Evaluation of Multipoint Dosing Strategy in a Miniaturized Tubular Reactor: Nitration of Salicylic Acid

A 2D non‐isothermal reaction engineering model for a tubular reactor was developed for a complex reaction network of salicylic acid nitration. The influence of different operating and design parameters was studied to minimize the amount of secondary nitration products and limit the maximum temperature inside the reactor. Critical temperature effects were observed for larger reaction tubes, whereas close to isothermal conditions were perceived in smaller tubes. With single‐point dosing of both reactants, complete conversion can be achieved but formation of secondary nitration products cannot be avoided. For a given number of dosing points, a suitable combination of the operating parameters allowed to achieve complete conversion and better yield of the desired product.     

Triplex Formation by Oligonucleotides Containing Organomercurated Base Moieties

Homothymine oligonucleotides with a single 5‐mercuricytosine or 5‐mercuriuracil residue at their termini have been synthesized and their capacity to form triplexes has been examined with an extensive array of double‐helical targets. UV and circular dichroism (CD) melting experiments revealed the formation and thermal denaturation of pyrimidine ? purine*pyrimidine‐type triple helices with all oligonucleotide combinations studied. Nearly all triplexes were destabilized upon mercuration of the 3′‐terminal residue of the triplex‐forming oligonucleotide, in all likelihood due to competing intramolecular Hg^II‐mediated base pairing. Two exceptions from this general pattern were, however, observed: 5‐mercuricytosine was stabilizing when placed opposite to a T ? A or A ? T base pair. The stabilization was further amplified in the presence of 2‐mercaptoethanol (but not hexanethiol, thiophenol or cysteine), suggesting a stabilizing interaction other than Hg^II‐mediated base pairing.     

“设计方法学”的基本步骤

本文通过过载保护装置的设计方法和步骤扼要阐述了“设计方法学”的基本观点与方法。并着重分析了任务提出、功能结构、物理效应、有效结构特征、评价选择、总体设计等基本步骤的实现以及寻找最佳方案的方法。     

Fast Distributed Outlier Detection in Mixed-Attribute Data Sets

Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinical diagnosis, from detecting anomalous defects in materials to fraud and intrusion detection. Over the past decade, researchers in data mining and statistics have addressed the problem of outlier detection using both parametric and non-parametric approaches in a centralized setting. However, there are still several challenges that must be addressed. First, most approaches to date have focused on detecting outliers in a continuous attribute space. However, almost all real-world data sets contain a mixture of categorical and continuous attributes. Categorical attributes are typically ignored or incorrectly modeled by existing approaches, resulting in a significant loss of information. Second, there have not been any general-purpose distributed outlier detection algorithms. Most distributed detection algorithms are designed with a specific domain (e.g. sensor networks) in mind. Third, the data sets being analyzed may be streaming or otherwise dynamic in nature. Such data sets are prone to concept drift, and models of the data must be dynamic as well. To address these challenges, we present a tunable algorithm for distributed outlier detection in dynamic mixed-attribute data sets.     

Model-based approximate querying in sensor networks

Declarative queries are proving to be an attractive paradigm for interacting with networks of wireless sensors. The metaphor that “the sensornet is a database” is problematic, however, because sensors do not exhaustively represent the data in the real world. In order to map the raw sensor readings onto physical reality, a model of that reality is required to complement the readings. In this article, we enrich interactive sensor querying with statistical modeling techniques. We demonstrate that such models can help provide answers that are both more meaningful, and, by introducing approximations with probabilistic confidences, significantly more efficient to compute in both time and energy. Utilizing the combination of a model and live data acquisition raises the challenging optimization problem of selecting the best sensor readings to acquire, balancing the increase in the confidence of our answer against the communication and data acquisition costs in the network. We describe an exponential time algorithm for finding the optimal solution to this optimization problem, and a polynomial-time heuristic for identifying solutions that perform well in practice. We evaluate our approach on several real-world sensor-network datasets, taking into account the real measured data and communication quality, demonstrating that our model-based approach provides a high-fidelity representation of the real phenomena and leads to significant performance gains versus traditional data acquisition techniques. This article includes and extends results that were previously published in VLDB 2004 [Desphande, A., Guestrin, C., Madden, S., Hellerstein, J.M., Hong, W.: Model-driven data acquisition in sensor networks. In {VLDB} (2004)], and combines these techniques with the conditional planning approach published in ICDE 2005 [Deshpande, A., Guestrin, C., Madden, S., Hong, W.: Exploiting correlated attributes in acquisitional query processing. In {ICDE} (2005)].     

Analysis of exoskeleton triglycerides ofLeptinotarsa decemlineata say

The exoskeleton triglyceride fraction isolated from the Colorado beetle,Leptinotarsa decemlineata Say, was studied. Analysis of the hydrolysis products and direct capillary column gas chromatography showed that, apart from triglycerides, the fraction contained no diol lipids. The composition of the natural triacylglccerol mixture was assessed by gas chromatography and by field desorption and electron impact mass spectrometry. Triglycerides isolated from the Colorado beetle are typical glycerol triesters, with long chain (mainly oleic or palmitic) fatty acids. The structures of two major components (91%), i.e., trioleoyl glycerol and 1,2-dioleoyl-3-palmitoyl glycerol, were determined.     

Automatisierte Mikrobild-Analyse zur Klassifizierung von Eisenerz für die Roheisenherstellung

The mineralogical composition and structural properties of iron ores control their behaviour in industrial reduction plants. Micro-images of polished sections are processed by the software VisuMet to determine the proportions of limonite, hematite and magnetite. From the mineralogical composition and the structural properties of iron ores VisuMet assesses their reduction properties at standard reduction conditions.     

Managing carbon regulatory risk in utility resource planning: Current practices in the Western United States

Concerns about global climate change have substantially increased the likelihood that future policy will seek to minimize carbon dioxide emissions. As such, even today, electric utilities are making resource planning and investment decisions that consider the possible implications of these future carbon regulations. In this article, we examine the manner in which utilities assess the financial risks associated with future carbon regulations within their long-term resource plans. We base our analysis on a review of the most recent resource plans filed by 15 electric utilities in the Western United States. Virtually all of these utilities made some effort to quantitatively evaluate the potential cost of future carbon regulations when analyzing alternate supply- and demand-side resource options for meeting customer load. Even without federal climate regulation in the US, the prospect of that regulation is already having an impact on utility decision-making and resource choices. That said, the methods and assumptions used by utilities to analyze carbon regulatory risk, and the impact of that analysis on their choice of a particular resource strategy, vary considerably, revealing a number of opportunities for analytic improvement. Though our review focuses on a subset of US electric utilities, this work holds implications for all electric utilities and energy policymakers who are seeking to minimize the compliance costs associated with future carbon regulations.