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Business analytics refers to the application of sophisticated tools to obtain valuable information from a large dataset that is generated by a company. Among these tools, fuzzy optimisation stands out because it helps decision-makers to solve optimisation problems considering the uncertainty that commonly occurs in application domains. This paper presents a bibliometric analysis following the PRISMA statement on the Dimensions database to obtain publications related to fuzzy optimisation applied to business domains. The purpose of this analysis is to gather useful information that can help researchers in this area. A total of 2,983 publications were analysed using VOSviewer to identify the trend in the number of publications per year, relationships in terms in both the title and abstract of these publications, most influential publications, and relationships among journals, authors, and institutions. [ABSTRACT FROM AUTHOR]

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]

Aims: Most plants produce a root tip extracellular matrix that includes viable border cell populations programmed to disperse into soil. Like neutrophils, border cells export structures that trap pathogens and prevent root tip infection. Border cells also trap metals. The goal of this study was to determine if border cells trap Pb.Methods: Border cell responses to Pb were observed microscopically. Border cell impact on Pb-induced injury to roots was assessed using root growth assays. Pb removal from solution was measured using inductively coupled plasma mass spectrometry (ICP-MS). Speciation of Pb associated with border cells was evaluated by synchrotron X-ray absorption spectroscopy (XAS).Results: Increased border cell trap size and number occurred within minutes in response to Pb but not silicon (Si). Transient immersion of root tips into Pb after border cells were removed resulted in growth inhibition. Immersion of root tips and border cells into Pb solution resulted in significant removal of Pb. Si levels in the presence of root tips remained unchanged. The Pb speciation, measured with Pb LIII XAS, altered when reacted with border cells, indicating that direct binding by extracellular traps occurred.Conclusions: Border cells can trap Pb and prevent damage to the root tip. [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]

PREMISE OF THE STUDY:: Root border cells are programmed to separate from the root cap as it penetrates the soil environment, where the cells actively secrete >100 extracellular proteins into the surrounding mucilage. The detached cells function in defense of the root tip by an extracellular trapping process that also requires DNA, as in mammalian white blood cells. Trapping in animals and plants is reversed by treatment with DNase, which results in increased infection. The goal of this study was to evaluate the role of DNA in the structural integrity of extracellular structures released as border cells disperse from the root tip upon contact with water. METHODS:: DNA stains including crystal violet, toluidine blue, Hoechst 33342, DAPI, and SYTOX green were added to root tips to visualize the extracellular mucilage as it absorbed water and border cell populations dispersed. DNase I was used to assess structural changes occurring when extracellular DNA was degraded. KEY RESULTS:: Complex masses associated with living border cells were immediately evident in response to each stain, including those that are specific for DNA. Treating with DNase I dramatically altered the appearance of the extracellular structures and their association with border cells. No extracellular DNA was found in association with border cells killed by freezing or high‐speed centrifugation. This observation is consistent with the hypothesis that, as with border cell extracellular proteins, DNA is secreted by living cells. CONCLUSION:: DNA is an integral component of border cell extracellular traps. [ABSTRACT FROM AUTHOR]

Background and aims: In a previous study, a compost water extract (CWE) applied to pea seedlings resulted in >95 % protection against root infection. The protection was correlated with retention of a sheath of root border cells surrounding each root tip. A transient exposure to CWE was correlated with 80 % reduction in infection, and with retention of border cell sheaths. Early effects of CWE on border cell dispersal therefore were examined. Materials and methods: Temporal and spatial dynamics of pea, maize, cotton, and cucumber border cell dispersal into water or CWE were measured. Results: Border cells formed a mass surrounding root tips within seconds after exposure to water, and most cells dispersed into suspension spontaneously. In CWE, >90 % of the border cell population instead remained appressed to the root surface, even after vigorous agitation. In cotton, for example, >25,000 border cells dispersed within seconds of immersion in water, but <100 border cells dispersed after >24 h in CWE. Conclusions: Border cells can contribute >90 % of carbon released from young roots, and a single border cell can trap hundreds of bacteria within minutes. The impact of altered border cell dispersal on soil properties, plant nutrition, and root disease development warrants further study. [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]

Today it is crucial to have up-to-date information for companies to be more competitive in this business world. There are applications based on speech recognition that allows access to data stored in databases. However, the proper functioning of these applications lies in good pronunciation, a skill that most people do not have. In this paper, the architecture of an English mispronunciation detection module integrated into a chatbot is proposed. It allows users to enter the audio of the phrases in which they want to evaluate their pronunciation. The output is the mispronounced words, thus helping the user to practice their English language pronunciation. The proposed architecture consists of an Automatic Speech Recognizer (ASR) model based on a Transformer network that converts the audio signal to text and an algorithm for string alignment that identifies mispronounced words using the Levenshtein distance. The Transformer network was trained using the LibriSpeech and L2-ARTIC datasets. The module was evaluated using the Accuracy metrics, reaching 90%, and the Character Error Rate metric, reaching 9.5%. Additionally, its performance was evaluated on a group of real users, showing promising results. [ABSTRACT FROM AUTHOR]

In a world where there is growing pressure to grow more with a smaller environmental footprint, alternative forms of plant protection are needed. The root tips of most plants produce border cells in a mucilage that also contains extracellular DNA (exDNA), which is known to be involved in plant defence. A decade after we first demonstrated that there was varietal difference in the number of border cells in Australian cotton cultivars, we enumerated current commercial cultivars and assessed the level of exDNA produced by individual root tips. The results exposed that there has been a change in the number of border cells per root tip, that cultivar variation still exists and that the recovered levels of exDNA also differs. However, there was no correlation between border cell number and disease resistance to two of the major wilt pathogens and the levels of exDNA did not change when a root tip suspension was incubated with spores of fungal pathogens. The results imply that, while there is potential for border cells and root tip properties to be incorporated into breeding programmes, we still need to develop a better understanding of how root tips are able to influence disease epidemiology if we are to capitalise on this phenotypic property. [ABSTRACT FROM AUTHOR]

In this paper, we develop and apply a genetic algorithm to solve surgery scheduling cases in a Mexican Public Hospital. Here, one of the most challenging issues is to process containers with heterogeneous capacity. Many scheduling problems do not share this restriction; because of this reason, we developed and implemented a strategy for the processing of heterogeneous containers in the genetic algorithm. The final product was named "genetic algorithm for scheduling optimization" (GAfSO). The results of GAfSO were tested with real data of a local hospital. Said hospital assigns different operational time to the operating rooms throughout the week. Also, the computational complexity of GAfSO is analyzed. Results show that GAfSO can assign the corresponding capacity to the operating rooms while optimizing their use. [ABSTRACT FROM AUTHOR]

Premise of the Study: Lead (Pb) is a contaminant whose removal from soil remains a challenge. In a previous study, border cells released from root tips were found to trap Pb, alter its chemistry, and prevent root uptake. Rhodizonic acid (RA) is a forensic tool used to reveal gunshot residue, and also to detect Pb within plant tissues. Here we report preliminary observations to assess the potential application of RA in exploring the dynamics of Pb accumulation at the root tip surface. Methods and Results: Corn root tips were immersed in Pb solution, stained with RA, and observed microscopically. Pb trapping by border cells was evident within minutes. The role of extracellular DNA was revealed when addition of nucleases resulted in dispersal of RA‐stained Pb particles. Conclusions: RA is an efficient tool to monitor Pb–root interactions. Trapping by border cells may control Pb levels and chemistry at the root tip surface. Understanding how plants influence Pb distribution in soil may facilitate its remediation. [ABSTRACT FROM AUTHOR]

Reduced water resources are of increasingly urgent global concern. One potential strategy to address the crisis is the use of drought tolerant crops in agriculture. Barley varieties developed for reduced irrigation ("Solum" and "Solar") use significantly less water than conventional varieties ("Cochise" and "Kopious"). The underlying mechanism of this drought tolerance is unknown but root structure and function play a key role in plant water uptake. In this study, an empirical survey compared early root development between drought tolerant and conventional varieties. Traits associated with root meristem-regulated cell division including rate of seed germination, border cell number and root cap mucilage production, and root hair emergence were quantified during root emergence. Preliminary results revealed that drought tolerant varieties exhibited faster seed germination and root hair production than conventional varieties. Border cell number and mucilage production in the drought tolerant varieties also were higher than in the conventional variety "Kopious," but lower than in "Cochise". Each trait, if found to be linked to the observed drought tolerance, could yield a simple, rapid, and inexpensive tool to screen for new crop varieties. Further detailed studies are needed. [ABSTRACT FROM AUTHOR]

One of the main concerns in Multicriteria Decision Aid (MCDA) is robustness analysis. Some of the most important approaches to model decision maker preferences are based on fuzzy outranking models whose parameters (e.g., weights and veto thresholds) must be elicited. The so-called preference-disaggregation analysis (PDA) has been successfully carried out by means of metaheuristics, but this kind of works lacks a robustness analysis. Based on the above, the present research studies the robustness of a PDA metaheuristic method to estimate model parameters of an outranking-based relational system of preferences. The method is considered robust if the solutions obtained in the presence of noise can maintain the same performance in predicting preference judgments in a new reference set. The research shows experimental evidence that the PDA method keeps the same performance in situations with up to 10% of noise level, making it robust. [ABSTRACT FROM AUTHOR]

Root border cells separate from plant root tips and disperse into the soil environment. In most species, each root tip can produce thousands of metabolically active cells daily, with specialized patterns of gene expression. Their function has been an enduring mystery. Recent studies suggest that border cells operate in a manner similar to mammalian neutrophils: Both cell types export a complex of extracellular DNA (exDNA) and antimicrobial proteins that neutralize threats by trapping pathogens and thereby preventing invasion of host tissues. Extracellular DNases (exDNases) of pathogens promote virulence and systemic spread of the microbes. In plants, adding DNase I to root tips eliminates border cell extracellular traps and abolishes root tip resistance to infection. Mutation of genes encoding exDNase activity in plant-pathogenic bacteria ( Ralstonia solanacearum) and fungi ( Cochliobolus heterostrophus) results in reduced virulence. The study of exDNase activities in plant pathogens may yield new targets for disease control. [ABSTRACT FROM AUTHOR]

The selection of a public project portfolio among a set of good portfolios directly impacts public organizations in a decisive manner. This task depends on the criteria of the decision maker and is especially hard when the solution is evaluated on many objectives. This combinational optimization problem has been addressed by multicriteria optimization algorithms which do not generate a single solution, but instead they generate a set of good solutions in the Pareto frontier. In this paper we propose to aid the recommendation of public projects with the utilization of simplified decision rules to explain the construction of the recommended project portfolio. Due to most decision problems can be represented in decision tables, we can form a decision table -- in portfolio selection problem -- with rules defined by the features of the projects (condition attributes) and the decision of support (the decision attribute). To facilitate the recommendation process, we simplify the decision rules via a hybrid rough set-based method that combines a genetic algorithm with an exact method. Less decision rules help the decision maker to faster analyze why some projects are accepted or rejected in a particular portfolio and --by this mean-- get more certainty about his/her decision. With the proposed approach, there is a significant reduction of the attributes of the decision rules with a high accuracy of classification, which was proven on a set of the UCI repository for machine learning test. [ABSTRACT FROM AUTHOR]

This paper introduces a strategy to enrich swarm intelligence algorithms with the preferences of the Decision Maker (DM) represented in an ordinal classifier based on interval outranking. Ordinal classification is used to bias the search toward the Region of Interest (RoI), the privileged zone of the Pareto frontier containing the most satisfactory solutions according to the DM's preferences. We applied this hybridising strategy to two swarm intelligence algorithms, i.e., Multi-objective Grey Wolf Optimisation and Indicator-based Multi-objective Ant Colony Optimisation for continuous domains. The resulting hybrid algorithms were called GWO-InClass and ACO-InClass. To validate our strategy, we conducted experiments on the DTLZ problems, the most widely studied test suit in the framework of multi-objective optimisation. According to the results, our approach is suitable when many objective functions are treated. GWO-InClass and ACO-InClass demonstrated the capacity of reaching the RoI better than the original metaheuristics that approximate the complete Pareto frontier. [ABSTRACT FROM AUTHOR]