Revealing microbial community structures in large- and small-scale activated sludge systems by barcoded pyrosequencing of 16S rRNA gene

The diversity of bacterial groups in activated sludge from large- and small-scale wastewater treatment plants was explored by barcoded pyrosequencing of 16S rRNA gene. Activated sludge samples (three small and 17 large scale) were collected from 12 wastewater treatment plants to clarify precise taxonomy and relative abundances. DNA was extracted, and amplified by 4 base barcoded 27f/519r primer set. The 454 Titanium (Roche) pyrosequences were obtained and analyses performed by Quantitative Insight Into Microbial Ecology (QIIME) with around 100,000 reads. Sequence statistics were computed, while constructing a phylogenetic tree and heatmap. Computed results explained total microbial diversity at phylum and class level and resolution was further extended to Operational Taxonomic Unit (OTU) based taxonomic assignment for investigating community distribution based on individual sample. Composition of sequence reads were compared and microbial community structures for large- and small-scale treatment plants were identified as major phyla (Proteobacteria and Bacteroidetes) and classes (Betaproteobacteria and Bacteroidetes). Also, family level breakdowns were explained and differences in family Nitrospiraceae and phylum Actinobacteria found at their species level were also illustrated. Thus, the pyrosequencing method provides high resolution insight into microbial community structures in activated sludge that might have been unnoticed with conventional approaches.     

An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.     

Colorimetric microdetermination of sulphites in foods by use of the modified rankine apparatus. IV.

Summary Detection and determination of traces of sulphites in foods was attempted by use of the modified Rankine apparatus and pararosaniline colorimetry. Replacement of alkaline titration reported previously by pararosaniline colorimetry lowered the absolute detection limit from 30 g (titration method) to 2 g. In view of clean analysis, in the color developing system, 0.1 N-sodium hydroxide was used in place of mercuric chloride solution commonly used as an absorbant of sulphites. In order to prevent oxidative decomposition of sulphites during operation, nitrogen gas was used as carrier instead of air. Dimedone and sodium azide were used for the elimination of aldehydes and nitrites, respecitvely, in the sample, which will disturb the color development of sulphites with pararosaniline-formaldehyde reagents. With this improved method, it was possible to determine the residual sulphites in frozen peeled shrimps, sugared beans and other foods with low sulphite contents accurately.

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Colorimetrische Mikrobestimmung von Sulfiten in Lebensmitteln bei Anwendung der modifizierten IV. Rankine Apparatur

Zusammenfassung Geringe Sulfitmengen in Lebensmitteln (geschälte Garnelen, gezuckerte Bohnen) können colorimetrisch bestimmt werden. Die neuentwickelte Methode beruht auf einer Kombination von colorimetrischer Bestimmung mittels p-Rosanilin und der Bestimmungsmethode nach Rankine. Auf diese Weise lassen sich Gehalte von 2 g noch genau bestimmen. Bei der Farbentwicklung wurde das giftige Quecksilbertetrachlorid durch 0.1 n-NaOH ersetzt, anstelle von Luft Stickstoff als Trägergas verwendet und somit eine Oxydation des Sulfits während der Bestimmung vermieden. Da Nitrit und Aldehyde die Farbentwicklung stören, wurde ihr Einfluß durch Dimedon und Natriumazid ausgeschaltet.

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Studies on the Analyses of Sulphites in Foods (IV)     

Helium gas permeability of montmorillonite/epoxy nanocomposites

Helium gas permeability of silicate clay (montmorillonite) particles/epoxy nanocomposites was examined. The incorporation of increasing amounts of montmorillonite particles reduced the helium gas permeability. Based on Fick’s law, gas permeation behavior of the nanocomposite was evaluated. With the increase of montmorillonite loading, gas diffusivity decreased, while gas solubility increased. Helium diffusion behavior is in agreement to the numerical results based on the Hatta–Taya–Eshelby theory. It has been revealed that dispersion of nanoscale platelets in polymer is effective in improving gas barrier property.     

Integrable multimode interference distributed Bragg reflector laser all-optical flip-flops

A novel fully integrable all-optical flip-flop has been created using distributed Bragg reflector multimode interference bistable laser diodes. The single metal-organic vapor phase epitaxy regrowth offset quantum well structure active/passive integrated flip-flop lases in single mode at 1554 nm and is compatible with standard fabrication methods of InP photonic integrated circuits (PICs). All-optical reset switching through cross-gain saturation was demonstrated over a 52-nm range, at 1522-1574 nm. An optical set has been achieved with -3 dBm and optical reset with less than -5-dBm external light injection. The flip-flop will be useful for integration in PICs of future photonic systems for self-routing and optical memories or buffers.     

Business process integration as a solution to the implementation of supply chain management systems

In the domain of supply chain management (SCM), various software packages have been developed for planning business strategies. To solve the problem of system productivity in applying planning packages, we propose a solution concept, business process integration (BPI), which fuses workflow and enterprise application integration (EAI) technology. Two characteristic policies are included in BPI. The first is to design the minimum set of business processes for real-time information sharing with planning packages without changing other processes. The second is to integrate several systems with EAI technology and to manage their execution with a workflow tool. Based on these policies, we propose various design templates and integration adapters. Our evaluation shows that using BPI, a target system can be developed with less manpower, in less time, and with higher quality than previous methods.     

On the computational power of insertion-deletion systems

Gene insertion and deletion are basic phenomena found in DNA processing or RNA editing in molecular biology. The genetic mechanism and development based on these evolutionary transformations have been formulated as a formal system with two operations of insertion and deletion, called insertion-deletion systems (Kari and Thierrin, 1996; Kari et al., 1997).We investigate the generative power of insertion-deletion systems (InsDel systems), and show that the family INS ¹ ₁ DEL ¹ ₁ is equal to the family of recursively enumerable languages. This gives a positive answer to an open problem posed in Kari et al. (1997) where it was conjectured contrary. This revised version was published online in June 2006 with corrections to the Cover Date.     

The characteristics of the external‐electrode mercury fluorescent lamp for backlighting liquid‐crystal‐television displays

Abstract— A reliable external‐electrode mercury fluorescent lamp (EEFL) has been developed for backlighting a liquid‐crystal‐television (LC‐TV) display. This involved the investigation of the EEFL characteristics and the improvement in the construction of the EEFL and drive waveforms, in the frequency range of 50–200 kHz, that affects the EEFL characteristics. The results showed that a sinusoidal waveform is suitable for driving the EEFL, and EEFL's voltage decreases when the frequency of the drive waveform is increased.     

Static Coarse Grain Task Scheduling with Cache Optimization Using OpenMP

Effective use of cache memory is getting more important with increasing gap between the processor speed and memory access speed. Also, use of multigrain parallelism is getting more important to improve effective performance beyond the limitation of loop iteration level parallelism. Considering these factors, this paper proposes a coarse grain task static scheduling scheme considering cache optimization. The proposed scheme schedules coarse grain tasks to threads so that shared data among coarse grain tasks can be passed via cache after task and data decomposition considering cache size at compile time. It is implemented on OSCAR Fortran multigrain parallelizing compiler and evaluated on Sun Ultra80 four-processor SMP workstation using Swim and Tomcatv from the SPEC fp 95. As the results, the proposed scheme gives us 4.56 times speedup for Swim and 2.37 times on 4 processors for Tomcatv respectively against the Sun Forte HPC Ver. 6 update 1 loop parallelizing compiler.     

Complete Mining of Frequent Patterns from Graphs: Mining Graph Data

Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.