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Long-term exposure to benzene causes several adverse health effects, including an increased risk of acute myeloid leukemia. This study was to identify genetic alternations involved in pathogenesis of leukemia in benzene-exposed workers without clinical symptoms of leukemia. This study included 33 shoe-factory workers exposed to benzene at levels from 1 ppm to 10 ppm. These workers were divided into 3 groups based on the benzene exposure time, 1-<7, 7-<12, and 12-<24 years. 17 individuals without benzene exposure history were recruited as controls. Cytogenetic analysis using Affymetrix Cytogenetics Array found copy-number variations (CNVs) in several chromosomes of benzene-exposed workers. Expression of targeted genes in these altered chromosomes, NOTCH1 and BSG, which play roles in leukemia pathogenesis, was further examined using real-time PCR. The NOTCH1 mRNA level was significantly increased in all 3 groups of workers, and the NOTCH1 mRNA level in the 12-<24 years group was significantly higher than that in 1-,7 and 7-,12 years groups. Compared to the controls, theBSG mRNA level was significantly increased in 7-<12 and 12-<24 years groups, but not in the 1-<7 years group. These results suggest that CNVs and leukemia-related gene expression might play roles in leukemia development in benzene-exposed workers. [ABSTRACT FROM AUTHOR]

Transparent data replication is a promising technique for improving the system performance of a large distributed network. Transcoding is an important technology which adapts the same multimedia object to diverse mobile appliances; thus, users' requests for a specified version of a multimedia object could be served by a more detailed version cached according to transcoding. Therefore, it is particularly of theoretical and practical necessity to determine the proper version to be cached at each node such that the specified objective is achieved. In this paper, we address the problem of multimedia object placement for transparent data replication. The performance objective is to minimize the total access cost by considering both transmission cost and transcoding cost. We present optimal solutions for different cases for this problem. The performance of the proposed solutions is evaluated with a set of carefully designed simulation experiments for various performance metrics over a wide range of system parameters. The simulation results show that our solution consistently and significantly outperforms comparison solutions in terms of all the performance metrics considered. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of cache replacement for transcoding proxy caching. Transcoding proxy is a proxy that has the functionality of transcoding a multimedia object into an appropriate format or resolution for each client. We first propose an effective cache replacement algorithm for transcoding proxy. In general, when a new object is to be cached, cache replacement algorithms evict some of the cached objects with the least profit to accommodate the new object. Our algorithm takes into account of the inter-relationships among different versions of the same multimedia object, and selects the versions to replace according to their aggregate profit which usually differs from simple summation of their individual profits as assumed in the existing algorithms. It also considers cache consistency, which is not considered in the existing algorithms. We then present a complexity analysis to show the efficiency of our algorithm. Finally, we give extensive simulation results to compare the performance of our algorithm with some existing algorithms. The results show that our algorithm outperforms others in terms of various performance metrics. [ABSTRACT FROM AUTHOR]

The author discusses articles published in the journal including one on new web segmentation methodology based on the image processing technology , one on field programmable gate array (FPGA) and one on high performance storage system for Resource Description Format (RDF) documents.

In this paper, a coefficient adaptive scoring method of molecular docking is presented to improve the docking accuracy with multiple available scoring functions. Based on force-field scoring function, we considered hydrophobic and deformation as well in the proposed method, Instead of simple combination with fixed weights, coefficients of each factor are adaptive in searching procedure. In order to improve the docking accuracy and stability, knowledge-based scoring function is used as another scoring factor. Genetic algorithm with the multi-population evolution and entropy-based searching technique with narrowing down space is used to solve the optimization model for molecular docking. To evaluate the method, we carried out a numerical experiment with 134 proteinligand complexes of the publicly available GOLD test set. The results validated that it improved the docking accuracy over the individual force-field scoring. In addition, analyses were given to show the disadvantage of individual scoring model. Through the comparison with other popular docking software, the proposed method showed higher accuracy. Among more than 77% of the complexes, the docked results were within 1.0 Å according to Root- Mean-Square Deviation (RMSD) of the X-ray structure. The average computing time obtained here is 563.9 s. [ABSTRACT FROM AUTHOR]

The increasing demand for the coverage of high-speed wireless local area networks (WLANs) is driving the installation of a very large number of access points (APs). Wireless mesh networks (WMNs) have emerged as a promising technology in the next generation networks to provide economical and scalable broadband access to wireless interconnection of multiple APs that manage individual WLANs in order to extend the coverage of the conventional single WLANs. In this paper, we develop a new analytical model to investigate the quality-of-service (QoS) performance metrics in WMNs interconnecting multiple WLANs. The model takes the phenomenon of communication locality into consideration. Extensive simulation experiments are conducted to validate the accuracy of the analytical model. The proposed model is then used to obtain the maximum achievable throughput, which is a key performance metrics in wireless networks. Moreover, we utilize the model to evaluate the impact of communication locality on network performance and investigate its effects on the optimization of integrated WLANs and multi-hop mesh networks. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Load balancing is effective in reducing network congestion and improving network throughput in wireless sensor networks (WSNs). Due to the fluctuation of wireless channels, traditional schemes achieving load balancing in WSNs need to maintain global or local congestion information, which turn out to be complicated to implement. In this paper, we design a flowlet switching based load balancing scheme, called EasyLB, by extending OpenFlow protocol. Flowlet switching is efficient to achieve adaptive load balancing in WSNs. Nevertheless, one tricky problem lies in determining the flowlet timeout value, δ. Setting it too small would risk reordering issue, while setting it too large would reduce flowlet opportunities. By formulating the timeout setting problem with a stationary distribution of Markov chain, we give a theoretical reference for setting an appropriate timeout value in flowlet switching based load balancing scheme. Moreover, non-equal probability path selection and multiple parallel load balancing paths are considered in timeout setting problem. Experimental results show that, by setting timeout value following the preceding theoretical reference, EasyLB is adaptive to wireless channel condition change and achieves fast convergence of load balancing after link failures. [ABSTRACT FROM AUTHOR]

Environmentally persistent organic pollutant (POP) is the general term for refractory organic compounds that show long-range atmospheric transport, environmental persistence, and bioaccumulation. It has been reported that the accumulation of POPs could lead to cellular DNA damage and adverse effects of on metabolic health. To better understand the mechanism of the health risks associated with POPs, we conducted an evidence-based cohort investigation (n = 5,955) at the Jinghai e-waste disposal center in China from 2009 to 2016, where people endure serious POP exposure. And high levels of aging-related diseases, including hypertension, diabetes, autoimmune diseases, and reproductive disorders were identified associated with the POP exposure. In the subsequent molecular level study, an increased telomere dysfunction including telomere multiple telomere signals, telomere signal-free ends, telomere shortening and activation of alternative lengthening of telomeres were observed, which might result from the hypomethylated DNA modification induced telomeric repeat-containing RNA overexpression. Moreover, dysfunctional telomere-leaded senescence-associated secretory phenotype was confirmed, as the proinflammatory cytokines and immunosenescence hallmarks including interleukin-6, P16INK4a, and P14ARF were stimulated. Thus, we proposed that the dysfunctional telomere and elevated systemic chronic inflammation contribute to the aging-associated diseases, which were highly developed among the POP exposure individuals. [ABSTRACT FROM AUTHOR]

Optimizations have been applied in many different engineering fields. Most of these applications may have similar characteristics: intensive on computing resources, time-consuming on calculation iterations, similar on computing environments and so on. This paper describes a generic cloud platform for engineering optimization by leveraging the compute resources hosted in cloud datacenters. The methodology developed was to decompose the engineering optimization processes into several interconnected sub-tasks, which were further converted and implemented as virtual applications for dynamic cloud deployment using OpenStack. The system can dynamically allocate and recycle the compute resources according to the specific engineering optimization applications. The research presented in the paper contributes on the generic engineering optimization process virtualization and cloud computing based implementation with innovative algorithms development. The system test results showed a way that potentially engineering optimization problems could be embedded into the put forward platform due to the developed large scale and intelligent cloud based optimization services. Further applications for building energy simulation and optimization, stents optimization, water distribution optimization are currently under development. [ABSTRACT FROM AUTHOR]

The health effects of exposure to pollutants from electronic waste (e-waste) pose an important issue. In this study, we explored the association between oxidative stress and blood levels of e-waste-related pollutants. Blood samples were collected from individuals living in the proximity of an e-waste recycling site located in northern China, and pollutants, as well as reactive oxygen species (ROS), were measured in comparison to a reference population. The geometric mean concentrations of PCBs, dechlorane plus, and 2,2',4,4',5,5'-hexabromobiphenyl in plasma from the exposure group were 60.4, 9.0, and 0.55 ng g-1 lipid, respectively, which were 2.2, 3.2, and 2.2 times higher than the corresponding measurement in the reference group. Correspondingly, ROS levels in white blood cells, including in neutrophil granulocytes, from the exposure group were significantly higher than in those from the reference group, suggesting potential ROS related health effects for residents at the e-waste site. In contrast, fewer ROS were generated in the respiratory burst of neutrophil granulocytes for the exposure group, indicating a depressed innate immune function for the individuals living at the e-waste site. These findings suggest a potential linkage between exposure to pollutants from e-waste recycling and both elevated oxidative stress and altered immune function. [ABSTRACT FROM AUTHOR]

With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing techniques from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including definition of big data, big data management platform, big data service models, distributed file system, data storage, data virtualization platform and distributed applications. Following the MapReduce parallel processing framework, we introduce some MapReduce optimization strategies reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments. [ABSTRACT FROM AUTHOR]