Accurate prediction of saw blade thicknesses from false start measurements

Background: False start analysis is the examination of incomplete saw marks created on bone in an effort to establish information on the saw that created them. The present study aims to use quantitative data from micro-CT cross-sections to predict the thickness of the saw blade used to create the mark. Random forest statistical models are utilised for prediction to present a methodology that is useful to both forensic researchers and practitioners. Method: 340 false starts were created on 32 fleshed cadaveric leg bones by 38 saws of various classes. False starts were micro-CT scanned and seven measurements taken digitally. A regression random forest model was produced from the measurement data of all saws to predict the saw blade thickness from false starts with an unknown class. A further model was created, consisting of three random forests, to predict the saw blade thickness when the class of the saw is known. The predictive capability of the models was tested using a second sample of data, consisting of measurements taken from a further 17 false starts created randomly selected saws from the 38 in the experiment. Results: Random forest models were able to accurately predict up to 100% of saw blade thicknesses for both samples of false starts. Conclusion: This study demonstrates the applicability of random forest statistical regression models for reliable prediction of saw blade thicknesses from false start data. The methodology proposed enables prediction of saw blade thickness from empirical data and offers a significant step towards reduced subjectivity and database formation in false start analysis. Application of this methodology to false start analysis, with a more complete database, will allow complementary results to current analysis techniques to provide more information on the saw used in dismemberment casework

Quantitative characterisation of ballistic cartridge cases from micro-CT

Evaluation of cartridge cases is essential within forensic ballistic analysis and is used in an attempt to establish a connection to the weapon used to fire it. This study consists of two experiments. The aims of Experiment 1 were to establish whether micro-CT is appropriate and repeatable for ballistic cartridge case analysis and if measurements can be extracted repeatably and reliably. Experiment 2 aimed to compare cartridge cases from two weapons to establish the magnitude of variation within and between weapons. A total of 48 cartridge cases fired by two distinct weapons were collected and micro-CT scanned to a high resolution. One randomly selected cartridge was scanned ten times under the same conditions to ensure repeatability of the scanning conditions in Experiment 1. Three novel measurements to quantitatively assess the firing pin impressions were proposed in Experiment 1 and comparatively analysed from two weapons in Experiment 2. Experiment 1 showed that micro-CT is an effective and highly repeatable and reliable method for 3-dimensional imaging and measurement of ballistic cartridge cases. Furthermore, high agreement for inter-rater reliability was found between five raters. Quantitative micro-CT analysis of the firing pin impression measurements in Experiment 2 showed a significant difference between the two studied weapons using Welch’s t-test (p < 0.01). This study shows the advantage and reliability of utilising micro-CT for firing pin impression analysis. Quantitation of the firing pin impression allows distinction between the weapons studied. With expansion to further weapons, application of this methodology could complement current analysis techniques through classification models

Science lives: School choices and ‘natural tendencies’

An analysis of 12 semi-structured interviews with university-based scientists and non-scientists illustrates their life journeys towards, or away from, science and the strengths and impact of life occurrences leading them to choose science or non-science professions. We have adopted narrative approaches and used Mezirow's transformative learning theory framework. The areas of discussion from the result have stressed on three main categories that include ‘smooth transition’, ‘incremental wavering transition' and ‘transformative transition’. The article concludes by discussing the key influences that shaped initial attitudes and direction in these people through natural inclination, environmental inspirations and perceptions of science

Finding the niche: A review of market assessment methodologies for rural electrification with small scale wind power

The mass roll out of solar PV across the Global South has enabled electricity access for millions of people. In the right context, Small Wind Turbines (SWTs) can be complementary, offering the potential to generate at times of low solar resource (night, monsoon season, winter, etc.) and increasing the proportion of the total energy system that can be manufactured locally. However, many contextual factors critically affect the viability of the technology, such as the extreme variability in the wind resource itself and the local availability of technical support. Therefore, performing a detailed market analysis in each new context is much more important. The Wind Empowerment Market Assessment Methodology (WEMAM) is a multi-scalar, transdisciplinary methodology for identifying the niche contexts where small wind can make a valuable contribution to rural electrification. This paper aims to inform the development of WEMAM with a critical review of existing market assessment methodologies. By breaking down WEMAM into its component parts, reflecting upon its practical applications to date and drawing upon insights from the literature, opportunities where it could continue to evolve are highlighted. Key opportunities include shifting the focus towards development outcomes; creating community archetypes; localised studies in high potential regions; scenario modelling and MCDA ranking of proposed interventions; participatory market mapping; and applying socio-technical transitions theory to understand how the small wind niche can break through into the mainstream

Contribution of Germline Mutations in the RAD51B, RAD51C, and RAD51D Genes to Ovarian Cancer in the Population

PURPOSE: The aim of this study was to estimate the contribution of deleterious mutations in the RAD51B, RAD51C, and RAD51D genes to invasive epithelial ovarian cancer (EOC) in the population and in a screening trial of individuals at high risk of ovarian cancer. PATIENTS AND METHODS: The coding sequence and splice site boundaries of the three RAD51 genes were sequenced and analyzed in germline DNA from a case-control study of 3,429 patients with invasive EOC and 2,772 controls as well as in 2,000 unaffected women who were BRCA1/BRCA2 negative from the United Kingdom Familial Ovarian Cancer Screening Study (UK_FOCSS) after quality-control analysis. RESULTS: In the case-control study, we identified predicted deleterious mutations in 28 EOC cases (0.82%) compared with three controls (0.11%; P < .001). Mutations in EOC cases were more frequent in RAD51C (14 occurrences, 0.41%) and RAD51D (12 occurrences, 0.35%) than in RAD51B (two occurrences, 0.06%). RAD51C mutations were associated with an odds ratio of 5.2 (95% CI, 1.1 to 24; P = .035), and RAD51D mutations conferred an odds ratio of 12 (95% CI, 1.5 to 90; P = .019). We identified 13 RAD51 mutations (0.65%) in unaffected UK_FOCSS participants (RAD51C, n = 7; RAD51D, n = 5; and RAD51B, n = 1), which was a significantly greater rate than in controls (P < .001); furthermore, RAD51 mutation carriers were more likely than noncarriers to have a family history of ovarian cancer (P < .001). CONCLUSION: These results confirm that RAD51C and RAD51D are moderate ovarian cancer susceptibility genes and suggest that they confer levels of risk of EOC that may warrant their use alongside BRCA1 and BRCA2 in routine clinical genetic testing

Higher C-reactive Protein Levels Predict Postoperative Delirium in Older Patients Undergoing Major Elective Surgery: A Longitudinal Nested Case-Control Study

Background—Delirium is a common, morbid, and costly postoperative complication.. We aimed to identify blood-based postoperative delirium markers in a nested case control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation. Methods and Materials—The Successful Aging after Elective Surgery Study enrolled dementia-free adults age ≥70 undergoing major scheduled non-cardiac surgery (N=566; 24% delirium). Plasma was collected at 4 timepoints: preoperatively (PREOP), post-anesthesia care unit (PACU), postoperative day 2 (POD2) and 1 month follow-up (PO1MO). Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). iTRAQ-based relative quantitation mass spectrometry proteomics was performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using non-parametric signed-rank tests were performed in all cohorts examining the association between the identified protein and delirium. Results—C-reactive protein (CRP) emerged from the proteomics analysis as the strongest delirium-related protein. ELISA validation confirmed that compared to controls, cases had significantly higher CRP levels (*p\u3c.05, **p\u3c.01) in the discovery, replication, and pooled cohorts at PREOP (median paired difference [mg/L] 1.97*, 0.29, 1.56**, respectively), PACU (2.83, 2.22*, 2.53**, respectively) and POD2 (71.97**, 35.18*, 63.76**, respectively), but not PO1MO (2.72, −0.66, 1.10, respectively). Discussion—Elevated pre- and postoperative plasma levels of CRP were associated with delirium, suggesting that a pre-inflammatory state and heightened inflammatory response to surgery are potential pathophysiological mechanisms of delirium