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Despite the vast research on many-objective optimisation problems, the presence of many objective functions is still a challenge worthy of further study. A way to treat this kind of problem is to incorporate the preferences of the decision maker (DM) into the optimisation process. In this paper, we introduce an interactive ant colony optimisation combined with an ordinal classification method in which classes are described by characteristic profiles. Through several interactions, the DM is supposed to identify some representative solutions of the classes 'satisfactory' and 'dissatisfactory,' which are used to initialise an ordinal classifier that increases the selective pressure by discriminating in favour of the 'satisfactory' class. This method can work with any either asymmetric or symmetric binary preference relation, a feature that confers a very wide generality. As another advantage, the interaction with the DM has minimal cognitive demands, which is an advisable feature for any approach based on interaction. Although the preference model is quite general, the proposal was tested using an eclectic model which combines compensatory preferences, veto conditions, and interval numbers to handle imprecise values; those preferences are aggregated in an asymmetric preference relation. Our approach performs particularly well in 10-objective problems according to the standards in the state-of-the-art literature. Numerical results and tests for statistical significance on the DTLZ and WFG test suites support this claim. [ABSTRACT FROM AUTHOR]

In recent years, Light Detection and Ranging (LiDAR) technology has been one of the most innovative subjects in laser scanning, remote sensing, and object detection systems. This technology may be popular because it can pinpoint structures or zones of interest in millimetre detail. It can also highlight variations and irregularities, such as surface degradation and vegetation growth. This paper presents a review of the specialised literature on LiDAR systems applied to precision agriculture; specifically, in cultivating crops. First, some preliminaries of LiDAR systems according to the mode of transport used, considering terrestrial, mobile, and aerial laser scanners, are given. Subsequently, a well-organised taxonomy of recent LiDAR applications based on the activity being performed is presented. Here, the following four categories are considered: (1) crop-related metric estimation, (2) tree and plant digitisation, (3) vision systems for object detection and navigation, and (4) planning and decision support. Lastly, we discuss some current trends and research challenges in applying LiDAR technology to cultivation activities in accordance with the state-of-the-art literature. • Compared with photogrammetry, LiDAR technology often obtains more precise 3D models. • Voxelisation is reasonably accurate when applied to tree digitisation. • The crop's health status is often monitored by estimating the NDVI, LAI or height. • The sunlight index and wood volume are adequate for evaluating pruning structures. • The most used LiDAR sensors are VLP-16, LMS400/111/511, UTM-30LX, and Focus X330. [ABSTRACT FROM AUTHOR]

This paper presents Outranking-based Particle Swarm Optimisation (O-PSO) a novel metaheuristic to address the multi-objective Unrelated Parallel Machine Scheduling Problem. It is a particle swarm optimisation algorithm enriched with the preferences of the Decision Maker (DM), articulated in a fuzzy relational system based on ELECTRE III. Unlike other multi-objective metaheuristics, O-PSO searches for the Region of Interest (RoI) instead of approximating a sample of the complete Pareto frontier. The RoI is the subset consisting of those Pareto-efficient solutions that satisfy the outranking relations, that is, they are the best solutions in terms of the DM's system of preferences. Therefore, O-PSO not only approximates the Pareto solutions but also supports multicriteria decision analysis of the schedules. The efficiency of O-PSO is validated on a benchmark of synthetic instances from the scientific literature, where the Wilcoxon rank-sum test provides statistical evidence that O-PSO offers high-quality solutions when compared with two state-of-the-art metaheuristics; specifically, O-PSO is capable of generating a greater proportion of solutions (on average, ranging from 7% to 14%) dominating those of the state-of-the-art algorithms, as well as finding more solutions (from 13% to 18%) that satisfy the DM's preferences. O-PSO is also applied to a real-world case study in the transport industry to provide evidence for its applicability. [ABSTRACT FROM AUTHOR]

Abstract: This review discusses how extracellular DNA (exDNA) might function in plant defense, and at what level(s) of innate immunity this process might operate. A new role for extracellular factors in mammalian defense has been described in a series of studies. These studies reveal that cells including neutrophils, eosinophils, and mast cells produce ‘extracellular traps’ (ETs) consisting of histone-linked exDNA. When pathogens are attracted to such ETs, they are trapped and killed. When the exDNA component of ETs is degraded, trapping is impaired and resistance against invasion is reduced. Conversely, mutation of microbial genes encoding exDNases that degrade exDNA results in loss of virulence. This discovery that exDNases are virulence factors opens new avenues for disease control. In plants, exDNA is required for defense of the root tip. Innate immunity-related proteins are among a group of >100 proteins secreted from the root cap and root border cell populations. Direct tests revealed that exDNA also is rapidly synthesized and exported from the root tip. When this exDNA is degraded by the endonuclease DNase 1, root tip resistance to fungal infection is lost; when the polymeric structure is degraded more slowly, by the exonuclease BAL31, loss of resistance to fungal infection is delayed accordingly. The results suggest that root border cells may function in a manner analogous to that which occurs in mammalian cells. [Copyright &y& Elsevier]