Population based optimization algorithms improvement using the predictive particles

A new efficient improvement, called Predictive Particle Modification (PPM), is proposed in this paper. This modification makes the particle look to the near area before moving toward the best solution of the group. This modification can be applied to any population algorithm. The basic philosophy of PPM is explained in detail. To evaluate the performance of PPM, it is applied to Particle Swarm Optimization (PSO) algorithm and Teaching Learning Based Optimization (TLBO) algorithm then tested using 23 standard benchmark functions. The effectiveness of these modifications are compared with the other unmodified population optimization algorithms based on the best solution, average solution, and convergence rate

Generalized optimal placement of PMUs considering power system observability, communication infrastructure, and quality of service requirements

This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems

FACTS allocation considering loads uncertainty, steady state operation constraints, and dynamic operation constraints

This study proposes an algorithm to allocate different types of flexible AC transmission system (FACTS) in power systems. The main objective of this study is to maximize profit by minimizing the system’s operating cost including FACTS devices (FDs) installation cost. Dynamic and steady state operating restrictions with loads uncertainty are included in the problem formulation. The overall problem is solved using both teaching learning based optimization (TLBO) technique for attaining the optimal allocation of the FDs as main-optimization problem and matpower interior point solver (MIPS) for optimal power flow (OPF) as the sub-optimization problem. The validation of the proposed approach is verified by applying it to test system of 59-bus; Simplified 14-Generator model of the South East Australian power system

Pyran-Squaraine as Photosensitizers for Dye-Sensitized Solar Cells: DFT/TDDFT Study of the Electronic Structures and Absorption Properties

In an effort to provide, assess, and evaluate a theoretical approach which enables designing efficient donor-acceptor dye systems, the electronic structure and optical properties of pyran-squaraine as donor-acceptor dyes used in dye-sensitized solar cells were investigated. Ground state properties have been computed at the B3LYP/6-31+G** level of theory. The long-range corrected density functionals CAM-B3LYP, PBEPBE, PBE1PBE (PBE0), and TPSSH with 6-311++G** were employed to examine absorption properties of the studied dyes. In an extensive comparison between experimental results and ab initio benchmark calculations, the TPSSH functional with 6-311++G** basis set was found to be the most appropriate in describing the electronic properties for the studied pyran and squaraine dyes. Natural transition orbitals (NTO), frontier molecular orbitals (FMO), LUMO, HOMO, and energy gaps, of these dyes, have been analyzed to show their effect on the process of electron injection and dye regeneration. Interaction between HOMO and LUMO of pyran and squaraine dyes was investigated to understand the recombination process and charge-transfer process involving these dyes. Additionally, we performed natural bond orbital (NBO) analysis to investigate the role of charge delocalization and hyperconjugative interactions in the stability of the molecule

Understanding the decomposition reaction mechanism of chrysanthemic acid: a computational study

<p>Abstract</p> <p>Background</p> <p>Chrysanthemic acid (<b>CHA</b>) is a major product from the photodecomposition of pyrethrin which is an important class of pesticide compounds.</p> <p>In the following paper, Hybrid density functional theory (DFT) calculations of the potential energy surface (PES) for three possible channels decomposition of chrysanthemic acid <b>(</b>cis-trans isomerization, rearrangement and fragmentation) have been carried at the B3LYP/6-311+G** level of theory. DFT was employed to optimize the geometry parameters of the reactants, transition states, intermediates and products based on detailed potential energy surfaces (PES).</p> <p>Results</p> <p>Our results suggest that all three pathways of <b>CHA </b>are endothermic. DFT calculations revealed that the activation barriers for cis-trans isomerization are low, leading to a thermodynamically favorable process than other two pathways. We also investigated the solvent effect on the PES using the polarizable continuum model (PCM). In addition, time-dependent density functional theory (TDDFT) calculations showed that these reactions occur in the ground state rather than in an excited state.</p> <p>Conclusion</p> <p>The rearrangement process seems to be more favorable than the decomposition of <b>CHA </b>to carbene formation. The solvent effect calculations indicated no changes in the shape of the PES with three continua (water, ethanol and cyclohexane), although the solvents tend to stabilize all of the species.</p

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century