The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

Lexical access, story re-telling and sequencing skills in adults who clutter and those who do not

Cluttering is a rate-based disorder of fluency, the scope of whose diagnostic criteria currently remains unclear. This paper reports preliminary findings from a larger study which aims to determine whether cluttering can be associated with language disturbances as well as motor and rate based ones. Subtests from the Mt Wilga High Level Language Test (MWHLLT) were used to determine whether people who clutter (PWC) have word finding difficulties, and use significantly more maze behaviours compared to controls, during story re-telling and simple sequencing tasks. Independent t tests showed that PWC were significantly slower than control participants in lexical access and sentence completion tasks, but returned mixed findings when PWCs were required to name items within a semantic category. PWC produced significantly more maze behaviour than controls in a task where participants were required to explain how to undertake commonly performed actions, but no difference in use of maze behaviour was found between the two groups when retelling a story from memory. The implications of these findings are discussed

Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

Effect of agitation on the performance of an anaerobic sequencing batch biofilm reactor in the treatment of dairy effluents

Agitation rate is an important parameter in the operation of Anaerobic Sequencing Biofilm Batch Reactors (ASBBRs), and a proper agitation rate guarantees good mixing, improves mass transfer, and enhances the solubility of the particulate organic matter. Dairy effluents have a high amount of particulate organic matter, and their anaerobic digestion presents inhibitory intermediates (e. g., long-chain fatty acids). The importance of studying agitation in such batch systems is clear. The present study aimed to evaluate how agitation frequency influences the anaerobic treatment of dairy effluents. The ASBBR was fed with wastewater from milk pasteurisation process and cheese manufacture with no whey segregation. The organic matter concentration, measured as chemical oxygen demand (COD), was maintained at approximately 8,000 mg/L. The reactor was operated with four agitation frequencies: 500 rpm, 350 rpm, 200 rpm, and no agitation. In terms of COD removal efficiency, similar results were observed for 500 rpm and 350 rpm (around 90%) and for 200 rpm and no agitation (around 80%). Increasing the system`s agitation thus not only improved the global efficiency of organic matter removal but also influenced volatile acid production and consumption and clearly modified this balance in each experimental condition.

Next Generation Sequencing of Pooled Samples Reveals New SNRNP200 Mutations Associated with Retinitis Pigmentosa

The gene SNRNP200 is composed of 45 exons and encodes a protein essential for pre-mRNA splicing, the 200 kDa helicase hBrr2. Two mutations in SNRNP200 have recently been associated with autosomal dominant retinitis pigmentosa (adRP), a retinal degenerative disease, in two families from China. In this work we analyzed the entire 35-Kb SNRNP200 genomic region in a cohort of 96 unrelated North American patients with adRP. To complete this large-scale sequencing project, we performed ultra high-throughput sequencing of pooled, untagged PCR products. We then validated the detected DNA changes by Sanger sequencing of individual samples from this cohort and from an additional one of 95 patients. One of the two previously known mutations (p.S1087L) was identified in 3 patients, while 4 new missense changes (p.R681C, p.R681H, p.V683L, p.Y689C) affecting highly conserved codons were identified in 6 unrelated individuals, indicating that the prevalence of SNRNP200-associated adRP is relatively high. We also took advantage of this research to evaluate the pool-and-sequence method, especially with respect to the generation of false positive and negative results. We conclude that, although this strategy can be adopted for rapid discovery of new disease-associated variants, it still requires extensive validation to be used in routine DNA screenings. (C) 2011 Wiley-Liss, Inc.

Exploring Bacterial Diversity of Endodontic Microbiota by Cloning and Sequencing 16S rRNA

Introduction: The characterization of microbial communities infecting the endodontic system in each clinical condition may help on the establishment of a correct prognosis and distinct strategies of treatment. The purpose of this study was to determine the bacterial diversity in primary endodontic infections by 16S ribosomal-RNA (rRNA) sequence analysis. Methods: Samples from root canals of untreated asymptomatic teeth (n = 12) exhibiting periapical lesions were obtained, 165 rRNA bacterial genomic libraries were constructed and sequenced, and bacterial diversity was estimated. Results: A total of 489 clones were analyzed (mean, 40.7 +/- 8.0 clones per sample). Seventy phylotypes were identified of which six were novel phylotypes belonging to the family Ruminococcaceae. The mean number of taxa per canal was 10.0, ranging from 3 to 21 per sample; 65.7% of the cloned sequences represented phylotypes for which no cultivated isolates have been reported. The most prevalent taxa were Atopobium rimae (50.0%), Dialister invisus, Pre-votella oris, Pseudoramibacter alactolyticus, and Tannerella forsythia (33.3%). Conclusions: Although several key species predominate in endodontic samples of asymptomatic cases with periapical lesions, the primary endodontic infection is characterized by a wide bacterial diversity, which is mostly represented by members of the phylum Firmicutes belonging to the class Clostridia followed by the phylum Bacteroidetes. (J Ended 2011;37:922-926)

Sequence-specific reconstruction from fragmentary databases using seed sequences: implementation and validation on SAGE, proteome and generic sequencing data

Motivation: DNA assembly programs classically perform an all-against-all comparison of reads to identify overlaps, followed by a multiple sequence alignment and generation of a consensus sequence. If the aim is to assemble a particular segment, instead of a whole genome or transcriptome, a target-specific assembly is a more sensible approach. GenSeed is a Perl program that implements a seed-driven recursive assembly consisting of cycles comprising a similarity search, read selection and assembly. The iterative process results in a progressive extension of the original seed sequence. GenSeed was tested and validated on many applications, including the reconstruction of nuclear genes or segments, full-length transcripts, and extrachromosomal genomes. The robustness of the method was confirmed through the use of a variety of DNA and protein seeds, including short sequences derived from SAGE and proteome projects.

Intraspecific variation in 16S rRNA gene of Mycoplasma synoviae determined by DNA sequencing

Mycoplasma synoviae (MS) is an important avian pathogen may cause both respiratory disease and joint inflammation synovitis in poultry, causing economic losses to the Brazilian poultry industry. The genotypic variation in 16S rRNA gene is unknown. Partial sequences of 16S rRNA gene of 19 strains of M. synoviae were sequenced and analyzed in order to obtain molecular characterization and evaluation of the genetic variability of strains from distinct Brazilian areas of poultry production. Different polymorphic patterns were observed. The number of polymorphic alterations in the studied strains ranged from 0 to 6. The nucleotide variations, including deletion, insertion and substitutions, ranged from 3 to 5. The genotypic diversity observed in this study may be explained by spontaneous mutations that may occur when a lineage remains in the same flock for long periods. The culling and reposition in poultry flocks may be responsible for the entry of new strains in different areas. (C) 2008 Elsevier Ltd. All rights reserved.