基于多级价值评估的专利交易定价机制

为解决专利市场定价混乱、交易无序的问题,该文通过利用综合评价法及专利价值分析指标体系,构建基于多级价值评估的专利交易定价机制,并利用实际发生案例验证其合理性,科学准确地确定专利交易价格,拓宽专利交易渠道,从而规范专利交易市场,提高科技成果转化率,促进技术转移。     

The W***D C*P of 2*1*: FIFA's intellectual property rights in South Africa

Legal context: This article focuses on the relationship between trade markrights and other forms of statutory protection. Key points: FIFA is the proprietor of a number of trade mark registrationsin South Africa. The strength of these registrations is discussedand the view taken that a number are open to attack, in termsof both distinctiveness and user requirements. It is then shownthat, if statutory protection is given for the same words andphrases, the weaknesses of the trade mark registrations willbe avoided. Practical significance: The article serves as an illustration of the manner in whichinternational sporting bodies attempt to extend their IP protectionbeyond the bounds of existing legislation.     

生前与死后电击伤皮肤NSE活性的观察

本实验采用非特异性酯酶Ｎｏｎ－ｓｐｅｃｉｆｉｃＥｓｔｅｒｓｅ（Ｎ．Ｓ．Ｅ）组织化学方法对生前与死后电损伤进行实验研究，发现生前与死后短时间内的电损伤皮肤胶原纤维上ＮＳＥ活性有显著差别（Ｐ＜０．０５），在相同实验条件控制下，电击后存活时间越长，电流斑皮肤周围的酯酶着色反应越深，范围越宽。实验结果表明，Ｎ．Ｓ．Ｅ对于鉴别生前电流斑与死后电流斑具有法医学意义。     

Analytical pyrolysis of Streptococcus saliivarius as and aid to identification in bite-mark investigation

The use of pyrolysis mass spectrometry (Py-MS) and statistical analysis of mass spectra is introduced as a method for “finger-printing” strains of Streptococcus salivarius. The objective is to provide correlative evidence regarding the identity of suspects in cases of assault or rape involving bite-marks. The results of the analysis of isolates from two individuals are presented, illustrating the differentiation of S. salivarius at strain level according to the origin of the isolate.     

专利创造性的经济学分析

专利创造性的主要经济学理论包括选择价值理论、连续发明理论、错误成本理论和互补发明理论.这些经济学理论对深入认识专利创造性提供了有益的视角,并能够对专利政策的制定以及专利创造性判断的司法实践提供帮助.分析表明,专利实践中的很多做法都暗含了这些理论分析所隐含的经济理性,但是由于经济学理论难以提供可操作性的工具,经济分析要为政策制定和创造性判断提供具体指导还需要进一步研究.     

专利价值之谜及其理论求解

在当今专利制度中,尽管多数专利的价值往往少于专利申请和维持的费用,但专利申请案和授权量却急剧增长。这被称之为专利价值之谜,其理论求解应从专利获取的目的出发。竞争者之所以通过申请大量专利的方式形成专利组合,是因为它既是竞争者的防卫之盾,也是其进攻之矛。非竞争者所拥有的专利组合备受人们指责;但事实上,非实施企业拥有的专利质量大都可靠。此外,大量专利的形成是专利制度为鼓励专利竞赛有意而为的结果。因为由大量专利结合而成的专利组合能够区分市场上真正的创新者和模仿者,从而保障创新者的竞争优势。我国应该采取合理的措施鼓励我国的创新企业形成自己的专利组合。     

MEDIA DIGES

正China’s Electric Vehicle Dilemma Caixin February 102014 marks the fourth year since Chinalaunched its industrialization of electric vehicles.However,even in pilot cities like Beijingand Shanghai,it remains difficult for consumers to buy an electric vehicle.In order to promote electric vehicles,which are more expensive than traditionalfuel-burning vehicles,both the central andlocal governments have provided subsidies toelectric vehicle purchasers.For example,for an     

The E-learning Miracle

正AUGUST marks the first anniversary of xue.taobao.com,an online education platform along the lines of Taobao(the Chinese online shopping website equivalent to eBay and Amazon).Nipping at its heels,having appeared last November,is Google’s new product Helpout,a C2C(consumer-to-consumer)e-learning platform.This successive branching out of Internet giants into the e-learning marketplace will undoubtedly have a posi-     

专利许可中价格限制的反垄断法分析

专利许可中的价格限制是许可人对被许可人实施许可专利而制造的专利产品销售价格的限制。专利许可中的价格限制可能对竞争产生影响,多数国家的反垄断法对这一行为表现出不同形式的关注。但多数坚持合理原则,即在界定相关市场的基础上,详细分析诸多涉案因素,综合衡量限制竞争与相关效率之利弊,做出最终判断。我国在制定相应指南时,应在坚持合理原则的基础上,强化指南的可操作性,寻求立法一般规定的具体化,形成有针对性的特殊规则,对初次销售价格限制与转售价格限制做区别对待,并在宏观上恰当协调和衔接价格法、专利法与反垄断法的相关规定。     

Automated detection of regions of interest in cartridge case images using deep learning

This paper explores a deep-learning approach to evaluate the position of circular delimiters in cartridge case images. These delimiters define two regions of interest (ROI), corresponding to the breech face and the firing pin impressions, and are placed manually or by an image-processing algorithm. This positioning bears a significant impact on the performance of the image-matching algorithms for firearm identification, and an automated evaluation method would be beneficial to any computerized system. Our contribution consists in optimizing and training U-Net segmentation models from digital images of cartridge cases, intending to locate ROIs automatically. For the experiments, we used high-resolution 2D images from 1195 samples of cartridge cases fired by different 9MM firearms. Our results show that the segmentation models, trained on augmented data sets, exhibit a performance of 95.6% IoU (Intersection over Union) and 99.3% DC (Dice Coefficient) with a loss of 0.014 for the breech face images; and a performance of 95.9% IoU and 99.5% DC with a loss of 0.011 for the firing pin images. We observed that the natural shapes of predicted circles reduce the performance of segmentation models compared with perfect circles on ground truth masks suggesting that our method provide a more accurate segmentation of the real ROI shape. In practice, we believe that these results could be useful for firearms identification. In future work, the predictions may be used to evaluate the quality of delimiters on specimens in a database, or they could determine the region of interest on a cartridge case image.