GPU-Based Parallel Particle Swarm Optimization Methods for Graph Drawing

Particle Swarm Optimization (PSO) is a population-based stochastic search technique for solving optimization problems, which has been proven to be effective in a wide range of applications. However, the computational efficiency on large-scale problems is still unsatisfactory. A graph drawing is a pictorial representation of the vertices and edges of a graph. Two PSO heuristic procedures, one serial and the other parallel, are developed for undirected graph drawing. Each particle corresponds to a different layout of the graph. The particle fitness is defined based on the concept of the energy in the force-directed method. The serial PSO procedure is executed on a CPU and the parallel PSO procedure is executed on a GPU. Two PSO procedures have different data structures and strategies. The performance of the proposed methods is evaluated through several different graphs. The experimental results show that the two PSO procedures are both as effective as the force-directed method, and the parallel procedure is more advantageous than the serial procedure for larger graphs

Integrating bioinformatics and experimental models to investigate the mechanism of the chelidonine-induced mitotic catastrophe via the AKT/FOXO3/FOXM1 axis in breast cancer cells

Breast cancer (BC) is currently the most frequent and lethal cancer among women, and therefore, identification of novel biomarkers and potential anticancer agents for BC is crucial. Chelidonine is one of the main active ingredients of Chelidonium majus, which has been applied in Chinese medicine prescriptions to treat cancer. This paper aimed to evaluate the ability of chelidonine to trigger mitotic catastrophe in BC cells and to clarify its mechanism through the AKT/FOXO3/FOXM1 pathway. Bioinformatics analysis revealed that forkhead box O3 (FOXO3) was downregulated in different subtypes of BC. Factors such as age, stage, Scarff-Bloom-Richardson (SBR) grade, diverse BC subclasses, and triple-negative status were inversely correlated to FOXO3 levels in BC patients compared with healthy controls. Notably, patients exhibiting higher FOXO3 expression levels demonstrated better overall survival (OS) and relapse-free survival (RFS). Moreover, FOXM1 levels were negatively correlated with both OS and RFS in BC patients. These results revealed that FOXO3 might be considered a predictive biomarker for the prognosis of BC. By utilizing Gene Set Enrichment Analysis (GSEA), we delved into the main Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathways of FOXO3, and the results suggested that FOXO3 was mainly involved in cancer-related pathways and the cell cycle. Thereafter, MTT and flow cytometry (FCM) analysis indicated that chelidonine inhibited BC cell line proliferation and induced M phase arrest. It was found that chelidonine treatment induced MCF-7 cell apoptosis, significantly reduced the expression of survivin and promoted the expression of p53 and caspase-9. Further morphological observation illustrated depolymerization of the actin skeleton and shortening of actin filaments in BC cells, leading to the typical characteristics of mitotic catastrophe, such as abnormal mitosis and multinucleated cells. Western blot analysis demonstrated that chelidonine inhibited the expression of p-AKT to promote the expression of FOXO3 protein and weaken the expression levels of FOXM1 and polo-like kinase 1 (PLK1). Taken together, our present work proved that FOXO3 might be considered a potential therapeutic target for BC. Chelidonine emerges as a promising agent to treat BC by inducing M phase arrest of BC cells and hindering the AKT/FOXO3/FOXM1 axis, thereby inducing mitotic catastrophe in BC

A Complex Chained P System Based on Evolutionary Mechanism for Image Segmentation

A new clustering membrane system using a complex chained P system (CCP) based on evolutionary mechanism is designed, developed, implemented, and tested. The purpose of CCP is to solve clustering problems. In CCP, two kinds of evolution rules in different chained membranes are used to enhance the global search ability. The first kind of evolution rules using traditional and modified particle swarm optimization (PSO) clustering techniques are used to evolve the objects. Another based on differential evolution (DE) is introduced to further improve the global search ability. The communication rules are adopted to accelerate the convergence and avoid prematurity. Under the control of evolution-communication mechanism, the CCP can effectively search for the optimal partitioning and improve the clustering performance with the help of the distributed parallel computing model. This proposed CCP is compared with four existing PSO clustering approaches on eight real-life datasets to verify the validity. The computational results on tested images also clearly show the effectiveness of CCP in solving image segmentation problems

Application of nitrogen adsorption – based SSA measurement in characterization of montmorillonite dissolution

635-644For characterizing the alkaline dissolution of montmorillonite, this paper applies Nitrogen Adsorption-Based large specific surface area (SSA) Measurement to measure the changing SSA, pore volume, and pore size, and to draw the adsorption/desorption curve of montmorillonite at different sodium hydroxide concentrations. It also determines the optimal experiment conditions like concentration (0.05mol/L) and charging/reaction time (3h) of sodium hydroxide solution which are suitable for oilfield development. According to the experiment, the dissolution characteristics of montmorillonite reflected by parameters acquired through Nitrogen Adsorption-Based SSA Measurement are consistent with the conclusion drawn from the changing pH value and ion (e.g. Si4+) concentration of the solution before and after the reaction

An Extended Clustering Membrane System Based on Particle Swarm Optimization and Cell-Like P System with Active Membranes

An extended clustering membrane system using a cell-like P system with active membranes based on particle swarm optimization (PSO), named PSO-CP, is designed, developed, implemented, and tested. The purpose of PSO-CP is to solve clustering problems. In PSO-CP, evolution rules based on the standard PSO mechanism are used to evolve the objects and communication rules are adopted to accelerate convergence and avoid prematurity. Subsystems of membranes are generated and dissolved by the membrane creation and dissolution rules, and a modified PSO mechanism is developed to help the objects escape from local optima. Under the control of the evolution-communication mechanism, the extended membrane system can effectively search for the optimal partitioning and improve the clustering performance with the help of the distributed parallel computing model. This extended clustering membrane system is compared with five existing PSO clustering approaches using ten benchmark clustering problems, and the computational results demonstrate the effectiveness of PSO-CP

A New Chaotic Starling Particle Swarm Optimization Algorithm for Clustering Problems

A new method using collective responses of starling birds is developed to enhance the global search performance of standard particle swarm optimization (PSO). The method is named chaotic starling particle swarm optimization (CSPSO). In CSPSO, the inertia weight is adjusted using a nonlinear decreasing approach and the acceleration coefficients are adjusted using a chaotic logistic mapping strategy to avoid prematurity of the search process. A dynamic disturbance term (DDT) is used in velocity updating to enhance convergence of the algorithm. A local search method inspired by the behavior of starling birds utilizing the information of the nearest neighbors is used to determine a new collective position and a new collective velocity for selected particles. Two particle selection methods, Euclidean distance and fitness function, are adopted to ensure the overall convergence of the search process. Experimental results on benchmark function optimization and classic clustering problems verified the effectiveness of this proposed CSPSO algorithm

HIV-Specific Reported Outcome Measures: Systematic Review of Psychometric Properties

BackgroundThe management of people living with HIV and AIDS is multidimensional and complex. Using patient-reported outcome measures (PROMs) has been increasingly recognized to be the key factor for providing patient-centered health care to meet the lifelong needs of people living with HIV and AIDS from diagnosis to death. However, there is currently no consensus on a PROM recommended for health care providers and researchers to assess health outcomes in people living with HIV and AIDS. ObjectiveThe purpose of this systematic review was to summarize and categorize the available validated HIV-specific PROMs in adults living with HIV and AIDS and to assess these PROMs using the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) methodology. MethodsThis systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A literature search of 3 recommended databases (PubMed, Embase, and PsychINFO) was conducted on January 15, 2021. Studies were included if they assessed any psychometric property of HIV-specific PROMs in adults living with HIV and AIDS and met the eligibility criteria. The PROMs were assessed for 9 psychometric properties, evaluated in each included study following the COSMIN methodology by assessing the following: the methodological quality assessed using the COSMIN risk of bias checklist; overall rating of results; level of evidence assessed using the modified Grading of Recommendations, Assessment, Development, and Evaluation approach; and level of recommendation. ResultsA total of 88 PROMs classified into 8 categories, assessing the psychometric properties of PROMs for adults living with HIV and AIDS, were identified in 152 studies including 79,213 people living with HIV and AIDS. The psychometric properties of most included PROMs were rated with insufficient evidence. The PROMs that received class A recommendation were the Poz Quality of Life, HIV Symptom Index or Symptoms Distress Module of the Adult AIDS Clinical Trial Group, and People Living with HIV Resilience Scale. In addition, because of a lack of evidence, recommendations regarding use could not be made for most of the remaining assessed PROMs (received class B recommendation). ConclusionsThis systematic review recommends 3 PROMs to assess health outcomes in adults living with HIV and AIDS. However, all these PROMs have some shortcomings. In addition, most of the included PROMs do not have sufficient evidence for assessing their psychometric properties and require a more comprehensive validation of the psychometric properties in the future to provide more scientific evidence. Thus, our findings may provide a reference for the selection of high-quality HIV-specific PROMs by health care providers and researchers for clinical practice and research