Particle swarm optimization using dimension selection methods

a b s t r a c t Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the PSO, and then gives a PSO variant without randomness to show that traditional PSO cannot work without randomness. Based on our analysis of the randomness, another way of using randomness is proposed in PSO with random dimension selection (PSORDS) algorithm, which utilizes random dimension selection instead of stochastic coefficients. Finally, deterministic methods to do the dimension selection are proposed, and the resultant PSO with distance based dimension selection (PSODDS) algorithm is greatly superior to the traditional PSO and PSO with heuristic dimension selection (PSOHDS) algorithm is comparable to traditional PSO algorithm. In addition, using our dimension selection method to a newly proposed modified particle swarm optimization (MPSO) algorithm also gets improved results. The experiment results demonstrate that our analysis about the randomness is correct and the usage of deterministic dimension selection method is very helpful

HSP70: a promising target for laryngeal carcinoma radiaotherapy by inhibiting cleavage and degradation of nucleolin

Previous studies have shown that heat shock proteins (HSPs) were upregulated in various types of tumors and were associated with histological grade, recurrence and metastasis of malignant tumors. In this study, we investigated whether heat shock protein 70 kDa (HSP70) was associated with histological grade of laryngeal squamous cell carcinomas (LSCC). We also determine the role of HSP70 in LSCC radiation resistance using a laryngeal carcinoma xenograft model by antisense HSP70 RNA technique. Immunohistochemistry data showed that HSP70 was detected in 96% of LSCC tissues (48 out of 50). The expression level of HSP70 was significantly lower in early stage of LSCC than that in late stage (P = 0.015). Radiation treatment result showed that the volumes and weights of implantation tumors in the group injected with antisense HSP70 oligos were significantly reduced comparing to the group injected with random oligos(p < 0.05). In addition, cleavage and degradation of tumor nucleolin in antisense HSP70 oligos injection group was significantly higher than that in random oligos injection group. Our result suggested that HSP70 may play a role in LSCC radiotherapy resistance by inhibiting cleavage and degradation of nucleolin

Surveillance of Norovirus contamination on scallops sold in Beijing

Objective To monitor the contamination of Norovirus and Rotavirus in scallops sold in Beijing and analyze their genetic characteristics. Methods A total of 72 scallops were collected during November 2014 and October 2015. The digestive tissues of scallops were excised, Norovirus was enriched using the polyethylene glycol (PEG) 8000 precipitation method. The virus RNA were extracted and tested for Norovirus and Rotavirus using the real-time reverse transcription-polymerase chain reaction (RT-PCR). The capsid gene of Norovirus was amplified by the semi-nested RT-PCR. PCR products were sequenced directly. Sequence alignment was performed using BioEdit 7.0.9.0 software and the phylogenetic tree was constructed by MEGA 6.06 software. Results Among 72 scallops, Rotavirus was detected negative, and the detection rate of Norovirus was 27.8% (20/72), including 16 strains of genogroup GⅡ, 2 strains of genogroup GⅠ, and 2 strains of mixed genogroups GⅠ and GⅡ. The highest detection rate of Norovirus (61.1%, 11/18) was found in winter, and none was detected in summer. A total of 8 strains were sequenced successfully and identified as GⅡ.17 genotype. These strains all belonged to the Cluster Ⅲb branch of GⅡ.17 genotype, among which 6 strains shared 100.0% sequence similarity with strains detected in Chinese people in 2015, in Japanese people in 2016 and 2017, in water samples in South Korea in 2017 and 2018, and in oysters in Japan in 2015. Conclusion Norovirus contamination existed in some scallops sold in Beijing, eating uncooked scallops would indicate a risk of viral acute gastroenteritis

Transcription Factor Crosstalk and Regulatory Networks in Hypopharyngeal Squamous Cell Carcinoma

licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited. Received: 2014.03.24; Accepted: 2014.04.18; Published: 2014.06.16 To date, no effective therapeutic treatments have been developed for hypopharyngeal squamous cell carcinoma (HPSCC), a disease that has a five-year survival rate of approximately 31 % because of its late diagnosis and aggressive nature. Despite recent improvements in diagnostic methods, there are no effective measures to prevent or detect HPSCC in an early stage. The goal of the current study was to identify molecular biomarkers and networks that can facilitate the speedy identification of HPSCC patients who could benefit from individualized treatment. Isobaric tags for relative and absolute quantification (iTRAQ) labeling was employed with two-dimensional liquid chromatography-tandem mass spectrometry to identify quantitatively the differentially expressed proteins among three types of HPSCC disease stages. The iTRAQ results were evaluated by literature searches and western blot analysis. For example, FUBP1, one of 412 proteins with significantl

Leucine Carboxyl Methyltransferase Downregulation and Protein Phosphatase Methylesterase Upregulation Contribute Toward the Inhibition of Protein Phosphatase 2A by α-Synuclein

The pathology of Parkinson’s disease (PD) is characterized by intracellular neurofibrillary tangles of phosphorylated α-synuclein (α-syn). Protein phosphatase 2A (PP2A) is responsible for α-syn dephosphorylation. Previous work has demonstrated that α-syn can regulate PP2A activity. However, the mechanisms underlying α-syn regulation of PP2A activity are not well understood. In this study, we found that α-syn overexpression induced increased α-syn phosphorylation at serine 129 (Ser129), and PP2A inhibition, in vitro and in vivo. α-syn overexpression resulted in PP2A demethylation. This demethylation was mediated via downregulated leucine carboxyl methyltransferase (LCMT-1) expression, and upregulated protein phosphatase methylesterase (PME-1) expression. Furthermore, LCMT-1 overexpression, or PME-1 inhibition, reversed α-syn-induced increases in α-syn phosphorylation and apoptosis. In addition to post-translational modifications of the catalytic subunit, regulatory subunits are involved in the regulation of PP2A activity. We found that the levels of regulatory subunits which belong to the PPP2R2 subfamily, not the PPP2R5 subfamily, were downregulated in the examined brain regions of transgenic mice. Our work identifies a novel mechanism to explain how α-syn regulates PP2A activity, and provides the optimization of PP2A methylation as a new target for PD treatment

A Forager Adjustment Strategy Used by the Bees Algorithm for Solving Optimization Problems in Cloud Manufacturing

Intelligent technologies have become increasingly important in manufacturing nowadays. Optimal service management and allocation in current cloud manufacturing model are impossible without applications of appropriate intelligent tools. The Bees Algorithm (BA) is a swarm-based intelligent optimizer that provides support for smart decision-making process in manufacturing models. A novel forager adjustment strategy (FAS) is proposed in this paper to manage the forager division in the algorithm, so as to make the entire colony perform with higher efficiency. The proposed FAS based Bees Algorithm (FAS-BA) is able to realize flexible allocation of its forager resources between different roles in accordance with the solution fitness sampled by current scout population. The proposed algorithm is presented in detail. Experiments are conducted based on a set of well-known benchmark functions and a case study. Comparisons between FAS-BA and an improved Bees Algorithm are made to highlight the effectiveness of FAS. The results demonstrate that the proposed algorithm requires less function evaluation cost than the improved version but is capable of obtaining at least the same optimal solution to a problem.</jats:p

Particle swarm optimization using dimension selection methods

a b s t r a c t Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the PSO, and then gives a PSO variant without randomness to show that traditional PSO cannot work without randomness. Based on our analysis of the randomness, another way of using randomness is proposed in PSO with random dimension selection (PSORDS) algorithm, which utilizes random dimension selection instead of stochastic coefficients. Finally, deterministic methods to do the dimension selection are proposed, and the resultant PSO with distance based dimension selection (PSODDS) algorithm is greatly superior to the traditional PSO and PSO with heuristic dimension selection (PSOHDS) algorithm is comparable to traditional PSO algorithm. In addition, using our dimension selection method to a newly proposed modified particle swarm optimization (MPSO) algorithm also gets improved results. The experiment results demonstrate that our analysis about the randomness is correct and the usage of deterministic dimension selection method is very helpful