largely dependent on and shape the Earth's climate, although their relationship with climate varies over space and time. The growth of phytoplankton and associated marine primary productivity in most of the modern global ocean is limited by the supply of nutrients, including the micronutrient iron. The addition of iron via episodic and frequent events drives the biological carbon pump and promotes the sequestration of atmospheric carbon dioxide (CO2) into the ocean. However, the dependence between iron and marine primary producers adaptively changes over different geological periods due to the variation in global climate and environment. In this review, we examined the role and importance of iron in modulating marine primary production during some specific geological periods, that is, the Great Oxidation Event (GOE) during the Huronian glaciation, the Snowball Earth Event during the Cryogenian, the glacial–interglacial cycles during the Pleistocene, and the period from the last glacial maximum to the late Holocene. Only the change trend of iron bioavailability and climate in the glacial–interglacial cycles is consistent with the Iron Hypothesis. During the GOE and the Snowball Earth periods, although the bioavailability of iron in the ocean and the climate changed dramatically, the changing trend of many factors contradicted the Iron Hypothesis. By detangling the relationship among marine primary productivity, iron availability and oceanic environments in different geological periods, this review can offer some new insights for evaluating the impact of ocean iron fertilization on removing CO2 from the atmosphere and regulating the climate. [ABSTRACT FROM AUTHOR]

The carbon isotope (δ 13 C) record from the Plio-Pleistocene shows prominent 400-kyr cycles with maximum values at eccentricity minima during the Pliocene. The period extends to 500 kyr in the Pleistocene after ~ 1.6 Ma. Five δ 13 C maxima occurred at ~ 0.2, 0.5, 1.0, 1.5 and 1.9 Ma over the last 2 Ma. Although several hypotheses have been suggested to explain why the 400–500-kyr cycles are so strong in δ 13 C records and how they may have originated, the mechanism is still not clear. The aim of this study was to test the dissolved organic carbon (DOC) hypothesis, which was proposed recently to explain this 400–500-kyr cycle in deeper time. We used an intermediate complexity box model that is computationally efficient for studies involving longer timescales. The model incorporates sophisticated microbial processes, dividing the oceanic carbon cycle into a rapid and a slow cycle. The model result suggests that when more nutrients enter the surface ocean, the rapid carbon cycle is more active, and less refractory DOC (RDOC) is produced. The opposite sequence occurs when fewer nutrients enter the ocean. The modeled RDOC concentration and the δ 13 C of dissolved inorganic carbon (DIC) are anti-correlated with riverine nutrient input. According to mass conservation, the release of isotopically lighter carbon from the RDOC pool leads to lighter DIC δ 13 C while an increase in the RDOC pool enriches it. The transient simulations produced a one-to-one correspondence between modeled and measured δ 13 C. This study supports the hypothesis that chemical weathering-induced variations in the DOC pool act as a pacemaker for δ 13 C changes over 400–500-kyr cycles. [ABSTRACT FROM AUTHOR]

Two robust kernel adaptive filter (KAF) algorithms, called the kernel least mean p-power (KLMP) and kernel recursive least mean p-power (KRLP), are developed by combining mean p-power error (MPE) criterion and kernel trick for noisy chaotic time series prediction (CTSP). The proposed algorithms employ the MPE to overcome the performance degradation of the CTSP when training data are corrupted by impulsive noises (especially the α-stable noises). First, the KLMP algorithm is proposed by the gradient decent method to improve the robustness of the traditional kernel least mean square (KLMS). Second, the recursion idea and the kernel method are utilized to develop a recursive KAF, namely KRLP, to improve the robustness of the traditional kernel recursive least squares (KRLS). Simulation results show that the proposed algorithms display notable robustness in CTSP when the training data contain different levels of noises, and can perform better in terms of testing MSE than other algorithms. [ABSTRACT FROM AUTHOR]

• Seasonal variability of dissolved organic carbon (DOC) transport through major straits of the South China Sea (SCS) is largely controlled by the East Asian monsoon. • Cross-isobath transport is determined by both the pressure gradient along the isobath and the Ekman transport, with the contribution of the latter increasing shoreward. • DOC is transported into the SCS via the Luzon Strait and out via the Taiwan, Karimata and Mindoro straits. • A net export of labile and semilabile DOC from the SCS is quantified. The South China Sea (SCS) is the largest semienclosed marginal sea in the western Pacific. The advective supply of dissolved organic carbon (DOC) from the open ocean to the SCS influences its carbon cycle and biogeochemical processes. However, quantitative studies of DOC exchange across different straits and the shelf to the SCS are particularly limited. In this study, we investigated seasonal DOC transport across four major straits and cross-shelf breaks using a coupled physical–biogeochemical model. The modeling results show that the seasonal variations in DOC transport through the major straits are largely controlled by the monsoon. In winter, associated with the northeast monsoon, the magnitudes of DOC transport from the four straits are generally larger than those in summer with the southwest monsoon. DOC transport is eastward at the Luzon Strait and northward at the Taiwan and Karimata straits during the southwest monsoon and changes direction during the northeast monsoon. The annual mean of depth-integrated DOC transport is 86.7 Tg C yr−1 westward at the Luzon Strait, 19.1 Tg C yr−1 northward at the Taiwan Strait, 25.9 Tg C yr−1 southward at the Karimata Strait, and 46.0 Tg C yr−1 southward at the Mindoro Strait. DOC transport across the shelf break is a result of geostrophic or quasigeostrophic balance. In the north and west, the annual net cross-shelf break transports are onshore with magnitudes of 8.8 and 31.1 Tg C yr−1, respectively. In the southern SCS, the annual net transport is offshore with a magnitude of 18.3 Tg C yr−1. The net export of total labile and semilabile DOC from the SCS has a flux of 10.7 Tg C yr−1. This study provides seasonal budgets of DOC exchange between the SCS and its adjacent oceans, which contribute to a better evaluation of the carbon cycle in the SCS. [ABSTRACT FROM AUTHOR]

• A novel numerical method to simulate cavitation induced by long-pulsed laser. • The processes of laser radiation, vaporization, and bubble/fluid dynamics are simulated simultaneously. • An embedded boundary method is proposed for laser-fluid coupling, well-posed with 2nd-order accuracy. • The level set method is combined with a phase transition law to track continuous vaporization. • Predictive capability demonstrated by simulations of different laser experiments. A computational method for simulating thermal cavitation induced by long-pulsed laser is presented. This method accounts for the absorption of laser light by a liquid, the formation of vapor bubbles due to localized heating, and the dynamics of the bubbles and the surrounding liquid. The physical model combines the Euler equations for a compressible inviscid two-phase fluid flow, a reduced form of the radiative transfer equation for laser radiation, and a local thermodynamic model of vaporization. The Euler equations are solved using the FInite Volume method with Exact two-phase Riemann solvers (FIVER). Following this method, numerical fluxes across phase boundaries are computed by constructing and solving one-dimensional bimaterial Riemann problems. The paper focuses on numerical methods for coupling the laser and fluid governing equations and tracking the vapor bubbles. An embedded boundary finite volume method is proposed to solve the laser radiation equation on the same mesh created for the Euler equations, which usually does not resolve the boundary and propagation directions of the laser beam. To impose boundary conditions, ghost nodes outside the laser domain are populated by mirroring and interpolation techniques. The existence and uniqueness of solution are proved for the two-dimensional case, leveraging the special geometry of the laser domain. The order of accuracy of the method is also proved, and verified using numerical tests. A method of latent heat reservoir is proposed to predict the onset of vaporization, which accounts for the accumulation and release of latent heat. A unique challenge associated with long-pulsed laser is that the dynamics of vapor bubbles is driven not only by the inertia of the bubble nuclei, but also by the continuation of vaporization. In this work, the localized level set method is employed to track the bubble surface, and a method of local correction and reinitialization is proposed to account for continuous phase transitions. Several numerical tests are presented to verify the convergence of these methods. Two realistic simulations of laser-induced cavitation are presented at the end, showing that the computational method is able to capture the key phenomena in these events, including non-spherical bubble expansion, shock waves, and the "Moses effect". [ABSTRACT FROM AUTHOR]

Pipe bend is a common junction in pipeline system. In this study, the post-buckling behavior of deep-sea thick-walled pipe bend under external pressure is studied by numerical simulation. A 4-node tetrahedron solid element based on vector form intrinsic finite element method (VFIFE) is introduced to simulate the whole buckling process. First, the VFIFE models of the thick-walled pipes are built and the results of the VFIFE method, traditional finite element method, and the experiments from other publications are compared to verify the proposed method. Then, collapse modes and collapse mechanism of the pipe bend when buckling propagates to the elbow under dynamic and quasi-static conditions are analyzed. Finally, the influence of different geometric parameters on the crossover pressure of the pipe bend is studied. These results can be used to support the buckling arrest design of pipe bends. • Analysis of post-buckling behavior of pipe bend based on VFIFE tetrahedral solid element. • A self-contact algorithm for the collision of the inner wall of pipe based on VFIFE tetrahedral solid element. • The collapse mode and collapse mechanism of pipe bend is analyzed. • The influence of transition zone on post-buckling critical pressure is discussed. • Effect analysis of the relative bend radius, the diameter–thickness ratios, and the bend angle. [ABSTRACT FROM AUTHOR]

Kalman filters (KFs) are widely used for state-of-charge (SOC) estimation of Li-ion batteries due to their excellent dynamic tracking capability. Especially the cubature KF (CKF), with the computational efficiency and nonlinear processing ability, is an outstanding candidate for SOC estimation. However, the actual working conditions are complex and changeable, and the measurement data is usually accompanied by non-Gaussian noise (outliers). Therefore, the performance of the original CKF with minimum mean square error (MMSE) criterion may be degraded seriously in these cases. In order to enhance the robustness of CKF, the MMSE in the CKF framework is substituted by the generalized maximum correntropy criterion (GMCC), and thus a robust CKF with GMCC (GMCC-CKF) is developed by fixed point iteration approach in this work. Furthermore, a SOC estimation model via the GMCC-CKF is proposed to improve estimation accuracy under non-Gaussian noise environments. The simulation results show that, compared with the traditional KFs, the proposed GMCC-CKF can accurately estimate the SOC of lithium batteries under different temperatures and operating conditions considering non-Gaussian noise interference. The results of mean absolute error (MAE) and root mean square error (RMSE) are less than 1%, which verifies the excellent performance of GMCC-CKF. • GMCC is introduced into the CKF framework to develop a novel robust CKF. • The proposed GMCC-CKF method is applied for robust SOC estimation under non-Gaussian noise interferences. • Some simulations under different conditions are performed to evaluate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Privacy-preserving Content-Based Image Retrieval (CBIR) method is a promising technology to achieve data confidentiality and searchability in cloud-assisted multimedia (i.e., image or video) data environment. However, inappropriate feature-preserving mechanisms and inefficient ciphertext descriptors resulted in lower performance than expected. Therefore, how to design encryption techniques with high security and how to extract effective features from ciphertext images still hinder privacy-preserving CBIR. For this goal, we propose a privacy-preserving image retrieval based on deep convolutional network features. First, a novel hybrid encryption technique is designed to encrypt images and an improved DenseNet model is fine-tuned by using the encrypted images to construct a feature extractor. The encrypted images and fine-tuning feature extractor are then uploaded to cloud server. Meanwhile, secure CBIR service is executed in the cloud server. We conduct experiments on two public benchmark datasets for performance evaluation in terms of mAP and accuracy. As demonstrated in the experimental results, the proposed method can achieve superior result compared with the existing methods, improving the performance on the two metrics by relatively 1.9% and 10%, respectively. Furthermore, the computational cost and parameters of depthwise separable convolution adopted by the improved DenseNet model are 8 to 9 times smaller than that of standard convolutions of the original DenseNet at only a small reduction in accuracy. • Preserving color features by replacing RGB channels. • The texture features are preserved by scrambling the pixel bit matrix. • A hybrid privacy-preserving mechanism for color and texture information. • The features of encrypted images are extracted by CNN on cloud server. • Experimental results show that our method is highly competitive. [ABSTRACT FROM AUTHOR]

A long-term increase in coccolith size over the Pleistocene has long been discovered in global oceans. Such a long-term and evolutionary change is expected to exert substantial impact on the carbon cycle as coccolithophores are one of the major components of marine carbonate counter pump (CCP). Here, we present coccolith morphological data as well as coccolith calcite export at Ocean Drilling Program Site 1143 in the South China Sea over the past 2 Myr. The results confirm the idea that Earth eccentricity controlled coccolith size diversity and calcite export production in tropical oceans in the Pleistocene. In addition, we consider a possible origin of the long-term increase in coccolith size as a result of increased oceanic alkalinity availability. As coccolithophores evolved simultaneously in global oceans, the increased coccolith calcification may have promoted global marine particulate inorganic carbon production, especially for the interglacial stages. Therefore, the enhanced coccolith-based CCP may account for a stepwise increase in interglacial CO 2 levels over the middle Pleistocene. High CO 2 levels at the onset of the interglacial stages may reduce the glaciation rate, thereby prolonging an entire interglacial-glacial cycle after the middle Pleistocene. • Long-term increase in coccolith size can result from increased availability of oceanic alkalinity. • Long-term increase in coccolith size may promote global PIC production over the Pleistocene. • Increased coccolith calcification may account for a long-term interglacial CO 2 change over the MPT. [ABSTRACT FROM AUTHOR]

In this paper, a meshless collocation method with barycentric rational interpolation is proposed to find and represent the solution of the two-dimensional hyperbolic telegraph equation. Barycentric rational interpolation functions are used for spatial variable and its partial derivatives, which produce a system of second order ordinary differential equations based on collocation method. The resulting system has been solved by central differential scheme. The accuracy and efficiency of proposed approach are demonstrated by several numerical experiments, where comparison is made with some earlier work. It is clear that the proposed method produces good results in comparison with those available in literature. Moreover, CPU time taken in our computation is much less. It is proved that the proposed method is very simple, fast and accurate. [ABSTRACT FROM AUTHOR]

Sparse adaptive filtering algorithms are utilized to exploit system sparsity as well as to mitigate interferences in many applications such as channel estimation and system identification. In order to improve the robustness of the sparse adaptive filtering, a novel adaptive filter is developed in this work by incorporating a correntropy-induced metric (CIM) constraint into the least logarithmic absolute difference (LLAD) algorithm. The CIM as an $$l_{0}$$ -norm approximation exerts a zero attraction, and hence, the LLAD algorithm performs well with robustness against impulsive noises. Numerical simulation results show that the proposed algorithm may achieve much better performance than other robust and sparse adaptive filtering algorithms such as the least mean p-power algorithm with $$l_{1}$$ -norm or reweighted $$l_{1}$$ -norm constraints. [ABSTRACT FROM AUTHOR]

Ø The KRSL based adaptive filtering algorithm with sinusoidal signal is derived; Ø A recursive MKRSL based harmonic estimation method is developed; Ø A RMKRSL with adaptive gain factor is proposed to enhance the tracking ability. The development of effective harmonics estimation method plays a crucial role for safe operation of power system. Recently several existing parametric estimation approaches, however, are mainly developed and discussed under the assumption of Gaussian noise which is always unsuitable in real power systems. This work is mainly concerned with the robust parametric estimation methods. The kernel risk sensitive loss (KRSL) shows an advantage in that its performance surface is flat around the optimal solution while sharp far away from the optimal solution and it may exhibit outstanding performance in terms of faster convergence rate and higher estimation accuracy under non-Gaussian noise cases. Therefore, a minimum KRSL (MKRSL) algorithm with sinusoidal signal is designed, and we further develop a novel recursive MKRSL (RMKRSL) algorithm for harmonics estimation in non-Gaussian noise cases. In addition, an adaptive gain factor is introduced into the gain matrix of RMKRSL algorithm to enhance its tracking capability. Some simulations by using the signal generated from the given models and IEEE-1159-PQE databases are conducted to illustrate the performance of the proposed methods under different conditions. [ABSTRACT FROM AUTHOR]

The response of underwater structures to a near-field explosion is coupled with the dynamics of the explosion bubble and the surrounding water. This multiphase fluid–structure interaction process is investigated in the paper using a two-dimensional model problem that features the yielding and collapse of a thin-walled aluminum cylinder. A recently developed computational framework that couples a finite volume compressible fluid dynamics solver with a finite element structural dynamics solver is employed. The fluid–structure and liquid–gas interfaces are tracked using embedded boundary and level set methods. The conservation of mass and momentum across the interfaces is enforced by solving one-dimensional bimaterial Riemann problems. The initial pressure inside the explosion bubble is varied by two orders of magnitude in different test cases. Three different modes of collapse are discovered, including an horizontal collapse (i.e. with one lobe extending towards the explosive charge) that appears counterintuitive, yet has been observed in previous laboratory experiments. Because of the transition of modes, the time it takes for the structure to reach self-contact does not decrease monotonically as the explosion magnitude increases. The fluid pressure and velocity fields, the bubble dynamics, and the transient structural deformation are visualized to elucidate the cause of each collapse mode and the mode transitions. The result suggests that, in addition to the incident shock wave, the second pressure pulse resulting from the contraction of the explosion bubble also has significant effect on the structure's collapse. The phase difference between the structural vibration and the bubble's expansion and contraction influences the structure's mode of collapse. Furthermore, the transient structural deformation has clear effect on the bubble dynamics, leading to a two-way interaction. A counter-jet that points away from the structural surface is observed. Compared to the liquid jets produced by bubbles collapsing near a rigid wall, this counter-jet is in the opposite direction. • Three different modes of structural collapse are discovered. • At relatively low magnitude, the cylinder collapses in a counter-intuitive mode. • Time to collapse does not decrease monotonically as explosion magnitude increases. • Two-way interaction between bubble and structural dynamics is analyzed. [ABSTRACT FROM AUTHOR]

The export flux of particulate organic carbon (POC) consumes upwelled dissolved inorganic carbon (DIC), which hinders surplus CO being released to the atmosphere. The export flux of POC is therefore crucial to the carbon and biogeochemical cycles. This study aims to model the long-term (1958-2009) variation of export flux and structure of the biological pump in the South China Sea (SCS) using a three-dimensional physical-biogeochemical coupled (ROMS-CoSiNE) model. The modeled POC export flux in the northeastern and north central SCS is high in winter and low in summer, whereas the flux in the central, southwestern and southern SCS varies following a 'W' shape: two maxima in winter and summer, and two minima in spring and autumn. The pattern follows the variation of the East Asian monsoon and is consistent with observations. On the interannual scale, export flux is anti-phased with the El Niño-Southern Oscillation such that El Niño (La Niña) conditions correspond to low (high) export flux. Modeled annual mean POC export flux reaches up to 1.95 mmol m day, which is underestimated comparing with field observations. The f-ratio is estimated to be ~0.4. The b value of the Martin equation for POC is 1.18±0.03. Remineralization rate of POC is greater than the classical Martin equation but is consistent with its subtropical counterparts. The modeled results indicate that the SCS is a weak source of atmospheric CO with a flux estimated at 1.0 mmol m day. The modeled results provide an insight of the temporal and spatial variability of the carbon cycle in this monsoon-driven, semi-enclosed basin. [ABSTRACT FROM AUTHOR]

We present mid-Miocene (∼12.0–16.0 Ma) high-resolution (∼3.8 kyr) deep thermocline planktonic foraminiferal δ 18 O and δ 13 C records at IODP Site U1337 from the eastern equatorial Pacific. The benthic and planktonic δ 18 O records of Site U1337 have a similar long-term cooling trend, but display obvious amplitude differences of glacial/interglacial cycles after 13.9 Ma. Planktonic δ 18 O cycles are usually larger than 1.0‰, nearly 2 times those of the benthic δ 18 O. The post-13.9 Ma change is probably caused by intensified upwelling along with ocean cooling, but may include upper ocean circulation changes. Both the benthic and planktonic δ 13 C records at Site U1337 reveal marked 400-kyr carbon isotope cycles during the MMCO (Middle Miocene Climate Optimum) with a trend toward lower δ 13 C from 16.0 Ma to 12.0 Ma. The similarity in response between surface and deep carbon isotopes indicates that the mid-Miocene carbon excursions in the east equatorial Pacific involved the whole ocean basin water column and thus are a global signal. Box model simulations reveal that the long eccentricity (400 kyr) paced carbon inputs from weathering changed the burial ratio of carbonates to organic carbon and helped to produce the significant 400-kyr cycles in oceanic δ 13 C. The increased weathering of carbonate, silicate and kerogen rocks are the major factors controlling the long-term decrease in oceanic δ 13 C after 16.0 Ma. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon (DOC) is a carbon reservoir that is as large as the atmospheric CO pool, and its contribution to the global carbon cycle is gaining attention. As DOC is a dissolved tracer, its distribution can serve to trace the mixing of water masses and the pathways of ocean circulation. Published proxy and model reconstructions have revealed that, during the last glacial maximum (LGM), the pattern of deep ocean circulation differed from that of the modern ocean, whereby additional carbon is assumed to have been sequestered in stratified LGM deep water. The aim of this study is to explore the distribution of DOC and its production/removal rate during the LGM using the Grid ENabled Integrated Earth system model (GENIE). Modeled results reveal that increased salinity of bottom waters in the Southern Ocean is associated with stronger stratification and oxygen depletion. The stratified LGM deep ocean traps more nutrients, resulting in a decrease in the DOC reservoir size that, in turn, causes a negative feedback for carbon sequestration. This finding requires an increase in DOC lifetime to compensate for the negative feedback. The upper limit of DOC lifetime is assumed to be 20,000 years. Modeled results derive an increase (decrease) in DOC reservoir by 100 Pg C leading to an atmospheric CO decrease (increase) of 9.1 ppm and a dissolved inorganic carbon δC increase (decrease) of 0.06‰. The DOC removal rate is estimated to be 39.5 Tg C year in the deep sea during the LGM. The contribution of DOC to the LGM carbon cycle elucidates potential carbon sink-increasing strategies. [ABSTRACT FROM AUTHOR]

Background: States of depression are associated with increased sensitivity to negative events. For this novel study, we have assessed the relationship between the number of depressive episodes and the dysfunctional processing of emotional facial expressions. Methodology/Principal Findings: We used a visual emotional oddball paradigm to manipulate the processing of emotional information while event-related brain potentials were recorded in 45 patients with first episode major depression (F-MD), 40 patients with recurrent major depression (R-MD), and 46 healthy controls (HC). Compared with the HC group, F-MD patients had lower N170 amplitudes when identifying happy, neutral, and sad faces; R-MD patients had lower N170 amplitudes when identifying happy and neutral faces, but higher N170 amplitudes when identifying sad faces. F-MD patients had longer N170 latencies when identifying happy, neutral, and sad faces relative to the HC group, and R-MD patients had longer N170 latencies when identifying happy and neutral faces, but shorter N170 latencies when identifying sad faces compared with F-MD patients. Interestingly, a negative relationship was observed between N170 amplitude and the depressive severity score for identification of happy faces in R-MD patients while N170 amplitude was positively correlated with the depressive severity score for identification of sad faces in F-MD and R-MD patients. Additionally, the deficits of N170 amplitude for sad faces positively correlated with the number of depressive episodes in R-MD patients. Conclusion/Significance: These results provide new evidence that having more recurrent depressive episodes and serious depressive states are likely to aggravate the already abnormal processing of emotional facial expressions in patients with depression. Moreover, it further suggests that the impaired processing as indexed by N170 amplitude for positive face identification may be a potentially useful biomarker for predicting propagation of depression while N170 amplitude for negative face identification could be a potential biomarker for depression recurrence. [ABSTRACT FROM AUTHOR]