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This paper deals with the stabilization problem of memristive recurrent neural networks with inertial items, discrete delays, bounded and unbounded distributed delays. First, for inertial memristive recurrent neural networks (IMRNNs) with second-order derivatives of states, an appropriate variable substitution method is invoked to transfer IMRNNs into a first-order differential form. Then, based on nonsmooth analysis theory, several algebraic criteria are established for the global stabilizability of IMRNNs under proposed feedback control, where the cases with both bounded and unbounded distributed delays are successfully addressed. Finally, the theoretical results are illustrated via the numerical simulations. [ABSTRACT FROM AUTHOR]

Apatite has recently gained considerable attention, providing new insight into a wide range of geological processes, such as geochronology, magmatism, metasomatism and metallogenesis. Here, we investigate the U-Th/He dates, in situ major- and trace- element concentrations, and 87 Sr/ 86 Sr ratios of apatites in the dacite from the southwestern Okinawa Trough to constrain its eruption age and the petrogenesis. The U-Th/He dating of apatites indicates that the volcanic eruption that formed the dacite was no older than 0.28 Ma and that the eruption was related to the replenishment of mafic magma. Apatites are present in the dacite as inclusions within pyroxene phenocrysts and are protected them from the external melt environment; therefore, they should retain a reliable record of their original chemical composition. In addition, all the apatite grains are fluorapatites with F contents of 1.58–2.54 wt.% and Cl contents of 0.57–0.88 wt.%. These grains are enriched in REEs (∑REE = 3341–5527 ppm) with significant Eu anomalies (Eu/Eu ∗ = 0.20–0.24), low Sr/Y radios (0.20–0.35), high 87 Sr/ 86 Sr ratios (range from 0.70635 to 0.70697). Based on these characteristics, we propose that the dehydration of subducted slab released fluids into the overlying mantle wedge and triggered mantle melting, which produced primitive mafic magma with high Cl content. Then, the mafic magma ascended into the crust, which has low Cl concentrations and high 87 Sr/ 86 Sr ratios. The mixing of a mantle-derived basaltic magma and a crustal felsic magma in a shallow magma chamber diluted the Cl content and elevated the 87 Sr/ 86 Sr ratio, thus producing the parental magma of the dacite. When the magma chamber was replenished by mafic magma at approximately 0.28 Ma, the high temperature from the injection would have caused the felsic melt to move upward and finally erupt. [ABSTRACT FROM AUTHOR]

This paper discusses impulsive synchronization of stochastic reaction–diffusion neural networks with Dirichlet boundary conditions and hybrid time delays. By virtue of inequality techniques, theories of stochastic analysis, linear matrix inequalities, and the contradiction method, sufficient criteria are proposed to ensure exponential synchronization of the addressed stochastic reaction–diffusion neural networks with mixed time delays via a designed impulsive controller. Compared with some recent studies, the neural network models herein are more general, some restrictions are relaxed, and the obtained conditions enhance and generalize some published ones. Finally, two numerical simulations are performed to substantiate the validity and merits of the developed theoretical analysis. [ABSTRACT FROM AUTHOR]

A series of novel isatin‐coumarin derivatives tethered through ethylene were designed, synthesized, and evaluated for their in vitro antimycobacterial activities against Mycobacterium tuberculosis (MTB) H37Rv and multidrug‐resistant tuberculosis (MDR‐TB). All hybrids exhibited potential antimycobacterial activities against MTB H37Rv and MDR‐TB with minimum inhibitory concentration (MIC) ranging from 32 to 256 μg/mL. In particular, the hybrid 4h (MIC: 50 and 32 μg/mL) was most active against MTB H37Rv and MDR‐TB strains, which was 2 and >4 folds more potent than the first‐line antitubercular agents rifampicin (MIC: 64 μg/mL) and isoniazid (MIC: >128 μg/mL) against MDR‐TB, warrant further optimization. [ABSTRACT FROM AUTHOR]

Hydrothermal precipitates and hydrothermal alteration products could record important information about temporal variations of seafloor hydrothermal systems. Geochemistry, mineralogy, and microscopic features of three pumice samples (T3-1, T3-2, and T3-3) near the Iheya North hydrothermal field were analyzed in this article. The results show that T3-3 sample has undergone at least two-stage influences by hydrothermal fluids. In the first stage, pure amorphous silica from hydrothermal fluid precipitated in the vesicles of all three T3 samples as a result of conductive cooling and fluid-seawater mixing. The precipitation temperatures according to oxygen isotope thermometer are approximately 13-21°C. In the second stage, T3-3 pumice underwent low-temperature hydrothermal alteration, during which the amorphous silica precipitates were redissolved, together resulting in losses of FeO and SiO2 and gains of MgO, Pb, Zn, and Cu. Furthermore, ferruginous filamentous silica, which might be related to activities of Fe-oxidizing bacteria, was formed in the altered pumice. The transformation from pure amorphous silica precipitation to redissolution of the silica in T3-3 pumice might indicate a rise of temperature and/or decrease in silica concentrations in hydrothermal fluids, implying a changing hydrothermal environment. [ABSTRACT FROM AUTHOR]

Studies on the concentrations of arsenic (As) and antimony (Sb) in seawater columns are very important for tracing hydrothermal plumes and understanding fluid characteristics of seafloor hydrothermal systems. The total As, Sb, Mn, and Cl− concentrations of three hydrothermal plume seawater column samples have been studied at Stations 18G, 18K, and 18B in the eastern Manus back-arc basin, Bismarck Sea, Papua New Guinea. At Stations 18G and 18K, the plumes above North Su and near the Suzette site in the SuSu Knolls hydrothermal field are both enriched in As, Sb, and Mn and depleted in Cl, as a result of contribution of As-Sb-Mn-enriched and Cl-depleted vent fluid outputs to the hydrothermal plume, which is most likely generated in the subseafloor by fluid-rock interaction, magma degassing, or phase separation (boiling of hydrothermal fluid). The plume at Station 18B is enriched in As, Sb, Mn, and Cl, suggesting that As-Sb-Mn-Cl-enriched fluid discharges from vents, which have been generated by fluid-rock interaction. The concentrations of As and Sb anomalous layers, like manganese (Mn), are higher than those of the other layers in the three hydrothermal plume seawater columns. As and Sb with Mn showed a positive correlation (R2>0.8, p<0.05), and the distributions of As and Sb within the hydrothermal plume are not controlled by particle adsorption or biogeochemical cycles, suggesting that As and Sb, like Mn, can be used to detect and describe the characteristics of hydrothermal plumes in seawater environment. In addition, anomalous layer with As/Sb ratio lower than those of ambient seawater at the same temperature is found in the eastern Manus basin, suggesting that the As/Sb ratio may also act as an effective tracer reflecting the effect of hydrothermal activity on As and Sb in the seawater column. [ABSTRACT FROM AUTHOR]

Studies of the major components of hydrothermal plumes in seafloor hydrothermal fields are critical for an improved understanding of biogeochemical cycles and the large-scale distribution of elements in the submarine environment. The composition of major components in hydrothermal plume water column samples from 25 stations has been investigated in the middle and southern Okinawa Trough. The physical and chemical properties of hydrothermal plume water in the Okinawa Trough have been affected by input of the Kuroshio current, and its influence on hydrothermal plume water from the southern Okinawa Trough to the middle Okinawa Trough is reduced. The anomalous layers of seawater in the hydrothermal plume water columns have higher K+, Ca2+, Mn2+, B3+, Ca2+/SO42-, and Mn2+/Mg2+ ratios and higher optical anomalies than other layers. The Mg2+, SO42-, Mg2+/Ca2+, and SO42-/Mn2+ ratios of the anomalous layers are lower than other layers in the hydrothermal plume water columns and are consistent with concentrations in hydrothermal vent fluids in the Okinawa Trough. This suggests that the chemical variations of hydrothermal plumes in the Tangyin hydrothermal field, like other hydrothermal fields, result in the discharge of high K+, Ca2+, and B3+ and low Mg2+ and SO42- fluid. Furthermore, element ratios (e.g., Sr2+/Ca2+, Ca2+/Cl−) in hydrothermal plume water columns were found to be similar to those in average seawater, indicating that Sr2+/Ca2+ and Ca2+/Cl− ratios of hydrothermal plumes might be useful proxies for chemical properties of seawater. The hydrothermal K+, Ca2+, Mn2+, and B3+ flux to seawater in the Okinawa Trough is about 2.62–873, 1.04–326, 1.30–76.4, and 0.293–34.7 × 106 kg per year, respectively. The heat flux is about 0.159–1,973 × 105 W, which means that roughly 0.0006% of ocean heat is supplied by seafloor hydrothermal plumes in the Okinawa Trough. [ABSTRACT FROM AUTHOR]

Along with the rapid development of miniaturization of mobile devices and wearable integrated electronics system, flexible integrated micro electrical energy storage devices with high-performance, deformability and cycling stability will be the technological trend for a long time in the future. In this work, template plasma etching method and electrochemical deposition method have been combined to fabricate nanoporous gold/manganese oxide interdigitated electrodes that can be easily utilized in flexible micro-supercapacitors(MSCs). These MSCs exhibit relatively high specific capacitance of 18.47 mF cm −2 in 0.5 M Na 2 SO 4 electrolyte and 11.58 mF cm −2 in polyvinyl alcohol (PVA)/LiCl solid state electrolyte. A high energy density of 6.93 × 10 −7 Wh cm −2 to 1.03 × 10 −6 Wh cm −2 while power density ranging from 4.63 × 10 −5  W cm −2 to 3.12 × 10 −4  W cm −2 . The NPG/MnO 2 MSCs excellent long term cycling stability of 80.7% can be seen even after cycling for 5000 times. Moreover, the MSCs devices also demonstrate a sound flexibility and a superior frequency response (1.25 ms). In addition, the effects of various finger width and finger spacing on performance are compared, the critical importance of adjusting interdigitated structure is highlighted. This present research may provide an innovative avenue for the new prospective high-performance flexible micro-supercapacitors. [ABSTRACT FROM AUTHOR]

A new general hybrid neural networks with inertial term and mixed time-varying delays are proposed here by using the memristors connections. Then by building appropriate Lyapunov functionals and inequality technique, some new conditions assuring the global exponential stability of the hybrid neural networks are derived. The circuit implementation of the proposed hybrid neural networks are also presented here. In addition, the new proposed results here enrich and extend the earlier publications on neural networks. Lastly, numerical simulations show the effectiveness of our results. [ABSTRACT FROM AUTHOR]

Injury of skeletal muscle, and particularly mechanically- induced damage, including contusion injury, frequently occurs in contact sports as well as in sports with accidental contact. Although the mechanisms of skeletal muscle regeneration are well understood, those involved in muscle contusion are not. A total of 40 male mice were randomly divided into control (n=8) and muscle contusion (n=32) groups. A muscle contusion model was established by weight-drop injury. Subsequently, the gastrocnemius muscles in the two groups were harvested at different times (1, 3, 7 and 14 days) post-injury. The changes in skeletal muscle morphology were assessed by hematoxylin and eosin (H&E) stains. Furthermore, quantitative polymerase chain reaction and western blotting were used to analyze inflammatory cytokines, oxidative stress factors and the Akt/mechanistic target of rapamycin (mTOR) pathway. The results revealed that pro-inflammatory cytokines [tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interferon-γ (IFN-γ)] increased significantly at day 1 and 3 and still exhibited high levels of expression at days 7 and 14 (except IL-6) post-injury. Additionally, the anti-inflammatory cytokine IL-10 increased significantly at 1, 3 and 7 days and reached its peak levels at 7 days post-injury. It was revealed that gp91phox mRNA increased significantly at all time points and gp91phox protein increased significantly at day 3 post-injury. Furthermore, it was observed that p-Akt/Akt increased significantly at 1 day post-injury. P-mTOR/mTOR increased significantly at day 1 and 7, and p-p70s6k/p70s6k and P-4EBP1/4EBP1 increased significantly at 1, 3, 7 and 14 days post-injury. These results Injury of skeletal muscle, and particularly mechanically- induced damage, including contusion injury, frequently occurs in contact sports as well as in sports with accidental contact. Although the mechanisms of skeletal muscle regeneration are well understood, those involved in muscle contusion are not. A total of 40 male mice were randomly divided into control (n=8) and muscle contusion (n=32) groups. A muscle contusion model was established by weight-drop injury. Subsequently, the gastrocnemius muscles in the two groups were harvested at different times (1, 3, 7 and 14 days) post-injury. The changes in skeletal muscle morphology were assessed by hematoxylin and eosin (H&E) stains. Furthermore, quantitative polymerase chain reaction and western blotting were used to analyze inflammatory cytokines, oxidative stress factors and the Akt/mechanistic target of rapamycin (mTOR) pathway. The results revealed that pro-inflammatory cytokines [tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interferon-γ (IFN-γ)] increased significantly at day 1 and 3 and still exhibited high levels of expression at days 7 and 14 (except IL-6) post-injury. Additionally, the anti-inflammatory cytokine IL-10 increased significantly at 1, 3 and 7 days and reached its peak levels at 7 days post-injury. It was revealed that gp91phox mRNA increased significantly at all time points and gp91phox protein increased significantly at day 3 post-injury. Furthermore, it was observed that p-Akt/Akt increased significantly at 1 day post-injury. P-mTOR/mTOR increased significantly at day 1 and 7, and p-p70s6k/p70s6k and P-4EBP1/4EBP1 increased significantly at 1, 3, 7 and 14 days post-injury. These results [ABSTRACT FROM AUTHOR]

Memristor is firstly postulated by Leon Chua and realized by Hewlett–Packard (HP) laboratory. Research results show that memristor can be used to simulate the synapses of neurons. This paper presents a class of recurrent neural network with HP memristors. Firstly, it shows that memristive recurrent neural network has more compound dynamics than the traditional recurrent neural network by simulations. Then it derives that n dimensional memristive recurrent neural network is composed of 2 2 n 2 sub neural networks which do not have a common equilibrium point. By designing the tracking controller, it can make memristive neural network being convergent to the desired sub neural network. At last, two numerical examples are given to verify the validity of our result. [ABSTRACT FROM AUTHOR]

Positive voltages and negative voltages are applied to adjust memristance in most memristive circuits. This paper presents a memristance changing circuit in which memristance is changed only by the positive voltage. A mathematical calculation method is proposed to analyze the memristance change approximately. Furthermore, memristance changing circuits are utilized as synapses to construct a neural network to imitate full-function Pavlov associative memory. Compared to the classical Pavlov associative memory, the full-function Pavlov associative memory contains additional food forgetting and ring forgetting processes. The forgetting processes will be triggered in the condition that either the food or the ring is given to the dog after the learning processes. The learning and forgetting time of the associative memory can be obtained by the proposed mathematical calculation method in advance approximately. [ABSTRACT FROM AUTHOR]

This paper is concerned with the global exponential dissipativity of memristive inertial neural networks with discrete and distributed time-varying delays. By constructing appropriate Lyapunov–Krasovskii functionals, some new sufficient conditions ensuring global exponential dissipativity of memristive inertial neural networks are derived. Moreover, the globally exponential attractive sets and positive invariant sets are also presented here. In addition, the new proposed results here complement and extend the earlier publications on conventional or memristive neural network dynamical systems. Finally, numerical simulations are given to illustrate the effectiveness of obtained results. [ABSTRACT FROM AUTHOR]

This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n -neuronal recurrent neural networks have exactly ( 4 k + 3 ) k 0 equilibria, ( 2 k + 2 ) k 0 of which are locally exponentially stable and the others are unstable, where k 0 is a nonnegative integer such that k 0 ≤ n . By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results. [ABSTRACT FROM AUTHOR]

In this paper, synchronization of stochastic reaction–diffusion neural networks with Dirichlet boundary conditions and unbounded discrete time-varying delays is investigated. By virtue of theories of partial differential equations, inequality methods, and stochastic analysis techniques, p th moment exponential synchronization and almost sure exponential synchronization of the underlying neural networks are developed. The obtained results in this study enhance and generalize some earlier ones. The effectiveness and merits of the theoretical criteria are substantiated by two numerical simulations. [ABSTRACT FROM AUTHOR]

This paper investigates a kind of switched discrete-time neural network. Such neural network is composed of multiple sub-networks and switched different sub-networks according to the states of neural network. There is no common equilibrium for all of sub-networks, i.e., multiple equilibria coexist. Firstly, a bounded condition is presented for the switched discrete-time neural network. And then sufficient conditions are derived to ensure region stability of the equilibrium points of such neural network by mathematical analysis and nonsingular M-matrix theory. Four examples are presented to verify the validity of our results. [ABSTRACT FROM AUTHOR]

In this paper, coexistence and stability of multiple equilibrium points of fractional-order recurrent neural networks are addressed. Several sufficient conditions are derived for ascertaining the existence of \prod i=1^{n(2Ki+1)} equilibrium points ( Ki\geq 0 ) and the local Mittag–Leffler stability of \prod i=1^{n(Ki+1)} equilibrium points of them by using the geometrical properties of activation functions and algebraic properties of nonsingular M -matrix. In contrast with many existing results, the derived results cover both mono-stability and multistability, and the activation functions herein could be nonmonotonic and nonlinear in any open interval. In addition, three numerical examples are elaborated to substantiate the efficacy and characteristics of the theoretical results. [ABSTRACT FROM AUTHOR]

This special issue presents robust, explainable, and efficient next-generation deep learning algorithms with data privacy and theoretical guarantees will improve the understanding and explainability of deep neural networks; improve the accuracy of deep learning leveraging new stochastic optimization and neural architecture search; and increase the computational efficiency and stability of the deep learning training process with new algorithms that will scale. [ABSTRACT FROM AUTHOR]

Sn 1−x S-CdS superlattice nanowires (NWs) with fast response and good selectivity in low-temperature operating environments for potential applications as gas sensing materials, were designed rationally and synthesized controllably. This work investigated in detail the dual selective gas sensing performance of Sn 1−x S-CdS superlattice nanowires that crystal facets change with the tunable composition. The results demonstrated that the Sn 0.38 S-CdS superlattice NWs with the structure of (0 0 4) lattice plane of SnS growing epitaxially along the [0 0 2] crystallization direction of CdS. And the gas sensors based on Sn 0.38 S-CdS superlattice NWs displayed the best gas sensing properties, including ultrafast response to acetone with 1 s at 290 °C, and good selectivity to H 2 S with selectivity value of 29886% at 190 °C. The gas sensing mechanism was carefully investigated by the chemical stability of gas molecules and the adsorption energy on the different crystal planes, as well as the energy band structure of the heterostructure. The study highlights an efficient rout to the development of high-performance multi-functional gas sensors. • High qualitive Sn 1-x S-CdS superlattice NWs were controllably synthesized via a facile CVD process. • The gas sensors based on Sn 1-x S-CdS superlattice NWs exhibited temperature dependent dual selectivity detection ability, ultrafast response to acetone with 1 s at 290 °C, and excellent selectivity to H2S with selectivity value of 29886 % at 190 °C. • The DFT calculation and experimental characterization reveals its gas sensing mechanism, the adsorption energy on the different crystal plane and chemical stability of the gas molecules, as well as the energy band structure of heterostructure determined how sensitive they are to gas. [ABSTRACT FROM AUTHOR]

This paper investigates the finite/fixed-time synchronization problem of delayed inertial memristive neural networks (DIMNNs) using interval matrix-based methods within a unified control framework. By employing set-valued mapping and differential inclusion theory, two distinct methods are applied to handle the switching behavior of memristor parameters: the maximum absolute value method and the interval matrix method. Based on these different approaches, two control strategies are proposed to select appropriate control parameters, enabling the system to achieve finite and fixed-time synchronization, respectively. Additionally, the resulting theoretical criteria differ based on the chosen control strategy, with one expressed in algebraic form and the other in the form of linear matrix inequalities (LMIs). Numerical simulations demonstrate that the interval matrix method outperforms the maximum absolute value method in terms of handling memristor parameter switching, achieving faster finite/fixed-time synchronization. Furthermore, the theoretical results are extended to the field of image encryption, where the response system is utilized for decryption and expanding the keyspace. • Inertial memristive neural networks (IMNNs) employ two methods to manage switching behaviors: maximum absolute value and interval matrix. • Controllers based on these methods yield distinct theorems: one in algebraic form and the other in the form of linear matrix inequalities (LMIs). • Simulation shows Theorem 2 (interval matrix) yields faster synchronization convergence than Theorem 1 (maximum absolute value), and the findings are also applicable to image encryption. [ABSTRACT FROM AUTHOR]

Since the fixed-time stability forms of nonlinear systems satisfy strict conditions, there are few general forms for nonlinear systems to achieve fixed-time stability. This work proposes a new class of more general fixed-time stability criteria. It is worth mentioning that, compared with the traditional method of estimating the convergence time, this paper obtains a more conservative stable time estimation formula through the integration method of the generalized integral mean theorem. In addition, given that the fixed-time stabilization of neural networks and chaotic oscillators have attracted extensive attention in recent years, and there are still many fixed-time stabilizations of nonlinear systems that have not been studied. Therefore, a discontinuous controller is designed in this paper. The above stability theory results are applied to the fixed-time stabilization of the Takagi-Sugeno (T-S) fuzzy competitive neural network and chaotic system (coupled Chua's oscillator). Finally, the validity and applicability of the theoretical results are verified by examples. [ABSTRACT FROM AUTHOR]

Studies of the chemical characteristics of mussels and clams in seafloor hydrothermal fields are important for understanding mass fluxes and elemental partitioning from hydrothermal vents into the biosphere, metal bioaccumulation of seafloor hydrothermal ecosystems, and the sources and sinks of biogeochemical and fluid cycles. We are the first to measure the mineral, major, trace and rare earth element, and carbon and oxygen isotope compositions of mussels ( Bathymodiolus platifrons ) and clams ( Conchocele bisecta ) from the Tangyin and Yonaguni Knoll IV hydrothermal fields in the southwestern Okinawa Trough. Mineralogical analysis shows that the carbonate shells of the mussel and clam samples are mainly composed of calcite and aragonite. Metal elements exhibit linear correlations in the shells (e.g., V and U) and tissues (e.g., Li and Rb) of the mussels and clams, suggesting that not all positive correlations of elements in tissues are inherited by the shells. V/As, Ca/Sr, and Fe/Cr ratios in the mussels and clams are close to those in the seawater, indicating that element ratios of seawater might be inherited by the mussels and clams. In addition, the Fe/Cr ratio of the shells of both mussels and clams can be used to trace the local seawater composition. The total LREE concentrations of mussel and clam tissue samples are higher than those of the mussel and clam shell samples, are similar to the hydrothermal fluids, exhibit LREE enrichment (La CN /Nd CN ratios = 1.86-32.1), and no or only slightly negative Eu anomalies, indicating that benthic animals are a sink of LREEs from hydrothermal fluids, and that the Eu/Eu* ratios of fluids change when fluids are incorporated into the tissues of the mussels and clams. In addition, the δ 13 C values of mussel shell samples are heavier than those of the clam shell samples in the hydrothermal field, indicating that more than one carbon source may be involved in defining the δ 13 C compositions of the shells. The majority of the δ 18 O values of clam shell samples fall in the range of δ 18 O values of the mussel shell samples, and are close to the hydrothermal fluid δ 18 O H2O values, implying that the δ 18 O values of mussel and clam shell carbonate is influenced by the hydrothermal environment (magmatic water and fluid dilution with seawater). [ABSTRACT FROM AUTHOR]

Studies of sulfur and lead isotopic compositions in hydrothermal deposits are an important tool to determine the source and processes of both sulfur and lead, and to understand the origin of hydrothermal ore deposits. Here, the sulfur and lead isotopic compositions of sulfide minerals have been studied for different hydrothermal fields in the East Pacific Rise (EPR), Mid-Atlantic Ridge (MAR), Central Indian Ridge (CIR), Southwest Indian Ridge (SWIR), and North Fiji Basin (NFB). The sulfur isotopic compositions of the studied sulfide samples are variable (δ 34 S 0.0 to 9.6‰, avg. δ 34 S 4.7‰; n = 60), being close to the associated igneous rocks (~ 0‰ for, e.g., basalt, serpentinized peridotite), which may reflect the S in the sulfide samples is derived mainly from the associated igneous rocks, and a relatively small proportion (< 36%) of seawater sulfur incorporated into these sulfides during mixing between seawater (δ 34 S 21‰) and hydrothermal fluid. In contrast for a mixed origin for the source of S, the majority of the lead isotopic compositions ( 206 Pb/ 204 Pb 17.541 ± 0.004 to 19.268 ± 0.001, 207 Pb/ 204 Pb 15.451 ± 0.001 to 15.684 ± 0.001, 208 Pb/ 204 Pb 37.557 ± 0.008 to 38.988 ± 0.002, n = 21) of the sulfides possess a basaltic Pb isotopic composition, suggesting that the lead in the massive sulfide is mainly leached from local basaltic rocks that host the sub-seafloor hydrothermal systems in sediment-free mid-ocean ridges and mature back-arc basins. Furthermore, sulfide minerals in the super-fast and fast spreading mid-ocean ridges (MORs) exhibit less spread in their the δ 34 S values compared to sulfides from super-slow, and slow spreading MORs, which is most easily explained as a lesser degree of fluid-rock interaction and hydrothermal fluid-seawater mixing during hydrothermal ore-forming process. Additionally, the S and Pb isotope compositions of sulfides are controlled by the fluid processes for forming seafloor massive sulfide deposits. We demonstrate that the variable sulfur and lead isotopic compositions exhibit a relationship with the sulfur and lead sources, fluid–rock interaction, and fluid–seawater mixing. [ABSTRACT FROM AUTHOR]

This paper addresses the controller design problem for global fixed-time synchronization of delayed neural networks (DNNs) with discontinuous activations. To solve this problem, adaptive control and state feedback control laws are designed. Then based on the two controllers and two lemmas, the error system is proved to be globally asymptotically stable and even fixed-time stable. Moreover, some sufficient and easy checked conditions are derived to guarantee the global synchronization of drive and response systems in fixed time. It is noted that the settling time functional for fixed-time synchronization is independent on initial conditions. Our fixed-time synchronization results contain the finite-time results as the special cases by choosing different values of the two controllers. Finally, theoretical results are supported by numerical simulations. [ABSTRACT FROM AUTHOR]

In conventional time series prediction techniques, uncertainty associated with predictions are usually ignored. Probabilistic predictors, on the other hand, can measure the uncertainty in predictions, to provide better supports for decision-making processes. A dynamic probabilistic predictor, named as echo state mean-variance estimation (ESMVE) model, is proposed. The model is constructed with two recurrent neural networks. These networks are trained into a mean estimator and a variance estimator respectively, following the algorithm of echo state networks. ESMVE generate point predictions by estimating the means of a target time series, while it also measures the uncertainty in its predictions by generating variance estimations. Experiments conducted on synthetic data sets show advantages of ESMVE over MVE models constructed with static networks. Effectiveness of ESMVE in real world prediction tasks have also been verified in our case studies. [ABSTRACT FROM AUTHOR]

In this paper, the periodic dynamics have been studied for a general kind of memristor-based neural networks with leakage and time-varying delays. Some new sufficient conditions have been derived ensuring that the existence, uniqueness and globally exponential stability of the periodic solution for the neural network by using differential inclusions theory, the topological degree theory in set-valued analysis and Lyapunov function technique and so on. As a special case, we have shown that the existence, uniqueness and global exponential stability of equilibrium point for the autonomous neural networks with leakage delays. [ABSTRACT FROM AUTHOR]

This paper addresses the complete stability of delayed recurrent neural networks with Gaussian activation functions. By means of the geometrical properties of Gaussian function and algebraic properties of nonsingular M -matrix, some sufficient conditions are obtained to ensure that for an n -neuron neural network, there are exactly 3 k equilibrium points with 0 ≤ k ≤ n , among which 2 k and 3 k − 2 k equilibrium points are locally exponentially stable and unstable, respectively. Moreover, it concludes that all the states converge to one of the equilibrium points; i.e., the neural networks are completely stable. The derived conditions herein can be easily tested. Finally, a numerical example is given to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with a class of recurrent neural networks (RNNs) with nonincreasing activation function. First, based on the fixed point theorem, it is shown that under some conditions, such an n -dimensional neural network with nondecreasing activation function can have at least ( 4 k + 3 ) n equilibrium points. Then, it proves that there is only ( 4 k + 3 ) n equilibria under some conditions, among which ( 2 k + 2 ) n equilibria are locally stable. Besides, by analysis and study of RNNs with nondecreasing activation function, we can also obtain the same number of equilibria for RNNs with nonincreasing activation function. Finally, two simulation examples are given to show effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a general class of fuzzy neurodynamic systems with piecewise constant argument of generalized type. Meanwhile, the time-varying input is under consideration. The pseudo-equilibria of this new type of neurodynamic systems is formulated and studied. Several sufficient conditions are obtained to ensure the existence and uniqueness of solutions. In addition, the global output convergence of such neurodynamic system is examined in detail. Several simulation examples are also given to verify the effectiveness of theoretical property and a potential application in analog associative memory. [ABSTRACT FROM PUBLISHER]

In this paper, stability for a class of uncertain switched neural networks with time-varying delay is investigated. By exploring the mode-dependent properties of each subsystem, all the subsystems are categorized into stable and unstable ones. Based on Lyapunov-like function method and average dwell time technique, some delay-dependent sufficient conditions are derived to guarantee the exponential stability of considered uncertain switched neural networks. Compared with general results, our proposed approach distinguishes the stable and unstable subsystems rather than viewing all subsystems as being stable, thus getting less conservative criteria. Finally, two numerical examples are provided to show the validity and the advantages of the obtained results. [ABSTRACT FROM AUTHOR]

With the rapid development of wearable and portable electronics, the demand for all-solid-state flexible energy storage devices with high performance, long-term cycling stability and bending stability has been aroused. Physical and chemical method for preparing thin-film materials has enabled planar flexible supercapacitors (SCs) to be fabricated for a variety of applications. In this work, we report on the facile fabrication of an all-solid-state flexible interdigitated supercapacitor with a convenient and efficient two-step method. 3-D nanostructured α-MnO 2 has been prepared on the surface of interdigitated Pt metal pattern on polyethylene terephthalate (PET) substrate as high-performance electrode material via in-situ catalytic solution route without any assistance of template or surfactant. The SCs are fabricated with PVA/H 3 PO 4 as solid-state electrolyte, which exhibited good electrochemical performance with areal capacitance as much as 20 mF cm −2 at a scan rate of 10 mV s −1 , relatively high energy density (3.6 × 10 −7 Wh cm −2 –1.9 × 10 −6 Wh cm −2 ) and power density (9 × 10 −5 W cm −2 –1.6 × 10 −4 W cm −2 ), and excellent long-term cycling stability with capacitance retention of 82.2% (10,000 times charge and discharge), and bending stability with capacitance retention of 89.6%. [ABSTRACT FROM AUTHOR]

This paper investigates new criteria of the robust $$H_\infty $$ stability for a class of uncertain stochastic fuzzy mixed-delay systems with nonlinear noise disturbances by employing an improved free-weighting matrix approach. The fuzzy system is based on the Takagi-Sugeno model that is often used to represent the complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning. To reflect more realistic dynamical behaviors of the system, both the parameter uncertainties and stochastic disturbances are considered, the stochastic disturbances are given in the form of a Brownian motion. The mixed delays comprise both discrete and distributed time-varying delays. In terms of a stochastic fuzzy Lyapunov functional, a sufficient criterion is proposed to investigate dynamical behaviors of the system in the mean-square sense with an $$H_\infty $$ performance index. [ABSTRACT FROM AUTHOR]

Complexity of analysis of landslide hazard is due to uncertainty. In this study, a novel approach multi-gene genetic programming based on separable functional network (MGGPSFN) is presented for predicting landslide displacement. Moreover, Pearson's cross-correlation coefficients and mutual information are adopted to look for the potential input variables for a forecast model in the paper. The performance of new model is verified through one case study in Baishuihe landslide in the Three Gorges Reservoir in China. In addition, we compared it with two methods, back-propagation neural network and radial basis function, and MGGPSFN got the best results in the same measurements. [ABSTRACT FROM AUTHOR]

This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of ( 2 K + 1 ) n equilibrium points and the exponential stability of ( K + 1 ) n equilibrium points among them for n -neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

The Pt nano-film Schottky diodes on Ge substrate have been fabricated to investigate the effect of annealing temperature on the characteristics of the device. The germanide phase between Pt nano-films and Ge substrate changed and generated interface layer PtGe at 573 K and 673 K, Pt 2 Ge 3 at 773 K. The current–voltage( I - V ) characteristics of Pt/n-Ge Schottky diodes were measured in the temperature range of 183–303 K. Evaluation of the I - V data has revealed an increase of zero-bias barrier height Φ B 0 but the decrease of ideality factor n with the increase in temperature. Such behaviors have been successfully modeled on the basis of the thermionic emission mechanism by assuming the presence of Gaussian distributions. The variation of electronic transport properties of these Schottky diodes has been inferred to be attributed to combined effects of interfacial reaction and phase transformation during the annealing process. Therefore, the control of Schottky barrier height at metal/Ge interface is important to realize high performance Ge-based CMOS devices. [ABSTRACT FROM AUTHOR]

This paper discusses a kind of discrete-time recurrent neural network with discontinuous activation functions. The theory of difference inclusion is introduced to model discrete-time neural network with discontinuous activation functions. By redefining the equilibrium point of discrete-time recurrent neural network with discontinuous activation functions and then using induction principle, sufficient conditions are derived to ensure global asymptotical stability of the equilibrium points of such neural network. Three examples are presented to verify the validity of our results. [ABSTRACT FROM AUTHOR]

This paper presents new theoretical results on the multistability analysis of a class of recurrent neural networks with nonmonotonic activation functions and mixed time delays. Several sufficient conditions are derived for ascertaining the existence of 3^n equilibrium points and the exponential stability of 2^n equilibrium points via state space partition by using the geometrical properties of activation functions and algebraic properties of nonsingular M -matrix. Compared with existing results, the conditions herein are much more computable with one order less linear matrix inequalities. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of the 2^n equilibrium points can be larger than their originally partitioned subspaces. Three numerical examples are elaborated with typical nonmonotonic activation functions to substantiate the efficacy and characteristics of the theoretical results. [ABSTRACT FROM PUBLISHER]

In this paper, stabilization control of fractional-order bidirectional associative memory neural networks is formulated and studied. By estimating Mittag-Leffler function and some novel analysis techniques of fractional calculation, a generalized Gronwall-like inequality of Caputo fractional derivative is established. Then by applying Lyapunov approach, linear state feedback control law and partial state feedback control law are presented to stabilize the fractional-order bidirectional associative memory neural networks. This analysis framework can be applied to closed-loop control of fractional-order systems. A numerical example is given to show the effectiveness of the derived results via computer simulations. [ABSTRACT FROM AUTHOR]

Unpredictable meteorological information, especially that endangers flight safety, should be transmitted to a cockpit to make a flight crew obtain meteorological early warning that affects flight safety as soon as possible and adopt countermeasures, thereby avoiding the occurrence of flight safety accidents. At present, there are limited ways of transmitting meteorological information to a cockpit, and the application of Automatic Dependent Surveiilance-Broadcast (ADS-B) is a new way of transmitting meteorological information to a cockpit. [ABSTRACT FROM AUTHOR]

We show that the ω -periodic fractional-order fuzzy neural networks cannot generate non-constant ω -periodic signals. In addition, several sufficient conditions are obtained to ascertain the boundedness and global Mittag-Leffler stability of fractional-order fuzzy neural networks. Furthermore, S -asymptotical ω -periodicity and global asymptotical ω -periodicity of fractional-order fuzzy neural networks is also characterized. The obtained criteria improve and extend the existing related results. To illustrate and compare the theoretical criteria, some numerical examples with simulation results are discussed in detail. [ABSTRACT FROM AUTHOR]

This paper studies synchronization problems of complex dynamical network with mixed coupling via impulsive control. The model involves both advanced and delayed arguments, and the problem of the existence of the model is analyzed. Based on the stability theory for impulsive differential equations, an effective impulsive control scheme is proposed to achieve synchronization for complex dynamical networks. Finally, an example with numerical simulations is given to illustrate our results. [ABSTRACT FROM AUTHOR]

Memristive neurodynamic systems find many potential applications in mixed analog-digital multichip neurogrid and integrated photo-supercapacitor nanotube arrays. Analysis and design of memristive neurodynamic systems have attracted a large amount of research interest. In this study, some new neurodynamic approaches are proposed for stability analysis of delayed memristive neural networks. Some less conservative stability criteria are established by considering the memristor multiport effect, which is ignored in the previous literature. Numerical examples are given to demonstrate the effectiveness of these stability criteria. [ABSTRACT FROM AUTHOR]

Studies of noble gases in seafloor sulfide deposits are an important tool for understanding the origin of ore-forming fluids, both enabling the determination of noble gas sources and revealing the degree of fluid–rock interaction and mantle degassing. The noble gas concentrations and isotopic compositions of 27 sulfide, 3 sulfate, and 2 opal mineral aggregate samples have been studied in different hydrothermal fields from the East Pacific Rise, Mid-Atlantic Ridge, Central Indian Ridge, Southwest Indian Ridge, and North Fiji Back-Arc Basin. The helium concentrations and isotopic ratios in the sulfide aggregate samples are variable ( 4 He 0.12 to 22 × 10 − 8 cm 3 STP/g; 3 He/ 4 He ~ 0.6 to 10.4 R a ), and most of the sulfide helium concentrations are higher than those in the opal mineral samples ( 4 He 0.017 and 0.028 × 10 − 8 cm 3 STP/g), suggesting that the low-temperature fluids have lost their mantle helium during cooling. The helium of high (> 7 Ra), medium (1–7 Ra), and low (≈ 1 Ra) 3 He/ 4 He ratio samples is derived mainly from the MORB or OIB mantle by magma degassing, from mixing between hydrothermal fluid and seawater during ore-forming processes, and from ambient seawater, respectively. The high 3 He/ 4 He ratios (> 7 Ra) of sulfides imply that high-temperature sulfides retain the helium isotopic compositions of the primary hydrothermal fluid, whereas low-temperature sulfides, sulfates, and opal minerals do not. The neon, argon, krypton, and xenon concentrations in the sulfide aggregate samples are also variable; in most of the sulfide aggregates, they are significantly lower than in the sulfate and opal mineral samples. It is known that barite and opal minerals are characteristic of low-temperature (< 200 °C) paragenetic associations, indicating that heavier noble gases (Ne, Ar, Kr and Xe) are enriched under low-temperature conditions. Most of the sulfide, sulfate and opal mineral aggregate samples possess heavy noble gas elemental abundances similar to those of air-saturated seawater and Ne, Ar, and Xe isotopic compositions that span narrow ranges around atmospheric values, an observation which is most easily explained by the dominance of a seawater-derived component. In addition, based on the calculated helium/heat ratios, global helium and heat fluxes to high-temperature hydrothermal vents are approximately 0.05–6 × 10 4 kg per year and 0.1–12 × 10 12 W, meaning that roughly 0.3% of ocean heat is supplied by seafloor high-temperature hydrothermal activity. [ABSTRACT FROM AUTHOR]