Forensic examination of multilayer white paint by lateral scanning Raman spectroscopy

Multilayer samples of white architectural paint potentially have very high evidential value in forensic casework, because the probability that two unrelated samples will have the same sequence of layers is extremely low. However, discrimination between the different layers using optical microscopy is often difficult or impossible. Here, lateral scanning Raman spectroscopy has been used to chemically map the cross-sections of multilayer white paint chips. It was found that the spectra did allow the different layers to be delineated on the basis of their spectral features. The boundaries between different layers were not as sharp as expected, with transitions occurring over length scales of > 20 µm, even with laser spot diameters <4 µm. However, the blurring of the boundaries was not so large as to prevent recording and identification of spectra from each of the layers in the samples. This method clearly provides excellent discrimination between different multilayer white paint samples and can readily be incorporated into existing procedures for examination of paint transfer evidence.

The use of geoscience methods for terrestrial forensic searches

Geoscience methods are increasingly being utilised in criminal, environmental and humanitarian forensic investigations, and the use of such methods is supported by a growing body of experimental and theoretical research. Geoscience search techniques can complement traditional methodologies in the search for buried objects, including clandestine graves, weapons, explosives, drugs, illegal weapons, hazardous waste and vehicles. This paper details recent advances in search and detection methods, with case studies and reviews. Relevant examples are given, together with a generalised workflow for search and suggested detection technique(s) table. Forensic geoscience techniques are continuing to rapidly evolve to assist search investigators to detect hitherto difficult to locate forensic targets.

Gaze fixation improves the stability of expert juggling

Novice and expert jugglers employ different visuomotor strategies: whereas novices look at the balls around their zeniths, experts tend to fixate their gaze at a central location within the pattern (so-called gaze-through). A gaze-through strategy may reflect visuomotor parsimony, i.e., the use of simpler visuomotor (oculomotor and/or attentional) strategies as afforded by superior tossing accuracy and error corrections. In addition, the more stable gaze during a gaze-through strategy may result in more accurate movement planning by providing a stable base for gaze-centered neural coding of ball motion and movement plans or for shifts in attention. To determine whether a stable gaze might indeed have such beneficial effects on juggling, we examined juggling variability during 3-ball cascade juggling with and without constrained gaze fixation (at various depths) in expert performers (n = 5). Novice jugglers were included (n = 5) for comparison, even though our predictions pertained specifically to expert juggling. We indeed observed that experts, but not novices, juggled significantly less variable when fixating, compared to unconstrained viewing. Thus, while visuomotor parsimony might still contribute to the emergence of a gaze-through strategy, this study highlights an additional role for improved movement planning. This role may be engendered by gaze-centered coding and/or attentional control mechanisms in the brain.

EXPERT-SYSTEM SUPPORT USING BAYESIAN BELIEF NETWORKS IN THE DIAGNOSIS OF FINE-NEEDLE ASPIRATION BIOPSY SPECIMENS OF THE BREAST

Aim-To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast.

Methods-Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node.

Results-The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. A typical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases.

Conclusion-The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

Molecular and clinicopathological markers of prognosis in breast cancer

A vast body of research in breast cancer prognostication has accumulated. Yet despite this, patients within current prognostic categories may have significantly different outcomes. There is a need to more accurately divide those cancer types associated with an excellent prognosis from those requiring more aggressive therapy. Gene expression array studies have revealed the numerous molecular breast cancer subtypes that are associated with differing outcomes. Furthermore, as next generation technologies evolve and further reveal the complexities of breast cancer, it is likely that existing prognostic approaches will become progressively refined. Future prognostication in breast cancer requires a morphomolecular, multifaceted approach involving the assessment of anatomical disease extent and levels of protein, DNA and RNA expression. One of the major challenges in prognostication will be the integration of potential assays into existing clinical systems and identification of appropriate patient subgroups for analysis.

Forensic analysis of architectural finishes using fourier transform infrared and raman spectroscopy, part II:White paint

White household paints are commonly encountered as evidence in the forensic laboratory but they often cannot be readily distinguished by color alone so Fourier transform infrared (FT-IR) microscopy is used since it can sometimes discriminate between paints prepared with different organic resins. Here we report the first comparative study of FT-IR and Raman spectroscopy for forensic analysis of white paint. Both techniques allowed the 51 white paint samples in the study to be classified by inspection as either belonging to distinct groups or as unique samples. FT-IR gave five groups and four unique samples; Raman gave seven groups and six unique samples. The basis for this discrimination was the type of resin and/ or inorganic pigments/extenders present. Although this allowed approximately half of the white paints to be distinguished by inspection, the other half were all based on a similar resin and did not contain the distinctive modifiers/pigments and extenders that allowed the other samples to be identified. The experimental uncertainty in the relative band intensities measured using FT-IR was similar to the variation within this large group, so no further discrimination was possible. However, the variation in the Raman spectra was larger than the uncertainty, which allowed the large group to be divided into three subgroups and four distinct spectra, based on relative band intensities. The combination of increased discrimination and higher sample throughput means that the Raman method is superior to FT-IR for samples of this type. © 2005 Society for Applied Spectroscopy.