Competitive service market: modeling, storage and management

In order to capture the business dynamics underlying SOA-based service systems, we propose and formalize the concept of a competitive service market (CSM). A CSM is composed of a set of composite service providers, each managing a collection of atomic service providers. With the help of service composition protocol, composite service providers are able to invoke atomic services and aggregate them into value-added composite services for servicing various types of customers\u27 requests. Centering around the setting of a competitive service market, our research is separated into three parts: 1. Aiming to support the quantitative-based decision processes of different market players, we construct stochastic models to conduct performance analysis at various levels spanning vertically on the structural hierarchy of the service market. 2. In the context of requirements analysis, we classify the concept of service and service instance in terms of their respective functional and non-functional features. Hereafter, we identify the related storage issues and propose a counting Bloom filter-based hybrid storage architecture for the service registry design underlying the service market. A feature-based service discovery protocol is developed to demonstrate the usefulness of this design. 3. The business relationship between different market players are typically framed through the service level agreements (SLAs), which specify the attributes of QoS-based metrics and service costs for the realized service provisioning. SLAs constitute the backbone structure for managing the CSM. We identify several SLA design patterns in terms of different business scenarios that can occur in the life cycle of a service market. Against each pattern we study the corresponding SLA design scheme that can meet its unique requirements. In addition, we systematically investigate the application of Bayes estimator in these schemes, since the knowledge of their negotiation counterpart or market competitors is essential for reaching the goal of utility optimization. At the end, we cast the hybrid SLA design framework into a stochastic model that allows decision makers to obtain evaluations of performance of interest

Development of attractants and repellents for Tuta absoluta based on plant volatiles from tomato and eggplant

IntroductionTuta absoluta is currently considered one of the most devastating invasive pests of solanaceous plants worldwide, causing severe damage to the tomato industry. Insects use volatile organic compounds (VOCs) to locate host plant for feeding and oviposition. Those VOCs could be developed as lures for pest monitoring and control.MethodsIn this study, the differentially accumulated VOCs between the preferred host (tomato) and non-preferred host (eggplant) were analyzed by GC–MS method, and their roles on female T. absoluta host selection and egg laying behaviors were investigated using electroantennography (EAG), olfactometer and cage experiments.ResultsA total of 39 differentially accumulated VOCs were identified in tomato and eggplant. Strong EAG signals were obtained in 9 VOCs, including 5 VOCs highly accumulated in tomato and 4 VOCs highly accumulated in eggplant. Further olfactometer bioassays showed that 4 compounds (1-nonanol, ethyl heptanoate, ethyl octanoate and o-nitrophenol) were attractive to T. absoluta females, while 5 compounds (2-phenylethanol, 2-pentylfuran, trans,trans-2,4-nonadienal, 2-ethyl-5-methylpyrazine and trans-2-nonenal) were repellent, indicating that VOCs from host plants play important roles in host plant preferences. The attractive activities of 1-nonanol and ethyl octanoate, as well as the repellent activities of trans,trans-2,4-nonadienal and trans-2-nonenal, were further confirmed in cage experiments.DiscussionIn this study, two attractants and two repellents for T. absoluta were developed from plant released VOCs. Our results could be useful to enhance the development of eco-friendly and sustainable pest management strategies for T. absoluta

Frequencies of board meetings on various topics and corporate governance: evidence from China

This paper examines the relationship between number of topic-specific board meetings and quality of corporate governance. The quality of corporate governance is estimated by CEO turnover-performance and compensation-performance sensitivities. Information about topic-specific meetings is collected from the reports of independent directors of Chinese listed firms. We find that more frequent discussions of growth strategies related to the use of IPO proceeds, investment and acquisitions increase CEO compensation-performance sensitivity. By contrast, more discussions about the nomination of directors and top management are likely to reduce the sensitivities of both CEO turnover and compensation to performance. Our findings shed light on what makes boards efficient, and how board monitoring of assorted decisions modifies the relationship between CEO interests and firm performance

Implicit methods for Markov chain state classification

Markov chains are a well-established and important tool to assess the performance and dependability of computer and communication systems. An important step in many types of Markov chain analysis is the classification of states into recurrent classes and the class of transient states. The state-space explosion problem requires us to use the symbolic methods to handle the Markov chains built to model the practical engineering systems. Current symbolic method for Markov chain state classification makes use of the pure random mechanism to select the "seed state", a core variable for controlling the required number of iterations. In this work, we present several distance based heuristics to improve the existing methods. These approaches are designed to re-gain some control over the selection of the seed state, which tries to reduce the required number of iterations. Experimental results indicate that our approaches can be quite effective in minimizing the required number of iterations. Extensive qualitative analysis is also conducted over several models to compare the performance of different heuristics.</p

Competitive service market: modeling, storage and management

In order to capture the business dynamics underlying SOA-based service systems, we propose and formalize the concept of a competitive service market (CSM). A CSM is composed of a set of composite service providers, each managing a collection of atomic service providers. With the help of service composition protocol, composite service providers are able to invoke atomic services and aggregate them into value-added composite services for servicing various types of customers' requests. Centering around the setting of a competitive service market, our research is separated into three parts: 1. Aiming to support the quantitative-based decision processes of different market players, we construct stochastic models to conduct performance analysis at various levels spanning vertically on the structural hierarchy of the service market. 2. In the context of requirements analysis, we classify the concept of service and service instance in terms of their respective functional and non-functional features. Hereafter, we identify the related storage issues and propose a counting Bloom filter-based hybrid storage architecture for the service registry design underlying the service market. A feature-based service discovery protocol is developed to demonstrate the usefulness of this design. 3. The business relationship between different market players are typically framed through the service level agreements (SLAs), which specify the attributes of QoS-based metrics and service costs for the realized service provisioning. SLAs constitute the backbone structure for managing the CSM. We identify several SLA design patterns in terms of different business scenarios that can occur in the life cycle of a service market. Against each pattern we study the corresponding SLA design scheme that can meet its unique requirements. In addition, we systematically investigate the application of Bayes estimator in these schemes, since the knowledge of their negotiation counterpart or market competitors is essential for reaching the goal of utility optimization. At the end, we cast the hybrid SLA design framework into a stochastic model that allows decision makers to obtain evaluations of performance of interest.</p

An Efficient Service Discovery Algorithm for Counting Bloom Filter-Based Service Registry

The Service registry, the yellow pages of Service-Oriented Architecture (SOA), plays a central role in SOA-based service systems. The service registry has to be scalable to manage large number of services along with their requirements on storage and discovery. Based on our previous work on feature-based services quantification, we characterize services according to their diverse functional and non-functional requirements, and represent them as string formats which can be stored, probed, and indexed by efficient data structures, such as hash table and Bloom filter. Then, we propose a comprehensive service-storage solution using the counting Bloom filter (CBF). The application of CBF enables us to structure candidate services into separate groups, resulting in an accelerated services discovery process. The contributions of this research work include a new approach to manage large number of services based on quantified service features, and a storage architecture design to support service discovery. Experimental results strongly support these claims.This is a manuscript of a proceeding published as S. Cheng, C. K. Chang and L. -J. Zhang, "An Efficient Service Discovery Algorithm for Counting Bloom Filter-Based Service Registry," 2009 IEEE International Conference on Web Services, 2009, pp. 157-164, doi: 10.1109/ICWS.2009.121. Posted with permission. © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Tectorigenin alleviates the apoptosis and inflammation in spinal cord injury cell model through inhibiting insulin-like growth factor-binding protein 6

Since tectorigenin has been reported to possess anti-inflammation, redox balance restoration, and anti-apoptosis properties, we determine to unravel whether tectorigenin has potential in alleviating spinal cord injury (SCI). Herein, PC12 cells were induced by lipopolysaccharide (LPS) to establish in vitro SCI models. The cell viability and apoptosis were detected through cell counting kit-8 and flow cytometry assays. The caspase-3/8/9 content was measured by colorimetric method. Western blot was conducted to quantify the expressions of cleaved caspse-3/8/9, IGFBP6, TLR4, IκBα, p-IκBα, RELA proto-oncogene, p65, and p-p65. Enzyme-linked immunosorbent assay and real-time quantitative polymerase chain reaction were carried out to quantitate expressions of IGFBP6, interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α). SwissTargetPrediction and GSE21497 database were utilized to predict the potential therapeutic targets of tectorigenin. Comparison of IGFBP6 expression in SCI tissues and normal tissues was analyzed by GEO2R. Our study found that LPS induced the declined cell viability, elevated cell apoptosis, upregulation of caspase-3/8/9, cleaved caspase-3/8/9, IL-1β, IL-6, TNF-α, IGFBP6, and TLR4, and the activation of IκBα and p65 in PC12 cells. Tectorigenin reversed the above effects of LPS. IGFBP6 was predicted to be the potential therapeutic target of tectorigenin and was overexpressed in SCI tissues. Notably, IGFBP6 overexpression offset the effects of tectorigenin on PC12 cells. In conclusion, tectorigenin could alleviate the LPS-induced apoptosis, inflammation, and activation of NF-κB signaling in SCI cell models via inhibiting IGFBP6