Linguistic Complexity: Relationships Between Phoneme Inventory Size, Syllable Complexity, Word and Clause Length, and Population Size

Starting from a view on language as a complex, hierarchically organized system composed of many parts that have many interactions, this paper investigates statistical relationships between the linguistic variables “phoneme inventory size,” “syllable size,” “length of words,” “length of clauses,” and the nonlinguistic variable “population size.” By analyzing parallel textual material of 61 languages (18 language families) we found strong positive correlations between phoneme inventory size, mean number of phonemes per syllable, and mean number of monosyllables. We observed significant negative correlations between phoneme inventory size and the mean length of words and the mean length of clauses, measured as number of syllables. We then correlated the linguistic complexity data with estimated speaker population sizes and could reveal that languages with more speakers tend to have more phonemes per syllable, shorter words in number of syllables, a higher number of monosyllabic words, and a higher number of words per clause. Moreover, we reproduce the results of former studies that found a positive correlation between population size and phoneme inventory size for our language sample. The findings are discussed in light of previous research and within the framework of Systemic Typology. We propose that syllable complexity is a key factor in the correlations identified in this study, and that Zipf's law of Abbreviation explains the associations between “word length,” “syllable complexity,” “phoneme inventory size,” and the extralinguistic variable “population size.”

Can a Population Targeted by a CRISPR-Based Homing Gene Drive Be Rescued?

CRISPR-based homing gene drive is a genetic control technique aiming to modify or eradicate natural populations. This technique is based on the release of individuals carrying an engineered piece of DNA that can be preferentially inherited by the progeny. The development of countermeasures is important to control the spread of gene drives, should they result in unanticipated damages. One proposed countermeasure is the introduction of individuals carrying a brake construct that targets and inactivates the drive allele but leaves the wild-type allele unaffected. Here we develop models to investigate the efficiency of such brakes. We consider a variable population size and use a combination of analytical and numerical methods to determine the conditions where a brake can prevent the extinction of a population targeted by an eradication drive. We find that a brake is not guaranteed to prevent eradication and that characteristics of both the brake and the drive affect the likelihood of recovering the wild-type population. In particular, brakes that restore fitness are more efficient than brakes that do not. Our model also indicates that threshold-dependent drives (drives that can spread only when introduced above a threshold) are more amenable to control with a brake than drives that can spread from an arbitrary low introduction frequency (threshold-independent drives). Based on our results, we provide practical recommendations and discuss safety issues.

Mathematical modeling of the transmission dynamics, control and vaccination of schistosomiasis with a variable population size

No Abstract.

A Novel Variable Population Size Artificial Bee Colony Algorithm with Convergence Analysis for Optimal Parameter Tuning

This paper introduces a novel algorithm called variable population size artificial bee colony (VPS-ABC) optimization algorithm. VPS-ABC is proposed to overcome the impact of the effect of initial population and improve the convergence rate of classical ABC. The main idea is based on reducing the number of food sources gradually and moving the bees towards the global best food source in each re-initialization process. Moreover, an analysis for convergence of the ABC algorithm is proofed in details. The convergence analysis is based on the relation between ABC variants and the general solution of the food source regeneration equation. To show the fitness of the proposed algorithm, a comparison is made between VPS-ABC versus classical ABC, PSO, and GA algorithms in tuning the proportional-integral-derivative (PID) controllers. Simulation results show that VPS-ABC algorithm is highly competitive, often outperforming PSO and GA algorithms.