New Technology and Researchers’ Access to Court and Tribunal Information: the need for European analysis

We discuss the limitations and rights which may affect the researcher’s access to and use of digital, court and administrative tribunal based information. We suggest that there is a need for a European-wide investigation of the legal framework which affects the researcher who might wish to utilise this form of information. A European-wide context is required because much of the relevant law is European rather than national, but much of the constraints are cultural. It is our thesis that research improves understanding and then improves practice as that understanding becomes part of public debate. If it is difficult to undertake research, then public debate about the court system – its effectiveness, its biases, its strengths – becomes constrained. Access to court records is currently determined on a discretionary basis or on the basis of interpretation of rules of the court where these are challenged in legal proceedings. Anecdotal evidence would suggest that there are significant variations in the extent to which court documents such as pleadings, transcripts, affidavits etc are made generally accessible under court rules or as a result of litigation in different jurisdictions or, indeed, in different courts in the same jurisdiction. Such a lack of clarity can only encourage a chilling of what might otherwise be valuable research. Courts are not, of course, democratic bodies. However, they are part of a democratic system and should, we suggest – both for the public benefit and for their proper operation – be accessible and criticisable by the independent researcher. The extent to which the independent researcher is enabled access is the subject of this article. The rights of access for researchers and the public have been examined in other common law countries but not, to date, in the UK or Europe.

The Colorectal cancer disease-specific transcriptome may facilitate the discovery of more biologically and clinically relevant information

BACKGROUND: To date, there are no clinically reliable predictive markers of response to the current treatment regimens for advanced colorectal cancer. The aim of the current study was to compare and assess the power of transcriptional profiling using a generic microarray and a disease-specific transcriptome-based microarray. We also examined the biological and clinical relevance of the disease-specific transcriptome.

METHODS: DNA microarray profiling was carried out on isogenic sensitive and 5-FU-resistant HCT116 colorectal cancer cell lines using the Affymetrix HG-U133 Plus2.0 array and the Almac Diagnostics Colorectal cancer disease specific Research tool. In addition, DNA microarray profiling was also carried out on pre-treatment metastatic colorectal cancer biopsies using the colorectal cancer disease specific Research tool. The two microarray platforms were compared based on detection of probesets and biological information.

RESULTS: The results demonstrated that the disease-specific transcriptome-based microarray was able to out-perform the generic genomic-based microarray on a number of levels including detection of transcripts and pathway analysis. In addition, the disease-specific microarray contains a high percentage of antisense transcripts and further analysis demonstrated that a number of these exist in sense:antisense pairs. Comparison between cell line models and metastatic CRC patient biopsies further demonstrated that a number of the identified sense:antisense pairs were also detected in CRC patient biopsies, suggesting potential clinical relevance.

CONCLUSIONS: Analysis from our in vitro and clinical experiments has demonstrated that many transcripts exist in sense:antisense pairs including IGF2BP2, which may have a direct regulatory function in the context of colorectal cancer. While the functional relevance of the antisense transcripts has been established by many studies, their functional role is currently unclear; however, the numbers that have been detected by the disease-specific microarray would suggest that they may be important regulatory transcripts. This study has demonstrated the power of a disease-specific transcriptome-based approach and highlighted the potential novel biologically and clinically relevant information that is gained when using such a methodology.

Impact of operator experience on information feedback and reusability

Keeping a record of operator experience remains a challenge to operation management and a major source of inefficiency in information management. The objective is to develop a framework that enables an explicit presentation of experience based on information use. A purposive sampling method is used to select four small and medium-sized enterprises as case studies. The unit of analysis is the production process in the machine shop. Data collection is by structured interview, observation and documentation. A comparative case analysis is applied. The findings suggest experience is an accumulation of tacit information feedback, which can be made explicit in information use interoperatability matrix. The matrix is conditioned upon information use typology, which is strategic in waste reduction. The limitations include difficulty of participant anonymity where the organisation nominates a participant. Areas for further research include application of the concepts to knowledge management and shop floor resource management.

Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.