The Effect of Varying the Composition of Fingerprint Sweat Deposits on the Corrosion of Brass and Fingerprint Visibility

Corrosion of α‐phase brass by sebaceous sweat fingerprint deposits produced identifiable impressions in a majority of samples (n = 40) 4 days after deposition. Combining sebaceous with eccrine sweat yielded a greater percentage of identifiable fingerprint deposits, although this increase was not statistically significant. Production of identifiable fingerprints from eccrine sweat deposits was dependent on the sampling time of year with deposits taken during summer months giving similar percentages of identifiable fingerprints to sebaceous deposits. A statistically significant positive correlation was found between elapsed days after deposition and identifiable eccrine (ρ = 0.787, p < 0.05), sebaceous (ρ = 0.724, p < 0.05), and eccrine/sebaceous mixture (ρ = 0.908, p < 0.01) fingerprints deposited during summer months. The summer increase in the percentage of identifiable eccrine sweat deposits was statistically significant compared to winter eccrine deposits (p < 0.0001). Observations were consistent with results obtained from artificial sebaceous and eccrine sweat.     

Photo‐ and Thermal‐Degradation Studies of Select Eccrine Fingerprint Constituents

Abstract: Photo‐ and thermal‐degradation studies on eccrine fingerprint components are presented herein. Dilute distinct solutions of urea, lactic acid, and seven amino acids were deposited on steel coupons and Teflon^® disks, exposed to artificial sunlight or heat, extracted, and analyzed. This aim of this study was to determine whether the investigated eccrine components, previously determined to be Raman active for a parallel study, experienced photo‐ or thermally induced degradation, and if so, to determine the rate and identify any detectable products. Neither the amino acids nor urea exhibited photo‐degradation; however, when heated for a period of three minutes, the onset of thermal‐degradation was initiated at 100°C for the amino acids and 100°C for urea. Lactic acid, the major polymerization initiator of superglue fuming, showed photochemical and thermal‐degradation. These results could be used for future development of new latent fingerprint visualization methods, especially when lactic acid is degraded.     

STR Profiles from DNA Samples with "Undetected" or Low Quantifiler™ Results

Abstract:  Screening methods capable of identifying DNA samples that will not yield short tandem repeat (STR) profiles are desired. In the past, quantitation methods have not been sensitive enough for this purpose. In this study, low level DNA samples were used to assess whether Quantifiler™ has a minimum quantitation value below which STR profiles would consistently fail to be detected. Buccal swabs were obtained and the DNA extracted, quantified, and serially diluted to concentrations ranging from 0.002 to 0.250 ng/μL. Samples were analyzed once with Quantifiler™, followed by Profiler Plus™ amplification and capillary electrophoresis analysis. An absolute minimum value below which STR results were unobtainable could not be defined. From the 96 low level samples tested, STR loci (including one full profile) were successfully amplified and detected from 27% of the samples "undetected" by Quantifiler™. However, no STR alleles were detected in 73% of these "undetected" samples, indicating that Quantifiler™ data may be useful for predicting STR typing success.     

A Comparison of Thresholding Methods for Forensic Reconstruction Studies Using Fluorescent Powder Proxies for Trace Materials

Image segmentation is a fundamental precursor to quantitative image analysis. At present, no standardised methodology exists for segmenting images of fluorescent proxies for trace evidence. Experiments evaluated (i) whether manual segmentation is reproducible within and between examiners (with three participants repeatedly tracing three images) (ii) whether manually defining a threshold level offers accurate and reproducible results (with 20 examiners segmenting 10 images), and (iii) whether a global thresholding algorithm might perform with similar accuracy, while offering improved reproducibility and efficiency (16 algorithms tested). Statistically significant differences were seen between examiners’ traced outputs. Manually thresholding produced good accuracy on average (within ±1% of the expected values), but poor reproducibility (with multiple outliers). Three algorithms (Yen, MaxEntropy, and RenyiEntropy) offered similar accuracy, with improved reproducibility and efficiency. Together, these findings suggest that appropriate algorithms could perform thresholding tasks as part of a robust workflow for reconstruction studies employing fluorescent proxies for trace evidence.     

Self-injury group psychotherapy intervention for young offenders: a pilot study

Objective: Self-injury (SI) is a significant and growing problem with the prison estate and a particularly acute issue with young offenders. Despite this, there are no evidence-based interventions for Young Offenders with SI difficulties. The Self-Injury Group Psychotherapy Intervention (SIGPI) was developed to target this.

Method: Drawing on existing evidence, the group was developed and piloted on a sample of 12 male Young Offenders (mean age 19.85 years) in custody with a history of SI. Participants were measured on observable SI behaviour, SI thoughts and urges and psychological distress. A within subject design was utilised with measures at baseline, 6 months and 1 year.

Results: At 12 months follow-up, a significant reduction in SI acts, time spent on SI monitoring, severity of urges and difficulty resisting SI. Psychological distress was also reduced.

Conclusions: SIGPI could be a potentially promising intervention and further investigation into its efficacy is warranted.     

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.