22 research outputs found

    The Guatemalan Beaded Lizard Breeding Program at Zoo Atlanta

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    The Guatemalan Beaded Lizard Breeding Program at Zoo Atlanta

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    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Spatial extent of invasiveness and invasion stage categorisation of established weeds of Queensland, Australia

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    The risk posed by invasive alien species is determined primarily by two factors: distribution (occupancy) and abundance (density). However, most ecological studies use distribution data for monitoring and assessment programs, but few incorporate abundance data due to financial and logistical constraints. Failure to take into account invaders’ abundance may lead to imprecise pest risk assessments. Since 2003 as part of the Annual Pest Distribution Survey (APDS) exercise in the state of Queensland, Australia, government biosecurity officials have collected data on distribution and abundance of more than 100 established and emerging weeds. This data acquisition was done at spatial grid sizes of 17–50 × 17–50 km and across a very broad and varied geographical land area of ~2 × 106 km2. The datasets provide an opportunity to compare weed dynamics at large-medium spatial scales. Analysis of the APDS datasets indicated that weed distributions were highest in regions along the southern and central, coastal parts of Queensland, and decreased in the less populated inland (i.e. western) and northern parts of the state. Weed abundance showed no discernible landscape or regional trends. Positive distribution–abundance relationships were also detected at multiple spatial scales. Using both traits of weed abundance and distribution, we derived a measure of invasion severity, and constructed, for several (64) weed species, ‘space-for-time’ invasion curves. State-wide and in each of Queensland’s 10 regions, we also categorised the invasion stages of these weeds. At the grassroots of local government area or regional levels, the derived invasion curves and stage categories can provide policy direction for long-term management planning of Queensland’s priority weeds

    NEOPLASIA IN SNAKES AT ZOO ATLANTA DURING 1992–2012

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    This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON COMPUTERS Resource Allocation in a Client/Server System for Massive Multi-

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    The creation of a Massive Multi-Player On-line Game (MMOG) has significant costs, such as maintenance of server rooms, server administration, and customer service. The capacity of servers in a client/server MMOG is hard to scale and cannot adjust quickly to peaks in demand while maintaining the required response time. To handle these peaks in demand, we propose to employ users ’ computers as secondary servers. The introduction of users ’ computers as secondary servers allows the performance of the MMOG to support an increase in users. Here, we consider two cases. First, for the minimization of the response times from the server, we develop and implement five static heuristics to implement a secondary server scheme that reduces the time taken to compute the state of the MMOG. Second, for our study on fairness, the goal of the heuristics is to provide a “fair ” environment for all the users (in terms of similar response times), and to be “robust ” against the uncertainty of the number of new players that may join a given system configuration. The number of heterogeneous secondary servers, conversion of a player to a secondary server, and assignment of players to secondary servers are determined by the heuristics implemented in this study. I

    Robust Resource Allocation in a Massive Multiplayer Online Gaming Environment

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    The environment considered in this research is a massive multiplayer online gaming (MMOG) environment. Each user controls an avatar (an image that represents and is manipulated by a user) in a virtual world and interacts with other users. An important aspect of MMOG is maintaining a fair environment among users (i.e., not give an unfair advantage to users with faster connections or more powerful computers). The experience (either positive or negative) the user has with the MMOG environment is dependent on how quickly the game world responds to the user’s actions. This study focuses on scaling the system based on demand, while maintaining an environment that guarantees fairness. Consider an environment where there is a main server (MS) that controls the state of the virtual world. If the performance falls below acceptable standards, the MS can off-load calculations to secondary servers (SSs). An SS is a user’s computer that is converted into a server. Four heuristics are proposed for determining the number of SSs, which users are converted to SSs, and how users are assigned to the SSs and the MS. The goal of the heuristics is to provide a “fair ” environment for all the users, and to be “robust ” against the uncertainty of the number of new players that may join a given system configuration. The heuristics are evaluated and compared by simulation
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