Changes in Δ5- and Δ7-sterols during germination and seedling development ofCucurbita maximaduring germination and seedling development ofCucurbita maxima

While seeds ofCucurbita maxima contain both Δ⁵- and Δ⁷-sterols, the former, which have been described earlier, now have been found to disappear during germination. This suggests that a function exists for the Δ⁵-compounds only in the early part of the life cycle ofC. maxima, unlike most of the other higher plants studied. In contrast to the Δ⁵-sterols, the level of Δ⁷-sterols increased during germination as well as during seedling development and maturation. The period of transition between germination and seedling development appeared to be of special importance in terms of sterol changes. This period represented a surge of sterol biosynthesis with an ontogenetic shift in sterol composition from approximately equal amounts of 24α- and 24β-ethyl stereochemistry to a predominance of the former. The sterol composition of the mature plants included only about 5% of the 24β-ethylsterols. The configurational relationships were demonstrated by high resolution¹H-NMR. The sterols of the mature plants were: 25(27)-dehydrochondrillasterol, 24β-ethyl-25(27)-dehydrolathosterol, avenasterol, spinasterol, 22-dihydrospinasterol and 24ξ-methyllathosterol. Based on the changes which occurred in the relative amounts of the Δ⁷-sterols, it did not appear that the Δ⁵-components were being converted to their Δ⁷-analogs. A portion of this work was presented at the meeting of the American Oil Chemists' Society in May, 1985 in Philadelphia.     

Parallel depth first search. Part II. Analysis

This paper presents the analysis of a parallel formulation of depth-first search. At the heart of this parallel formulation is a dynamic work-distribution scheme that divides the work between different processors. The effectiveness of the parallel formulation is strongly influenced by the work-distribution scheme and the target architecture. We introduce the concept of isoefficiency function to characterize the effectiveness of different architectures and work-distribution schemes. Many researchers considered the ring architecture to be quite suitable for parallel depth-first search. Our analytical and experimental results show that hypercube and shared-memory architectures are significantly better. The analysis of previously known work-distribution schemes motivated the design of substantially improved schemes for ring and shared-memory architectures. In particular, we present a work-distribution algorithm that guarantees close to optimal performance on a shared-memory/-network-with-message-combining architecture (e.g. RP3). Much of the analysis presented in this paper is applicable to other parallel algorithms in which work is dynamically shared between different processors (e.g., parallel divide-and-conquer algorithms). The concept of isoefficiency is useful in characterizing the scalability of a variety of parallel algorithms.This work was supported by Army Research Office Grant No. DAAG29-84-K-0060 to the Artificial Intelligence Laboratory, and Office of Naval Research Grant N00014-86-K-0763 to the Computer Science Department at the University of Texas at Austin.     

Modeling drop breakage using the full energy spectrum and a specific realization of turbulence anisotropy

The assumption of homogeneous isotropic turbulence when modeling drop breakage in industrially relevant geometries is questionable. We describe the development of an anisotropic breakage model, where the anisotropy is introduced via the inclusion of a perturbed turbulence spectrum. The selection of the perturbed spectrum is itself motivated by our previous large-eddy simulations of high-pressure homogenizers. The model redistributes energy from small to large scales, and assumes that the anisotropic part of the Reynolds stresses is confined to the energy-containing range. The second-order structure function arising from the perturbed spectrum is used in the standard framework of Coulaloglou and Tavlarides to calculate breakage frequency. While the base model exhibits non-monotonic behavior (by predicting a maximum value for a certain drop size), the effect of anisotropy is shown to increase breakage frequency in length scales larger than this peak, thereby reducing non-monotonicity. This effect is more pronounced for small turbulence Reynolds numbers.     

Replication-Based Fault Tolerance for MPI Applications

As computational clusters increase in size, their mean time to failure reduces drastically. Typically, checkpointing is used to minimize the loss of computation. Most checkpointing techniques, however, require central storage for storing checkpoints. This results in a bottleneck and severely limits the scalability of checkpointing, while also proving to be too expensive for dedicated checkpointing networks and storage systems. We propose a scalable replication-based MPI checkpointing facility. Our reference implementation is based on LAM/MPI; however, it is directly applicable to any MPI implementation. We extend the existing state of fault-tolerant MPI with asynchronous replication, eliminating the need for central or network storage. We evaluate centralized storage, a Sun-X4500-based solution, an EMC storage area network (SAN), and the Ibrix commercial parallel file system and show that they are not scalable, particularly after 64 CPUs. We demonstrate the low overhead of our checkpointing and replication scheme with the NAS Parallel Benchmarks and the High-Performance LINPACK benchmark with tests up to 256 nodes while demonstrating that checkpointing and replication can be achieved with a much lower overhead than that provided by current techniques. Finally, we show that the monetary cost of our solution is as low as 25 percent of that of a typical SAN/parallel-file-system-equipped storage system.     

Quantitative analysis of microstructure refinement in ultrafine-grained strips of Al6063 fabricated using large strain extrusion machining

Abstract

In present research work, ultrafine-grained strips of Al-6063 alloy were fabricated using hybrid extrusion machining technique known as “large strain extrusion machining (LSEM).” Fabrication of strips was done using the customized HSS tools of different rake angles varying from 0° to 10° under different machining conditions. Microstructural and mechanical characterizations of these strips were done to ascertain the effect of different parameters on their properties. From the results of hardness measurement of strips, it was concluded that hardness of the strips increased by 34–97% of the base material as of the refinement of grain size occurred. Surface lay was improved by 30% with higher cutting velocity and rake angle. Crystallite size was found to decrease with increase in the rate of strain. The shear strain was increased as chip compression ratio increased and rake angle decreased. Fabrication ability of strips increased due to increase in strain hardening exponent and it may result in the large scope of their applications. Nano-hardness of the strips was found to be more than bulk alloy. These above said results showed that ultrafine strips fabricated using LSEM process can become a good choice for future material fabrication.     

A tetrode based fast pulsed microwave source for electron cyclotron resonance breakdown experiments

To study electron cylotron resonance (ECR) breakdown and afterglow plasma in an experimental linear plasma system, a pulsed microwave source with rapid rise and fall of microwave power is desired. A pulsed microwave source with fast rise and fall capability for ECR breakdown experiments has been designed and tested for performance in the system. A tetrode, controlled by a modulator card, is used as a fast switch to initiate microwave power from a conventional magnetron operating at 2.45 GHz. The typical rise time of microwave power is approximately 3 micros and a fall time of approximately 10 micros. Using this scheme in a realistic pulsed microwave source at 800 W power, ECR breakdown of neutral gas is achieved and the plasma delay and fall time are observed from the plasma density measurements using a Langmuir probe. The design details of the fast rise pulsed microwave source are presented in this article with initial experimental results.     

A reference based analysis framework for understanding anomaly detection techniques for symbolic sequences

Anomaly detection for symbolic sequence data is a highly important area of research and is relevant in many application domains. While several techniques have been proposed within different domains, understanding of their relative strengths and weaknesses is limited. The key factor for this is that the nature of sequence data varies significantly across domains, and hence while a technique might perform well in its original domain, its performance is not guaranteed in a different domain. In this paper, we aim at establishing this understanding for a wide variety of anomaly detection techniques for symbolic sequences. We present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. Many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data. The analysis presented in this paper allows relative comparison of the different anomaly detection techniques and highlights their strengths and weaknesses. We extend the reference based analysis (RBA) framework, which was originally proposed to analyze multivariate categorical data, to analyze symbolic sequence data sets. We visualize the symbolic sequences using the characteristics provided by the RBA framework and use the visualization to understand various aspects of the sequence data. We then use the characterization done by RBA to understand the performance of the different techniques. Using the RBA framework, we propose two anomaly detection techniques for symbolic sequences, which show consistently superior performance over the existing techniques across the different data sets.     

Estimation of greenhouse gas emissions from municipal wastewater treatment systems in India

Greenhouse gas (GHG) emissions generated from municipal wastewater treatment plants in India is estimated in this study. The emissions from the wastewater treatment process as well as from the electricity used during the treatment process are estimated by using the methodology of Intergovernmental Panel on Climate Change. The present treatment plants of capacity 15 997 million litres per day (MLD) contributes towards GHG emissions of 7.3 Mt of CO₂‐eq/year. The future GHG emissions would depend upon the treatment technology used for treating 34 109 MLD of untreated wastewater. The highest GHG emissions would occur if all new wastewater treatment plants are based on upflow anaerobic sludge blanket technology, 19.66 Mt CO₂‐eq/year and lowest if sequential batch reactor technology is adopted, 2.93 MtCO₂‐eq/year.     

Correction to: Pool Fires in Chemical Process Industries: Occurrence,Mechanism, Management

Journal of Failure Analysis and Prevention - In the original version of this article, Vipin’s name was incorrect. It is correct as reflected here. The original article has also been corrected.