Lawyers on Trial: Juror Hostility to Defendants in Legal Malpractice Trials

In contrast to medical malpractice, legal malpractice is a phenomenon that has attracted little attention from empirically-oriented scholars. This paper is part of a larger study of legal malpractice claiming and litigation. Given the evidence on the frequency of legal malpractice claims, there are surprisingly few legal malpractice cases that result in jury verdicts. There are many possible explanations for this, one of which reflects the perception that lawyers are held in such low esteem by potential jurors that they risk harsh treatment by jurors when they are defendants in legal malpractice trials. Because we could find no empirical evidence that that either supported or rejected the reality of this perception, we designed a simple jury simulation experiment to test this as an hypothesis. Using three different case scenarios, each in two forms (one set within a legal malpractice framework and one outside legal malpractice), we found support for the hypothesis in only one of the three scenarios and even there the effects were at best modest. These results held up controlling for other possible factors that might influence juror responses to the case scenarios

Viscous instability of a compressible round jet

The compressible linear stability equations are derived from the Navier Stokes equations in cylindrical polar coordinates. Numerical solutions for locally parallel flow are found using a direct matrix method. Discretization with compact finite difference is found to have better convergence properties than a Chebyshev spectral method for a round jet test case. The method is validated against previous results and convergence is tested for a range of jet profiles. Finally and en method is used to determine the dominant frequency of a Mach 0.9 jet

Calculating and understanding the value of any type of match evidence when there are potential testing errors

It is well known that Bayes’ theorem (with likelihood ratios) can be used to calculate the impact of evidence, such as a ‘match’ of some feature of a person. Typically the feature of interest is the DNA profile, but the method applies in principle to any feature of a person or object, including not just DNA, fingerprints, or footprints, but also more basic features such as skin colour, height, hair colour or even name. Notwithstanding concerns about the extensiveness of databases of such features, a serious challenge to the use of Bayes in such legal contexts is that its standard formulaic representations are not readily understandable to non-statisticians. Attempts to get round this problem usually involve representations based around some variation of an event tree. While this approach works well in explaining the most trivial instance of Bayes’ theorem (involving a single hypothesis and a single piece of evidence) it does not scale up to realistic situations. In particular, even with a single piece of match evidence, if we wish to incorporate the possibility that there are potential errors (both false positives and false negatives) introduced at any stage in the investigative process, matters become very complex. As a result we have observed expert witnesses (in different areas of speciality) routinely ignore the possibility of errors when presenting their evidence. To counter this, we produce what we believe is the first full probabilistic solution of the simple case of generic match evidence incorporating both classes of testing errors. Unfortunately, the resultant event tree solution is too complex for intuitive comprehension. And, crucially, the event tree also fails to represent the causal information that underpins the argument. In contrast, we also present a simple-to-construct graphical Bayesian Network (BN) solution that automatically performs the calculations and may also be intuitively simpler to understand. Although there have been multiple previous applications of BNs for analysing forensic evidence—including very detailed models for the DNA matching problem, these models have not widely penetrated the expert witness community. Nor have they addressed the basic generic match problem incorporating the two types of testing error. Hence we believe our basic BN solution provides an important mechanism for convincing experts—and eventually the legal community—that it is possible to rigorously analyse and communicate the full impact of match evidence on a case, in the presence of possible error

Nongaussianity from Tachyonic Preheating in Hybrid Inflation

In a previous work we showed that large nongaussianities and nonscale-invariant distortions in the CMB power spectrum can be generated in hybrid inflation models, due to the contributions of the tachyon (waterfall) field to the second order curvature perturbation. Here we clarify, correct, and extend those results. We show that large nongaussianity occurs only when the tachyon remains light throughout inflation, whereas n=4 contamination to the spectrum is the dominant effect when the tachyon is heavy. We find constraints on the parameters of warped-throat brane-antibrane inflation from nongaussianity. For F-term and D-term inflation models from supergravity, we obtain nontrivial constraints from the spectral distortion effect. We also establish that our analysis applies to complex tachyon fields.Comment: 16 pages, 2 figures. Comments added to introductio

The use of field-programmable gate arrays for the hardware acceleration of design automation tasks

This paper investigates the possibility of using Field-Programmable Gate Arrays (Fr’GAS) as reconfigurable co-processors for workstations to produce moderate speedups for most tasks in the design process, resulting in a worthwhile overall design process speedup at low cost and allowing algorithm upgrades with no hardware modification. The use of FPGAS as hardware accelerators is reviewed and then achievable speedups are predicted for logic simulation and VLSI design rule checking tasks for various FPGA co-processor arrangements

Flexible Integration of Alternative Energy Sources for Autonomous Sensing

Recent developments in energy harvesting and autonomous sensing mean that it is now possible to power sensors solely from energy harvested from the environment. Clearly this is dependent on sufficient environmental energy being present. The range of feasible environments for operation can be extended by combining multiple energy sources on a sensor node. The effective monitoring of their energy resources is also important to deliver sustained and effective operation. This paper outlines the issues concerned with combining and managing multiple energy sources on sensor nodes. This problem is approached from both a hardware and embedded software viewpoint. A complete system is described in which energy is harvested from both light and vibration, stored in a common energy store, and interrogated and managed by the node