Copyright, Licences, and Statutory Fraud

In this article we explore the interplay between the law of copyright, contract, and statutory fraud within the digital environment, and in particular with respect to the business of commercial image licensing within the UK.

Kinetics and mechanism of a fast leuco-Methylene Blue oxidation by copper(II)-halide species in acidic aqueous media

The kinetics of a fast leuco-Methylene Blue (LMB) re-oxidation to Methylene Blue (MB) by copper(II)-halide (Cl-, Br-) complexes in acidic aqueous media has been studied spectrophotometrically using a stopped-flow technique. The reaction follows a simple first order rate expression under an excess of the copper(II) species (and H+(aq)), and the pseudo-first order rate constant (k'(obs)) is largely independent of the atmosphere used (air, oxygen, argon). The rate law, at constant Cl- (Br-) anion concentration, is given by the expression: (d[MB+])/dt = ((k(a)K[H+] + k(b))/(1 + K[H+])).[Cu-II][LMB] = k'(obs)[LMB], where K is the protonation constant, and k(a) and k(b) are the pseudo-second order rate constants for protonated and deprotonated forms of LMB, respectively The rate law was determined based on the observed k'(obs) vs. [Cu-II] and [H+] dependences. The rate dramatically increases with [Cl-] over the range: 0.1-1.5 M, reflecting the following reactivity order: Cu2+(aq)

Symptom Free: Will the Law Strike a Knockout Blow on Concussion in Rugby

As the Six Nations rugby tournament approaches its half way stage, the usual media chatter on who might win go on to win the championship has been substituted by concern over a number of high profile, concussion-related injuries.

Improved lexicon-based sentiment analysis for social media analytics

Social media channels, such as Facebook or Twitter, allow for people to express their views and opinions about any public topics. Public sentiment related to future events, such as demonstrations or parades, indicate public attitude and therefore may be applied while trying to estimate the level of disruption and disorder during such events. Consequently, sentiment analysis of social media content may be of interest for different organisations, especially in security and law enforcement sectors. This paper presents a new lexicon-based sentiment analysis algorithm that has been designed with the main focus on real time Twitter content analysis. The algorithm consists of two key components, namely sentiment normalisation and evidence-based combination function, which have been used in order to estimate the intensity of the sentiment rather than positive/negative label and to support the mixed sentiment classification process. Finally, we illustrate a case study examining the relation between negative sentiment of twitter posts related to English Defence League and the level of disorder during the organisation’s related events.