Raman Microspectroscopic Mapping: A Tool for Identification of Fused Materials in Fire Debris

Examination of fire debris can provide information about the types of materials which were present at the time of the fire to give insights for fire scene reconstruction and understanding compartment fire dynamics. This paper demonstrates the ability of Raman spectroscopy for material identification postfire in complex situations, such as the production of fused masses during fire dropdown. A validated Raman spectral library is combined with Raman mapping in three fire case studies, to determine the individual materials in the fused masses formed. The case studies accessed material combinations of several common polymers. Raman mapping was carried out on a 10 μm × 10 μm square of the masses. Material identification using this technique ranged from a high of 85% match to a low of 40% match. This work demonstrated that complex masses found in the fire debris can be resolved into the individual material components for identification and spatial distribution.     

Brexit and Parliamentary Sovereignty

This note addresses the implications of R (Miller) v Secretary of State for Exiting the European Union for the legal principle of parliamentary sovereignty, and argues that the strong restatement of the latter is the most significant feature of the decision. The aim here is to show how traditional principle in the Dicey tradition has been strongly applied against the competing claims of EU law, the royal prerogative, the referendum and devolution. However, the note also argues that the claims relating to parliamentary sovereignty could have produced a different result and that the most compelling feature of the case was the argument that was not forcefully put by the Government, namely that Parliament had already provided sufficient authority for the triggering of Article 50.     

Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap

Keith T. Poole Center for Advanced Study in the Behavioral Sciences and Department of Political Science, University of Houston, Houston, TX 77204-3011 e-mail: kpoole{at}uh.edu Over the last 15 years a large amount of scholarship in legislativepolitics has used NOMINATE or other similar methods to constructmeasures of legislators' ideological locations. These measuresare then used in subsequent analyses. Recent work in politicalmethodology has focused on the pitfalls of using such estimatesas variables in subsequent analysis without explicitly accountingfor their uncertainty and possible bias ( Herron and Shotts2003, Political Analysis 11:44–64). This presents a problemfor those employing NOMINATE scores because estimates of theirunconditional sampling uncertainty or bias have until now beenunavailable. In this paper, we present a method of forming unconditionalstandard error estimates and bias estimates for NOMINATE scoresusing the parametric bootstrap. Standard errors are estimatedfor the 90th U.S. Senate in two dimensions. Standard errorsof first–dimension placements are in the 0.03 to 0.08range. The results are compared with those obtained using theMarkov chain Monte Carlo estimator of Clinton et al. (2002,Stanford University Working Paper). We also show how the bootstrapcan be used to construct standard errors and confidence intervalsfor auxiliary quantities of interest such as ranks and the locationof the median senator.