Linkage fabrics are gaining in popularity and finding applications in architecture, aerospace, healthcare, and fashion because they can deliver materials with bespoke flexibility and strength through the geometric design of linkage nodes. In this article, we provide a perspective on linkage fabrics as a new class of programmable materials. We describe the theory and design principles of these linkage fabrics and show how they can be designed and simulated using digital tools, and fabricated using 3D printing. This digital approach overcomes a major obstacle to the adoption of these materials, namely their complexity. We show how simulation methods can be verified and calibrated through experimental testing. This perspective article also discusses design-led research challenges for linkage fabrics such as the development of wearable assistive devices for those with physical disabilities.

In this research, a force tracking smoothing adaptive admittance controller is proposed that grants precise contact forces (performance necessary for many critical interaction tasks such as polishing) for unknown interaction environments (e.g., leather or thin and soft materials). First, an online indirect adaptive update strategy is proposed for generating the reference trajectory required by the desired tracking force, considering the uncertainty of the interaction. The sensor noise amplitude is environment dynamics and the necessity condition for traditional admittance controller to achieve ideal steady-state force tracking. Then, a pre-PD controller is introduced to increase the parameter convergence rate while ensuring the steady-state force tracking accuracy and enhancing the robustness of the system. The robustness boundary is also analyzed to provide assurance for the stability of the system. Finally, we verify the effectiveness of the proposed method in simulations. Simultaneously, an experiment is conducted on the AUBO-i5 serial collaborative robot, and the experimental results proved the excellent comprehensive performance of the control framework.

In this paper, to address the cooperative localisation of a heterogeneous UAV swarm in the GNSS-denied environment, an adaptive simulated annealing-particle swarm optimisation (SA-PSO) cooperative localisation algorithm is proposed. Firstly, the forming principle of the communication and measurement framework is investigated in light of a heterogeneous UAV swarm composition. Secondly, a reasonably cooperative localisation function is established based on the proposed forming principle, which can minimise the relative localisation error with limited available information. Then, an adaptive weight principle is incorporated into the particle swarm optimisation (PSO) for better performance. Furthermore, in order to overcome the drawbacks of PSO algorithm easily falling into the local extreme point, an adaptive SA-PSO algorithm is improved to promote the convergence speed of cooperative localisation. Finally, comparative simulations are performed among the adaptive SA-PSO, adaptive PSO, and PSO algorithms to demonstrate the feasibility and superiority of the proposed adaptive SA-PSO algorithm. Simulation results show that the proposed algorithm has better performance in convergence speed, and the cooperative localisation precision can be guaranteed.

Weapon target allocation (WTA) is an effective method to solve the battlefield fire optimisation problem, which plays an important role in intelligent automated decision-making. We researched the multitarget allocation problem to maximise the attack effectiveness when multiple interceptors cooperatively attack multiple ground targets. Firstly, an effective and reasonable fitness function is established, based on the situation between the interceptors and targets, by comprehensively considering the relative range, relative angle, speed, capture probability and radiation source matching performance and thoroughly evaluating them based on the advantage of the attack effectiveness. Secondly, the optimisation performance of the particle swarm optimisation (PSO) algorithm is adaptively improved. We propose an adaptive simulated annealing-particle swarm optimisation (SA-PSO) algorithm by introducing the simulated annealing algorithm into the adaptive PSO algorithm. The proposed algorithm can enhance the convergence speed and overcome the disadvantage of the PSO algorithm easily falling into a local extreme point. Finally, a simulation example is performed in a scenario where ten interceptors cooperate to attack eight ground targets; comparative experiments are conducted between the adaptive SA-PSO algorithm and PSO algorithm. The simulation results indicate that the proposed adaptive SA-PSO algorithm demonstrates great performance in convergence speed and global optimisation capabilities, and a maximised attack effectiveness can be guaranteed.

The differentiation of pathological stress responses from responses that are appropriate and adaptive is a challenge with little to guide the clinician. This refreshment considers adjustment disorder and possible approaches to distinguishing those who have the disorder from those who are responding ‘normally’ to stressful events.

Infection of pregnant cows with noncytopathic (ncp) bovine viral diarrhea virus (BVDV) induces rapid innate and adaptive immune responses, resulting in clearance of the virus in less than 3 weeks. Seven to 14 days after inoculation of the cow, ncpBVDV crosses the placenta and induces a fetal viremia. Establishment of persistent infection with ncpBVDV in the fetus has been attributed to the inability to mount an immune response before 90–150 days of gestational age. The result is ‘immune tolerance’, persistent viral replication and shedding of ncpBVDV. In contrast, we describe the chronic upregulation of fetal Type I interferon (IFN) pathway genes and the induction of IFN-γ pathways in fetuses of cows infected on day 75 of gestation. Persistently infected (PI) fetal IFN-γ concentrations also increased at day 97 at the peak of fetal viremia and IFN-γ mRNA was significantly elevated in fetal thymus, liver and spleen 14–22 days post maternal inoculation. PI fetuses respond to ncpBVDV infection through induction of Type I IFN and IFN-γ activated genes leading to a reduction in ncpBVDV titer. We hypothesize that fetal infection with BVDV persists because of impaired induction of IFN-γ in the face of activated Type I IFN responses. Clarification of the mechanisms involved in the IFN-associated pathways during BVDV fetal infection may lead to better detection methods, antiviral compounds and selection of genetically resistant breeding animals.

In September 2010 and again in February 2011, the city of Christchurch was rocked by earthquakes of magnitude 7.1 and 6.3 respectively. The second earthquake was shallow and caused extensive damage and loss of life, destroying most of the Central Business District. This paper focuses on recovery management at the University of Canterbury, exploring the extent to which the senior management team learned lessons from the September event which informed the way that the recovery was managed after the February earthquake. It examines the counter-intuitive possibility that successfully dealing with a prior, lesser event, may not necessarily better equip managers to deal with a subsequent, more extreme event.

Many complex systems can be modeled via Markov jump processes. Applications include chemical reactions, population dynamics, and telecommunication networks. Rare-event estimation for such models can be difficult and is often computationally expensive, because typically many (or very long) paths of the Markov jump process need to be simulated in order to observe the rare event. We present a state-dependent importance sampling approach to this problem that is adaptive and uses Markov chain Monte Carlo to sample from the zero-variance importance sampling distribution. The method is applicable to a wide range of Markov jump processes and achieves high accuracy, while requiring only a small sample to obtain the importance parameters. We demonstrate its efficiency through benchmark examples in queueing theory and stochastic chemical kinetics.

Sharing of benefits from nature conservation is widely regarded as a way to enhance local residents’ support for protected areas. While in past years, the effectiveness of such approaches has been investigated in detail, governance processes underpinning benefit sharing have received less attention. This study examines the legislation and implementation practice of a revenue sharing scheme in southern Ethiopia, an area that is currently undergoing substantial social and environmental changes that threaten livelihoods and ecosystems. Based on qualitative data from interviews, group discussions and workshops, four main areas of shortcomings in the current legislation and implementation practice were identified: information provision; imbalanced roles and responsibilities; compromised accountability; and the lack of connection between revenue and wildlife tourism in the minds of the recipients. While some of these factors fostered misunderstandings and misuse of the monies, others meant that even where revenue was disbursed it was not connected with wildlife conservation, and thus did not have the intended effect. A comparison between these factors and those in the literature on the evaluation of comanagement arrangements revealed substantial overlap. Revenue sharing may be regarded as part of the comanagement of wildlife areas, but to be successful the management of these areas needs to be shared, and not just the financial benefits.

Radical radiotherapy to the bladder for muscle-invasive bladder cancer is a challenging treatment to plan and deliver because of organ mobility and its varying volume. The dynamic target volume can be tracked with imaging during the treatment course, enabling an adaptive response and adjustment of the patient’s individual treatment plan. This article summarises the difficulties encountered when treating the bladder, different approaches to patient imaging and adaptive radiotherapy techniques. Ultimately these technological advances support the delivery of a personalised treatment plan to ensure optimal dose delivery to the tumour and simultaneous sparing of adjacent normal tissue.

A novel, highly efficient and accurate adaptive higher-order finite element method (hp-FEM) is used to simulate a multi-frequency resistivity logging-while-drilling (LWD) tool response in a borehole environment. Presented in this study are the vector expression of Maxwell’s equations, three kinds of boundary conditions, stability weak formulation of Maxwell’s equations, and automatic hp-adaptivity strategy. The new hp-FEM can select optimal refinement and calculation strategies based on the practical formation model and error estimation. Numerical experiments show that the new hp-FEM has an exponential convergence rate in terms of relative error in a user-prescribed quantity of interest against the degrees of freedom, which provides more accurate results than those obtained using the adaptive h-FEM. The numerical results illustrate the high efficiency and accuracy of the method at a given LWD tool structure and parameters in different physical models, which further confirm the accuracy of the results using the Hermes library (http://hpfem.org/hermes) with a multi-frequency resistivity LWD tool response in a borehole environment.

From an evolutionary standpoint, a default presumption is that true beliefs are adaptive and misbeliefs maladaptive. But if humans are biologically engineered to appraise the world accurately and to form true beliefs, how are we to explain the routine exceptions to this rule? How can we account for mistaken beliefs, bizarre delusions, and instances of self-deception? We explore this question in some detail. We begin by articulating a distinction between two general types of misbelief: those resulting from a breakdown in the normal functioning of the belief formation system (e.g., delusions) and those arising in the normal course of that system's operations (e.g., beliefs based on incomplete or inaccurate information). The former are instances of biological dysfunction or pathology, reflecting “culpable” limitations of evolutionary design. Although the latter category includes undesirable (but tolerable) by-products of “forgivably” limited design, our quarry is a contentious subclass of this category: misbeliefs best conceived as design features. Such misbeliefs, unlike occasional lucky falsehoods, would have been systematically adaptive in the evolutionary past. Such misbeliefs, furthermore, would not be reducible to judicious – but doxastically1 noncommittal – action policies. Finally, such misbeliefs would have been adaptive in themselves, constituting more than mere by-products of adaptively biased misbelief-producing systems. We explore a range of potential candidates for evolved misbelief, and conclude that, of those surveyed, only positive illusions meet our criteria.

An effective linearization technique capable of equalizing IM3 products resulting from an arbitrary out-of-band blocking scenario in a wideband direct conversion receiver is presented. IM3 products are regenerated in the RF analog domain of a low-power mixed-signal feedforward path and are used to cancel analogous signal terms in the original receiver at digital baseband via adaptive equalization. The composite SAW-less receiver achieves an improvement in effective IIP3 from −7.1 to +5.3 dBm under worst-case UMTS Region 1 blocking when the feedforward path is active.

The dynamics modeling and payload adaptability of a light-weight flexible one-link manipulator are studied. Using the FEM (Finite-Element Method) model of a flexible manipulator, a lower order Linear Quadratic Gaussian compensator can provide satisfactory performance without controller/observer spillover. Moreover, the payload can be separated from the beam model, therefore, it is expected that the identification algorithm should have better robustness than the other schemes. The simulation results have shown that the proposed payload-adaptation synthesizer, which synthesizes a payload identifier and a nominal regulator/estimator interpolator to obtain a near-optimal compensator, has good adaptability with varying payload. And the resulting synthesizer also provides a near-optimal damping for this sensor-actuator noncolocated system.

In the paper a formal model is presented of the discrete control of a bile robot moving over a plane. The model synthesis has been directed in such a way as to justify the use as a controller of the automaton with internal and external parameters. It has been shown that, while controlled in discrete time the mobile robot performance can be expressed by a one-sidely optimized tree of a two-person extensive game. The tree, after transforming into the form of the state diagram of an automaton, serves as a basis for the synthesis of the automaton with internal and external parameters playing the role of a controller. A method is presented of synthesizing an automaton of this type, being a hardware realization of the mobile robot controller.

While a robot moves, online hand–eye calibration to determine the relative pose between the robot gripper/end-effector and the sensors mounted on it is very important in a vision-guided robot system. During online hand–eye calibration, it is impossible to perform motion planning to avoid degenerate motions and small rotations, which may lead to unreliable calibration results. This paper proposes an adaptive motion selection algorithm for online hand–eye calibration, featured by dynamic threshold determination for motion selection and getting reliable hand–eye calibration results. Simulation and real experiments demonstrate the effectiveness of our method.

The extended Kalman filter, when employed in the GPS receiver as the navigation state estimator, provides optimal solutions if the noise statistics for the measurement and system are completely known. In practice, the noise varies with time, which results in performance degradation. The covariance matching method is a conventional adaptive approach for estimation of noise covariance matrices. The technique attempts to make the actual filter residuals consistent with their theoretical covariance. However, this innovation-based adaptive estimation shows very noisy results if the window size is small. To resolve the problem, a multilayered neural network is trained to identify the measurement noise covariance matrix, in which the back-propagation algorithm is employed to iteratively adjust the link weights using the steepest descent technique. Numerical simulations show that based on the proposed approach the adaptation performance is substantially enhanced and the positioning accuracy is substantially improved.