Codonopsis pilosula twines either to the left or to the right

We report the twining handedness of Codonopsis pilosula, which has either a left- or right-handed helix among different plants, among different tillers within a single plant, and among different branches within a single tiller. The handedness was randomly distributed among different plants, among the tillers within the same plants, but not among the branches within the same tillers. Moreover, the handedness of the stems can be strongly influenced by external forces, i.e. the compulsory left and right forming inclined to produce more left- and right-handed twining stems, respectively, and the reversing could make a left-handed stem to be right-handed and vice versa. We also discuss the probable mechanisms these curious cases happen

An Empirical Study of the Application of Machine Learning and Keyword Terms Methodologies to Privilege-Document Review Projects in Legal Matters

Protecting privileged communications and data from disclosure is paramount for legal teams. Unrestricted legal advice, such as attorney-client communications or litigation strategy. are vital to the legal process and are exempt from disclosure in litigations or regulatory events. To protect this information from being disclosed, companies and outside counsel must review vast amounts of documents to determine those that contain privileged material. This process is extremely costly and time consuming. As data volumes increase, legal counsel employ methods to reduce the number of documents requiring review while balancing the need to ensure the protection of privileged information. Keyword searching is relied upon as a method to target privileged information and reduce document review populations. Keyword searches are effective at casting a wide net but return over inclusive results -- most of which do not contain privileged information -- and without detailed knowledge of the data, keyword lists cannot be crafted to find all privilege material. Overly-inclusive keyword searching can also be problematic, because even while it drives up costs, it also can cast `too far of a net' and thus produce unreliable results.To overcome these weaknesses of keyword searching, legal teams are using a new method to target privileged information called predictive modeling. Predictive modeling can successfully identify privileged material but little research has been published to confirm its effectiveness when compared to keyword searching. This paper summarizes a study of the effectiveness of keyword searching and predictive modeling when applied to real-world data. With this study, this group of collaborators wanted to examine and understand the benefits and weaknesses of both approaches to legal teams with identifying privilege material in document populations.Comment: 2018 IEEE International Conference on Big Data (Big Data