925 resultados para sequencing batch reactors


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Switchgrass was treated by 1% (w/w) H₂SO₄in batch tube reactors at temperatures ranging from 140–220°C for up to 60 minutes. In this study, release patterns of glucose, 5-hydroxymethylfurfural (5-HMF), and levulinic acid from switchgrass cellulose were investigated through a mechanistic kinetic model. The predictions were consistent with the measured products of interest when new parameters reflecting the effects of reaction limitations, such as cellulose crystallinity, acid soluble lignin–glucose complex (ASL–glucose) and humins that cannot be quantitatively analyzed, were included. The new mechanistic kinetic model incorporating these parameters simulated the experimental data with R² above 0.97. Results showed that glucose yield was most sensitive to variations in the parameter regarding the cellulose crystallinity at low temperatures (140–180°C), while the impact of crystallinity on the glucose yield became imperceptible at elevated temperatures (200–220 °C). Parameters related to the undesired products (e.g. ASL–glucose and humins) were the most sensitive factors compared with rate constants and other additional parameters in impacting the levulinic acid yield at elevated temperatures (200–220°C), while their impacts were negligible at 140–180°C. These new findings provide a more rational explanation for the kinetic changes in dilute acid pretreatment performance and suggest that the influences of cellulose crystallinity and undesired products including ASL–glucose and humins play key roles in determining the generation of glucose, 5-HMF and levulinic acid from biomass-derived cellulose.

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This study presents a comprehensive mathematical model for open pit mine block sequencing problem which considers technical aspects of real-life mine operations. As the open pit block sequencing problem is an NP-hard, state-of-the-art heuristics algorithms, including constructive heuristic, local search, simulated annealing, and tabu search are developed and coded using MATLAB programming language. Computational experiments show that the proposed algorithms are satisfactory to solve industrial-scale instances. Numerical investigation and sensitivity analysis based on real-world data are also conducted to provide insightful and quantitative recommendations for mine schedulers and planners.

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Objective Ankylosing spondylitis (AS) is a highly heritable common inflammatory arthritis that targets the spine and sacroiliac joints of the pelvis, causing pain and stiffness and leading eventually to joint fusion. Although previous studies have shown a strong association of IL23R with AS in white Europeans, similar studies in East Asian populations have shown no association with common variants of IL23R, suggesting either that IL23R variants have no role or that rare genetic variants contribute. The present study was undertaken to screen IL23R to identify rare variants associated with AS in Han Chinese. Methods A 170-kb region containing IL23R and its flanking regions was sequenced in 50 patients with AS and 50 ethnically matched healthy control subjects from a Han Chinese population. In addition, the 30-kb region of peak association in white Europeans was sequenced in 650 patients with AS and 1,300 healthy controls. Validation genotyping was undertaken in 846 patients with AS and 1,308 healthy controls. Results We identified 1,047 variants, of which 729 were not found in the dbSNP genomic build 130. Several potentially functional rare variants in IL23R were identified, including one nonsynonomous single-nucleotide polymorphism (nsSNP), Gly149Arg (position 67421184 GA on chromosome 1). Validation genotyping showed that the Gly149Arg variant was associated with AS (odds ratio 0.61, P = 0.0054). Conclusion This is the first study to implicate rare IL23R variants in the pathogenesis of AS. The results identified a low-frequency nsSNP with predicted loss-of-function effects that was protectively associated with AS in Han Chinese, suggesting that decreased function of the interleukin-23 (IL-23) receptor protects against AS. These findings further support the notion that IL-23 signaling has an important role in the pathogenesis of AS.

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Background Genetic testing is recommended when the probability of a disease-associated germline mutation exceeds 10%. Germline mutations are found in approximately 25% of individuals with phaeochromcytoma (PCC) or paraganglioma (PGL); however, genetic heterogeneity for PCC/PGL means many genes may require sequencing. A phenotype-directed iterative approach may limit costs but may also delay diagnosis, and will not detect mutations in genes not previously associated with PCC/PGL. Objective To assess whether whole exome sequencing (WES) was efficient and sensitive for mutation detection in PCC/PGL. Methods Whole exome sequencing was performed on blinded samples from eleven individuals with PCC/PGL and known mutations. Illumina TruSeq™ (Illumina Inc, San Diego, CA, USA) was used for exome capture of seven samples, and NimbleGen SeqCap EZ v3.0 (Roche NimbleGen Inc, Basel, Switzerland) for five samples (one sample was repeated). Massive parallel sequencing was performed on multiplexed samples. Sequencing data were called using Genome Analysis Toolkit and annotated using annovar. Data were assessed for coding variants in RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX. Target capture of five exome capture platforms was compared. Results Six of seven mutations were detected using Illumina TruSeq™ exome capture. All five mutations were detected using NimbleGen SeqCap EZ v3.0 platform, including the mutation missed using Illumina TruSeq™ capture. Target capture for exons in known PCC/PGL genes differs substantially between platforms. Exome sequencing was inexpensive (<$A800 per sample for reagents) and rapid (results <5 weeks from sample reception). Conclusion Whole exome sequencing is sensitive, rapid and efficient for detection of PCC/PGL germline mutations. However, capture platform selection is critical to maximize sensitivity.

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This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

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One-quarter of the total primary production on earth is contributed by diatoms1. These are photosynthetic, unicellular algae with ornamented silica shells found in all aquatic and moist environments. They form the base of energy-efficient food webs that support all aquatic life forms. More than 250 genera of living diatoms, with as many as 100,000 species are known2. Fossil diatoms are known as early as the Cretaceous, 144–65 m.y. ago3. In India, deposits of diatoms occur in Rajasthan and are known as ‘multani mitti’. Multani mitti or Indian Fuller’s earth or diatomaceous earth as it is called in the West, is applied as a paste on the surface of the skin for 15–20 min and then washed-off. This leaves the skin feeling smooth, soft, moist and rejuvenated. Diatomaceous earth is now being used in the formulation of soaps, cleansing products, face powders and skincare preparations. Diatomaceous earth is a mineral material consisting mainly of siliceous fragments of various species of fossilized remains of diatoms.

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The work reported herein is part of an on-going programme to develop a computer code which, given the geometrical, process and material parameters of the forging operation, is able to predict the die and the billet cooling/heating characteristics in forging production. The code has been experimentally validated earlier for a single forging cycle and is now validated for a small batch production. To facilitate a step-by-step development of the code, the billet deformation has so far been limited to its surface layers, a situation akin to coining. The code has been used here to study the effects of die preheat-temperature, machine speed and rate of deformation the cooling/heating of the billet and the dies over a small batch of 150 forgings. The study shows: that there is a pre-heat temperature at which the billet temperature changes little from one forging to the next; that beyond a particular number of forgings, the machine speed ceases to have any pronounced influence on the temperature characteristics of the billet; and that increasing the rate of deformation reduces the heat loss from the billet and gives the billet a stable temperature profile with respect to the number of forgings. The code, which is simple to use, is being extended to bulk-deformation problems. Given a practical range of possible machine, billet and process specifics, the code should be able to arrive at a combination of these parameters which will give the best thermal characteristics of the die-billet system. The code is also envisaged as being useful in the design of isothermal dies and processes.

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Abstract is not available.

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It is proposed that over 4-5 years of study period, multiple collaborative sites will be established with on-farm cooperators to demonstrate better integration of crop-legume sequencing for improved root growth and functioning under limited water, leading to improved productivity and carbon sequestration, and reduced runoff and deep drainage losses.

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The impact of erroneous genotypes having passed standard quality control (QC) can be severe in genome-wide association studies, genotype imputation, and estimation of heritability and prediction of genetic risk based on single nucleotide polymorphisms (SNP). To detect such genotyping errors, a simple two-locus QC method, based on the difference in test statistic of association between single SNPs and pairs of SNPs, was developed and applied. The proposed approach could detect many problematic SNPs with statistical significance even when standard single SNP QC analyses fail to detect them in real data. Depending on the data set used, the number of erroneous SNPs that were not filtered out by standard single SNP QC but detected by the proposed approach varied from a few hundred to thousands. Using simulated data, it was shown that the proposed method was powerful and performed better than other tested existing methods. The power of the proposed approach to detect erroneous genotypes was approximately 80% for a 3% error rate per SNP. This novel QC approach is easy to implement and computationally efficient, and can lead to a better quality of genotypes for subsequent genotype-phenotype investigations.

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Khaya senegalensis (African mahogany or dry-zone mahogany) is a high-value hardwood timber species with great potential for forest plantations in northern Australia. The species is distributed across the sub-Saharan belt from Senegal to Sudan and Uganda. Because of heavy exploitation and constraints on natural regeneration and sustainable planting, it is now classified as a vulnerable species. Here, we describe the development of microsatellite markers for K. senegalensis using next-generation sequencing to assess its intra-specific diversity across its natural range, which is a key for successful breeding programs and effective conservation management of the species. Next-generation sequencing yielded 93943 sequences with an average read length of 234bp. The assembled sequences contained 1030 simple sequence repeats, with primers designed for 522 microsatellite loci. Twenty-one microsatellite loci were tested with 11 showing reliable amplification and polymorphism in K. senegalensis. The 11 novel microsatellites, together with one previously published, were used to assess 73 accessions belonging to the Australian K. senegalensis domestication program, sampled from across the natural range of the species. STRUCTURE analysis shows two major clusters, one comprising mainly accessions from west Africa (Senegal to Benin) and the second based in the far eastern limits of the range in Sudan and Uganda. Higher levels of genetic diversity were found in material from western Africa. This suggests that new seed collections from this region may yield more diverse genotypes than those originating from Sudan and Uganda in eastern Africa.

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Abstract is not available.

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Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16-45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

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Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of ∼994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and non-suppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria , Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression. © 2014 Penton et al.