A Spontaneous Wireless Ad Hoc Trusted Neighbor Network Creation Protocol

Spontaneous networks lack an a priori communication infrastructure, the neighbors are unknown right after the deployment, and they are used during a period of time and in a certain location. In this paper, we present a new randomized creation model of a spontaneous wireless ad hoc network based on trusted neighbors. The idea is to manage the neighbor discovery with the exchange of identity cards, and the checking of a signature establishes a relationship based on trust of the neighbors. To asses the performance of our randomized trusted network proposal and compare it against an existing deterministic protocol used as reference, we relied on Castalia 3.2 simulator, regarding 4 metrics: time, energy consumption, throughput, and number of discoveries vs packet sent ratio. We found that our proposal outperforms the reference protocol in terms of time, energy, and discoveries vs packet sent ratio in a one-hop setting, while it outperforms the reference protocol regarding all 4 metrics in multihop environments. We also evaluated our proposal through simulations varying the transmission probability and proved that it does not require to know the number of nodes if a fixed transmission probability is set, providing reasonable results. Moreover, our proposal is based on collision detection, it knows when to terminate the process, it does not require a transmission schedule, and it follows more realistic assumptions. In addition, a qualitative comparison is carried out, comparing our proposal against existing protocols from the literature.

Advanced Metaheuristic Method for Decision-Making in a Dynamic Job Shop Scheduling Environment

As a well-known NP-hard problem, the dynamic job shop scheduling problem has significant practical value, so this paper proposes an Improved Heuristic Kalman Algorithm to solve this problem. In Improved Heuristic Kalman Algorithm, the cellular neighbor network is introduced, together with the boundary handling function, and the best position of each individual is recorded for constructing the cellular neighbor network. The encoding method is introduced based on the relative position index so that the Improved Heuristic Kalman Algorithm can be applied to solve the dynamic job shop scheduling problem. Solving the benchmark example of dynamic job shop scheduling problem and comparing it with the original Heuristic Kalman Algorithm and Genetic Algorithm-Mixed, the results show that Improved Heuristic Kalman Algorithm is effective for solving the dynamic job shop scheduling problem. The convergence rate of the Improved Heuristic Kalman Algorithm is reduced significantly, which is beneficial to avoid the algorithm from falling into the local optimum. For all 15 benchmark instances, Improved Heuristic Kalman Algorithm and Heuristic Kalman Algorithm have obtained the best solution obtained by Genetic Algorithm-Mixed. Moreover, for 9 out of 15 benchmark instances, they achieved significantly better solutions than Genetic Algorithm-Mixed. They have better robustness and reasonable running time (less than 30 s even for large size problems), which means that they are very suitable for solving the dynamic job shop scheduling problem. According to the dynamic job shop scheduling problem applicability, the integration-communication protocol was presented, which enables the transfer and use of the Improved Heuristic Kalman Algorithm optimization results in the conventional Simio simulation environment. The results of the integration-communication protocol proved the numerical and graphical matching of the optimization results and, thus, the correctness of the data transfer, ensuring high-level usability of the decision-making method in a real-world environment.

On genetic diversity in caraway: Genotyping of a large germplasm collection

Caraway (Carum carvi) is a widespread and frequently used spice and medicinal plant with a long history of cultivation. However, due to ongoing climatic changes, the cultivation is becoming increasingly risky. To secure caraway cultivation in future, timely breeding efforts to develop adapted material are necessary. Analysis of genetic diversity can accompany this process, for instance, by revealing untapped gene pools. Here, we analyzed 137 accessions using genotyping by sequencing (GBS). Hence, we can report a broad overview of population structure and genetic diversity of caraway. Population structure was determined using a principal coordinate analysis, a Bayesian clustering analysis, phylogenetic trees and a neighbor network based on 13,155 SNPs. Genotypic data indicate a clear separation of accessions into two subpopulations, which correlates with the flowering type (annual vs. biennial). Four winter-annual accessions were closer related to biennial accessions. In an analysis of molecular variance, genetic variation between the two subpopulations was 7.84%. In addition, we estimated the genome size for 35 accessions by flow cytometry. An average genome size of 4.282 pg/2C (± 0.0096 S.E.) was estimated. Therefore, we suggest a significantly smaller genome size than stated in literature.

The spread of epidemic under voluntary vaccination with heterogeneous infection rates

Epidemics usually spread widely and can cause a great deal of loss to humans. In the real world, vaccination is the principal method for suppressing the spread of infectious diseases. The Susceptible-Infected-Susceptible (SIS) model suggests that voluntary vaccination may affect the spread of an epidemic. Most studies to date have argued that the infection rates of nodes in the SIS model are not heterogeneous. However, in reality, there exist differences in the neighbor network structure and the number of contacts, which may affect the spread of infectious diseases in society. As a consequence, it can be reasonably assumed that the infection rate of the nodes is heterogeneous because of the amount of contact among people. Here, we propose an improved SIS model with heterogeneity in infection rates, proportional to the degree of nodes. By conducting simulations, we illustrate that almost all vaccinated nodes have high degrees when the infection rate is positively correlated with the degree of a node. These vaccinated nodes can divide the whole network into many connected sub-graphs, which significantly slows down the propagation of an epidemic; the heterogeneity of infection rates has a strong inhibitory effect on epidemic transmission. On the other hand, when the infection rate is negatively related to the degrees of the infection rate nodes, it is difficult for most nodes to meet the inoculation conditions, and the number of inoculations is close to zero.

Areal dependency of consonant inventories

This paper discusses the impact of linguistic contact on the make-up of consonantal inventories of the languages of Eurasia. New measures for studying the importance of language contact for the development of phonological inventories are proposed, and two empirical studies are reported. First, using two different measures of dissimilarity of phonemic inventories (the Jaccard dissimilarity measure and the novel Closest-Relative Cumulative Jaccard Dissimilarity measure), it is demonstrated that language contact—operationalized as languages being connected by an edge in a neighbor network—makes a significant contribution to between-inventory differences when phylogenetic variables are controlled for. Second, a novel measure of the exposure of a language to a particular segment—the Neighbor-Pressure Metric (NPM)—is proposed as a means of quantifying language contact with respect to phonological inventories. It is shown that addition of NPM helps achieve higher prediction accuracy than using bare phylogenetic data and that distributions of different consonants display a different degree of dependence on language-contact processes. Finally, more complex models for predicting consonant inventories are briefly explored, demonstrating the presence of complex non-linear relationships between inventories of neighboring languages.

Using Core Genome Alignments To Assign Bacterial Species

ABSTRACTWith the exponential increase in the number of bacterial taxa with genome sequence data, a new standardized method to assign species designations is needed that is consistent with classically obtained taxonomic analyses. This is particularly acute for unculturable, obligate intracellular bacteria with which classically defined methods, like DNA-DNA hybridization, cannot be used, such as those in theRickettsiales. In this study, we generated nucleotide-based core genome alignments for a wide range of genera with classically defined species, as well as those within theRickettsiales. We created a workflow that uses the length, sequence identity, and phylogenetic relationships inferred from core genome alignments to assign genus and species designations that recapitulate classically obtained results. Using this method, most classically defined bacterial genera have a core genome alignment that is ≥10% of the average input genome length. BothAnaplasmaandNeorickettsiafail to meet this criterion, indicating that the taxonomy of these genera should be reexamined. Consistently, genomes from organisms with the same species epithet have ≥96.8% identity of their core genome alignments. Additionally, these core genome alignments can be used to generate phylogenomic trees to identify monophyletic clades that define species and neighbor-network trees to assess recombination across different taxa. By these criteria,Wolbachiaorganisms are delineated into species different from the currently used supergroup designations, whileRickettsiaorganisms are delineated into 9 distinct species, compared to the current 27 species. By using core genome alignments to assign taxonomic designations, we aim to provide a high-resolution, robust method to guide bacterial nomenclature that is aligned with classically obtained results.IMPORTANCEWith the increasing availability of genome sequences, we sought to develop and apply a robust, portable, and high-resolution method for the assignment of genera and species designations that can recapitulate classically defined taxonomic designations. Using cutoffs derived from the lengths and sequence identities of core genome alignments along with phylogenetic analyses, we sought to evaluate or reevaluate genus- and species-level designations for diverse taxa, with an emphasis on the orderRickettsiales, where species designations have been applied inconsistently. Our results indicate that theRickettsiagenus has an overabundance of species designations, that the currentAnaplasmaandNeorickettsiagenus designations are both too broad and need to be divided, and that there are clear demarcations ofWolbachiaspecies that do not align precisely with the existing supergroup designations.

Genetic variability and distance between Lactuca serriola L. populations from Sweden and Slovenia assessed by SSR and AFLP markers

The study involved 121 samples of the common weed, Lactuca serriola L. (prickly lettuce), representing 53 populations from Sweden and Slovenia. The seed materials, originating from different habitats, were regenerated and taxonomically validated at the Department of Botany, Palacký University in Olomouc, Czech Republic. The morphological characterizations of the collected plant materials classified all 121 samples as L. serriola f. serriola; one sample was heterogeneous, and also present was L. serriola f. integrifolia. Differences in the amount and distribution of the genetic variations between the two regions were analyzed using 257 amplified fragment length polymorphism (AFLP) and 7 microsatellite (SSRs) markers. Bayesian clustering and Neighbor-Network were used for visualization of the differences among the samples by country. Under the Bayesian approach, the best partitioning (according to the most frequent signals) was resolved into three groups. While the absence of an admixture or low admixture was detected in the Slovenian samples, and the majority of the Swedish samples, a significant admixture was detected in the profiles of five Swedish samples collected near Malmö, which bore unique morphological features of their rosette leaves. The Neighbor-Network analysis divided the samples into 6 groups, each consisting of samples coming from a particular country. Reflection of morphology and eco-geographical conditions in genetic variation are also discussed.