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Aiming at the dissemination of malicious information on online social networks, this paper proposes a new positive–negative information propagation model that incorporates the conformist psychological factors of communicators during the dissemination process. Firstly, the local and global stability of information-free equilibrium is analyzed and three types of information-spread equilibria are obtained. The persistence of information spreading is expounded in detail. Secondly, two different control strategies are designed to suppress the spread of negative information on online social networks. One is the real-time optimal control with minimal control cost that enables the negative information to be effectively controlled in the expected time by executing two collaborative intervention methods, and the other is the event-triggered impulsive control, in which the control instant is determined by an event-triggered function. Finally, the above theoretical results are verified by some numerical simulations and a practical example. [ABSTRACT FROM AUTHOR]

Motivated by the self-pursuit of controlled objects, we consider the exact controllability of a linear mean-field type game-based control system (MF-GBCS, for short) generated by a linear-quadratic (LQ, for short) Nash game. A Gram-type criterion for the general time-varying coefficients case and a Kalman-type criterion for the special time-invariant coefficients case are obtained. At the same time, the equivalence between the exact controllability of this MF-GBCS and the exact observability of a dual system is established. Moreover, an admissible control that can steer the state from any initial vector to any terminal random variable is constructed in closed form. [ABSTRACT FROM AUTHOR]

In this work, we focus on an infinite horizon mean-field linear-quadratic stochastic control problem with jumps. Firstly, the infinite horizon linear mean-field stochastic differential equations and backward stochastic differential equations with jumps are studied to support the research of the control problem. The global integrability properties of their solution processes are studied by introducing a kind of so-called dissipation conditions suitable for the systems involving the mean-field terms and jumps. For the control problem, we conclude a sufficient and necessary condition of open-loop optimal control by the variational approach. Besides, a kind of infinite horizon fully coupled linear mean-field forward-backward stochastic differential equations with jumps is studied by using the method of continuation. Such a research makes the characterization of the open-loop optimal controls more straightforward and complete. [ABSTRACT FROM AUTHOR]

Accurate monitoring of urban waterlogging contributes to the city's normal operation and the safety of residents' daily travel. However, due to feedback delays or high costs, existing methods make large-scale, fine-grained waterlogging monitoring impossible. A common method is to forecast the city's global waterlogging status using its partial waterlogging data. This method has two challenges: first, existing predictive algorithms are either driven by knowledge or data alone; and second, the partial waterlogging data is not collected selectively, resulting in poor predictions. To overcome the aforementioned challenges, this paper proposes a framework for large-scale and fine-grained spatiotemporal waterlogging monitoring based on the opportunistic sensing of limited bus routes. This framework follows the Sparse Crowdsensing and mainly comprises a pair of iterative predictor and selector. The predictor uses the collected waterlogging status and the predicted status of the uncollected area to train the graph convolutional neural network. It combines both knowledge-driven and data-driven approaches and can be used to forecast waterlogging status in all regions for the upcoming term. The selector consists of a two-stage selection procedure that can select valuable bus routes while satisfying budget constraints. The experimental results on real waterlogging and bus routes in Shenzhen show that the proposed framework could easily perform urban waterlogging monitoring with low cost, high accuracy, wide coverage, and fine granularity. [ABSTRACT FROM AUTHOR]

As an important part of modern transportation, smart rail system need to handle a large number of delay-sensitive and task-intensive tasks in a high-speed mobile state. However, high-speed mobility challenges the traditional information processing modes a lot, such as service interruptions and information congestion. In order to solve these problems, we proposed a service migration strategy based on intelligent agent group cooperative prediction combined with edge computing service migration technology. The aim is to reduce system latency and overhead and ensure service continuity. Firstly, we constructed a cloud-edge-end collaborative scheduling network architecture model for distributed smart rail system is constructed, integrating mobility management and business orchestration to provide effective support for intelligent decision-making. Then we proposed an intelligent grouping collaborative migration strategy by consolidating resources for similar or identical tasks and employing a group negotiation mechanism, where the migration process is divided into four steps: detection, interaction, coordination and execution. Finally, a deep reinforcement learning algorithm is utilized to train multi-agent models for group collaborative prediction in edge migration strategies. The strategy dynamically adjusts task migration between edge nodes and the cloud based on real-time system status and task requirements to optimize its performance. Experimental results show that the proposed architecture and algorithm can effectively reduce total task delay and system overhead. Instead it can guarantee migration rate for task-intensive requirements, and effectively improve the reliability, effectiveness, and safety of smart rail system services. The present study lays a foundation for the future researches on applications of smart rail system. [ABSTRACT FROM AUTHOR]

Glial fibrillary acidic protein (GFAP) in serum has been shown as a biomarker of traumatic brain injury (TBI) which is a significant global public health concern. Accurate and rapid detection of serum GFAP is critical for TBI diagnosis. In this study, a time-resolved fluorescence immunochromatographic test strip (TRFIS) was proposed for the quantitative detection of serum GFAP. This TRFIS possessed excellent linearity ranging from 0.05 to 2.5 ng/mL for the detection of serum GFAP and displayed good linearity (Y = 598723X + 797198, R2 = 0.99), with the lowest detection limit of 16 pg/mL. This TRFIS allowed for quantitative detection of serum GFAP within 15 min and showed high specificity. The intra-batch coefficient of variation (CV) and the inter-batch CV were both < 4.0%. Additionally, this TRFIS was applied to detect GFAP in the serum samples from healthy donors and patients with cerebral hemorrhage, and the results of TRFIS could efficiently discern the patients with cerebral hemorrhage from the healthy donors. Our developed TRFIS has the characteristics of high sensitivity, high accuracy, and a wide linear range and is suitable for rapid and quantitative determination of serum GFAP on-site. [ABSTRACT FROM AUTHOR]

Urine retinol-binding protein 4 (RBP4) has recently been reported as a novel earlier biomarker of chronic kidney disease (CKD) which is a global public health problem with high morbidity and mortality. Accurate and rapid detection of urine RBP4 is essential for early monitor of impaired kidney function and prevention of CKD progression. In the present study, we developed a time-resolved fluorescence immunochromatographic test strip (TRFIS) for the quantitative and rapid detection of urine RBP4. This TRFIS possessed excellent linearity ranging from 0.024 to 12.50 ng/mL for the detection of urine RBP4, and displayed a good linearity (Y = 239,581 × X + 617,238, R2 = 0.9902), with the lowest visual detection limit of 0.049 ng/mL. This TRFIS allows for quantitative detection of urine RBP4 within 15 min and shows high specificity. The intra-batch coefficient of variation (CV) and the inter-batch CV were both < 8%, respectively. Additionally, this TRFIS was applied to detect RBP4 in the urine samples from healthy donors and patients with CKD, and the results of TRFIS could efficiently discern the patients with CKD from the healthy donors. The developed TRFIS has the characteristics of high sensitivity, high accuracy, and a wide linear range, and is suitable for rapid and quantitative determination of urine RBP4. [ABSTRACT FROM AUTHOR]

The innovative application of Crowd Intelligent Devices (CIDS) in edge networks has garnered attention due to the rapid development of artificial intelligence and computer technology. This application offers users more reliable and low-latency computing services through computation offloading technology. However, the dynamic nature of network terminals and the limited coverage of edge servers pose challenges, such as data loss and service interruption. Furthermore, the high-speed mobility of intelligent terminals in the dynamic edge network environment further complicates the design of computation offloading and service migration strategies. To address these challenges, this paper explores the computation offloading model of cluster intelligence collaboration in a heterogeneous network environment. This model involves multiple intelligences collaborating to provide computation offloading services for terminals. To accommodate various roles, a switching strategy of split-cluster group collaboration is introduced, assigning the cluster head, the alternate cluster head, and the ordinary user are assigned to a group with different functions. Additionally, the paper formulates the optimal offloading strategy for group smart terminals as a Markov decision process, taking into account factors such as user mobility, service delay, service accuracy, and migration cost. To implement this strategy, the paper utilizes the deep reinforcement learning-based CCSMS algorithm. Simulation results demonstrate that the proposed edge network service migration strategy, rooted in groupwise cluster collaboration, effectively mitigates interruption delay and enhances service migration efficiency. [ABSTRACT FROM AUTHOR]

Indirect transmission systems achieve higher output torque compared to direct transmission systems under constrained conditions and limited space. However, the prevalent undesired backlash dynamics in indirect transmission systems can lead to an increase positional error and unstable limit cycle oscillations. In order to suppress the adverse effects of backlash dynamics using a simple and practical approach, we propose a bounded-saturation-based disturbance observer (DOB) to enhance the precision positioning performance of transmission systems. The core of this approach lies in the incorporation of a nonlinear saturation function into the traditional DOB, limiting the amplitude output of the compensation signal, thereby altering the trajectory of closed-loop poles, resulting in a backlash-suppression structure with higher bandwidth and improved stability performance compared to conventional observers. In the novel full-closed loop feedback structure, we also analyze the suppression effect of the introduced saturation function on limit cycle oscillations by the extended Nyquist stability criterion. Experimental validation is conducted on a positioning turntable platform driven by the flexible timing-belt. The results demonstrate an effective suppression on the severe reverse backlash dynamics induced during velocity reversals, with a reduction of over 30% in tracking positioning error. The method proposed in this paper does not involve intricate mathematical derivations, exhibits strong real-time suppression capability for backlash dynamics, and can be extended to precision positioning systems in practical industrial applications featuring backlash dynamics. [ABSTRACT FROM AUTHOR]

Cutting-edge chipping is a randomly happened but critical tool failure, which could seriously affect machining quality without effective and timely treatment especially in the automated machining process. Accurate and timely monitoring chipping is the first key step for properly handling edge chipping issues, while there are still gaps between academic research and industrial application as chipping initiation and propagation are always stochastic especially for milling complex structural parts with mass of ever-changing cutting conditions. This paper proposes a chipping monitoring method for automated milling process based on cutting vibration polar coordinate image features and residual neural network (ResNet) model, which lies on the change of cutting vibration signals that reveal just after an event of edge chipping has occurred. With the creatively proposed polar coordinate transform method, cutting vibration signals are first preprocessed for real-time chipping detection. The preprocessed signals with easily distinguished shape features of polar coordinate images are then employed for developing a ResNet50-based classification model. And consequently, the cutting-edge chipping could be monitored in almost real time. Experimental validation for real-time chipping detection has been conducted with the proposed method. The accuracy of No. 5~8 experiments are 92%, 88%, 83% and 84%, respectively. More importantly, the method is suited for edge chipping monitoring for milling complex structural parts, where the effects of constantly changing cutting conditions have been eliminated. [ABSTRACT FROM AUTHOR]

This paper studies the cluster consensus of multi-agent systems (MASs) with objective optimization on directed and detail balanced networks, in which the global optimization objective function is a linear combination of local objective functions of all agents. Firstly, a directed and detail balanced network is constructed that depends on the weights of the global objective function, and two kinds of novel continuous-time optimization algorithms are proposed based on time-invariant and time-varying objective functions. Secondly, by using fixed-time stability theory and convex optimization theory, some sufficient conditions are obtained to ensure that all agents' states reach cluster consensus within a fixed-time, and asymptotically converge to the optimal solution of the global objective function. Finally, two examples are presented to show the efficacy of the theoretical results. [ABSTRACT FROM AUTHOR]

Cathode materials, nickel doped Cr8O21, were synthesized by a solid-state method. The effects of Ni doping on the electrochemical performances of Cr8O21 were investigated. The experimental results show that the discharge capacities of the samples depend on the nickel contents, which increases firstly and then decreases with increasing Ni contents. Optimized Ni0.5Cr7.5O21 delivers a first capacity up to 392.6 mAh·g−1 at 0.1 C. In addition, Ni doped sample also demonstrates enhanced cycling stability and rate capability compared with that of the bare Cr8O21. At 1 C, an initial discharge capacity of 348.7 mAh·g−1 was achieved for Ni0.5Cr7.5O21, much higher than 271.4 mAh·g−1 of the un-doped sample, with an increase of more than 28%. Electrochemical impedance spectroscopy results confirm that Ni doping reduces the growth of interface resistance and charge transfer resistance, which is conducive to the electrochemical kinetic behaviors during charge-discharge. [ABSTRACT FROM AUTHOR]

In this paper, anhydrous porous CuF2 with a micro-nano-hierarchical structure has been successfully fabricated via a precipitation method and a following solid-state reaction process. Scanning electron microscopy, transmission electron microscopy and N2 adsorption–desorption isotherms results confirm that the prepared porous CuF2 bulks are composed of loosely packed nanoparticles with a size range mainly between 30 and 50 nm, forming a micro-nano-hierarchical structure and possessing a large specific Brunauer–Emmett–Teller surface area of 24.93 m2 g−1. The porous CuF2 exhibits an outstanding initial discharge capability of 523 mAh g−1 at 0.1C and a superior rate capacity of 403 mAh g−1 at 5C with a cutoff voltage of 1.5 V versus Li/Li+. Moreover, electrochemical impedance spectroscopy, cyclic voltammetry and galvanostatic intermittent titration technique results verify porous structure can decrease the charge transfer resistance and boost the Li+ diffusion coefficient in CuF2. The method proposed in this work could be potentially used to synthesize other metal fluorides for high-performance lithium-ion batteries. [ABSTRACT FROM AUTHOR]

In this study, a hybrid nanostructure composed of porous CuF2 and a three-dimensional (3D) electronic network of CNTs has been successfully fabricated by a precipitation method and a following solid-state reaction process as cathode material for lithium-ion batteries. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) results demonstrate the intimate contract of CuF2 particles and the reserve of the porous structure after the addition of CNTs. Inherited the advantage of porous structure and the three-dimensional (3D) conductive network of CNTs, the CNTs/porous CuF2 composite exhibits enhanced electrochemical performance than porous CuF2, where the initial discharge capacity increases from 531 to 618 mAh g−1 at 0.1C. Moreover, electrochemical impedance spectroscopy (EIS) and galvanostatic intermittent titration technique (GITT) results demonstrate the decrease of the charge-transfer resistance and the promotion of the Li+ diffusion in virtue of CNTs. The hybrid nanostructure proposed in this work may be potentially used in other transition metal fluorides as cathode materials for lithium-ion batteries with high energy densities. [ABSTRACT FROM AUTHOR]

This study is aimed to develop and validate a novel nomogram model that can preoperatively predict axillary lymph node pathological complete response (pCR) after NAT and avoid unnecessary axillary lymph node dissection (ALND) for breast cancer patients. A total of 410 patients who underwent NAT and were pathologically confirmed to be axillary lymph node positive after breast cancer surgery were included. They were divided into two groups: patients with axillary lymph node pCR and patients with residual node lesions after NAT. Then the nomogram prediction model was constructed by univariate and multivariate logistic regression. The result of multivariate logistic regression analysis showed that molecular subtypes, molybdenum target (MG) breast, computerized tomography (CT) breast, ultrasound (US) axilla, magnetic resonance imaging (MRI) axilla, and CT axilla (all p < 0.001) had a significant impact on the evaluation of axillary lymph node status after NAT. The nomogram score appeared that AUC was 0.832 (95% CI 0.786–0.878) in the training cohort and 0.947 (95% CI 0.906–0.988) in the validation cohort, respectively. The decision curve represented that the nomogram has a positive predictive ability, indicating its potential as a practical clinical tool. [ABSTRACT FROM AUTHOR]

For ultra-large-scale integrated circuits to proceed at a rapid pace, dielectric materials with an ultralow permittivity, excellent mechanical properties, and moisture resistance are highly sought after. Herein, a series of F-SiO2/PI nanofiber films with an ultralow-k value have been successfully created by coaxial electrospinning and in situ sol–gel techniques, allowing them to be used under moisture conditions. Thanks to the introduction of fluorinated substituents and high porosity, F-SiO2/PI films exhibited ultralow dielectric constants, less than 1.8 at 1 MHz, and high hydrophobicity with contact angles greater than 145°. In addition, when TEOS was added in quantities ranging from 0.25 to 1.00 ml, F-SiO2/PI films with dielectric constants of 1.81–2.65 (1 MHz) at 80% R.H., and the water contact angles of 146.1°, 148.0°, 151.9°, and 154.2°, respectively, were obtained, compared to 4.17 of dielectric constant at 80% R.H. and contact angle with water 112.0° for pure PI nanofiber films. In this regard, the F-SiO2/PI films offered great promise as an insulating material for electronics and microelectronics. [ABSTRACT FROM AUTHOR]

MXenes are proved to be ideal sulfur hosts in lithium-sulfur batteries because of their high conductivity and strong polysulfide affinity. However, their synthesis methods are mainly based on the involvement of hazardous HF solution. In this work, Ti3C2Tx Mxene (MS-Ti3C2Tx) prepared via an environment-friendly molten salt etched method was evaluated as the host material for sulfur. The results indicate that etching temperature is essential to regulate the phase composition and the morphology of MS-Ti3C2Tx, thus to determine the electrochemical performances of cathodes with MS-Ti3C2Tx. The as-fabricated MS-Ti3C2Tx-600/S cathode achieved a much higher sulfur utilization (1089 mAh g−1 at 0.05 °C), an improved rate capacity (712 mAh g−1 under 0.5 °C) and a promoted capacity retention of 76.19% after 100 cycles at 0.1 °C compared with the pristine sulfur cathode. Its promoted electrochemical performances might be ascribed to the prepared MS-Ti3C2Tx-600, which not only provides a conductive framework to accelerate electrochemical kinetics, but also supports a strong adsorption to anchor the lithium polysulfides. [ABSTRACT FROM AUTHOR]

Breast cancer has become the most prevalent cancer, globally. Adriamycin is a first-line chemotherapeutic agent, however, cancer cells acquire resistance to it, which is one of the most common causes of treatment failure. ROS and NRF2 are essential oxidative stress factors that play a key role in the oxidative stress process and are associated with cancer. Our goal is to create novel therapeutic drugs or chemical sensitizers that will improve chemotherapy sensitivity. The optimal concentration and duration for MCF-7 and MCF-7/ADR cells in ADR and CYT were determined using the CCK-8 assay. We found that ADR + CYT inhibited the activity of MCF-7 and MCF-7/ADR cells in breast cancer, as well as causing apoptosis in MCF-7 and MCF-7/ADR cells and blocking the cell cycle in the G0/G1 phase. ADR + CYT induces apoptosis in MCF-7 and MCF-7/ADR cells through ROS generation and the P62/NRF2/HO-1 signaling pathway. In breast cancer-bearing nude mice, ADR + CYT effectively suppressed tumor development in vivo. Overall, our findings showed that CYT in combination with ADR has potent anti-breast cancer cell activity both in vivo and in vitro, suggesting CYT as the main drug used to improve chemosensitivity. [ABSTRACT FROM AUTHOR]

The comprehensive study of the spatial-cellular anatomy of the human liver is critical to addressing the cellular origins of liver disease. Here we conducted spatial transcriptomics on normal human liver tissue sections, providing detailed information of liver zonation at the transcriptional level. We present 6581 high-quality spots from normal livers of two human donors. In this dataset, cells were mainly hepatocytes, and we classified them into four sub-groups. Collectively, these data provide a reliable reference for studies on spatial heterogeneity of liver lobules. Measurement(s) mRNA Expression Technology Type(s) spatial transcriptomics Sample Characteristic - Organism Homo sapiens [ABSTRACT FROM AUTHOR]

Filamentous cyanobacteria have substantial niche overlap, and the causal mechanism behind their succession remains unclear. This has practical significance since several filamentous genera are the main producers of the musty odorant 2-methylisoborneol (MIB), which lead to odor problems in drinking water. This study investigates the relationships between two filamentous cyanobacteria, the MIB-producing genus Planktothrix and the non-MIB-producing genus Pseudanabaena, in a drinking water reservoir. We firstly identified their niche characteristics based on a monitoring dataset, combined this information with culture experiments and developed a niche-based model to clarify these processes. The results reveal that the optimal light requirements of Pseudanabaena (1.56 mol m−2 d−1) are lower than those of Planktothrix (3.67 mol m−2 d−1); their light niche differentiation led to a fundamental replacement of Planktothrix (2013) by Pseudanabaena (2015) along with MIB decreases in this reservoir during 2013 and 2015. This study suggests that light is a major driving force responsible for the succession between filamentous cyanobacteria, and that subtle niche differentiation may play an important role in shaping the filamentous cyanobacterial assemblages that drives the MIB odor problems in drinking water reservoirs. [ABSTRACT FROM AUTHOR]

Fe0.5Co0.5S2 combined the advantages of FeS2 and CoS2 has been considered as one of the most promising cathode materials for thermal batteries. However, traditional methods are inefficient or difficult to prepare high-purity Fe0.5Co0.5S2. Here, a facile salt method was used to successfully prepare the cathode material Fe0.5Co0.5S2 for thermal batteries. The Fe0.5Co0.5S2 exhibited a discharge specific capacity of 705 mAh g−1 with a cut-off voltage of 1.2 V, which was 27.5% higher than FeS2 and 14.8% higher than CoS2. Simultaneously, its discharge pulses could reach 19, while there were only 16 pulses for FeS2 and CoS2. Furthermore, the Fe0.5Co0.5S2 also showed good air stability. After being stored at 100% relative humidity and 30 °C for a week, no visible impurities or significant reduction in discharge pulses were found. This work provided a simple, efficient, and low-cost synthesis method that would well support the preparation of Fe0.5Co0.5S2 for thermal batteries. [ABSTRACT FROM AUTHOR]

We study a general kind of partial information nonzero sum two-player stochastic differential games, where the state variable is governed by a stochastic differential equation and the control domain of each player can be non-convex. Moreover, the control variables of both players can enter the diffusion coefficients of the state equation. We establish Pontryagin's maximum principle for open-loop Nash equilibria of the game. Then, a verification theorem is obtained for Nash equilibria when the control domain is convex. Finally, the theoretical results are applied to studying a linear-quadratic game. [ABSTRACT FROM AUTHOR]

The design of highly active and stable RuO2-based nanostructures for acidic oxygen evolution reaction (OER) is extremely important for the development of water electrolysis technology, yet remains great challenges. We here demonstrate that the incorporation of S into RuCuO nanorings (NRs) can significantly enhance the acidic OER performance. Experimental investigations show that the incorporation of S can optimize the interaction of Ru and O, and therefore significantly suppresses the dissolution of Ru in acidic condition. The optimized catalyst (SH-RuCuO NRs) displays superior OER performance to the commercial RuO2/C. Impressively, the SH-RuCuO NRs can exhibit significantly enhanced stability for 3,000 cycles of cyclic voltammetry test and more than 250 h chronopotentiometry test at 10 mA·cm−2 in 0.5 M H2SO4. This work highlights a potential strategy for designing active and stable RuO2-based electrocatalysts for acidic OER. [ABSTRACT FROM AUTHOR]

Although high-efficiency production of hydrogen peroxide (H2O2) can be realized separately by means of direct, electrochemical, and photocatalytic synthesis, developing versatile catalysts is particularly challenging yet desirable. Herein, for the first time we reported that palladium-sulphur nanocrystals (Pd-S NCs) can be adopted as robust and universal catalysts, which can realize the efficient O2 conversion by three methods. As a result, Pd-S NCs exhibit an excellent selectivity (89.5%) to H2O2 with high productivity (133.6 mol·kgcat−1h−1) in the direct synthesis, along with the significantly enhanced H2O2 production activity and stability via electrocatalytic and photocatalytic syntheses. It is demonstrated that the isolated Pd sites can enhance the adsorption of O2 and inhibit its O-O bond dissociation, improving H2O2 selectivity and reducing H2O2 degradation. Further study confirms that the difference in surface atom composition and arrangement is the key factor for different ORR mechanisms on Pd NCs and Pd-S NCs. [ABSTRACT FROM AUTHOR]

In this paper, inspired by various stochastic linear-quadratic (LQ, for short) problems, we develop the method of continuation to study nonlinear forward–backward stochastic differential equations (FBSDEs, for short) in a kind of domination-monotonicity frameworks. The coupling of FBSDEs is in a general form, i.e., it not only appears in integral terms and terminal terms, but also in initial terms. By virtue of introducing various matrices, matrix-valued random variables and matrix-valued stochastic processes, we present the domination-monotonicity framework carefully and rigorously. A unique solvability result and a pair of estimates for coupled FBSDEs are obtained (see Theorem 3.5 in the case of simple domination-monotonicity conditions and Theorem 5.2 in the case of multi-level self-similar domination-monotonicity structures). As applications of theoretical results, the related stochastic Hamiltonian systems of several LQ problems are discussed. [ABSTRACT FROM AUTHOR]

A kind of linear-quadratic Stackelberg games with the multilevel hierarchy driven by both Brownian motion and Poisson processes is considered. The Stackelberg equilibrium is presented by linear forward-backward stochastic differential equations (FBSDEs) with Poisson processes (FBSDEPs) in a closed form. By the continuity method, the unique solvability of FBSDEPs with a multilevel self-similar domination-monotonicity structure is obtained. [ABSTRACT FROM AUTHOR]

Glass Passivation Parts (GPP) wafer texture defects are one of the most important factors affecting the accuracy of wafer defect detection. Template matching has local errors and low efficiency, and deep learning requires many training samples. In the early stage, defect training sample sets cannot be provided. This paper discusses the design of an effective GPP wafer grain region texture defect detection algorithm using a sub-region one-to-one mapping. A set of standard wafer datum is selected as the reference of grain region segmentation detection, and then the standard wafer images and test GPP wafer images are automatically calibrated and segmented, respectively. Then, a series of pre-processes were performed to equalize the sizes of the two grain-region images. Then the grain region was divided into an equal number of rectangular sub-regions of the same size according to the measurement precision requirement. The correlation degree of each test sub-region is judged by the designed three-channel RGB gray-scale similarity decision functions. Experiments show that the algorithm successfully achieved the necessary calibration and segmentation for the grain region. Compared with the template and histogram matching algorithms, the proposed method does not require a training set, the detection accuracy is significantly improved and the detection efficiency is up to 29.74 times better on average using the proposed algorithm. [ABSTRACT FROM AUTHOR]

Gas saturation is an essential parameter in natural gas reservoir evaluation. As complex pore structure reduces the resistivity contrast between gas and water layers, gas saturation is difficult to calculate accurately by rock resistivity in low-porosity and low-permeability reservoir. The gas saturation is positively correlated with the relative value of compressional wave (P wave) slowness' square based on the rock acoustic wave theory. In this study, rock samples are divided into four types of pore structures according to nuclear magnetic resonance (NMR) data. Relation models between the gas saturation and the relative value of P wave slowness' square are established for each type. New models are further applied in field logging data in low-porosity and low-permeability gas-bearing sandstone reservoirs. The result shows that the new models calculated gas saturation is in good agreement with the gas-producing test. This paper provides a new way of qualitative evaluation of gas saturation. It enriches effective evaluation methods in low-porosity and low-permeability gas-bearing reservoirs with non-electrical logging data. [ABSTRACT FROM AUTHOR]

This paper proposes some distributed algorithms to solve the multi-agent optimization problem with equality constraints, in which the team objective is a sum of local convex objective functions. Firstly, a directed network related to equality constraints is constructed before converting the constrained optimization problem into an unconstrained one. Secondly, a continuous algorithm is designed by using local information of agents, and the objective function converges to the global optimum in a fixed-time interval. Moreover, in order to reduce the communication cost, an event-triggered algorithm with sign function is devised. It is found that the optimal value can be achieved in a fixed-time interval, but the sign function can cause high-frequency chattering when the sate variables converge to the optimal value. Therefore, an event-triggered algorithm with saturation function is proposed, which can effectively overcome this disadvantage. Finally, the proposed algorithms are verified by some numerical simulations. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, collected data usually have a certain degree of loss and are unable to meet actual application needs due to node failures or energy limitation, etc. The current data recovery methods in wireless sensor networks focus on the usage of spatial–temporal correlation between perceptual data but seldom exploit the correlation between different attributes. This paper proposes a data recovery algorithm based on the Attribute Correlation and Extremely randomized Trees (ACET). Firstly, the Spearman's correlation coefficient is adopted to construct the correlation model between different attributes. In case that a given attribute is lost, the correlation model is used to select other attributes that have a strong correlation with this attribute, and then take advantage of them to train the extremely randomized trees. Finally, the lost data can be recovered by the trained model. Experimental results show that the correlation between attributes can improve the effectiveness of data recovery compared with other methods. [ABSTRACT FROM AUTHOR]

In this paper, the issue of the exponential synchronization for complex-valued neural networks with both discrete and distributed delays is investigated by applying impulsive control protocol. Based on the Lyapunov–Krasovskii function, average impulsive interval as well as the comparison principle, some simple verifiable sufficient criteria are established to guarantee the exponential synchronization between the master and the slave systems. Meanwhile, through the serious analysis of the networks systems, the exponential convergence rate can be specified. Additionally, a numerical example is finally given to illustrate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

The application of mass spectrometry imaging (MSI) for the study of spatiotemporal alterations of the metabolites in tumors has brought a number of significant biological results. At present, metabolite profiling based on MSI is typically performed on frozen tissue sections; however, the majority of clinical specimens need to be fixed in tissue fixative to avoid autolysis and to preserve antigenicity. In this study, we present the global impacts of different fixatives on the MS imaging of gastric cancer tissue metabolites. The MSI performances of 17 kinds of metabolites, such as amino acids, polyamines, cholines, organic acids, polypeptides, nucleotides, nucleosides, nitrogen bases, cholesterols, fatty acids, and phospholipids, in untreated, 10% formalin–, 4% paraformaldehyde–, acetone-, and 95% ethanol–fixed gastric cancer tissues were thoroughly explored for the first time. Furthermore, we also investigated the spatial expressions of 6 metabolic enzymes, namely, GLS, FASN, CHKA, PLD2, cPLA2, and EGFR, closely related to tumor-associated metabolites. Immunohistochemical staining carried out on the same tissue sections‚ which have undergone MSI analysis‚ suggests that enzymatic characterization is feasible after metabolite imaging. Combining the spatial signatures of metabolites and pathway-related metabolic enzymes in heterogeneous tumor tissues offers an insight to understand the complex tumor metabolism. [ABSTRACT FROM AUTHOR]

This paper studies the rumor propagation model with heterogeneous networks in a multilingual environment. Firstly, a rumor propagation model with two language spreaders, in which the immunologic mechanism is considered in the ignorant, is proposed on heterogeneous networks. Secondly, the basic reproduction number and the dynamic behaviors are analyzed by using the next-generation matrix method and Lyapunov stability theory, respectively. Moreover, two control strategies are designed to effectively suppress the spread of the rumor. The one is continuous control strategy. By applying real-time control to the spreaders, the rumor spreading time can be greatly reduced and the rumor can die out in a short time. The other is event-triggered impulsive control strategy, which can effectively reduce the consumption of resources and ensure the extinction of the rumor. Finally, the correctness of theoretical analysis and the feasibility of control methods are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem of multi-agent systems with input saturation and directed communication topology, by utilizing the low-gain feedback method and the event-triggered control laws. Two event-triggered control laws, the centralized and the distributed laws, are proposed to guarantee semi-global consensus of the multi-agent systems. Then, a sufficient condition is presented to prove strictly positive low bound of inner-event time, i.e., the Zeno behavior can be avoided. Finally, the effectiveness of the proposed event-triggered laws is further verified by an example. [ABSTRACT FROM AUTHOR]

The aim is to design a self-adapting contrast enhancement algorithm that can remove the background noise and divide the foreground and background very well. For the self-adapting contrast enhancement algorithm, we looked for all background RGB pixel values, and found the minimum values in the RGB components so that ∂=255/min(Ipixel(R, G, B)). The results were compared to classical contrast enhancement techniques. Five steps to extract the wafer contour, respectively, were the preservation filter, self-adapting contrast enhancement, closing morphological operation, image binarization based on the Otsu method and using the first derivative extract contour. The results of contour extraction were compared with the traditional Canny, Sobel and Scharr algorithms using different parameter values. The experiment results showed that the self-adapting contrast enhancement algorithm could remove the background noise effectively compared to traditional methods. In comparison with the Canny, Sobel and Scharr algorithms, the first derivative after the original image filtering by optimized self-adapting contrast enhancement algorithm was better at extracting wafer contours. Therefore, we concluded that the wafer self-adapting contrast enhancement algorithm method was correct and feasible. The theories in this paper could be applied to image processing in the agricultural, industrial, and military fields. [ABSTRACT FROM AUTHOR]

Effects of sintering temperatures on the phases, microstructures, defect structures and dielectric behaviors of the SrTi0.985(Nb2/3Zn1/3)0.015O3 ceramics have been systematically investigated. Giant permittivity (~ 10100) and low tangent loss (~ 0.035) are achieved in the ceramics sintered at 1500 °C. With an increase in sintering temperature, the grain size increases first and then stabilizes gradually, while the lattice constant increases first and then decreases. Higher sintering temperature is beneficial to the thermal stabilities of permittivity and tangent loss. Further investigations reveal that the giant permittivity mainly results from defect polarization. More Ti3+ ions and more oxygen vacancy-related defect complexes ( Ti 3 + - V O · · - Ti 3 + and V O · · - Zn Ti ″ , etc.) are involved in the ceramics sintered at 1500 °C, contributing to the giant permittivity and low tangent loss. The presence of point defects breaks the local structural symmetry and distorts the oxygen octahedron. Dielectric properties are deteriorated at excessive sintering temperature due to the dissociation of defect complexes as well as the enhanced interfacial polarization. [ABSTRACT FROM AUTHOR]

Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01428-w 8 Zhao J, Chen C, Huang H, Xiang C (2021) Unifying Uber and taxi data via deep models for taxi-passenger demand prediction. Mobile Crowd Sensing (MCS) has emerged as a paradigm for gathering information about the physical world. Personal Ubiquitous Comput. https://doi.org/10.1007/s00779-020-01443-x 7 Shi Y, Zhang X, Hu Q, Cheng H (2021) Data recovery algorithm based on generative adversarial networks in crowd sensing internet of things. [Extracted from the article]

In this paper, a class of cluster consensus problem of the multi-agent systems with aperiodic intermittent communication is studied through tracking approach. Due to the transmission ways of information in the network, a new notion of layered intermittence is developed. To track the leading subnetwork and reach the desired consensus, a new type of pinning-like consensus protocol with aperiodic intermittent effects is designed according to the topological properties of agents. Considering both the control protocol with intermittent effects and the intermittent communication, the protocol is applied to construct several new intermittent switching systems. Besides, the graph of the networked system is assumed to be directed and weakly connected. Some consensus criteria are derived to guarantee that the agents in the same cluster follow the leader asymptotically, while agents in different clusters reach the desired delay consensus via tracking their leaders. Finally, some numerical simulations are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

To reduce the severe overpotential of oxygen reduction and evolution reaction (ORR and OER) for rechargeable Li-O2 batteries, the dandelion-like α-MnO2 hollow spheres (HS) with high surface area (105.54 m2 g−1) were prepared by a facile in situ pyrolysis of manganese alkoxide for the first time. The ORR diffusion limiting current density and OER current density at 1.0 versus (Ag/AgCl)/V are 6.32 and 45.82 mA cm−2 at 1600 rpm in alkaline solution, respectively, indicating that dandelion-like α-MnO2-HS catalyst exhibits superior bifunctional catalytic activity. The Li-O2 batteries with α-MnO2-HS catalyst can yield high initial discharge specific capacity of 7897.6 mA h g−1 at 100 mA g−1. Moreover, the cycle life of Li-O2 batteries with α-MnO2-HS catalyst is significantly improved and can sustain 108 cycles. These results indicate that as-fabricated hollow sphere structure without adding any hard templates is favorable for superior bifunctional catalytic activity in aqueous and non-aqueous electrolyte. [ABSTRACT FROM AUTHOR]

This paper considers a high-order consensus problem of multi-agent system with feedforward nonlinear and time-varying input delay in a directed network. In order to achieve the consensus, we propose a low gain distributed protocol which can get rid of impacts of feedforward nonlinearity and an arbitrarily bounded input delay on the consensus problem. Moreover, for any upper bound time-varying delay and strongly connected diagraph, the proposed controller can solve the consensus problem of multi-agent systems with feedforward nonlinearity if the designed parameter θ is great than the threshold value. Finally, several numerical simulations are presented to demonstrate the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

With the popularization of wireless networks and mobile intelligent terminals, mobile crowd sensing is becoming a promising sensing paradigm. Tasks are assigned to users with mobile devices, which then collect and submit ambient information to the server. The composition of participants greatly determines the quality and cost of the collected information. This paper aims to select fewest participants to achieve the quality required by a sensing task. The requirement namely “t-sweep k-coverage” means for a target location, every t time interval should at least k participants sense. The participant selection problem for “t-sweep k-coverage” crowd sensing tasks is NP-hard. Through delicate matrix stacking, linear programming can be adopted to solve the problem when it is in small size. We further propose a participant selection method based on greedy strategy. The two methods are evaluated through simulated experiments using users’ call detail records. The results show that for small problems, both the two methods can find a participant set meeting the requirement. The number of participants picked by the greedy based method is roughly twice of the linear programming based method. However, when problems become larger, the linear programming based method performs unstably, while the greedy based method can still output a reasonable solution. [ABSTRACT FROM AUTHOR]

In this paper, the cluster consensus problem of first-order nonlinear multi-agent systems with aperiodic intermittent communication is studied through pinning leader-following approach. The pinning consensus algorithm based on the relative local intermittent information is designed according to the varies linking ways of clustered network structure. New notions of leading intermittence and inter-cluster intermittence which related to the intermittent linking ways of leader-following clustered structure are developed, and several new systems with intermittence are established due to the new notions. Besides, dynamics with inherent delay are also considered to extend our results to a more general framework. The original communication graph without intermittent pattern is supposed to be directed and weakly connected. Some consensus criteria are derived to guarantee that the cluster consensus problem for the systems with intermittent communication can be solved. Finally, numerical simulations are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

We discuss the stochastic linear-quadratic (LQ) optimal control problem with Poisson processes under the indefinite case. Based on the wellposedness of the LQ problem, the main idea is expressed by the definition of relax compensator that extends the stochastic Hamiltonian system and stochastic Riccati equation with Poisson processes (SREP) from the positive definite case to the indefinite case. We mainly study the existence and uniqueness of the solution for the stochastic Hamiltonian system and obtain the optimal control with open-loop form. Then, we further investigate the existence and uniqueness of the solution for SREP in some special case and obtain the optimal control in close-loop form. [ABSTRACT FROM AUTHOR]

In this study, two parallel lab-scale anaerobic membrane bioreactors (AnMBRs), one of which was dosed with polyaluminum chloride (PAC) for membrane fouling control, were operated for treating excess activated sludge collected from a wastewater treatment plant (WWTP). The AnMBRs were inoculated with anaerobic digested sludge collected from an anaerobic digester of another WWTP. The microbial community of digested sludge and cake layer in AnMBRs, as well as that of excess sludge, was analyzed through polymerase chain reaction coupled with denaturing gradient gel electrophoresis (PCR-DGGE) and Illumina MiSeq. The dynamic variation of archaeal community in AnMBRs was not as obvious as that of bacterial community based on the PCR-DGGE results. Under the circumstance of stable operation, Cloacimonetes, Chloroflexi, Bacteroidetes, Proteobacteria, Firmicutes, and Ignavibacteriae were observed as the predominant phyla in digested sludge based on the Illumina results. In addition to that, the cake layer possessed similar predominant phyla with the digested sludge but owned a higher diversity. Furthermore, overlapping bacterial communities were discovered between the excess sludge and digested sludge. However, the abundance of aerobic bacteria was substantially reduced, while the abundance of anaerobic microorganisms like phylum Cloacimonetes and Smithella was enriched in digested sludge over time. Additional PAC dosing, on the one hand, affected the bioavailable substrate, thus further changing the microbial community structure; on the other hand, aluminum itself also affected specific microbial communities. Besides, PAC dosing indirectly influenced the bacterial diversity in AnMBR as well. [ABSTRACT FROM AUTHOR]

The micro-structural characteristics of sodium dodecyl sulfate (SDS)/benzyl alcohol (BA)/HO micelle were studied by the methods of theoretical calculation, viscosity, dynamic light scattering, and Raman spectra. The radius of the spherical micelle was about 22.86-35.85 nm. The maximum length of rod-like micelle could reach up to 250.95 nm. In the micelle, the carbon chain of SDS was not completely stretched but still bended. The total chain length of SDS molecule in the micelle appeared to be 2 nm approximately. Both the axis ratio and the shape factor of rod-like micelles increased with the increase of aggregation number. The intrinsic viscosity and relative viscosity of spherical micelles were less than those of the rod-like micelles. The relative viscosity and critical micelle concentration values decreased gradually with the increase of BA content. The second critical micelle concentration of surfactant could also be determined through viscosity method. [ABSTRACT FROM AUTHOR]

Ni doped perovskite oxides LaSrCoNiO ( x = 0, 0.05, 0.1) have been synthesized by a dry gel combustion method using citric acid and EDTA (ethylene diamine tetraacetic acid) as complex agent. The Li-O batteries on the basis of the LaSrCoNiO perovskite nanoparticles and non-aqueous electrolytes were also fabricated and measured. The oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) activity of as-prepared electrodes were measured by cyclic voltammetry (CV) curves. The peak current increased in the order of pure Super P, LaSrCoO, LaSrCoNiO, and LaSrCoNiO. The electrochemical impedance spectroscopy (EIS) measurements revealed that LaSrCoNiO catalyst could restrain the increase of impedance during discharge process and promote the decomposition of discharge products during charge process. LaSrCoNiO and LaSrCoNiO catalysts displayed enhanced performances compared with LaSrCoO catalyst. The initial capacity of batteries using LaSrCoNiO and LaSrCoNiO as the cathode catalyst displayed enhanced performances compared with LaSrCoO catalyst, which was in agreement with the trend of CV curves. [ABSTRACT FROM AUTHOR]

With the occurrence of large-scale human trajectories, which imply spatial and temporal patterns, the subject of mobility prediction has been widely studied. A number of approaches are proposed to predict the next location of a user. In this paper, we expect to lengthen the temporal dimension of prediction results beyond one hop. To predict the future locations of a user at every time unit within a specified time, we propose a Markov-based multi-hop mobility prediction (Markov-MHMP) algorithm. It is a hybrid approach that considers multiple factors including personal habit, weekday similarity, and collective behavior. On a GPS dataset, our approach performs prediction better than baseline and state-of-the-art approaches under several evaluation criteria. [ABSTRACT FROM AUTHOR]