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To address the issue of frequency stability in microgrids with limited communication resources and bandwidth, this paper proposed an event-triggered control method based on a cloud-edge collaborative architecture. Firstly, to address the limited communication resources, event-triggered detector is set up at the edge to upload state variables and update control instructions only when the frequency deviation exceeds a pre-set threshold. Secondly, a fractional-order PI–PD controller is designed at the cloud control center, which achieves higher control degrees of freedom and stronger robustness than traditional integer-order PID control schemes. Additionally, to obtain better control parameters, an optimized design method based on an improved Big Bang-Big Crunch method (BB-BC3) is proposed for the fractional-order PI–PD controller. At last, a simulation example is given to prove the validity of the proposed method. Simulation results show that compared to the integer-order PI–PD controller, the fractional-order PI–PD controller based on the BB-BC3 algorithm proposed in this paper reduces the peak value of the response curve by 5%, and shortens the setting time by 0.14 s. [ABSTRACT FROM AUTHOR]

There are many rotating spheroids in the universe, and many astronomers and physicists have used theoretical methods to study the characteristics of stellar gravity since Newton's time. This paper derives the solutions of eight scattering states (ϕ(0),χ(0),ϕ(1),χ(1),ϕ(2)$$ \Big({\phi}^{(0)},{\chi}^{(0)},{\phi}^{(1)},{\chi}^{(1)},{\phi}^{(2)} $$,χ(2),ϕ(3)$$ {\chi}^{(2)},{\phi}^{(3)} $$, andχ(3))$$ {\chi}^{(3)}\Big) $$ for the Dirac equation with positive‐energy E=im$$ E= im $$, and establishes the relationship between the differential scattering cross section σi(p,θ,φ)$$ {\sigma}_i\left(p,\theta, \varphi \right) $$ and the stellar density μ$$ \mu $$. It is found that: (1) For the eight scattering states, their average scattering cross‐sections σi‾$$ \overline{\sigma_i} $$ are proportional to μ2$$ {\mu}^2 $$, and depend on the star's radius, and the higher the stellar density μ$$ \mu $$, the greater the sensitivity of σi‾$$ \overline{\sigma i} $$ to the change of μ$$ \mu $$; (2) For the four scattering states χ(i),i=0,1,2,3$$ {\chi}^{(i)},i=0,1,2,3 $$, their average scattering amplitudes f‾(p,θ)$$ \overline{f}\left(p,\theta \right) $$ and σ‾(p,θ)$$ \overline{\sigma}\left(p,\theta \right) $$ depend on the mass m$$ m $$ of the particles; while for the other four scattering states ϕ(i)$$ {\phi}^{(i)} $$, i=0,1,2,3$$ i=0,1,2,3 $$, then f‾$$ \overline{f} $$ and σ‾$$ \overline{\sigma} $$ are independent of m$$ m $$. This study links the gravitational characteristics of stars with the scattering cross section, creating a new method for studying the gravitational characteristics, which helps to reveal the mystery of the gravity of rotating ellipsoidal stars. [ABSTRACT FROM AUTHOR]

Selective and concise construction of ring systems that are ubiquitous skeletons across chemistry, drugs and materials, is indispensable for human life. Of note, directed C−H annulation with alkynes for the expedient delivery of ring systems holds great importance, featuring step‐ and atom‐economy, mild conditions, and broad substrate scope. However, regioselectivity issues remained when using unsymmetrical alkynes for the directed C−H annulation. Herein, we summarized recent achievements towards solving this problem by developing directing groups, metal catalysts, and alkynes with versatile and traceless functionality that ensure the overall regioselectivity, enantioselectivity, efficiency, and synthetic application. We hope this concept will promote the further development of the precise construction of functional molecules using C−H annulation with unsymmetrical alkynes. [ABSTRACT FROM AUTHOR]

The complexity of the environment makes rapidly-exploring random tree (RRT) difficult to handle dynamic obstacle avoidance and system constraint in real-time path planning for autonomous vehicles. To handle this issue, this paper proposes a novel real-time double-tree rapidly-exploring random tree (RDT-RRT) algorithm framework. The collision-free path by RRT after B-spline smooth treatment is adopted as the reference path to reduce invalid sampling. Integrating G1 Hermite interpolation with G2 Hermite interpolation reduces the sampling dimension and takes more efficient samples. The optimal distance metric is designed considering dynamic collision detection mechanism and utilized to estimate the costs of the samples in terms of path curvature. Moreover, to have a better understanding of the environment, convolutional neural network (CNN) is embedded to strengthen the collision detection mechanism. By RDT-RRT the smooth, collision-free paths with small curvature changes can be evaluated. For the evaluations of our proposal in global and local planning, the experiments for a real scaled autonomous vehicle are implemented through parallel computing. By comparing with the mainstream RRT-based algorithms, it has shown that in terms of the path quality, our method reduces 92 % and 88 % of cumulative curvature change respectively in obstacle-free and static obstacle scenarios. Compared with other RRT methods, RDT-RRT performs faster convergence rate and Parallel computing increases the updating frequency from 1.1 Hz to 5.5 Hz. The obstacle avoidance capabilities are also improved. [ABSTRACT FROM AUTHOR]

Toward the aim of zero tracking error and user-specified convergence rate, a data-driven output tracking design for unknown linear discrete-time systems is investigated in this work. For policy learning, we customize a virtual auxiliary system, based on which an enhanced Bellman equation with the user-specified convergence rate is derived. This allows us not to explicitly measure the time for the system evolution, while only the input–output data are sufficient in our design. By utilizing the robust output regulation technique, we can learn an optimal tracker for such an auxiliary system via policy iteration and value iteration. It is proved that the output tracking error of the original discrete-time system converges to zero at the specified convergence rate. The effectiveness of the proposed algorithms is illustrated by a simulation example. [ABSTRACT FROM AUTHOR]

Summary: In this article, we consider the resilience analysis of the even‐based consensus control of networked Lagrangian systems under denial‐of‐service (DoS) attacks, which are usually implemented by the attackers to block the communication channels. Comparing with the linear cyber‐physical systems, the secure control of the networked Lagrangian systems is more complex and challenging, especially under the conditions of asymmetry communication and discontinuous control. To this end, an event‐based controller is first designed for consensus control of networked Lagrangian systems in the absence of DoS attacks. Sufficient conditions are given to stabilize the closed‐loop systems. Then the resilience analysis is presented for the event‐based controller under DoS attacks. Some conditions associated with the DoS duration and frequency are proposed for the control parameters against the attacks. Then Zeno behaviors are proved to be nonexistent in the proposed control scheme. An algorithm is also given to guide the control design. [ABSTRACT FROM AUTHOR]

This work aims to propose an event-triggered synchronization adaptive learning scheme for uncertain nonlinear multi-agent systems with communication link faults. In reality, the link faults are ubiquitous and responsible for modeling delays and disturbances in communications and also capturing time-varying communication weights between any two nodes in the network. To address this challenge, based on Lyapunov analysis, adaptive learning neural networks are employed to settle unknown link faults and system uncertainties. To reduce the consumption of communication resources, an event-triggered control strategy is introduced on the input side of the controller, whose triggering events are relative thresholds that can be spontaneously modified with the system states. In addition, a set of smooth functions are inserted in the Lyapunov function that assure the asymptotic stability of the system even with corrupted link faults. Meanwhile, it is rigorously verified that the synchronous tracking errors converge to a user-defined interval. Finally, the effectiveness of the proposed control protocol is demonstrated by a numerical simulation. [ABSTRACT FROM AUTHOR]

There are many stars that are rotating spheroids in the Universe, and studying them is of very important significance. Since the times of Newton, many astronomers and physicists have researched gravitational properties of stars by considering the moment equations derived from Eulerian hydrodynamic equations. In this paper we study the scattering of spinors of the Dirac equation, and in particular investigate the scattering issue in the limit case of rotating Maclaurin spheroids. Firstly we give the metric of a rotating ellipsoid star, then write the Dirac equation under this metric, and finally derive the scattering solution to the Dirac equation and establish a relation between differential scattering cross-section, σ , and stellar matter density, μ . It is found that the sensitivity of σ to the change in μ is proportional to the density μ . Because of the weak gravitational field and the constant mass density, our results are reasonable. The results can be applied to white dwarfs, main sequence stars, red giants, supergiant stars and so on, as long as their gravitational fields are so weak that they can be treated in the Newtonan approximations, and the fluid is assumed to be incompressible. Notice that we take the star's matter density to be its average density and the star is not taken to be compact. Obviously our results cannot be used to study neutron stars and black holes. In particular, our results are suitable for white dwarfs, which have average densities of about 10 5 – 10 6 g cm - 3 , corresponding to a range of mass of about 0.21 - 0.61 M ⨀ and a range of radius of about 6000 - 10 , 000 km. [ABSTRACT FROM AUTHOR]

There is an unmet need for treatments for diseases associated with aging. The antiaging, life‐extending, and cognition‐enhancing protein Klotho is neuroprotective due to its anti‐inflammatory, antioxidative, and pro‐myelinating effects. In addition, Klotho is also a tumor suppressor and has beneficial roles in multiple organs. Klotho is downregulated as part of the aging process. Thus, upregulating Klotho in the brain may lead to novel therapeutics to people suffering or at risk for neurodegenerative diseases such as Alzheimer's, Parkinson's, and amyotrophic lateral sclerosis, and demyelinating diseases such as multiple sclerosis. We attempted to upregulate Klotho for its beneficial effects in the brain and elsewhere. Here, we describe a method to specifically activate Klotho gene expression. To accomplish this task, we designed zinc finger proteins (ZFPs) targeting within −300 bps of the human Klotho promoter. We designed the ZPF constructs either de novo from modular building blocks, or modified sequences from the natural endogenous Egr1 transcription factor backbone structure. Egr1 is known to upregulate Klotho expression. We tested the transcriptional activation effects of these ZFPs in a dual luciferase coincidence reporter system under the control of 4‐kb promoter of human Klotho in stable HEK293 cells and in HK‐2 cells that express Klotho protein endogenously. We found that the best ZFPs are the de novo designed ones targeting −250 bps of Klotho promoter and one of the Egr1‐binding sites. We further enhanced Klotho's activation using p65‐Rta transcriptional activation domains in addition to VP64. These upregulation approaches could be useful for studying Klotho's protective effects and designing Klotho boosting therapeutics for future in vivo experiments. [ABSTRACT FROM AUTHOR]

Klotho is an age-extending, cognition-enhancing protein found to be down-regulated in aged mammals when age-related diseases start to appear. Low levels of Klotho occur in neurodegenerative diseases, kidney disease and many cancers. Many normal and pathologic processes involve the proteolytic shedding of membrane proteins. Transmembrane (TM) Klotho contains two homologous domains, KL1 and KL2 with homology to glycosidases. After shedding by ADAM 10 and 17, a shed Klotho isoform is released into serum and urine by the kidney, and into the CSF by the choroid plexus. We previously reported that human Klotho contains two major cleavage sites. However, the exact cleavage site responsible for the cleavage between the KL1 and KL2 domains remains unknown for the human Klotho, and both sites are unknown for mouse Klotho. In this study, we aimed to identify the cleavage sites leading to the shed forms of human and mouse Klotho. Mutations in the region close to the TM domain of mouse Klotho result in the reduced shedding of the 130 kD (KL1+KL2) and 70 kD (KL1) fragments, suggesting that the cleavage site lies within the mutated region. We further identified the cleavage sites responsible for the cleavage between KL1 and KL2 of human and mouse Klotho. Moreover, mutated Klotho proteins have similar subcellular localization patterns as wild type Klotho. Finally, in an FGF23 functional assay, all Klotho mutants with a nine amino acid deletion can also function as an FGFR1 co-receptor for FGF23 signaling, however, the signaling activity was greatly reduced. The study provides new and important information on Klotho shedding, and paves the way for studies aimed to distinguish between the distinct roles of the various isoforms of Klotho. [ABSTRACT FROM AUTHOR]

This work presents an output-feedback policy learning algorithm underlining input–output system data for distributed robust optimal synchronization of heterogeneous multi-agent systems. The output-feedback synchronization problem in the context of this work is formulated via robust output regulation and reinforcement learning modeling the interactions among agents by a zero-sum game. The proposed learning and control structure only requires the local system data for each agent and distributed output data among communicating neighbors. We utilize system-level synchysis for the continuous-time state reconstruction for the distributed learning with convergence and stability proofs under the proposed output-feedback policy for solving the zero-sum game. We further show that policy learning is assured under the proposed data criteria relating to input–output data only rather than any inter-immediate gains from policy iterations. Based on the cooperative robust output regulation, this work gains robustness after the learning is complete and establishes an output data-driven distributed optimal robust synchronization without knowing accurate system dynamics. A numerical example shows the effectiveness of the proposed learning algorithm. [ABSTRACT FROM AUTHOR]

Abstract Resilience of multi-agent systems (MAS) reflects their capability to maintain normal operation, at a prescribed level in the presence of unintended faults. In this paper, we investigate resilient control of MAS under faults on sensors and actuators. We propose four resilient state feedback based leader–follower tracking protocols. For the case of sensor faults, we develop an adaptive compensation protocol and an H ∞ control protocol. For the case of simultaneous sensor and actuator faults, we further propose an enhanced adaptive compensation protocol and an enhanced H ∞ control protocol. We show the duality between the adaptive compensation protocols and the H ∞ control protocols. For adaptive compensation protocols, faults on sensors and actuators are rejected by using local adaptive sensor and actuator compensators, respectively. Moreover, by employing a static output-feedback design technique, we propose H ∞ control protocols that guarantee bounded L 2 gains of certain errors in terms of the L 2 norms of fault signals. This further allows us to prove resilience even if sensor faults are unbounded. Finally, simulation studies validate the effectiveness of the proposed protocols. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is characterized by the accumulation of neurotoxic amyloid-β (Aβ) peptides consisting of 39-43 amino acids, proteolytically derived fragments of the amyloid-β protein precursor (AβPP), and the accumulation of the hyperphosphorylated microtubule-associated protein tau. Inhibiting Aβ production may reduce neurodegeneration and cognitive dysfunction associated with AD. We have previously used an AβPP-firefly luciferase enzyme complementation assay to conduct a high throughput screen of a compound library for inhibitors of AβPP dimerization, and identified a compound that reduces Aβ levels. In the present study, we have identified an analog, compound Y10, which also reduced Aβ. Initial kinase profiling assays identified the receptor tyrosine kinase cKit as a putative Y10 target. To elucidate the precise mechanism involved, AβPP phosphorylation was examined by IP-western blotting. We found that Y10 inhibits cKit phosphorylation and increases AβPP phosphorylation mainly on tyrosine residue Y743, according to AβPP751 numbering. A known cKit inhibitor and siRNA specific to cKit were also found to increase AβPP phosphorylation and lower Aβ levels. We also investigated a cKit downstream signaling molecule, the Shp2 phosphatase, and found that known Shp2 inhibitors and siRNA specific to Shp2 also increase AβPP phosphorylation, suggesting that the cKit signaling pathway is also involved in AβPP phosphorylation and Aβ production. We further found that inhibitors of both cKit and Shp2 enhance AβPP surface localization. Thus, regulation of AβPP phosphorylation by small molecules should be considered as a novel therapeutic intervention for AD. [ABSTRACT FROM AUTHOR]

Abstract Making a trade-off between the control accuracy and computational reduction is a problem frequently encountered in the system control design. This is especially difficult when one designs adaptive fuzzy (or neural network) controls for nonlinear systems, in which fuzzy controls have to consume many computational resources to tune a sufficiently large number of adaptive parameters, meanwhile nonlinear uncertainties block the high demanding control accuracy. Current works usually face a dilemma that, either the computation is reduced but the control accuracy is degraded due to the use of the norm estimation, or the asymptotic control is resulted but the computation is increased due to the extra compensation controls. To address such dilemma, we propose an asymptotic adaptive fuzzy tracking control algorithm, whose main feature is that only two adaptive laws are needed throughout the control scheme. In particular, we allocate one adaptive law to achieve adaptive fuzzy backstepping control for nonlinear systems with a focus on stabilizing the closed-loop system. We then allocate the other adaptive law not only to asymptotically drive the stabilization error to the zero, but also to achieve the elimination of overparametrization in a Nussbaum-like design, which is inspired by the tuning function-based approach. [ABSTRACT FROM AUTHOR]

Three pyrazolium ionic liquids, 1,2-diethylpyrazolium bromide (DEPzBr), 1,2-diethyl-3-methylpyrazolium bromide (DEMPzBr), and 1,2-diethyl-3,5-dimethylpyrazolium bromide (DEDMPzBr), are firstly applied as catalysts for coupling reaction of carbon dioxide (CO 2 ) and propylene oxide (PO) with the propylene carbonate (PC) yields in a range of 82.7%–88.7% under a benign condition, 120 °C, 2.0 MPa initial CO 2 pressure and 4 h with 0.5 mol% catalysts loading. The relationship between structure and catalytic activity of pyrazolium ionic liquids are investigated by two different theoretical models, which indicates that both electrostatic interaction and hydrogen bond promote the ring-opening of PO. Both the theoretical and experimental results present that the catalytic activity decreases in the sequence of DEPzBr > DEDMPzBr > DEMPzBr. Pyrazolium ionic liquids would be employed as a novel efficient single-component catalyst without solvent and co-catalyst. It is expected that we would open an express pathway to develop new catalysts with the desired properties. [ABSTRACT FROM AUTHOR]

The efficient fixation of CO 2 without co-catalyst and solvent under metal-free condition is still an urgent topic in sustainable chemistry. In this work, a series of dialkylpyrazolium ionic liquids are employed to promote the cycloaddition of CO 2 and PO to produce PC. They would be easily synthesized by a simple one-pot reaction. The effect of alkyl chain length in cation and different anion is explored. Diethylpyrazolium iodide presents the excellent catalytic activity with the product yield of 96% and selectivity of 99% in a benign condition. Moreover, the catalyst could be reused for at least five times without significant loss of catalytic activity. An intensive structure-activity research testifies that the cycloaddition of CO 2 with PO is activated by a synergistic effect from both cation and anion of ILs. To confirm it, the detailed mechanism is investigated by density functional theory associated with the non-covalent interactions and atoms in molecule analysis. Besides the electrostatic interaction between cation of ionic liquid and PO, the noncovalent interaction, especially for hydrogen bond, plays a vital role in promoting the reaction. [ABSTRACT FROM AUTHOR]

The scarcity of high efficient red-emitting phosphorescent emitters, especially for deeply red emitter, has become the major road stone to block the further development of organic light-emitting diodes. Most of studies have been devoted to developing new Ir(III) complexes by variation of primary ligands. The ancillary ligand has attracted less attention. Four Ir(III) complexes, (DPQ) 2 Ir(pic) ( 1 ), (DPQ) 2 Ir(tmd) ( 2 ), (DPQ) 2 Ir(ozl) ( 3 ), and (DPQ) 2 Ir(iml) ( 4 ) with different ancillary ligands are explored from both emissive rule and quantum yields, where DPQ is 2,4-diphenylquinoline with a CF 3 group at meta position of the phenyl ring, pic is picolinate, tmd is 2,2,6,6-tetramethylheptane-3,5-diketonate, ozl is 2-(4,5-dihydrooxazol-2-yl)phenol, and iml is 2-(1-ethyl-4,5-dihydro-1 H -imidazol-2-yl)phenol. Radiative rate constant for phosphorescence ( k r ) is calculated by quadratic response time-dependent density functional theory (QR-TDDFT). The transition dipole moment, spin-orbit coupling matrix element, and singlet-triplet splitting energy related with the k r are also analyzed to further uncover the crucial factors to affect the k r . While the nonradiative rate constant for phosphorescence ( k nr ) is qualitatively estimated from both temperature-independent nonradiative rate constant ( k ′ nr ) and temperature-dependent nonradiative rate constant ( k nr (T)) viewpoints. The emissive wavelength of new designed Ir(III) complex 4 locates in the deeply red region. Moreover, it has the larger quantum yield because of both larger k r and smaller k nr . The variation of ancillary ligand is also an advisable choice to develop red-emitting Ir(III) complex with ideal quantum efficiency. [ABSTRACT FROM AUTHOR]

Multivariable adaptive control is an important and challenging research area, where it usually requires designing adaptive laws to estimate a number of unknown parameters. Hence, this process may excessively consume limitedly available computational resources and large amount of computational time, which may degrade system performances, particularly for the case of online updating of parameter estimates. Thus reducing the number of parameters to be estimated is a promising way to solve the problem. The state-of-the-art result in the area is to update just one adaptive parameter. However, the tracking errors are only ensured bounded and thus the resulting closed-loop system is not asymptotically stable. Hence, a question that arises is whether such a result of non-zero tracking errors is the price paid for reducing the number of updating parameters. Up to now, there is still no answer to this question. In this paper, we address such an issue and realize asymptotic stability with online estimation of just one parameter. To achieve such a goal, a novel dynamic loop gain function based approach is proposed to incorporate with the backstepping control design procedure, which enables us to solve the algebraic loop problem caused by all the existing traditional Nussbaum function based approaches and thus establish system stability. A bound for the tracking error is explicitly established in terms of L 2 norm, which helps improve the transient performance by selecting the control parameters. Moreover, guaranteed by the Barbalat’s Lemma, the tracking error is further ensured to approach zero asymptotically. Finally, simulation examples are conducted to testify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Fused deposition modeling (FDM) is a process of fabricating three-dimensional physical models by layered manufacturing. However, the surface quality of acrylonitrile butadiene styrene (ABS) built with FDM technologies is not acceptable and is not satisfactory for most general engineering purposes. In this study, a polishing system was demonstrated to enhance surface finish of ABS parts fabricated by FDM. Polishing mechanism for ABS parts was investigated. The features of this system include high polishing efficiency, no waste chemicals, ease of operation, with excellent dimensional accuracy, and low equipment costs. Improving surface roughness of ABS parts by the use of acetone vapor not only has required dimensional accuracy but also has high process stability. A great reduction in average surface roughness for ABS parts about 98% was obtained. The polishing mechanisms for ABS parts fabricated by additive manufacturing were investigated in this study. [ABSTRACT FROM AUTHOR]

To achieve satisfying motion/force objectives, it is required for the multiarm robot manipulation to tackle unknown nonlinearities and uncertainties. Existing control schemes have a requirement that the deadzone nonlinearity in the sensor channel could be ignored. However, the sensor deadzone is widely spread in real world applications; and its existence significantly limits the robotic performances. Moreover, the kinematics and dynamics of the manipulated object cannot be accurately known as the prior knowledge. Hence, such robotic systems may not be perfectly controlled by conventional approaches. In this paper, a coordinated motion/force control method is presented to handle unknown sensor deadzone and object’s uncertainty. The proposed method ensures the motion and internal force errors be bounded in a small neighborhood around the origin. Finally, comparative studies are presented to show the effectiveness and robustness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Reinforcement learning provides a powerful tool for designing a satisfactory controller through interactions with the environment. Although off-policy learning algorithms were recently designed for tracking problems, most of these results either are full-state feedback or have bounded control errors, which may not be flexible or desirable for engineering problems in the real world. To address these problems, we propose an output-feedback-based reinforcement learning approach that allows us to find the optimal control solution using input–output data and ensure the asymptotic tracking control of continuous-time systems. More specifically, we first propose a dynamical controller revised from the standard output regulation theory and use it to formulate an optimal output tracking problem. Then, a state observer is used to re-express the system state. Consequently, we address the rank issue of the parameterization matrix and analyze the state re-expression error that are crucial for transforming the off-policy learning into an output-feedback form. A comprehensive simulation study is given to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In quadratic optimal control theory, the multivariable linear quadratic regulator is guaranteed to have excellent stability margins if the weight on the control inputs is diagonal. However, for the non-diagonal case, it may suffer from poor robustness. In this paper, these robustness properties are studied in relation to weight selection. For general weighting matrices, a new lower bound on the minimum singular value of the return difference is presented. New guaranteed stability margins are also presented. This gives a formal mathematical basis for guidelines for weight selection. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The mechanism of reaction HCNO + HO2 is investigated by means of CCSD(T)/6-311 + G(d,p)//B3LYP/6-311 + G(d,p) method, in which Pi with the i = 1, 2, 3, ..., 7 are involved, to determine a more reasonable pathway. Among four possible entrance patterns, the attack of oxygen to carbon is the most energetically feasible leading to complex a1. Starting from the a1, the rupture of O2–O3 bond to form P3 (HC(O)NO + OH) is the most favorable pathway. Alternatively, the a1 undergoes N–O1 bond rotation to form the isomer a2. A concerted O2–O3 bond and C–N bond cleavage leading to P4 (OH + HCO + NO) is the secondary feasible pathway. Other products are not energetically accessible because of higher barrier-consumed and/or complicated processes. We hope that the present work would be helpful to experimentally identify the product distributions and deeply understand the mechanism of the title reaction. [ABSTRACT FROM AUTHOR]

To isolate the mounted object from the vibration sources, it is required that the qualities of the actuators in an active vibration isolation system are highly promising. Therefore, it is unreasonable to ignore actuator nonlinearity to realize the excellent performances of the vibration isolation. In this paper, the problem of unknown actuator backlash in the vibration isolation system is investigated. To handle the lines–segments backlash nonlinearity, an adaptive smooth backlash inverse is employed to compensate the deleterious effect. Moreover, a promising controller is proposed to ensure that the motion of the moving platform converges to desired values. Based on Lyapunov’s second method, all of the involved signals in the closed-loop system are proved to be stable. Finally, comparative studies involving active vibration isolation with actuator backlash are constructed and carried out to validate the effectiveness of the proposed control scheme. [ABSTRACT FROM PUBLISHER]

Recent results have emerged that policy iteration is a powerful reinforcement learning tool in designing a stabilizing control policy for continuous-time systems with unknown system dynamics. Policy iteration involves a model-based initialization stage, i.e., seeking an initial stabilizing control policy, which is, however, dependent on the full system dynamics including the drift dynamics and system input matrix. To remove such model requirements, this paper utilizes a homotopy-based initialization strategy for policy iteration, wherein a stabilizing control policy for continuous-time systems is obtained by gradually moving a stable system to the original system. We propose two homotopic policy iteration-based stabilizing control schemes, namely, a model-based design and a model-free design using system data, which are proved to place unstable poles into a stable region. The effectiveness of the proposed designs is validated through an illustrative example. [ABSTRACT FROM AUTHOR]

The Ankrd1 (ankyrin repeat domain 1) gene is known to be up-regulated in heart failure and acts as a co-activator of p53, modulating its transcriptional activity, but it remains inconclusive whether this gene promotes or inhibits cell apoptosis. In the present study, we attempted to investigate the role of Ankrd1 on AngII (angiotensin II)- or pressure-overload-induced cardiomyocyte apoptosis. In the failing hearts of mice with pressure overload, the protein expression of Ankrd1-encoded CARP (cardiac ankyrin repeat protein) was significantly increased. In NRCs (neonatal rat cardiomyocytes), AngII increased the expression of Ankrd1 and CARP. In the presence of AngII in NRCs, infection with a recombinant adenovirus containing rat Ankrd1 cDNA (Ad-Ankrd1) enhanced the mitochondrial translocation of Bax and phosphorylated p53, increased mitochondrial permeability and cardiomyocyte apoptosis, and reduced cell viability, whereas these effects were antagonized by silencing of Ankrd1. Intra-myocardial injection of Ad-Ankrd1 in mice with TAC (transverse aortic constriction) markedly exacerbated cardiac dysfunction with an increase in the lung weight/body weight ratio and a decrease in left ventricular fractional shortening. Cardiomyocyte apoptosis and the expression of phosphorylated p53 were also significantly increased in Ad-Ankrd1-infected TAC mice, whereas knockdown of Ankrd1 significantly inhibited the apoptotic signal pathway as well as cardiomyocyte apoptosis in pressure-overload mice. These findings indicate that overexpression of Ankrd1 exacerbates pathological cardiac dysfunction through enhancement of cardiomyocyte apoptosis mediated by the up-regulation of p53. [ABSTRACT FROM AUTHOR]

The gene ankyrin repeat domain 1 (Ankrd1) is an enigmatic gene and may exert pleiotropic function dependent on its expression level, subcellular localization and even types of pathological stress, but it remains unclear how these factors influence the fate of cardiomyocytes. Here we attempted to investigate the role of CARP on cardiomyocyte hypertrophy. In neonatal rat ventricular cardiomyocytes (NRVCs), angiotensin II (Ang II) increased the expression of both calpain 1 and CARP, and also induced cytosolic translocation of CARP, which was abrogated by a calpain inhibitor. In the presence of Ang-II in NRVCs, infection with a recombinant adenovirus containing rat Ankrd1 cDNA (Ad-Ankrd1) enhanced myocyte hypertrophy, the upregulation of atrial natriuretic peptide and β-myosin heavy chain genes and calcineurin proteins as well as nuclear translocation of nuclear factor of activated T cells. Cyclosporin A attenuated Ad-Ankrd1-enhanced cardiomyocyte hypertrophy. Intra-myocardial injection of Ad-Ankrd1 in mice with transverse aortic constriction (TAC) markedly increased the cytosolic CARP level, the heart weight/body weight ratio, while short hairpin RNA targeting Ankrd1 inhibited TAC-induced hypertrophy. The expression of calcineurin was also significantly increased in Ad-Ankrd1-infected TAC mice. Olmesartan (an Ang II receptor antagonist) prevented the upregulation of CARP in both Ang II-stimulated NRVCs and hearts with pressure overload. These findings indicate that overexpression of Ankrd1 exacerbates pathological cardiac remodeling through the enhancement of cytosolic translocation of CARP and upregulation of calcineurin. [ABSTRACT FROM AUTHOR]

In this work, an event-triggered coordination problem for multi-agent systems with general linear dynamics is considered over directed communication graphs with a spanning tree. We study such a problem by using a Lyapunov equation for leaderless consensus. It is shown that a Lyapunov-based approach can complete stability analysis of event-triggered consensus of multi-agent systems over general directed graphs. [ABSTRACT FROM AUTHOR]

Abstract: In this study, both experiments and simulations are performed to investigate the thermal-fluid characteristics of a flat-fin heat sink with a pair of vortex generators installed in a cross flow channel. The effects of the distance between the trailing edges of the vortex generators, the distance between each vortex generator and the heat sink, the attack angle of the vortex generators, the height of the vortex generators, the configuration of the vortex generators, and the Reynolds number on the thermal-fluid performance of the plate-fin heat sink are elucidated. The performance of the heat sink with the vortex generators was compared to that without. The results thus obtained revealed that when the distance between the trailing edges of the vortex generators is too small, the thermal performance becomes worse because the air cannot easily flow into the heat sink. Regarding the effect of the position of the vortex generators on thermal performance, the best performance is achieve when the distance between the vortex generator trailing edges equals the length of the heat sink and the distance between the trailing edge of each vortex generator and the front end of the heat sink is zero. An attack angle of the vortex generators of 30° is preferred to optimize the thermal resistance and pressure difference. Although heat transfer increases with the height of the vortex generators, the pressure difference also increases. Regarding the effect of the configuration of the vortex generators on the performance of the heat sink, a common-flow-up configuration outperforms a common-flow-down configuration. The enhancement of the heat transfer of the heat sink by the use of vortex generators is greater, and the increase of the pressure difference is lower, at lower Reynolds numbers. [Copyright &y& Elsevier]

As an indispensable branch of machine learning (ML), reinforcement learning (RL) plays a prominent role in the decision-making process of autonomous driving (AD), which enables autonomous vehicles (AVs) to learn an optimal driving strategy through continuous interaction with the environment. This paper proposes a deep reinforcement learning (DRL)-based motion planning strategy for AD tasks in the highway scenarios where an AV merges into two-lane road traffic flow and realizes the lane changing (LC) maneuvers. We integrate the DRL model into the AD system relying on the end-to-end learning method. An improved DRL algorithm based on deep deterministic policy gradient (DDPG) is developed with well-defined reward functions. In particular, safety rules (SR), safety prediction (SP) module and trauma memory (TM) as well as the dynamic potential-based reward shaping (DPBRS) function are adopted to further enhance safety and accelerate learning of the LC behavior. For validation, the proposed DSSTD algorithm is trained and tested on the dual-computer co-simulation platform. The comparative experimental results show that our proposal outperforms other benchmark algorithms in both driving safety and efficiency. [ABSTRACT FROM AUTHOR]

Amyloidogenic processing of the amyloid-β protein precursor (AβPP) produces amyloid-β peptides (Aβ), the major constituent of amyloid plaques in the brains of Alzheimer's disease (AD) patients. Experimental evidence suggests that increased dimerization of AβPP increases Aβ while decreased dimerization of AβPP decreases Aβ production. If true, developing tools for detecting AβPP-AβPP interactions to understand AβPP processing leading to Aβ production would be important. Here, we developed the method of β-galactosidase (β-gal) enzyme fragment complementation as a means to detect AβPP-AβPP interactions. Inactive β-gal fragments are independently tagged to the C-terminal ends of monomeric AβPPs, and will come together to form a functional enzyme upon AβPP-AβPP interactions. Successful detection of β-gal activity has been used to qualitatively visualize and quantify the amount of AβPP dimers or higher oligomers. This method can be used to enhance our understanding of the biological processes dependent upon AβPP-AβPP interactions. [ABSTRACT FROM AUTHOR]

Summary: Objectives: The aim of this study was to develop a low shrinkage visible light curable nanocomposite dental restorative material without sacrificing the other properties of conventional materials. This nanocomposite was developed by using an epoxy resin 3,4-epoxycyclohexylmethyl-(3,4-epoxy)cyclohexane carboxylate (ERL4221) matrix with 55% wt of 70–100nm nanosilica fillers through ring-opening polymerization. GPS (γ-glycidoxypropyl trimethoxysilane) was used to modify the surfaces of silica nanoparticles. Results: The nanocomposite was shown to exhibit low polymerization shrinkage strain, which is only a quarter of currently used methacrylate-based composites. It also exhibited a low thermal expansion coefficient of 49.8μm/m°C which is comparable to that of the methacrylate based composites (51.2μm/m°C). The strong interfacial interactions between the resin and fillers at nanoscales were demonstrated by an observed high strength and high thermal stability of the nanocomposite. A microhardness of 62KHN and a tensile strength of 47MPa were reached. A high degree of conversion (∼70%) can be obtained after less than 60s of irradiation upon the nanocomposite. A transmission electron microscope (TEM) study of the nanocomposite showed no aggregation of fillers. Comparable results to the methacrylate based composites were obtained from the one day MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide) cytotoxicity test. Significance: The developed epoxy resin based nanocomposite demonstrated low shrinkage and high strength and is suitable for dental restorative material applications. [Copyright &y& Elsevier]

Presents information on a study that determined the mobility of cytochrome 450 in the endoplasmic reticulum membrane. Materials and methods; Results; Discussion.

The resilience of multi-agent systems (MAS) measures the capability of recovering the cooperative performance after experiencing faults or uncertainties. In this paper, we seek the improvement of the synchronization resilience for MAS by means of addressing unknown faults on communication links. To this end, we first transform the resilient control problem into designing distributed state observers. In addition, we show that the proposed state observers are resilient to communication link faults. Finally, we provide the main result of this paper as a synchronization protocol for MAS even in the presence of communication link faults. [ABSTRACT FROM AUTHOR]

With the rapid development of industrial internet of things, multi-sensor technology has been widely used in system condition monitoring and residual useful life (RUL) estimation, which plays a crucial role in preventing catastrophic failures and reducing maintenance losses. However, current prognosis using multi-sensor data faces the following challenges: (i) Manual feature selection and extraction and exploration of degradation failure mechanism for a complex domain require a substantial amount of human labor and expertise from the practitioner, which is seldom available. (ii) Data fusion and prognosis are usually divided into two separate steps, resulting in the lack of intrinsic relationship between the two tasks. (iii) The end-to-end prediction methods directly based on deep learning behave like the black-box and provide no information for degradation progression. To overcome these drawbacks, a prediction framework comprising two deep learning models is proposed in this paper. Through the proposed supervised joint training scheme, the framework not only provides a continuous visualization progression of system degradation but also ensures that the generated fusion signal effectively performs in RUL prediction. As a framework application, a joint model of RUL estimation based on an ordinary long short-term memory network is designed. In the experiment section, a simulation study is firstly performed to show its RUL prediction performance. Then, a case study is conducted using two public experimental data sets (the aircraft turbofan engine data and the milling). Furthermore, the advantage of the proposed joint model is validated by carrying out a comparison with other methods based on the same experimental data sets. [ABSTRACT FROM AUTHOR]

GDP-amylose transporter protein 1 (SLC35C1) plays an important role in many types of cancer. Therefore, it is clinically important to further investigate the expression profile of SLC35C1 in human tumors to provide new molecular clues for the pathogenesis of glioma. In this study, we performed a comprehensive pan-cancer analysis of SLC35C1 using a series of bioinformatics approaches and validated its differential tissue expression and biological function. The results showed that SLC35C1 was aberrantly expressed in different types of tumors and significantly correlated with overall survival (OS) and progression-free interval (PFI). More importantly, the expression level of SLC35C1 was closely correlated with Tumor Microenvironment (TME), immune infiltration and immune-related genes. In addition, we found that SLC35C1 expression was also closely related to Tumor Mutation Burden (TMB), Microsatellite Instability (MSI) and antitumor drug sensitivity in various cancer types. Functional bioinformatics analysis indicated that SLC35C1 may be involved in multiple signaling pathways and biological processes in glioma. Based on SLC35C1 expression, a risk factor model was found to predict OS of glioma. In addition, in vitro experiments showed that SLC35C1 knockdown significantly inhibited the proliferation, migration and invasive ability of glioma cells, while SLC35C1 overexpression promoted proliferation, migration, invasion and colony formation of glioma cells. Finally, quantitative real-time PCR confirmed that SLC35C1 was highly expressed in gliomas. [ABSTRACT FROM AUTHOR]

The electronic, optical, and hole transporting mobility of three organic hole transporting materials (HTMs), X59, X59-P, and X59-T, are investigated by combination of first principle and molecular dynamics associated with Marcus theory and Einstein equation. As compared with the experimental reported X59, the new designed X59-P has more stable HOMO energy level. Moreover, the latter has smaller reorganization energy and larger hole transfer integral resulting in the larger hole transporting mobility. Besides the hole transporting mobility, the solubility and stability of two designed molecules are also evaluated by comparison with X59, which are two important items to determine the cost and performance in real application of solar cell. More importantly, they would be synthesized in a benign condition without expensive materials. Our studies introduce a possible pathway to explore the efficient HTMs by suitable combination mode rather than development of new groups. [ABSTRACT FROM AUTHOR]

With the increasing demand for secure biometric identification systems, finger vein recognition has received widespread attention. Recent studies have made progress in the verification of finger veins, but the extraction of the discriminative features of finger veins from images remains challenging. Although the traditional method of extracting features by combining softmax function and cross-entropy loss function can achieve separation between classes, it lacks discriminability. In addition, the method of setting a fixed margin yields good results, but it may cause some features to overlap. We argue that when some features are separated well from other features, the margin set needs to be reduced. Therefore, a dynamic margin softmax loss (dynamic softmax) is proposed in this study to obtain discriminative image features. Features and weight vectors are normalized, and the loss function dynamics are subsequently adjusted to achieve different cosine intervals for different classes. The main idea of this method is to maximize the distance between inter-class and minimize the distance between intra-class. This method can keep features separated without increasing the complexity of optimizing the neural network model. It is simpler and more effective than other loss functions. Experiments prove the effectiveness of the proposed method for finger vein recognition. [ABSTRACT FROM AUTHOR]

We propose a novel, computationally efficient, and robust light detection and ranging (LiDAR)-only odometry framework based on truncated least squares termed T-LOAM. Our method focuses on alleviating the impact of outliers to allow robust navigation in sparse, noisy, or cluttered scenarios where degeneration occurs. As preprocessing, the multiregion ground extraction and dynamic curved-voxel clustering methods are proposed to accomplish the segmentation of 3D point clouds and filter out unstable objects. A novel feature extraction module is tailored to discriminate four peculiar features: edge features, sphere features, planar features, and ground features. As frontend, a hierarchical feature-based LiDAR-only odometry performs precise motion estimates through the truncated least squares method for directly processing various features. The preprocessing model and motion estimation precision have been evaluated on the KITTI odometry benchmark as well as various campus scenarios. The experimental results have demonstrated the real-time capability and superior precision of the proposed T-LOAM over other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

As the hardware of FLIM technique becomes mature, the most important criterion for FLIM application is the correct interpretation of its data. In this research, first of all, a more orthogonal phasor approach, called as Modified Phasor Approach (MPA), is put forward. It is a way to calculate the lifetime of the complex fluorescent process, and a rule to measure how much the fluorescence process deviates from single exponential decay. Secondly, MPA is used to analysis the time-resolved fluorescence processes of the transfected CHO-K1 Cell lines expressing adenosine receptor AR tagged by CYP and YFP, measured in the channel of the acceptor. The image of the fluorescence lifetime and the multiplication of the fluorescence lifetime and deviation from single exponential decay reveal the details of the Homo-FRET. In one word, MPA provides the physical meaning in its whole modified phasor space, and broadens the way for the application of the fluorescence lifetime imaging. [ABSTRACT FROM AUTHOR]

The Asian citrus psyllid, Diaphorina citri is the principal vector of huanglongbing, which transmits Candidatus Liberibacter asiaticus. Trehalase is a key enzyme involved in trehalose hydrolysis and plays an important role in insect growth and development. The specific functions of this enzyme in D. citri have not been determined. In this study, three trehalase genes (DcTre1‐1, DcTre1‐2, and DcTre2) were identified based on the D. citri genome database. Bioinformatic analysis showed that DcTre1‐1 and DcTre1‐2 are related to soluble trehalase, whereas DcTre2 is associated with membrane‐bound trehalase. Spatiotemporal expression analysis indicated that DcTre1‐1 and DcTre1‐2 had the highest expression levels in the head and wing, respectively, and DcTre2 had high expression levels in the fat body. Furthermore, DcTre1‐1 and DcTre1‐2 expression levels were induced by 20‐hydroxyecdysone and juvenile hormone Ⅲ, but DcTre2 was unaffected. The expression levels of DcTre1‐1, DcTre1‐2, and DcTre2 were significantly upregulated, which resulted in high mortality after treatment with validamycin. Trehalase activities and glucose contents were downregulated, but the trehalose content increased after treatment with validamycin. In addition, the expression levels of chitin metabolism‐related genes significantly decreased at 24 and 48 h after treatment with validamycin. Furthermore, silencing of DcTre1‐1, DcTre1‐2, and DcTre2 reduced the expression levels of chitin metabolism‐related genes and led to a malformed phenotype of D. citri. These results indicate that D. citri trehalase plays an essential role in regulating chitin metabolism and provides a new target for control of D. citri. [ABSTRACT FROM AUTHOR]