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1. 发明申请

US20070088086A1 Method of using synthetic L-Se-methylselenocysteine as a nutriceutical and a method of its synthesis 审中-公开
标题翻译：使用合成的L-Se-甲基硒代半胱氨酸作为营养物质的方法及其合成方法
公开(公告)号：US20070088086A1
公开(公告)日：2007-04-19
申请号：US11583630
申请日：2006-10-18
申请人： Julian Spallholz , Ted Reid , Robert Walkup
发明人： Julian Spallholz , Ted Reid , Robert Walkup
IPC分类号： A61K31/198
CPC分类号： C07C391/00 , A23L33/165 , A23L33/175 , A23V2002/00 , A23V2200/308 , A23V2250/0616 , A23V2250/1626
摘要： A synthesis of and use for L-Se-methylselenocysteine as a nutriceutical is described, based upon the knowledge that L-Se-methylselenocysteine is less toxic than L-selenomethionine towards normal cells. The synthesis proceeds by mixing N-(tert-butoxycarbonyl)-L-serine with a dialkyl diazodicarboxylate and at least one of a trialkylphosphine, triarylphosphine, and phosphite to form a first mixture that includes N-(tert-butoxycarbonyl)-L-serine β-lactone. Methyl selenol or its salt is mixed with the N-(tert-butoxycarbonyl)-L-serine β-lactone to form a second mixture that includes N-(tert-butoxycarbonyl)-Se-methylselenocysteine. The tert-butoxycarbonyl group is removed from the N-(tert-butoxycarbonyl)-Se-methylselenocysteine to form L-Se-methylselenocysteine. This synthesis significantly improves the manufacturability, manufacturing efficiency, and utility of this naturally occurring rare form of organic-selenium. L-Se-methylselenocysteine formed, for example, in this manner may be used as a nutriceutical for supplementation into the diets of humans or animals for various beneficial purposes, such as, for example, to prevent or reduce the risk of developing cancer.
摘要翻译：基于L-Se-甲基硒代半胱氨酸对正常细胞毒性低于L-硒代甲硫氨酸的知识，描述了L-Se-甲基硒代半胱氨酸作为营养素的合成和用途。通过将N-（叔丁氧基羰基）-L-丝氨酸与二烷基二重氮二羧酸酯和三烷基膦，三芳基膦和亚磷酸酯中的至少一种混合以形成包含N-（叔丁氧基羰基）-L-丝氨酸 β-内酯。将甲基硒酚或其盐与N-（叔丁氧基羰基）-L-丝氨酸β-内酯混合以形成包括N-（叔丁氧基羰基）-Se-甲基硒代半胱氨酸的第二混合物。从N-（叔丁氧基羰基）-Se-甲基硒代半胱氨酸中除去叔丁氧羰基，形成L-Se-甲基硒代半胱氨酸。这种合成显着提高了这种天然存在的稀有形式的有机硒的可制造性，制造效率和效用。例如，以这种方式形成的L-Se-甲基硒代半胱氨酸可以用作补充到人类或动物的饮食中用于各种有益目的的营养物质，例如用于预防或降低发生癌症的风险。

2. 发明申请

US20060101104A1 Optimizing layout of an application on a massively parallel supercomputer 失效
标题翻译：在大型并行超级计算机上优化应用程序的布局
公开(公告)号：US20060101104A1
公开(公告)日：2006-05-11
申请号：US10963101
申请日：2004-10-12
申请人： Gyan Bhanot , Alan Gara , Philip Heidelberger , Eoin Lawless , James Sexton , Robert Walkup
发明人： Gyan Bhanot , Alan Gara , Philip Heidelberger , Eoin Lawless , James Sexton , Robert Walkup
IPC分类号： G06F1/16
CPC分类号： G06F9/5066
摘要： A general computer-implement method and apparatus to optimize problem layout on a massively parallel supercomputer is described. The method takes as input the communication matrix of an arbitrary problem in the form of an array whose entries C(i, j) are the amount to data communicated from domain i to domain j. Given C(i, j), first implement a heuristic map is implemented which attempts sequentially to map a domain and its communications neighbors either to the same supercomputer node or to near-neighbor nodes on the supercomputer torus while keeping the number of domains mapped to a supercomputer node constant (as much as possible). Next a Markov Chain of maps is generated from the initial map using Monte Carlo simulation with Free Energy (cost function) F=Σi,jC(i,j)H(i,j)—where H(i,j) is the smallest number of hops on the supercomputer torus between domain i and domain j. On the cases tested, found was that the method produces good mappings and has the potential to be used as a general layout optimization tool for parallel codes. At the moment, the serial code implemented to test the method is un-optimized so that computation time to find the optimum map can be several hours on a typical PC. For production implementation, good parallel code for our algorithm would be required which could itself be implemented on supercomputer.
摘要翻译：描述了在大型并行超级计算机上优化问题布局的通用计算机实现方法和装置。该方法采用数组形式的任意问题的通信矩阵作为输入，其条目C（i，j）是从域i到域j传送的数据量。给定C（i，j），首先实现启发式映射，其尝试顺序地将域及其通信邻居映射到超级计算机节点或超级计算机环面上的近邻节点，同时保持域的数量映射到超级计算机节点常数（尽可能多）。接下来，使用具有自由能量（成本函数）的蒙特卡罗模拟，从初始映射生成马尔可夫链映射，其中F =Σi，j C（i，j）H（i，j） H（i，j）是域i和域j之间的超级计算机环面上的最小跳数。在测试的情况下，发现该方法产生良好的映射，并且有可能被用作并行代码的通用布局优化工具。此时，实现测试方法的序列号未优化，以便在典型的PC上找到最佳映射的计算时间可以为几个小时。对于生产实现，将需要我们的算法的良好的并行代码，这本身可以在超级计算机上实现。

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