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In response to challenges such as voltage limit violations, excessive currents, and power imbalances caused by the integration of distributed photovoltaic (distributed PV) systems into the distribution network, this study proposes at two-level optimization configuration method. This method effectively balances the grid capacity and reduces the active power losses, thereby decreasing the operating costs. The upper-level optimization enhances the distribution network's capacity by determining the siting and sizing of distributed PV devices. The lower-level aims to reduce the active power losses, improve the voltage stability margins, and minimize the voltage deviations. The upper-level planning results, which include the siting and sizing of the distributed PV, are used as initial conditions for the lower level. Subsequently, the lower level feeds back its optimization results to further refine the configuration. The model is solved using an improved second-order oscillating chaotic map particle swarm optimization algorithm (SCMPSO) combined with a second-order relaxation method. The simulation experiments on an improved IEEE 33-bus test system show that the SCMPSO algorithm can effectively reduce the voltage deviations, decrease the voltage fluctuations, lower the active power losses in the distribution network, and significantly enhance the power quality. [ABSTRACT FROM AUTHOR]

Linkage disequilibrium (LD) is an important genetic parameter used to infer the genetic diversity of natural populations and their evolutionary history. Traditionally, LD is defined as the non‐random association of non‐alleles at different loci in gametes for diploids, but has a limited use for polyploids.We formulate a framework to define tetraploid‐specific LD including (a) Hardy–Weinberg disequilibria at each locus, (b) composite digenic disequilibrium, (c) trigenic disequilibrium and (d) composite quadrigenic disequilibrium at different loci. These four types of disequilibria affect population variation singly or jointly through a web. We implement the EM algorithm to estimate each disequilibrium parameter and test its significance in allotetraploid populations.We perform computer simulation to examine the statistical properties of our computational model. Through analysing a population genetic data of allotetraploid switchgrass, we chart the genomic distribution of LD on different chromosomes from which the evolutionary history of switchgrass is inferred, demonstrating the practical usefulness of the model.We have developed a statistical model for LD analysis in allotetraploids. The model can be generalized as a tool to study the population diversity and evolution of polyploid populations. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) spreads mainly through close contact of infected persons, but the molecular mechanisms underlying its pathogenesis and transmission remain unknown. Here, we propose a statistical physics model to coalesce all molecular entities into a cohesive network in which the roadmap of how each entity mediates the disease can be characterized. We argue that the process of how a transmitter transforms the virus into a recipient constitutes a triad unit that propagates COVID-19 along reticulate paths. Intrinsically, person-to-person transmissibility may be mediated by how genes interact transversely across transmitter, recipient, and viral genomes. We integrate quantitative genetic theory into hypergraph theory to code the main effects of the three genomes as nodes, pairwise cross-genome epistasis as edges, and high-order cross-genome epistasis as hyperedges in a series of mobile hypergraphs. Charting a genome-wide atlas of horizontally epistatic hypergraphs can facilitate the systematic characterization of the community genetic mechanisms underlying COVID-19 spread. This atlas can typically help design effective containment and mitigation strategies and screen and triage those more susceptible persons and those asymptomatic carriers who are incubation virus transmitters. [ABSTRACT FROM AUTHOR]