An Efficient Fitness Function in Genetic Algorithm Classifier for Landuse Recognition on Satellite Images

Genetic algorithm (GA) is designed to search the optimal solution via weeding out the worse gene strings based on a fitness function. GA had demonstrated effectiveness in solving the problems of unsupervised image classification, one of the optimization problems in a large domain. Many indices or hybrid algorithms as a fitness function in a GA classifier are built to improve the classification accuracy. This paper proposes a new index, DBFCMI, by integrating two common indices, DBI and FCMI, in a GA classifier to improve the accuracy and robustness of classification. For the purpose of testing and verifying DBFCMI, well-known indices such as DBI, FCMI, and PASI are employed as well for comparison. A SPOT-5 satellite image in a partial watershed of Shihmen reservoir is adopted as the examined material for landuse classification. As a result, DBFCMI acquires higher overall accuracy and robustness than the rest indices in unsupervised classification

CpGPAP: CpG island predictor analysis platform

<p>Abstract</p> <p>Background</p> <p>Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).</p> <p>Results</p> <p>CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at <url>http://bio.kuas.edu.tw/CpGPAP/</url>.</p> <p>Conclusions</p> <p>The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.</p

Computed Tomographic Appearance of Internal Herniation Through the Sigmoid Mesocolon

The case of a patient with surgically proven internal herniation of a loop of ileum through the sigmoid mesocolon is described. This 66-year-old man presented clinically with acute lower abdominal pain and an elevated white blood cell count. A computed tomography (CT) scan showed a thickened bowel loop with “bird-beak” appearance in the pelvis, centered towards the medial side and lying aside the effaced sigmoid colon. We think this CT picture is highly suggestive of internal herniation of the ileum through the sigmoid mesocolon, which is a rare clinical entity

An Empirical Study on Consumption Intention of Virtual Tour Streaming

This study employs the social interaction motivation of the audience to explore the social capital dual-model relationship generated by the audience of “Virtual Tour Streaming,” a term that describes virtual tour streaming’s nascent digital economy. This is situated in a virtual tour streaming platform to ascertain how it influences the intention of the audience and to use “Swift Guanxi” as the interaction variable to actual intention behavior. This is done to understand the contributions of virtual tour streaming adoption in a direct dial platform of different audience levels and their consumption behavior. The remaining sections discuss the theoretical and practical implications of the study

The Regulation Requirement of Dengue Vaccines

Dengue fever (dengue), a mosquito-borne disease caused by dengue viruses (DENVs), represents severe public health problems in Southeast Asia, Latin America, Africa and other subtropical regions. Many regulatory issues arise along with the development of dengue vaccines. It is required to follow the regulatory pathway for the license application. Dengue vaccines can be approved without local clinical phase III data. The national regulatory authorities (NRAs) must have the information, training and ability to review and approve the application. A novel vaccine product Dengvaxia® for dengue has been approved in many countries. The approval is based on clinical trials that show the vaccine could reduce about 60% dengue, prevented 90% of severe cases and 80% of hospitalizations. Several other DNA, live-attenuated, purified inactivated, subunit, vectored and chimeric vaccine candidates are currently developing in clinical phases. Although there are still some challenges for the development and regulation of vaccine, the prospects of dengue vaccines are promising provided that we can overcome the difficulty

Luteolin Suppresses Inflammatory Mediator Expression by Blocking the Akt/NFκB Pathway in Acute Lung Injury Induced by Lipopolysaccharide in Mice

Acute lung injury (ALI), instilled by lipopolysaccharide (LPS), is a severe illness with excessive mortality and has no specific treatment strategy. Luteolin is an anti-inflammatory flavonoid and widely distributed in the plants. Pretreatment with luteolin inhibited LPS-induced histological changes of ALI and lung tissue edema. In addition, LPS-induced inflammatory responses, including increased vascular permeability, tumor necrosis factor (TNF)-α and interleukin (IL)-6 production, and expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), were also reduced by luteolin in a concentration-dependent manner. Furthermore, luteolin suppressed activation of NFκB and its upstream molecular factor, Akt. These results suggest that the protection mechanism of luteolin is by inhibition of NFκB activation possibly via Akt

Nanotechnologies Applied in Biomedical Vaccines

Vaccination, one of the most effective strategies to prevent infectious diseases, is the administration of antigenic materials to stimulate an individual’s immune system to develop adaptive immunity to a specific pathogen. Though it is so advantageous for diseases control and prevention, vaccines still have some limitations. Nanotechnology is an approach to prepare a novel biomedicine vaccine with the vaccine consumption and side effects significantly decreased. Regulation is the most important criterion for the development of nanovaccines. All marketing products have to meet the requirement of regulation. The fast-track designation potentially aids in the development and expedites the review of nanovaccines that show promises in an unmet medical need. Here, some successful nanovaccine products are introduced—Inflexal® V, Epaxal®, GardasilTM, and CervarixTM have been widely used for the clinical applications, which are delivered either in the form of virosomes or virus-like particles. Vaccines based on nanotechnology may overcome their original disadvantages and lead to the development of painless, safer, and more effective products

Biotechnologies Applied in Biomedical Vaccines

Vaccination, the administration of an antigenic material (vaccine), is considered to be the most effective method for disease prevention and control. A vaccine usually contains an agent that resembles a diseases‐causing pathogen and is often made from inactivated microbes, live attenuated microbes, its toxins, or part of surface antigens (subunit). However, the modern biotechnological tools and genomics have opened a new era to develop novel vaccines and many products are successfully marketing around the world. It is important to formulate and deliver these vaccines appropriately to maximize the potential advances in prevention, therapy, and vaccinology. New vaccines employing biotechnological innovations are helping us to change the way for illness prevention. The clinical application of vaccines will be diversified along with the development of biotechnologies. In modern society, the outbreak of many infectious diseases has decreased through vaccination, but the burden of noninfectious diseases is growing. The new biotechnologies may result in not only the appreciation of vaccines which are critical in inducing protection against an infectious disease but also the production of therapeutic vaccines which are effective for alldiseases including infectious and noninfectious diseases

Improved branch and bound algorithm for detecting SNP-SNP interactions in breast cancer

BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with a breast cancer risk. Identifying possible SNP-SNP interactions in genome-wide case–control studies is an important task when investigating genetic factors that influence common complex traits; the effects of SNP-SNP interaction need to be characterized. Furthermore, observations of the complex interplay (interactions) between SNPs for high-dimensional combinations are still computationally and methodologically challenging. An improved branch and bound algorithm with feature selection (IBBFS) is introduced to identify SNP combinations with a maximal difference of allele frequencies between the case and control groups in breast cancer, i.e., the high/low risk combinations of SNPs. RESULTS: A total of 220 real case and 334 real control breast cancer data are used to test IBBFS and identify significant SNP combinations. We used the odds ratio (OR) as a quantitative measure to estimate the associated cancer risk of multiple SNP combinations to identify the complex biological relationships underlying the progression of breast cancer, i.e., the most likely SNP combinations. Experimental results show the estimated odds ratio of the best SNP combination with genotypes is significantly smaller than 1 (between 0.165 and 0.657) for specific SNP combinations of the tested SNPs in the low risk groups. In the high risk groups, predicted SNP combinations with genotypes are significantly greater than 1 (between 2.384 and 6.167) for specific SNP combinations of the tested SNPs. CONCLUSIONS: This study proposes an effective high-speed method to analyze SNP-SNP interactions in breast cancer association studies. A number of important SNPs are found to be significant for the high/low risk group. They can thus be considered a potential predictor for breast cancer association