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Multiple sequence alignment (MSA) is one of essential bioinformatics methods for decoding cis‐regulatory elements in gene regulation, predicting structure and function of proteins and RNAs, reconstructing phylogenetic tree, and other common tasks in biomolecular sequence analysis. The purpose of this paper is to describe briefly the basic concepts and formulations of gapped MSA and un‐gapped motif discovery approaches, and then review computational intelligence (CI) applications in MSA and motif‐finding problems.

This paper performs exhaustive literature review on the MSA and motif discovery using CI techniques.

Although CI‐based MSA algorithms were developed nearly a decade ago, most recent CI effort seems attempted to tackle the NP‐complete motif discovery problem. Applications of various CI techniques to solve motif discovery problem, including neural networks, self‐organizing map, genetic algorithms, swarm intelligence and combinations thereof, are surveyed. Finally, the paper concludes with discussion and perspective.

The algorithms and software discussed in this paper can be used to align DNA, RNA and protein sequences, discover motifs, predict functions and structures of protein and RNA sequences, and estimate phylogenetic tree.

The paper contributes to the first comprehensive survey of CI techniques that are applied to MSA and motif discovery.

The purpose of this paper is to identify the strain of oyster mushroom (OM) Pleurotus sapidus cultivated in a local (commercial) farm, and to generate a total quality index (TQI) on the strain using different modified atmosphere packaging (MAP) gas mixtures.

A phylogenetic tree was constructed using the MEGA software to identify the specific strain of P. sapidus grown in a local farm. The effects of MAP on fresh fruiting bodies of the identified strain were determined under three conditions: high carbon dioxide packaging (HCP: 20 per cent CO₂, 15 per cent O₂), low carbon dioxide packaging (LCP: 2 per cent CO₂, 30 per cent O₂) and high nitrogen packaging (HNP: 85 per cent N₂, 15 per cent O₂). All samples were stored at 4 ^oC for up to ten days, and subjected to total phenolic content (TPC), colour retention (CR) and sensory analysis. Quality parameters such as chewiness and odour were used to obtain the TQI.

From the phylogenetic analysis, a new strain (P. sapidus strain QDR) with 99 per cent similarity to P. sapidus was identified. Among the three MAP treatments, HCP recorded the highest TPC (2.85 mg GAE/g) and CR (60.36) after ten days, although only its CR was significantly different (p<0.05) from the control. Feedback from 30 sensory panellists indicated that both HCP and LCP were generally more effective in retaining the colour–odour of OM. The optimum TQI for HCP was obtained based on the observed parameters, which is useful for the large-scale packaging of OM.

Scientific evidence has revealed that packaging trend for commercially grown OM affects consumer’s acceptance.

This paper aims to study the application of high-tolerance and flexible indigenous bacteria and fungi, along with the co-metabolism in recycled paper and cardboard mill (RPCM) wastewater treatment (WWT).

The molecular characterization of isolated indigenous bacteria and fungi was performed by 16S rRNA and 18S rRNA gene sequencing, respectively. Glucose was used as a cometabolic substrate to enhance the bioremediation process.

The highest removal efficiency was achieved for both chemical oxygen demand (COD) and color [78% COD and 45% color removal by Pseudomonas aeruginosa RW-2 (MZ603673), as well as approximately 70% COD and 48% color removal by Geotrichum candidum RW-4 (ON024394)]. The corresponding percentages were higher in comparison with the efficiency obtained from the oxidation ditch unit in the full-scale RPCM WWT plant.

Indigenous P. aeruginosa RW-2 and G. candidum RW-4 demonstrated effective capability in RPCM WWT despite the highly toxic and low biodegradable nature, especially with the assistance of glucose.

Based on the significance of ectomycorrhizae (ECM) and increased publication activity on this subject, it was decided to carry out a bibliometric analysis of scientific outputs in this area. The purpose of this study is to reveal the research trends of scientific outputs on ECM for the past 30 years and provide a potential guide for future research.

A method of bibliometric analysis was performed, based on the online version of the Science Citation Index Expanded, Web of Science, from 1986 to 2017. The authors evaluated the publication types, languages, source countries, journals, the patterns of publication outputs, most-cited articles, most-productive authors, institutional distributions, subject categories, high-frequency keywords and keywords plus and high-frequency terms in the title and abstract of ectomycorrhizal research. Keywords, keywords plus and high-frequency terms in the title and abstract were analyzed via VOSviewer to illustrate the extent of co-occurrence. This study further describes the recent research priority or hotspots and reveals the research trends.

From 1986 to 2017, the publication output on ECM showed a rising trend; the number of articles has rapidly increased after 2003. Based on co-occurrence analysis for keywords, keywords plus and terms in the title and abstract, “ectomycorrhizal fungi” is the most popular keyword and keywords plus; “concentration” is the most high-frequency terms in the title and abstracts. Plant biology, mycology and ecology are the hotspots in the ectomycorrhizal research. Ectomycorrhizal taxonomy, the molecular mechanisms of ectomycorrhizal symbioses and the common mycorrhizal networks are the future direction.

A bibliometric analysis has been carried out to analyze the trends of ECM research with 30 years. This study provides a potential guide for future research related to ectomycorrhizae.

The purpose of this paper is to introduce error ellipse into the bootstrap method to improve the reliability of small samples and the credibility of the S-N curve.

Based on the bootstrap method and the reliability of the original samples, two error ellipse models are proposed. The error ellipse model reasonably predicts that the discrete law of expanded virtual samples obeys two-dimensional normal distribution.

By comparing parameters obtained by the bootstrap method, improved bootstrap method (normal distribution) and error ellipse methods, it is found that the error ellipse method achieves the expansion of sampling range and shortens the confidence interval, which improves the accuracy of the estimation of parameters with small samples. Through case analysis, it is proved that the tangent error ellipse method is feasible, and the series of S-N curves is reasonable by the tangent error ellipse method.

The error ellipse methods can lay a technical foundation for life prediction of products and have a progressive significance for the quality evaluation of products.

Bacterial vaginosis (BV) is quite common and linked with serious public health issues such as premature delivery and spread of sexually transmitted infections. The study aims to identify different genital mycoplasmas (GM) in high vaginal swabs (HVS) from adult females in Bahrain.

In total, 401 HVS were collected and cultured on MYCOFAST^® RevolutioN 2 test for identification and antibiotic susceptibility. Polymerase chain reaction (PCR) was performed for detection of Mycoplasma genitalium (Mg), Mycoplasma hominis (Mh) and Ureaplasma species. DNA-probe based detection for Gardnerella, Candida and Trichomonas was performed by BD Affirm Assay. Representative PCR amplicons were sequenced by Sanger sequencing.

In PCR, Ureaplasma sp. was the most common GM, followed by Mg and Mh; the prevalence being 21.2, 5.2 and 1.5%, respectively. On the contrary, 10.7% samples showed positivity for Ureaplasma urealyticum (Uu) and 1.7% for Mh in MYCOFAST^® RevolutioN 2. The concordance rates between MYCOFAST^® RevolutioN 2 and PCR for Mh and Ureaplasma sp. were 97.7 and 84%, respectively. Considering PCR as gold standard, sensitivity, specificity, positive predictive value, and negative predictive value of MYCOFAST^® RevolutioN 2 were 33.3, 98.8, 28.6, 98.9 and 37.7, 96.5, 74.4, 85.2% for Mh and Ureaplasma sp., respectively. The Uu and Mh isolates showed antibiotic-resistance ranging from 53%–58% and 71%–86%, respectively.

The prevalence of Ureaplasma sp. was high. Significant co-occurrence of GM was noticed with BV. MYCOFAST^® RevolutioN 2 had lower detection-rate than PCR, so a combination is suggested for wider diagnostic coverage.

The research reflects on status of prevalence of GM in adult females in Bahrain, and their co-occurrence with bacterial vaginosis. Diagnostic approach with combination of tests is suggested for wider coverage. The research has epidemiologic, diagnostic, and therapeutic implications.

This is the first report from the Kingdom of Bahrain reflecting on burden of GM from this geographic location. The diagnostic efficacy of MYCOFAST^® RevolutionN 2 test and polymerase chain reaction was evaluated for GM detection.

Fingerprints and blood samples are important for the identification of individuals and criminals. The present study aims to identify the predominant fingerprint patterns and the association between the fingerprint patterns and ABO–Rh blood groups in Omani population.

A cross-sectional study was conducted on 200 Omani individuals aged 18 years (104 males and 96 females). The imprints of all right and left-hand fingers were taken, and the types of the fingerprints were determined using a standard protocol. The blood group of all the subjects was recorded. Chi-square test was performed to identify the association between the fingerprint patterns and the ABO and Rh blood groups.

The loop fingerprint pattern was the most common in Omani subjects (49.4%), followed by whorl (44.9%) and arch (5.7%) pattern. A significant association (p < 0.001) was found between gender and fingerprint pattern. The loop was the highest occurring pattern in the females (54.6%), while the whorl was more in males (50.0%). The whorl pattern was the most common in the AB+ and O− groups. The loop was a predominant pattern in the A+, A−, B+, B− and O+ groups. The Chi-square test also revealed a significant correlation between different fingerprint patterns and blood groups of the subjects (p < 0.001).

The present study is an outcome of undergraduate student's research project thesis for the Doctor of Medicine (MD) program. The results of the present study may help in creating a data bank for biometrics, which can be useful for diagnosing associated diseases and also help in identification of individuals.

Fish are considered as one of the important aquatic animals in the planet. They play a vital role in the nutrient cycle. They can be considered as one of the healthy food for human beings. They can also act as a solution for some of the human health problems. If fish are affected by several diseases, they in turn provide an adverse effect on human health. Therefore, it is very much essential to protect fish from being affected by any diseases.

This paper is mainly focused on the identification of the red spot diseased area in fish. In this work, a fuzzy rule based method (FRBAM) and triangular membership function (TMFN) is used to identify the red spot disease (RSD) in the fish by analyzing several red spot diseased fish (RSDF) images. The canny edge detector is used for intermediate processing of RSDF images.

The proposed method is able to identify the red pixels over the fish by marking the affected area with red color by using a standard RGB model.

The proposed method follows FRBAM and TMFN in order to detect the RSD and canny edge detector for processing of RSDF images. Finally, it is tested using ten different image sizes and the results show its better performance in terms of detection of RSD affected regions of fish and execution time.

Corrosion-producing microorganisms have different physiology and include sulfate-reducing bacteria, iron oxidizers and magnesium oxidizers. Biocorrosion has been seen in various industries, especially the petrochemicals and oil industries. One proposal to solve this problem is the use of bacteriophages to treat the bacteria-caused corrosion. The aims of this study were isolation and identification of corrosion-producing bacteria from petroleum pipeline corrosion as well as finding their specific bacteriophages for phage therapy purposes.

The sample pipes with the corrosion were obtained from the Gandomkar petroleum pipeline station, Chaharmahal and Bakhtiari, Iran. For screening the corrosion-producing bacteria, the rusted pipe samples were cultured in a selective culture medium, manganese agar. The purified individual colonies were subjected to molecular examinations. For isolating bacteriophages from silversmithing workshops wastewater in Isfahan, whole plate titration methods and transmission electron microscopy were used to isolate and detect phages.

The cultivation of corrosion-based material on manganese agar after 18 hours incubation at 30°C resulted in the isolation of cream-colored colonies. The microscopic examinations showed Gram-negative coccobacilli. Based on molecular examinations, the isolated bacteria were identified as Stenotrophomonas maltophilia strain PBM-IAUF-2 with Genebank accession number of KU145278.1. The found bacteriophage was related to the Siphoviridae family of phages.

This paper is the first report of isolation and identification of corrosion-producing bacteria and its specific lytic phages from Gandomkar petroleum pipeline station, Chaharmahal and Bakhtiari, Iran. The biological procedures for preventing the microbial corrosion could be an asset and considered as a potential in the petroleum and industrial microbiology. Phage therapy is considered as one of the economical methods for reducing the biocorrosion.

The aim is to report on the 175th Annual Meeting of the American Association for the Advancement of Science (AAAS), held in February 2009 in Chicago.

Provides a concise review of the conference, whose theme was Our Planet and Its Life: Origins and Futures.

Not surprisingly, because of the primary focus on Darwin and the ecology of the earth, there were few symposia that concentrated on the application of technology outside of the Life Sciences and of the Earth Sciences. However, in view of the current evolution of “cloud computing” and the formation of “mega grids,” there were two symposia devoted to these topics.

The paper is a useful summary of a conference of interest to library and information management professionals.