Quantification of the Individual Characteristics of the Human Dentition

The considerations for admissibility suggested by the Daubert trilogy challenge forensic experts to provide scientific support for opinion testimony. The defense bar has questioned the reliability of bitemark analysis. Under an award from the U. S. Department of Justice, via the Midwest Forensic Resource Center, a two-year feasibility study was undertaken to quantify six dental characteristics. Using two computer programs, the exemplars of 419 volunteers were digitally scanned, characteristics were measured, and frequency was calculated. The study demonstrates that there were outliers or rare dental characteristics in measurements. An analysis of the intra-observer and inter-observer consistency demonstrated a high degree of agreement. Expansion of the sample size through collaboration with other academic researchers will be necessary to be able to quantify the occurrence of these characteristics in the general population. The automated software application, Tom\u27s Toolbox, developed specifically for this research project, could also provide a template for precisely quantifying other pattern evidence

On the introduction of canny operator in an advanced imaging algorithm for real-time detection of hyperbolas in ground-penetrating radar data

This paper focuses on the use of the Canny edge detector as the first step of an advanced imaging algorithm for automated detection of hyperbolic reflections in ground-penetrating radar (GPR) data. Since the imaging algorithm aims to work in real time; particular attention is paid to its computational efficiency. Various alternative criteria are designed and examined, to fasten the procedure by eliminating unnecessary edge pixels from Canny-processed data, before such data go through the subsequent steps of the detection algorithm. The effectiveness and reliability of the proposed methodology are tested on a wide set of synthetic and experimental radargrams with promising results. The finite-difference time-domain simulator gprMax is used to generate synthetic radargrams for the tests, while the real radargrams come from GPR surveys carried out by the authors in urban areas. The imaging algorithm is implemented in MATLAB

Line Source Scattering by Buried Perfectly Conducting Circular Cylinders

A two-dimensional scattering problem of a line source by a set of perfectly conducting circular cylinders buried in a semi-infinite medium is solved, in both TE and TM polarization. A cylindrical-wave approach is used and applied to both the field emitted by the source and the field scattered by the buried objects. Reflection and transmission of such fields through the planar interface are evaluated making use of the plane-wave spectrum of a cylindrical wave. Numerical results are presented, with checks confirming the validity of the method

Line Source Scattering by Buried Perfectly Conducting Circular Cylinders

A two-dimensional scattering problem of a line source by a set of perfectly conducting circular cylinders buried in a semi-infinite medium is solved, in both TE and TM polarization. A cylindrical-wave approach is used and applied to both the field emitted by the source and the field scattered by the buried objects. Reflection and transmission of such fields through the planar interface are evaluated making use of the plane-wave spectrum of a cylindrical wave. Numerical results are presented, with checks confirming the validity of the method

Accelerated and interpretable oblique random survival forests

The oblique random survival forest (RSF) is an ensemble supervised learning method for right-censored outcomes. Trees in the oblique RSF are grown using linear combinations of predictors to create branches, whereas in the standard RSF, a single predictor is used. Oblique RSF ensembles often have higher prediction accuracy than standard RSF ensembles. However, assessing all possible linear combinations of predictors induces significant computational overhead that limits applications to large-scale data sets. In addition, few methods have been developed for interpretation of oblique RSF ensembles, and they remain more difficult to interpret compared to their axis-based counterparts. We introduce a method to increase computational efficiency of the oblique RSF and a method to estimate importance of individual predictor variables with the oblique RSF. Our strategy to reduce computational overhead makes use of Newton-Raphson scoring, a classical optimization technique that we apply to the Cox partial likelihood function within each non-leaf node of decision trees. We estimate the importance of individual predictors for the oblique RSF by negating each coefficient used for the given predictor in linear combinations, and then computing the reduction in out-of-bag accuracy. In general benchmarking experiments, we find that our implementation of the oblique RSF is approximately 450 times faster with equivalent discrimination and superior Brier score compared to existing software for oblique RSFs. We find in simulation studies that 'negation importance' discriminates between relevant and irrelevant predictors more reliably than permutation importance, Shapley additive explanations, and a previously introduced technique to measure variable importance with oblique RSFs based on analysis of variance. Methods introduced in the current study are available in the aorsf R package.Comment: 40 pages, 6 figure

Are routinely collected NHS administrative records suitable for endpoint identification in clinical trials? Evidence from the West of Scotland coronary prevention study

Background: Routinely collected electronic patient records are already widely used in epidemiological research. In this work we investigated the potential for using them to identify endpoints in clinical trials.<p></p> Methods: The events recorded in the West of Scotland Coronary Prevention Study (WOSCOPS), a large clinical trial of pravastatin in middle-aged hypercholesterolaemic men in the 1990s, were compared with those in the record-linked deaths and hospitalisations records routinely collected in Scotland.<p></p> Results: We matched 99% of fatal study events by date. We showed excellent matching (97%) of the causes of fatal endpoint events and good matching (.80% for first events) of the causes of nonfatal endpoint events with a slightly lower rate of mismatching of record linkage than study events (19% of first study myocardial infarctions (MI) and 4% of first record linkage MIs not matched as MI). We also investigated the matching of non-endpoint events and showed a good level of matching, with .78% of first stroke/TIA events being matched as stroke/TIA. The primary reasons for mismatches were record linkage data recording readmissions for procedures or previous events, differences between the diagnoses in the routinely collected data and the conclusions of the clinical trial expert adjudication committee, events occurring outside Scotland and therefore being missed by record linkage data, miscoding of cardiac events in hospitalisations data as ‘unspecified chest pain’, some general miscoding in the record linkage data and some record linkage errors.<p></p> Conclusions: We conclude that routinely collected data could be used for recording cardiovascular endpoints in clinical trials and would give very similar results to rigorously collected clinical trial data, in countries with unified health systems such as Scotland. The endpoint types would need to be carefully thought through and an expert endpoint adjudication committee should be involved.<p></p&gt

In vitro biocompatibility of a new hydrogel with Crocin, powerful antioxidant found in Crocus Sativus L. flowers

Recently, attention has been paid to the identification of natural antioxidants from the petals of Crocus S. flowers that are normally considered waste[1]. The antioxidant activities are mainly attributed to carotenoid compounds, like crocin. Scientific evidences demonstrate that this kind of compounds are among the most important natural plant sources of antioxidant activity in the human diet, protecting the body against damages caused by reactive oxygen species (ROS). This antioxidant was extracted using methanol and ethanol. In this experiment, it was used a new hydrogel consisting of three polymers - Polyvinyl pyrrolidone (PVP), Agar and Polyethylene glycol (PEG) – and Crocin, mixed, reticulated and then sterilized by gamma irradiation at 25 kGy. For the in vitro experimental protocol, it was used a primary culture of fibroblasts taken from the subcutaneous tissue of a newborn mice, seeding the cells on a little square (1cm2 area) of both kinds of hydrogel. As the ISO protocol prescribes, the experiments were repeated 3 times for each kind of hydrogel, stopping the culture at the 3rd, 7th and 14th day after the seeding. For all steps, 3 Petri dishes were used as controls without biomaterials. At fixed deadline, all Petri dishes were stained, using the Wright method for cell counting and morphological evaluations. The microscopic analysis revealed the complete biocompatibility of the hydrogel. The Petri dishes with this kind of new hydrogel has an overproduction of collagen from the fibroblasts. The presence of this natural important compound in saffron petals, now offers new possibilities for the best use of the hole flower. This study is still in progress.http://www.fupress.net/index.php/ijae/article/view/1495

Apolipoprotein L1 gene variants associate with prevalent kidney but not prevalent cardiovascular disease in the Systolic Blood Pressure Intervention Trial.

Apolipoprotein L1 gene (APOL1) G1 and G2 coding variants are strongly associated with chronic kidney disease (CKD) in African Americans (AAs). Here APOL1 association was tested with baseline estimated glomerular filtration rate (eGFR), urine albumin:creatinine ratio (UACR), and prevalent cardiovascular disease (CVD) in 2571 AAs from the Systolic Blood Pressure Intervention Trial (SPRINT), a trial assessing effects of systolic blood pressure reduction on renal and CVD outcomes. Logistic regression models that adjusted for potentially important confounders tested for association between APOL1 risk variants and baseline clinical CVD (myocardial infarction, coronary, or carotid artery revascularization) and CKD (eGFR under 60 ml/min per 1.73 m(2) and/or UACR over 30 mg/g). AA SPRINT participants were 45.3% female with a mean (median) age of 64.3 (63) years, mean arterial pressure 100.7 (100) mm Hg, eGFR 76.3 (77.1) ml/min per 1.73 m(2), and UACR 49.9 (9.2) mg/g, and 8.2% had clinical CVD. APOL1 (recessive inheritance) was positively associated with CKD (odds ratio 1.37, 95% confidence interval 1.08-1.73) and log UACR estimated slope (β) 0.33) and negatively associated with eGFR (β -3.58), all significant. APOL1 risk variants were not significantly associated with prevalent CVD (1.02, 0.82-1.27). Thus, SPRINT data show that APOL1 risk variants are associated with mild CKD but not with prevalent CVD in AAs with a UACR under 1000 mg/g

ObStruct: A method to objectively analyse factors driving population structure using Bayesian ancestry profiles

Bayesian inference methods are extensively used to detect the presence of population structure given genetic data. The primary output of software implementing these methods are ancestry profiles of sampled individuals. While these profiles robustly partition the data into subgroups, currently there is no objective method to determine whether the fixed factor of interest (e.g. geographic origin) correlates with inferred subgroups or not, and if so, which populations are driving this correlation. We present ObStruct, a novel tool to objectively analyse the nature of structure revealed in Bayesian ancestry profiles using established statistical methods. ObStruct evaluates the extent of structural similarity between sampled and inferred populations, tests the significance of population differentiation, provides information on the contribution of sampled and inferred populations to the observed structure and crucially determines whether the predetermined factor of interest correlates with inferred population structure. Analyses of simulated and experimental data highlight ObStruct's ability to objectively assess the nature of structure in populations. We show the method is capable of capturing an increase in the level of structure with increasing time since divergence between simulated populations. Further, we applied the method to a highly structured dataset of 1,484 humans from seven continents and a less structured dataset of 179 Saccharomyces cerevisiae from three regions in New Zealand. Our results show that ObStruct provides an objective metric to classify the degree, drivers and significance of inferred structure, as well as providing novel insights into the relationships between sampled populations, and adds a final step to the pipeline for population structure analyses. © 2014 Gayevskiy et al