Revision rules in the theory of evidence

Combination rules proposed so far in the Dempster-Shafer theory of evidence, especially Dempster rule, rely on a basic assumption, that is, pieces of evidence being combined are considered to be on a par, i.e. play the same role. When a source of evidence is less reliable than another, it is possible to discount it and then a symmetric combination operation is still used. In the case of revision, the idea is to let prior knowledge of an agent be altered by some input information. The change problem is thus intrinsically asymmetric. Assuming the input information is reliable, it should be retained whilst the prior information should
be changed minimally to that effect. Although belief revision is already an important subfield of artificial intelligence, so far, it has been little addressed in evidence theory. In this paper, we define the notion of revision for the theory of evidence and propose several different revision rules, called the inner and outer
revisions, and a modified adaptive outer revision, which better corresponds to the idea of revision. Properties of these revision rules are also investigated.

Where the Lake Meets the Sea: Strong Reproductive Isolation Is Associated with Adaptive Divergence between Lake Resident and Anadromous Three-Spined Sticklebacks

Contact zones between divergent forms of the same species are often characterised by high levels of phenotypic diversity over small geographic distances. What processes are involved in generating such high phenotypic diversity? One possibility is that introgression and recombination between divergent forms in contact zones results in greater phenotypic and genetic polymorphism. Alternatively, strong reproductive isolation between forms may maintain distinct phenotypes, preventing homogenisation by gene flow. Contact zones between divergent freshwater-resident and anadromous stickleback (Gasterosteus aculeatus L.) forms are numerous and common throughout the species distribution, offering an opportunity to examine these contrasting hypotheses in greater detail. This study reports on an interesting new contact zone located in a tidally influenced lake catchment in western Ireland, characterised by high polymorphism for lateral plate phenotypes. Using neutral and QTL-linked microsatellite markers, we tested whether the high diversity observed in this contact zone arose as a result of introgression or reproductive isolation between divergent forms: we found strong support for the latter hypothesis. Three phenotypic and genetic clusters were identified, consistent with two divergent resident forms and a distinct anadromous completely plated population that migrates in and out of the system. Given the strong neutral differentiation detected between all three morphotypes (mean FST = 0.12), we hypothesised that divergent selection between forms maintains reproductive isolation. We found a correlation between neutral genetic and adaptive genetic differentiation that support this. While strong associations between QTL linked markers and phenotypes were also observed in this wild population, our results support the suggestion that such associations may be more complex in some Atlantic populations compared to those in the Pacific. These findings provide an important foundation for future work investigating the dynamics of gene flow and adaptive divergence in this newly discovered stickleback contact zone.

Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information

Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.

Unexpected Role for Adaptive αβTh17 Cells in Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is a devastating disorder characterized by increased alveolar permeability with no effective treatment beyond supportive care. Current mechanisms underlying ARDS focus on alveolar endothelial and epithelial injury caused by products of innate immune cells and platelets. However, the role of adaptive immune cells in ARDS remains largely unknown. In this study, we report that expansion of Ag-specific αβTh17 cells contributes to ARDS by local secretion of IL-17A, which in turn directly increases alveolar epithelial permeability. Mice with a highly restrictive defect in Ag-specific αβTh17 cells were protected from experimental ARDS induced by a single dose of endotracheal LPS. Loss of IL-17 receptor C or Ab blockade of IL-17A was similarly protective, further suggesting that IL-17A released by these cells was responsible for this effect. LPS induced a rapid and specific clonal expansion of αβTh17 cells in the lung, as determined by deep sequencing of the hypervariable CD3RβVJ region of the TCR. Our findings could be relevant to ARDS in humans, because we found significant elevation of IL-17A in bronchoalveolar lavage fluid from patients with ARDS, and rIL-17A directly increased permeability across cultured human alveolar epithelial monolayers. These results reveal a previously unexpected role for adaptive immune responses that increase alveolar permeability in ARDS and suggest that αβTh17 cells and IL-17A could be novel therapeutic targets for this currently untreatable disease.

A mixed cost-function adaptive algorithm for ADSL time-domain equalization

We propose a mixed cost-function adaptive initialization algorithm for the time domain equalizer in a discrete multitone (DMT)-based asymmetric digital subscriber line. Using our approach, a higher convergence rate than that of the commonly used least-mean square algorithm is obtained, whilst attaining bit rates close to the optimum maximum shortening SNR and the upper bound SNR. Furthermore, our proposed method outperforms the minimum mean-squared error design for a range of time domain equalizer (TEQ) filter lengths. The improved performance outweighs the small increase in computational complexity required. A block variant of our proposed algorithm is also presented to overcome the increased latency imposed on the feedback path of the adaptive system.

Adaptive backstepping droop controller design for multi-terminal high-voltage direct current systems

Wind power is one of the most developed renewable energy resources worldwide. To integrate offshore wind farms to onshore grids, the high-voltage direct current (HVDC) transmission cables interfaced with voltage source converters (VSCs) are considered to be a better solution than conventional approaches. Proper DC voltage indicates successive power transfer. To connect more than one onshore grid, the DC voltage droop control is one of the most popular methods to share the control burden between different terminals. However, the challenges are that small droop gains will cause voltage deviations, while higher droop gain settings will cause large oscillations. This study aims to enhance the performance of the traditional droop controller by considering the DC cable dynamics. Based on the backstepping control concept, DC cables are modelled with a series of capacitors and inductors. The final droop control law is deduced step-by-step from the original remote side. At each step the control error from the previous step is considered. Simulation results show that both the voltage deviations and oscillations can be effectively reduced using the proposed method. Further, power sharing between different terminals can be effectively simplified such that it correlates linearly with the droop gains, thus enabling simple yet accurate system operation and control.

A co-operative formation-based collision avoidance approach for a group of autonomous vehicles (Special Issue on Adaptive Control and Signal Processing in Marine System)

This paper employs a unique decentralised cooperative control method to realise a formation-based collision avoidance strategy for a group of autonomous vehicles. In this approach, the vehicles' role in the formation and their alert and danger areas are first defined, and the formation-based intra-group and external collision avoidance methods are then proposed to translate the collision avoidance problem into the formation stability problem. The extension–decomposition–aggregation formation control method is next employed to stabilise the original and modified formations, whilst manoeuvring, and subsequently solve their collision avoidance problem indirectly. Simulation study verifies the feasibility and effectiveness of the intra-group and external collision avoidance strategy. It is demonstrated that both formation control and collision avoidance problems can be simultaneously solved if the stability of the expanded formation including external obstacles can be satisfied.

Local Conventions in Game Play in an Evolving Dual Social Network Framework

People usually perform economic interactions within the social setting of a small group, while they obtain relevant information from a broader source. We capture this feature with a dynamic interaction model based on two separate social networks. Individuals play a coordination game in an interaction network, while updating their strategies using information from a separate influence network through which information is disseminated. In each time period, the interaction and influence networks co-evolve, and the individuals’ strategies are updated through a modified naive learning process. We show that both network structures and players’ strategies always reach a steady state, in which players form fully connected groups and converge to local conventions. We also analyze the influence exerted by a minority group of strongly opinionated players on these outcomes.

Do ectomycorrhizal fungi exhibit adaptive tolerance to potentially toxic metals in the environment?

The effects of potentially toxic metals on ectomycorrhizal (ECM) fungi and their higher plant hosts are examined in this review. Investigations at a species and community level have revealed wide inter- and intraspecific variation in sensitivity to metals. Adaptive and constitutive mechanisms of ECM tolerance are proposed and discussed in relation to proven tolerance mechanisms in bacteria, yeasts and plants. Problems with methodology and research priorities are highlighted. These include the need for a detailed understanding of the genetic basis of tolerance in the ECM symbiosis, and for studies of ECM community dynamics in polluted sites.

An Adaptive Predictive Control Strategy for RMPPT under Partially Shaded Conditions

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.