Event Detection on Twitter

Detecting events by using social media has been an active research problem. In this work, we investigate and compare the performance of two methods for event detection in Twitter by using Apache Storm as the stream processing infrastructure. The first event detection method is based on identifying uncommonly common words inside tweet blocks, and the second one is based on clustering tweets to detect a cluster as an event. Each of the methods has its own characteristics. Uncommonly common word based method relies on the burst of words and hence is not affected from concurrency problems in distributed environment. On the other hand, clustering based method includes a finer grained analysis, but it is sensitive to the concurrent processing. We investigate the effect of stream processing and concurrency handling support provided by Apace Storm on event detection by these methods

A redox-neutral, two-enzyme cascade for the production of malate and gluconate from pyruvate and glucose

A triple mutant of NADP(H)-dependent malate dehydrogenase from thermotolerant Thermococcus kodakarensis has an altered cofactor preference for NAD+, as well as improved malate production compared to wildtype malate dehydrogenase. By combining mutant malate dehydrogenase with glucose dehydrogenase from Sulfolobus solfataricus and NAD+/NADH in a closed reaction environment, gluconate and malate could be produced from pyruvate and glucose. After 3 h, the yield of malate was 15.96 mM. These data demonstrate the feasibility of a closed system capable of cofactor regeneration in the production of platform chemicals

Pharmaceutical applications of lignin-derived chemicals and lignin-based materials: linking lignin source and processing with clinical indication

Lignocellulosic biomass is one of the most abundant bioresources on Earth. Over recent decades, various valorisation techniques have been developed to produce value-added products from the cellulosic and hemicellulosic fractions of this biomass. Lignin is the third major component accounting for 10–30% (w/w). However, it currently remains a largely unused fraction due to its recalcitrance and complex structure. The increase in the global demand for lignocellulosic biomass, for energy and chemical production, is increasing the amount of waste lignin available. Approaches to date for valorizing this renewable but heterogeneous chemical resource have mainly focused on production of materials and fine chemicals. Greater value could be gained by developing higher value pharmaceutical applications which would help to improve integrated biorefinery economics. In this review, different lignin extraction methods, such as organosolv and ionic liquid, and the properties and potential of the extracted chemical building blocks are first summarized with respect to pharmaceutical use. The review then discusses the many recent advances made regarding the medical or therapeutic potential of lignin-derived materials such as antimicrobial, antiviral, and antitumor compounds and in controlled drug delivery. The aim is to draw out the link between the source and the processing of the biomass and potential clinical applications. We then highlight four key areas for future research if therapeutic applications of lignin-derived products are to become commercially viable. These relate to the availability and processing of lignocellulosic biomass, technologies for the purification of specific compounds, enhancements in process yield, and progression to human clinical trials

Pharmaceutical applications of lignin-derived chemicals and lignin-based materials: linking lignin source and processing with clinical indication

Lignocellulosic biomass is one of the most abundant bioresources on Earth. Over recent decades, various valorisation techniques have been developed to produce value-added products from the cellulosic and hemicellulosic fractions of this biomass. Lignin is the third major component accounting for 10–30% (w/w). However, it currently remains a largely unused fraction due to its recalcitrance and complex structure. The increase in the global demand for lignocellulosic biomass, for energy and chemical production, is increasing the amount of waste lignin available. Approaches to date for valorizing this renewable but heterogeneous chemical resource have mainly focused on production of materials and fine chemicals. Greater value could be gained by developing higher value pharmaceutical applications which would help to improve integrated biorefinery economics. In this review, different lignin extraction methods, such as organosolv and ionic liquid, and the properties and potential of the extracted chemical building blocks are first summarized with respect to pharmaceutical use. The review then discusses the many recent advances made regarding the medical or therapeutic potential of lignin-derived materials such as antimicrobial, antiviral, and antitumor compounds and in controlled drug delivery. The aim is to draw out the link between the source and the processing of the biomass and potential clinical applications. We then highlight four key areas for future research if therapeutic applications of lignin-derived products are to become commercially viable. These relate to the availability and processing of lignocellulosic biomass, technologies for the purification of specific compounds, enhancements in process yield, and progression to human clinical trials

A Novel Wind Power Forecast Model: Statistical Hybrid Wind Power Forecast Technique (SHWIP)

As the result of increasing population and growing technological activities, nonrenewable energy sources, which are the main energy providers, are diminishing day by day. Due to this factor, efforts on efficient utilization of renewable energy sources have increased all over the world. Wind is one of the most significant alternative energy resources. However, in comparison with other renewable energy sources, it is so variable that there is a need for estimating and planning of wind power generation. In this paper, a new statistical short-term (up to 48 h) wind power forecast model, namely statistical hybrid wind power forecast technique (SHWIP), is presented. In the proposed model, weather events are clustered with respect to the most important weather forecast parameters. It also combines the power forecasts obtained from three different numerical weather prediction (NWP) sources and produces a hybridized final forecast. The proposed model has been in operation at the Wind Power Monitoring and Forecast System for Turkey (RITM), and the results of the newmodel are compared with well-known statistical models and physical models in the literature. The most important characteristics of the proposed model is the need for a lesser amount of historical data while constructing the mathematical model compared with the other statistical models such as artificial neural networks (ANN) and support vector machine (SVM). To produce a reliable forecast, ANN and SVM need at least 1 year of historical data; on the other hand, the proposed SHWIP method's results are applicable even under 1 month of training data, and this is an important feature for the forecast of the newly established wind power plants (WPPs)

ABSTRACT TASK HANDLING IN WORKFLOW MANAGEMENT SYSTEMS

Work ow management systems aim to automate the execution of business processes. One of the objectives of the work ow systems is to include the already existing applications such as legacy applications as well as new applications, which are termed as tasks, into the system and provide synchronized execution among them. To achieve this, amechanism is necessary to support the communication between the tasks and the system. The communication mechanism should handle the transfer of data necessary for the execution of the tasks and for the scheduling of the tasks. Another point tobenoted is the necessity of the handling user tasks that have to be performed by the users of the work ow system. Since the trend is toward distributed execution to avoid the bottlenecks due to the nature of central systems