会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 5. 发明授权
    • Use of photopolymerization for amplification and detection of a molecular recognition event
    • 使用光聚合进行扩增和检测分子识别事件
    • US07354706B2
    • 2008-04-08
    • US11372485
    • 2006-03-09
    • Kathy L. RowlenJohn W. BirksChristopher BowmanHadley SikesRyan HansenRobert Kuchta
    • Kathy L. RowlenJohn W. BirksChristopher BowmanHadley SikesRyan HansenRobert Kuchta
    • C12Q1/68C12Q1/70G01N33/53
    • C12Q1/6816C12Q2565/401
    • The invention provides methods to detect molecular recognition events. The invention also provides methods to detect the presence of or identify a target species based on its interaction with one or more probe species. The methods of the invention are based on amplification of the signal due to each molecular recognition event. The amplification is achieved through photopolymerization, with the polymer formed being associated with the molecular recognition event. In an embodiment, a fluorescent polymer, a magnetic polymer, a radioactive polymer or an electrically conducting polymer can form the basis of detection and amplification. In another embodiment, a polymer gel swollen with a fluorescent solution, a magnetic solution, a radioactive solution or an electrically conducting solution can form the basis of detection and amplification. In another embodiment, sufficient polymer forms to be detectable by visual inspection.
    • 本发明提供检测分子识别事件的方法。 本发明还提供了基于其与一种或多种探针物种的相互作用来检测靶物种的存在或鉴定目的物种的方法。 本发明的方法基于由于每个分子识别事件引起的信号的放大。 通过光聚合实现扩增,形成的聚合物与分子识别事件相关联。 在一个实施方案中,荧光聚合物,磁性聚合物,放射性聚合物或导电聚合物可以形成检测和扩增的基础。 在另一个实施方案中,用荧光溶液,磁性溶液,放射性溶液或导电溶液溶胀的聚合物凝胶可以形成检测和扩增的基础。 在另一个实施方案中,足够的聚合物形式可通过目视检查来检测。
    • 6. 发明申请
    • Novel photopolymers and use in dental restorative materials
    • 新型光聚合物和用于牙科修复材料
    • US20070082966A1
    • 2007-04-12
    • US10576635
    • 2004-10-22
    • Christopher BowmanHui LuJeffrey Stansbury
    • Christopher BowmanHui LuJeffrey Stansbury
    • C08F2/50
    • C08G75/045A61C13/08A61C13/087A61K6/083C08F2/50G03F7/0275C08L33/00
    • Photopolymerizable polymer composites based on dimethacrylate systems have been increasingly utilized as dental restorative materials. One of the biggest drawbacks of current dental resin systems is the volume shrinkage and shrinkage induced stresses that arise during the polymerization. Other major problems include incomplete double bond conversion and insufficient wear resistance. This invention involves the development of an entirely novel approach to the photopolymerization process that utilizes thiol-ene systems as low shrinkage and ultra-low shrinkage stress dental restorative materials. Compared with the traditional dimethacrylate dental resins, these novel photopolymerizations have demonstrated a dramatically decreased volume shrinkage, extremely rapid polymerization, abilities to photopolymerize ultrathick materials and achieve much higher conversion, lack of oxygen inhibition and ultra-low shrinkage stress due to low volume shrinkage and drastically delayed gel point conversion. These polymers have thus shown outstanding suitability as dental restorative materials.
    • 基于二甲基丙烯酸酯体系的可光聚合聚合物复合材料越来越多地用作牙科修复材料。 现有牙科树脂系统的最大缺点之一是在聚合期间产生的体积收缩和收缩诱导的应力。 其他主要问题包括不完全双键转化和耐磨性不足。 本发明涉及开发一种全新的光聚合方法,其利用硫醇系统作为低收缩和超低收缩应力牙科修复材料。 与传统的二甲基丙烯酸酯牙科树脂相比,这些新型光聚合已经显示体积收缩率显着降低,聚合极快,光聚合超薄材料的能力,并且由于低体积收缩而实现了更高的转化率,缺少氧抑制和超低收缩应力, 急剧延迟凝胶点转化。 因此,这些聚合物显示出作为牙科修复材料的突出的适用性。
    • 7. 发明申请
    • Use of photopolymerization for amplification and detection of a molecular recognition event
    • 使用光聚合扩增和检测分子识别事件
    • US20060286570A1
    • 2006-12-21
    • US11372485
    • 2006-03-09
    • Kathy RowlenJohn BirksChristopher BowmanHadley SikesRyan HansenRobert Kuchta
    • Kathy RowlenJohn BirksChristopher BowmanHadley SikesRyan HansenRobert Kuchta
    • C12Q1/70C12Q1/68
    • C12Q1/6816C12Q2565/401
    • The invention provides methods to detect molecular recognition events. The invention also provides methods to detect the presence of or identify a target species based on its interaction with one or more probe species. The methods of the invention are based on amplification of the signal due to each molecular recognition event. The amplification is achieved through photopolymerization, with the polymer formed being associated with the molecular recognition event. In an embodiment, a fluorescent polymer, a magnetic polymer, a radioactive polymer or an electrically conducting polymer can form the basis of detection and amplification. In another embodiment, a polymer gel swollen with a fluorescent solution, a magnetic solution, a radioactive solution or an electrically conducting solution can form the basis of detection and amplification. In another embodiment, sufficient polymer forms to be detectable by visual inspection.
    • 本发明提供检测分子识别事件的方法。 本发明还提供了基于其与一种或多种探针物种的相互作用来检测靶物种的存在或鉴定目的物种的方法。 本发明的方法基于由于每个分子识别事件引起的信号的放大。 通过光聚合实现扩增,形成的聚合物与分子识别事件相关联。 在一个实施方案中,荧光聚合物,磁性聚合物,放射性聚合物或导电聚合物可以形成检测和扩增的基础。 在另一个实施方案中,用荧光溶液,磁性溶液,放射性溶液或导电溶液溶胀的聚合物凝胶可以形成检测和扩增的基础。 在另一个实施方案中,足够的聚合物形式可通过目视检查来检测。
    • 10. 发明授权
    • Detecting, classifying, and tracking abnormal data in a data stream
    • 检测,分类和跟踪数据流中的异常数据
    • US08306931B1
    • 2012-11-06
    • US12462634
    • 2009-08-06
    • Christopher BowmanDuane DeSieno
    • Christopher BowmanDuane DeSieno
    • G06E1/00G06E3/00G06F15/18G06G7/00G06N3/04
    • G06N3/0454
    • The present invention extends to methods, systems, and computer program products for detecting, classifying, and tracking abnormal data in a data stream. Embodiments include an integrated set of algorithms that enable an analyst to detect, characterize, and track abnormalities in real-time data streams based upon historical data labeled as predominantly normal or abnormal. Embodiments of the invention can detect, identify relevant historical contextual similarity, and fuse unexpected and unknown abnormal signatures with other possibly related sensor and source information. The number, size, and connections of the neural networks all automatically adapted to the data. Further, adaption appropriately and automatically integrates unknown and known abnormal signature training within one neural network architecture solution automatically. Algorithms and neural networks architecture are data driven, resulting more affordable processing. Expert knowledge can be incorporated to enhance the process, but sufficient performance is achievable without any system domain or neural networks expertise.
    • 本发明扩展到用于检测,分类和跟踪数据流中的异常数据的方法,系统和计算机程序产品。 实施例包括使得分析者能够基于标记为主要正常或异常的历史数据来检测,表征和跟踪实时数据流中的异常的集成算法。 本发明的实施例可以检测,识别相关的历史背景相似性,并且将意外和未知的异常签名与其他可能相关的传感器和源信息融合。 神经网络的数量,大小和连接都自动适应数据。 此外,自适应适应并自动将未知和已知的异常签名训练集成在一个神经网络架构解决方案中。 算法和神经网络架构是数据驱动的,从而实现更加实惠的处理。 可以结合专家知识来增强过程,但是没有任何系统领域或神经网络专长就可以实现足够的性能。