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In this note we study the generation of non‐trivial oscillations of a class of mechanical systems with underactuation one. The proposed design consists of two terms, that is, a partial linearizing state feedback, and an immersion and invariance orbital stabilization controller. The first step is adopted to simplify analysis and design, however, bringing an additional difficulty that the model loses its Euler–Lagrange structure after the collocated pre‐feedback. To address this, we propose a constructive solution to the orbital stabilization problem via a smooth controller in an analytic form, and the model class identified in the article is characterized via some easily a priori verifiable assumptions on the inertia matrix and the potential energy function. [ABSTRACT FROM AUTHOR]

Dengue virus (DENV) is the cause of dengue fever, infecting 390 million people worldwide per year. It is transmitted to humans through the bites of mosquitoes and could potentially develop severe symptoms. In spite of the rising social and economic impact inflicted by the disease on the global population, a conspicuous lack of efficacious therapeutics against DENV still persists. In this study, catechin, a natural polyphenol compound, was evaluated as a DENV infection inhibitor in vitro. Through time-course studies, catechin was shown to inhibit a post-entry stage of the DENV replication cycle. Further investigation revealed its role in affecting viral protein translation. Catechin inhibited the replication of all four DENV serotypes and chikungunya virus (CHIKV). Together, these results demonstrate the ability of catechin to inhibit DENV replication, hinting at its potential to be used as a starting scaffold for further development of antivirals against DENV infection. [ABSTRACT FROM AUTHOR]

Machining contours on a large thin-walled part is a difficult task due to inevitable deformation of the actual part. The deformation of the contour can significantly influence the rigidity of the thin-walled part; thus, it is of importance to minimize the deformation of the contour compared with the design contour. This paper proposes a novel method to adaptively calculate the optimal contour on the deformed surface based on optimized parallel projection. The geometry data of free-form surface is obtained by on-machine measurement (OMM), and then, the actual surface is reconstructed using the measurement data. The reconstructed surface is matched with the design surface, and then, the design contour was projected onto the reconstructed surface to obtain the locating contour. The iterative nearest point (ICP) algorithm is used to adjust the design contour to match the locating contour. Finally, the projection direction is optimized to minimize contour deformation, and the adjusted contour is projected onto the reconstructed surface along the optimal direction to obtain the new contour. The effectiveness of this method is verified by machining and measuring experiments. [ABSTRACT FROM AUTHOR]

Surface reconstruction is an essential operation in the evaluation of free-form surface form error. As a feasible technology in free-form surface sampling, touch-trigger probing has been widely used in on-machine measurement and coordinate measurement machine. However, surface reconstruction quality is influenced by limited sampling point size. This study proposes a surface reconstruction method based on surface position error and deformation error model. Surface form error is decomposed into surface position error and deformation error. Then, the design surface is taken as a rigid body, and a point-to-surface function-based iterative algorithm is conducted to adjust surface location and orientation to best match the sampling points. The advantage of this algorithm is that it considers the probe dimension, so further compensation of probe radius is not required. The geometry of the adjusted design surface is modified based on thin plate energy minimization and point-to-surface function. Due to the inherent feature of the proposed method, geometric features of the design surface are kept. Experiments are conducted to verify the effectiveness of the proposed method, and results show that the proposed method can achieve lower error compared with existing methods. • Surface location error and deformation error are defined and computed to evaluate the form error. • Geometry of the measured surface is modified based on thin plate energy minimization and point-to-surface function. • Experiment results show that the reconstruction accuracy is improved by 37.9%, compared with an existing method. [ABSTRACT FROM AUTHOR]

Free-form surfaces have been widely used in aerospace, automotive and other fields. Due to its complex geometry, free-form surface inspection is generally conducted by touch-trigger or measuring probe-based Coordinate Measurement Machines or On-machine Measurement. Sampling strategy plays a decisive role in improving both measurement accuracy and efficiency, which is determined by sample size and distribution of sample points. However, it is difficult to simultaneously take the surface curvature, sampling density and approximation error into account, considering the complexity of surface geometry. In this paper, triangle mesh simplification is innovatively adopted in sampling planning to achieve multi-geometric constraints. As triangle mesh has outstanding advantages in representing the surface features, strong stability and is easy to modify its structure, free-form surface is converted to a dense triangle mesh. Triangle mesh simplification is implemented by iteratively contracting triangle edges. An improved quadric error metric is established to decide contraction order and optimal target vertices under discrete curvature constraint. Sampling density is controlled by limiting the triangle edge length. Detailed adaptive sampling algorithm under multi-geometric constraints is then developed. Both simulation and experiment are conducted to validate feasibility and robustness of the proposed method. The results are compared with uniform sampling and existing adaptive sampling strategy to show that the proposed method can prominently reduce sampling error when sample size is small. • Free-form surface sampling method under multi-geometric constraints can improve sampling accuracy. • Both surface curvature and sampling density are necessary in surface sampling. • Triangle mesh simplification is firstly used for multi-geometric constraints-based surface sampling. [ABSTRACT FROM AUTHOR]

In this paper, we study the performance enhancement of tracking control for a class of nonlinear systems with prescribed performance, by employing a novel pair of prescribed monotone tube boundary functions. Compared to the standard prescribed performance approach, the key merit relies on the capability to assign some quantitative indices (e.g., overshoot, accuracy and convergence time) – which are widely required in industry – in terms of the novel links between these indices and the proposed boundary functions. We provide a constructive solution to achieve the pre-assigned performance, which is characterized by forward invariance and boundedness of the closed loop. [ABSTRACT FROM AUTHOR]

Summary: This article aims to provide a new problem formulation of path following for mechanical systems without time parameterization nor guidance laws, namely, we express the control objective as an orbital stabilization problem. It is shown that it is possible to adapt the immersion and invariance technique to design static state‐feedback controllers that solve this problem. In particular, we select the target dynamics adopting the recently introduced Mexican sombrero energy assignment method. To demonstrate the effectiveness of the proposed method we apply it to control underactuated marine surface vessels. [ABSTRACT FROM AUTHOR]

Summary: In this article we propose an energy pumping‐and‐damping technique to regulate nonholonomic systems described by kinematic models. The controller design follows the widely popular interconnection and damping assignment passivity‐based methodology, with the free matrices partially structured. Two asymptotic regulation objectives are considered: drive to zero the state or drive the systems total energy to a desired constant value. In both cases, the control laws are smooth, time‐invariant, state‐feedbacks. For the nonholonomic integrator we give an almost global solution for both problems, with the objectives ensured for all system initial conditions starting outside a set that has zero Lebesgue measure and is nowhere dense. For the general case of higher order nonholonomic systems in chained form, a local convergence result is given. Simulation results comparing the performance of the proposed controller with other existing designs are also provided. [ABSTRACT FROM AUTHOR]

Summary: Immersion and invariance is a technique for the design of stabilizing and adaptive controllers and state observers for nonlinear systems. In all these applications the problem considered is the stabilization of equilibrium points. Motivated by some modern applications, we show that the technique can also be used to solve the problem of orbital stabilization, where the final objective is to generate periodic solutions that are attractive. The feasibility of our result is illustrated by means of some classical mechanical engineering and power electronics examples. [ABSTRACT FROM AUTHOR]

For leader-following multiagent systems with input saturation, the existing protocols use a low gain feedback approach to achieve semi-global consensus. The main drawback of this approach is the ineffective utilization of the actuator potential, resulting in bad performance. To improve the transient performance of the consensus tracking, this paper proposes a gain scheduled approach for multiagent systems subject to the saturator saturations. A novel kind of scheduler-based protocols are proposed, which consists of state feedback controllers with time-varying gain and parameter schedulers. The role of the controllers is to achieve the consensus tracking, while the schedulers can accelerate this consensus progress by enlarging the gain parameter. To remove the dependence of the schedulers on global information, a minimum-value-based consensus algorithm is put forward, with idea of driving all values of agents throughout the network to their minimum value. Its implementation is guaranteed by the network-topology connectivity. Finally, our approach is further extended to the case where the leader’s control input is nonzero, time-varying, and bounded. The discontinuous protocol and its continuous approximation counterpart are designed, yielding the exact- and quasi-consensus tracking, respectively. Simulation results verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper presents an output feedback indirect dynamic inversion (IDI) approach for a class of uncertain nonaffine systems with input unmodelled dynamics. Compared with previous approaches to achieve performance recovery, the proposed method aims at dealing with a broader class of nonaffine-in-control systems with triangular structure. An IDI state feedback law is designed first, in which less knowledge of the model plant is needed compared to earlier approximate dynamic inversion methods, thus yielding more robust performance. After that, an extended high-gain observer is designed to accomplish the task with output feedback. Finally, we prove that the designed IDI controller is equivalent to an adaptive proportional-integral (PI) controller, with respect to both time response equivalence and robustness equivalence. The conclusion implies that for the studied strict-feedback non-affine systems with unmodelled dynamics, there always exits a PI controller to stabilise the systems. The effectiveness and benefits of the designed approach are verified by three examples. [ABSTRACT FROM PUBLISHER]

Parameter estimation-based observers are a new kind of state reconstruction methods where the state observation task is translated into an on-line parameter estimation problem. A key step for its application is the transformation of the system dynamics into a particular cascade form, which involves the solution of a partial differential equation that, moreover, should satisfy some injective requirement. In this note we use a recently proposed technique of signal injection to generate new outputs and simplify these tasks. In this way, we make this observer applicable to a wider class of nonlinear systems—even with indistinguishable states. The application of the proposed approach is illustrated with the design of a novel sensorless controller for magnetic levitation systems. [ABSTRACT FROM AUTHOR]

This paper deals with the trajectory tracking problem of autonomous underwater vehicles (AUVs) in the presence of dynamic uncertainties and time-varying external disturbances. Three exponentially convergent robust controllers, namely, the min-max type controller, the saturation type controller and the smooth transition type controller are proposed to drive an AUV to track a predefined trajectory. It is shown that the filtered tracking errors, position tracking errors and velocity tracking errors for the three proposed controllers are exponentially convergent. Moreover, all the above tracking errors for the three proposed controllers can be shaped by specific analytic expressions and such expressions illustrate how the transient responses of the above tracking errors can be modified by adjusting the control parameters. The characteristics of the three proposed controllers are summarized and demonstrated with numerical simulations. Theoretical comparison analysis and comparative simulations with the existing RISE-based controller of AUV are presented to show the effectiveness of the three proposed exponentially convergent robust controllers. [ABSTRACT FROM AUTHOR]

The paper aims to develop a novel path following control law for nonlinear vessel models in two-time scales. For the 4-DOF path following model, we explore that the guidance dynamics are much slower than the ship motion dynamics. Based on such characteristic, a singular perturbation method is used to decompose the full system into two-time-scale subsystems. The two-time-scale structure allows independent analysis of dynamics in each time scale. Separate control strategies for the quasi-steady-state subsystem and the boundary layer subsystem are designed to stabilize the full system, yielding a rudder angle control law which is compact and uncomplicated to implement in practice. Singular perturbation methods are utilized to provide mathematical expressions for the upper bound of the singularly perturbed parameter and establish the exponential stability of the full system. The paper proves that the control law is robust in the presence of bounded perturbations and unmodeled dynamics, resulting states converge into an invariant set arbitrarily closed to the origin. Simulation results show the effectiveness and robustness of the proposed method for path following. The primary benefit of the proposed method is the simplicity of implementation. [ABSTRACT FROM AUTHOR]

The design of a globally convergent position observer for feature points from visual information is a challenging problem, especially for the case with only inertial measurements and without assumptions of uniform observability, which remained open for a long time. We give a solution to the problem in this paper assuming that only the bearing of a feature point, and biased linear acceleration and rotational velocity of a robot – all in the body-fixed frame – are available. Further, in contrast to existing related results, we do not need the value of the gravitational constant either. The proposed approach builds upon the parameter estimation-based observer recently developed in Ortega et al. (2015) and its extension to matrix Lie groups in our previous work. Conditions on the robot trajectory under which the observer converges are given, and these are strictly weaker than the standard persistency of excitation and uniform complete observability conditions. Finally, as an illustration, we apply the proposed design to the visual inertial navigation problem. [ABSTRACT FROM AUTHOR]

The increasing energy and material consumption associated with global economic growth has resulted in the need for more severe efforts at mitigating global climate change. The iron and steel industry consumes 8% of energy and emits 7% of total CO 2 globally. China's iron and steel industry contributes to 15% of that country's total CO 2 emissions. Therefore, there is an urgent need to explore the possibility of net zero emissions in the iron and steel industry in China to meet China's goal of carbon neutrality before 2060. In the study presented in this paper, the MESSAGEix–China iron and steel model was developed by integrating the process-based technology of the sector into the IIASA's MESSAGEix framework to explore zero CO 2 emission pathways and their associated impacts on resources, energy, and water in China's iron and steel industry up to 2100. We found that there are multiple pathways to achieving zero CO 2 emissions in the Chinese iron and steel industry by the end of the 21st century. More specifically, in all the pathways developed in this study, CO 2 emissions decreased significantly between 2030 and 2060 due to the rapid application of 100% scrap-based Electric Arc Furnaces (EAFs) and hydrogen-based Direct Reduced Iron (DRI)-EAFs steel-making technologies. However, by 2060, there will still be 70–360 Mt of CO 2 emissions from China's iron and steel industry; consequently, carbon sink or negative emission technologies are required to offset this and achieve the country's carbon neutrality goal. Furthermore, technologies for achieving zero emissions differ widely in terms of their impacts on the consumption of materials and energy. Compared to the electric (ELE) scenarios, 25–40% of extra iron ore is consumed in the current and new national policy (NPS) scenarios and the DRI scenarios, but 25–220% of scrap is required. At the same time, 20–150% more energy will be saved in the ELE scenarios than in the NPS and DRI scenarios. Finally, we recommend that policy makers design a cross-cutting strategy to achieve zero CO 2 emissions and enhance efforts for material recycling and the provision of clean energy and water. • There are multiple pathways to achieving net zero emissions in China's iron and steel industry. • Steel outputs are essential for reducing CO 2 emissions and conserving materials, energy, and water. • Hydrogen-based DRI and 100% scrap-EAFs technologies are key to achieving zero emissions. • CO 2 mitigation measures have limited impacts on water consumption. [ABSTRACT FROM AUTHOR]

B-spline curve approximation is widely used for fitting linear toolpaths to improve machining quality and efficiency in CNC machining. For a high-quality smoothing method, the control of both approximation error and curve curvature needs to be taken into account. To reduce the maximum curve curvature while meeting the precision requirements, a B-spline approximation scheme with tool tip position adjustment is proposed in this paper. Toolpaths are first divided into several subdivisions according to the discrete curvature of each tool tip point. For subdivisions that need adjustment, tool tip positions are adjusted to minimize the maximum discrete curvature. An existing approximation method named energy-term-incorporated progressive and iterative approximation for least square fitting (ELSPIA) is selected and improved to fit the adjusted toolpaths and lower the chord errors. For improving the numerical stability of the ELSPIA method, the way of searching appropriate foot point parameters is discussed in this paper. Deviation expansion factors of tooltip points are also defined to make the ELSPIA method suitable for fitting the adjusted toolpaths. Both simulations and experimental studies are conducted to prove that the proposed method can significantly decrease the maximum curvature of fitted B-spline curves and improve the machining efficiency without exceeding the tolerance. For example, experimental results show that for the tested butterfly and rabbit toolpaths, the proposed method can improve the machining efficiency by 2.61% and 2.37%, compared with the ELSPIA method without tool tip position adjustment. [ABSTRACT FROM AUTHOR]

In this paper we provide two significant extensions to the recently developed parameter estimation-based observer design technique for state-affine systems. First, we consider the case when the full state of the system is reconstructed in spite of the presence of unknown, time-varying parameters entering into the system dynamics. Second, we address the problem of reduced order observers with finite convergence time. For the first problem, we propose a simple gradient-based adaptive observer that converges asymptotically under the assumption of generalised persistent excitation. For the reduced order observer we invoke the advanced dynamic regressor extension and mixing parameter estimator technique to show that we can achieve finite convergence time under the weak interval excitation assumption. Simulation results that illustrate the performance of the proposed adaptive observers are given. This include, an unobservable system, an example reported in the literature and the widely popular, and difficult to control, single-ended primary inductor converter. [ABSTRACT FROM AUTHOR]

The design of a position observer for the interior permanent magnet synchronous motor is a challenging problem that, in spite of many research efforts, remained open for a long time. In this paper we present the first globally exponentially convergent solution to it, assuming that the saliency is not too large. As expected in all observer tasks, a persistency of excitation condition is imposed. Conditions on the operation of the motor, under which it is verified, are given. In particular, it is shown that at rotor standstill – when the system is not observable – it is possible to inject a probing signal to enforce the persistent excitation condition. The high performance of the proposed observer, in standstill and high speed regions, is verified by extensive series of test-runs on an experimental setup. [ABSTRACT FROM AUTHOR]

In this brief note we pose, and solve, the problem of robustification of controller designs where the actuator dynamics was neglected. This situation is very common in applications where, to validate the assumption that the actuator dynamics can be neglected, a high-gain inner-loop that enforces a time-scale separation between the actuator and the plant dynamics is implemented. Of course, the injection of the high-gain has well-known deleterious effects. Moreover, a stability, and robustness, analysis of such a control configuration is usually unavailable. Our first main contribution is to provide an alternative to such a scheme, with provable robust stability properties. The second contribution is to, applying this result, propose a robustification procedure to the industry standard field-oriented control of current-fed induction motors , which is usually implemented neglecting the actuator dynamics, with no rigorous proof of stability available to date. Finally, we propose the first solution of smooth, time-invariant regulation of the dynamic model of a class of nonholonomic systems, that includes the widely popular unicycle example. Simulation examples prove the superior performance of the proposed controller compared with the existing switching and/or time-varying alternatives reported in the literature. [ABSTRACT FROM AUTHOR]

• We investigate the integration cost of wind and solar on both the power supply and demand sides. • The integration costs from both sides are increasing with the penetration of variable renewable electricity. • Consumers will bear more cost of variable renewable electricity integration than power system. • Solar power has a lower integration cost than wind power. • Blindly reducing the renewable energy curtailment rate may not be cost-effective. Variable renewable electricity (VRE) is expected to play an important role in global decarbonization. However, due to VRE's intermittency and uncertainty, integrating VRE into the power system may cause additional integration costs for both power systems and consumers. Estimating these integration costs can provide insights for power system planning, support policy making and power market designs. In this paper, the integration costs of wind and solar on both demand and supply sides are quantitatively investigated by an economic power dispatch model combined with Monte Carlo simulation. A case study of Guangdong Province in China is conducted under three scenarios of power mix changes (only increasing the VRE installation; replacing the existing coal-fired power; and replacing the existing coal-fired power without power storage). The results show that integration costs from both supply and demand sides are non-negligible when VRE replaces existing capacity, and the costs are increasing with the penetration rate of VRE. On supply side, it ranges from −2.3 to 12.1 $/MWh for wind penetration from 5% to 30%, and −5.5 to 7.1 $/MWh for that of solar penetration. Moreover, consumers on demand side will bear −7.3 to 185.9 $/MWh integration costs for wind and solar integration, which is much higher than the supply side. In addition, solar power has a lower integration cost than wind power due to a more consistent power output with the load curve of power demand on the time scale. Moreover, our results reveal that blindly reducing the renewable energy curtailment rate may not be cost-effective. [ABSTRACT FROM AUTHOR]

In this paper we show that a slight modification to the widely popular interconnection and damping assignment passivity-based control method – originally proposed for stabilization of equilibria of nonlinear systems – allows us to provide a solution to the more challenging orbital stabilization problem. Two different, though related, ways how this procedure can be applied are proposed. First, the assignment of an energy function that has a minimum in a closed curve, i.e. , with the shape of a Mexican sombrero. Second, the use of a damping matrix that changes "sign" according to the position of the state trajectory relative to the desired orbit, that is, pumping or dissipating energy. The proposed methodologies are illustrated with the example of the induction motor and prove that it yields the industry standard field oriented control. [ABSTRACT FROM AUTHOR]

Background: Chikungunya virus (CHIKV) has reemerged as a major public health concern, causing chikungunya fever with increasing cases and neurological complications. Methods: In the present study, we investigated a low-passage human isolate of the East/ Central/South African (ECSA) lineage of CHIKV strain LK(EH)CH6708, which exhibited a mix of small and large viral plaques. The small and large plaque variants were isolated and designated as CHIKV-SP and CHIKV-BP, respectively. CHIKV-SP and CHIKV-BP were characterized in vitro and in vivo to compare their virus production and virulence. Additionally, whole viral genome analysis and reverse genetics were employed to identify genomic virulence factors. Results: CHIKV-SP demonstrated lower virus production in mammalian cells and attenuated virulence in a murine model. On the other hand, CHIKV-BP induced higher pro-inflammatory cytokine levels, compromised the integrity of the blood–brain barrier, and led to astrocyte infection in mouse brains. Furthermore, the CHIKV-SP variant had limited transmission potential in Aedesalbopictus mosquitoes, likely due to restricted dissemination. Whole viral genome analysis revealed multiple genetic mutations in the CHIKV-SP variant, including a Glycine (G) to Arginine (R) mutation at position 55 in the viral E2 glycoprotein. Reverse genetics experiments confirmed that the E2-G55R mutation alone was sufficient to reduce virus production in vitro and virulence in mice. Conclusions: These findings highlight the attenuating effects of the E2-G55R mutation on CHIKV pathogenicity and neurovirulence and emphasize the importance of monitoring this mutation in natural infections. [ABSTRACT FROM AUTHOR]

Virus genome recoding is an attenuation method that confers genetically stable attenuation by rewriting a virus genome with numerous silent mutations. Prior flavivirus genome recoding attempts utilised codon deoptimisation approaches. However, these codon deoptimisation approaches act in a species dependent manner and were unable to confer flavivirus attenuation in mosquito cells or in mosquito animal models. To overcome these limitations, we performed flavivirus genome recoding using the contrary approach of codon optimisation. The genomes of flaviviruses such as dengue virus type 2 (DENV2) and Zika virus (ZIKV) contain functional RNA elements that regulate viral replication. We hypothesised that flavivirus genome recoding by codon optimisation would introduce silent mutations that disrupt these RNA elements, leading to decreased replication efficiency and attenuation. We chose DENV2 and ZIKV as representative flaviviruses and recoded them by codon optimising their genomes for human expression. Our study confirms that this recoding approach of codon optimisation does translate into reduced replication efficiency in mammalian, human, and mosquito cells as well as in vivo attenuation in both mice and mosquitoes. In silico modelling and RNA SHAPE analysis confirmed that DENV2 recoding resulted in the extensive disruption of genomic structural elements. Serial passaging of recoded DENV2 resulted in the emergence of rescue or adaptation mutations, but no reversion mutations. These rescue mutations were unable to rescue the delayed replication kinetics and in vivo attenuation of recoded DENV2, demonstrating that recoding confers genetically stable attenuation. Therefore, our recoding approach is a reliable attenuation method with potential applications for developing flavivirus vaccines. Author summary: The mosquito-borne flaviviruses such as dengue virus (DENV) and Zika virus (ZIKV) have established themselves as major human pathogens. Live attenuated vaccines are seen as the most effective method for preventing flavivirus infection. Flavivirus genome recoding has emerged as a next-generation vaccine development method that acts by rewriting the flavivirus genome. Previous flavivirus genome recoding attempts were based on deoptimising the flavivirus genome. However, these deoptimised flaviviruses were found to be attenuated in a species dependent manner. For example, deoptimised DENV and ZIKV did not demonstrate attenuation in mosquito cells or mosquito animal models, which is undesirable because these mosquito-borne flaviviruses should be attenuated in their mosquito vector to prevent vaccine escape. To overcome these limitations, we adopted a flavivirus genome recoding approach based on the contrary approach of optimising the flavivirus genome and applied it to DENV2 and ZIKV. We found that this genome recoding approach of codon optimisation could confer attenuation in both mouse and mosquito animal models. This indicates that our flavivirus genome recoding approach may be used as a reliable method to construct attenuated vaccine backbones for the mosquito-borne-flaviviruses in general. [ABSTRACT FROM AUTHOR]

Environmental disturbances and systematical uncertainties are the main obstacles for ship motion control. This paper devotes to enhancing the control system robustness of underactuated surface ships with model uncertainties and environmental disturbances. A novel nonlinear robust adaptive scheme with sliding mode control is proposed for underactuated ships to track the desired path generated by the logical virtual ship in the presence of unknown plant parameters and environmental disturbances. Compared with the existing results, the proposed controller is designed based on the combination of PI sliding mode control and the upper bound estimation of disturbances. With the proposed design, the control scheme could not only obtain a better performance of the control system, the continuous scheme also reduce the chattering of system by a special construction of the sliding manifolds. Numerical simulations are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Purpose: To develop a mathematical model combined between physiologically based pharmacokinetic and BTK occupancy (PBPK-BO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of acalabrutinib (ACA) and active metabolite ACP-5862 in healthy humans as well as PD in patients. Next, to use the PBPK-BO to determine the optimal dosing regimens in patients alone, with different CYP3A4 variants, when co-administration with four CYP3A4 modulators and in patients with hepatic impairment, respectively. Methods: The PBPK-BO model was built using physicochemical and biochemical properties of ACA and ACP-5862 and then verified by observed PK and PD data from healthy humans and patients. Finally, the model was applied to determine optimal dosing regimens in various clinical situations. Results: The simulations demonstrated that 100 mg ACA twice daily (BID) was the optimal dosing regimen in patients alone. Additionally, dosage regimens might be reduced to 50 mg BID in patients with five CYP3A4 variants. Moreover, the dosing regimen should be modified to 100 mg (even to 50 mg) once daily (QD) when co-administration with erythromycin or clarithromycin, and be increased to 200 mg BID with rifampicin, and but be avoided co-administration with itraconazole. Furthermore, dosage regimen simulations showed that optimal dosing might be decreased to 50 mg BID in patients with mild and moderate hepatic impairment, and be avoided taking ACA in severely hepatically impaired patients. Conclusion: This PBPK-BO model can predict PK and PD in healthy humans and patients and also predict the optimal dosing regimens in various clinical situations. [ABSTRACT FROM AUTHOR]

Integrated energy system (IES) can achieve multi energy complementarity, but it still faces the problem of energy surplus or shortage. Therefore, there are demands for energy sharing among different IESs, but how to determine the trading quantity and trading price? To address this confusion, a distributed optimization model for multi-IES participating in peer-to-peer (P2P) transactions based on asymmetric Nash negotiation is innovatively proposed. First, to facilitate the energy sharing of several IESs with different structures, a P2P trading framework is designed. Second, to meet the needs of individual rationality and alliance cooperation at the same time, a distributed transaction optimization model based on Nash negotiation is proposed. Considering the discourse power determined by contribution, an asymmetric bargaining mechanism is designed. Third, to protect the privacy and improve solution performance, the improved adaptive step-size alternating direction multiplier algorithm (ADMM) is used for the distributed sequential solution. Finally, the effectiveness of the proposed trading framework, bargaining mechanism, optimization model, and solution algorithm are verified by the implementation of simulation. The simulation results show that: 1) The proposed model and algorithm can assist managers in determining the quantity and price of P2P electricity transactions. 2) Compared with the independent operation mode, the cooperative operation mode has significantly improved the overall interests and individual interests. 3) In distributed transactions, managers only need to submit limited information, which protects the privacy and security of each agent. 4) The asymmetric Nash negotiation mechanism can measure discourse power based on contribution. 5) The improved ADMM has the advantages of stronger convergence performance and faster solution speed. [Display omitted] • The framework for P2P transactions is designed • An asymmetric and fairer bargaining mechanism is proposed • A distributed transaction model based on Nash negotiation is established • An improved adaptive step-size ADMM is adopted for distributed solution [ABSTRACT FROM AUTHOR]

The aviation industry is one of the key areas to achieve carbon neutrality due to its difficulty in fuel substitution. In developing countries, aviation industry will be in a period of rapid growth for a long time, which means that it will be more affected by the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA). Therefore, aviation carbon emission reduction in developing countries needs to be paid more attention. This study utilizes the full sample data of global developing countries' fight-level information of June 2018, including a total of 1,048,655 flight data, to account for the aviation fuel consumption, CO 2 emissions, and emission intensity of 109 developing countries based on 70 aircraft types. The impacts of aircraft structure and flight pattern on energy efficiency and emission intensity are explored by combining micro fight-level aviation data with spatial index decomposition method. The results show that the average emission intensity of developing countries is actually better than that of developed countries. Most of them are concentrated in the range of 65–85 gCO 2 per seat-kilometers. The emission reduction potential of traditional measures in developing countries can theoretically close to 20%, of which about three-fifths comes from the adjustment of aircraft structure, while the remainder comes from the improvement in flight pattern. There is still a lot of room for structural adjustment of long-haul large-sized aircraft in developing countries by avoiding less efficient four-engine aircrafts and choosing more efficient ones in terms of new fleet deployments. But the potential for restructuring of medium-sized aircraft is limited, thus needing to further improve efficiency by increasing flight distance. Large-sized aircraft should be avoided as much as possible within the range that medium-sized aircraft can reach, which is crucial in route planning in many developing countries. • Full sample data of global developing countries' fight-level information is used. • Aviation fuel consumption, CO 2 emissions, and emission intensity are accounted for. • Flight-level aviation data is combined with the spatial index decomposition method. • Impacts of aircraft structure and flight pattern on energy efficiency are explored. [ABSTRACT FROM AUTHOR]

Zika virus (ZIKV) is a mosquito-borne virus that has re-emerged as a significant threat to global health in the recent decade. Whilst infections are primarily asymptomatic, the virus has been associated with the manifestation of severe neurological complications. At present, there is still a lack of approved antivirals for ZIKV infections. In this study, chelerythrine chloride, a benzophenanthridine alkaloid, was identified from a mid-throughput screen conducted on a 502-compound natural products library to be a novel and potent inhibitor of ZIKV infection in both in-vitro and in-vivo assays. Subsequent downstream studies demonstrated that the compound inhibits a post-entry step of the viral replication cycle and is capable of disrupting viral RNA synthesis and protein expression. The successful generation and sequencing of a ZIKV resistant mutant revealed that a single S61T mutation on the viral NS4B allowed ZIKV to overcome chelerythrine chloride inhibition. Further investigation revealed that chelerythrine chloride could directly inhibit ZIKV protein synthesis, and that the NS4B–S61T mutation confers resistance to this inhibition. This study has established chelerythrine chloride as a potential candidate for further development as a therapeutic agent against ZIKV infection. • A high-throughput screen was performed on a 502-compound natural products library. • Chelerythrine chloride was identified as an inhibitor of ZIKV infection. • Chelerythrine chloride targets a post-entry stage(s) of the ZIKV replication cycle. • Chelerythrine chloride could directly inhibit ZIKV NS4B protein synthesis. [ABSTRACT FROM AUTHOR]

Dynamic regressor extension and mixing is a new technique for parameter estimation with guaranteed performance improvement – with respect to classical gradient or least-squares estimators – that has proven instrumental in the solution of several open problems in system identification and adaptive control. In this brief note we give two interpretations of this parameter estimator in terms of the recent extensions, to the cases of nonlinear systems and observation of linear functionals for time-varying systems, of the classical Luenberger’s state observers. [ABSTRACT FROM AUTHOR]

Our aim is to build a physiologically based pharmacokinetic and JAK2 occupancy model (PBPK-JO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of baricitinib (BAR) in healthy humans when co-administrated with kidney transporters OAT3 and MATE2-K inhibitors, and in patients with hepatic and renal impairment. Probenecid and vandetanib were selected as OAT3 and MATE2-K competitive inhibitors, respectively. The PBPK-JO model was built using physicochemical and biochemical properties of BAR, and then verified by observed clinical PK. Finally, the model was applied to determine optimal dosing regimens in various clinical situations. Here, we have successfully simulated PK and JAK2 occupancy profiles in humans by PBPK-JO model. Moreover, this modelling reproduced every observed PK data, and every mean relative deviation (MRD) was below 2. The simulation suggested that PK of BAR had a significant change (2.22-fold increase), however PD only had a slight increase of 1.14-fold. Additionally, the simulation also suggested that vandetanib was almost unlikely to affect the PK and PD of BAR. In simulations of hepatic and renal impairment patients, the predictions suggested that significant changes in the PK and PD of BAR occurred. However, there was a lower fold increase in JAK2 occupancy than in PK in patients relative to healthy individuals. Administration dose adjustment of BAR when co-administrated with OAT3 inhibitors or in patients with hepatic or renal impairment should combine PK and PD changes of BAR, instead of only considering PK alteration. [Display omitted] • A new PBPK-JO model can assess PK and PD profiles of baricitinib simultaneously in humans. • The PBPK-JO model can assess PK-related and PD-related DDIs between baricitinib and OAT3 and MATE2-K inhibitors. • The PBPK-JO model can assess PK and PD alterations in patients with hepatic/renal impairment. [ABSTRACT FROM AUTHOR]