911 resultados para Forensic specialists
Resumo:
ABSTRACT A list of the Coleoptera of importance from Brazil, based on published records was compiled. The checklist contains 345 species of 16 families allocated to 16 states of the country. In addition, three species of two families are registered for the first time. The fauna of Coleoptera of forensic importance is still not entirely known and future collection efforts and taxonomic reviews could increase the number of known species considerably in the near future.
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Molecular species identification in mixed or contaminated biological material has always been problematic. We developed a simple and accurate method for mammal DNA identification in mixtures, based on interspecific mitochondrial DNA control region length polymorphism. Contrary to other published methods dealing with species mixtures, our protocol requires a single universal primer pair and amplification step, and is not based on a pre-defined panel of species. This protocol has been routinely employed by our laboratory for species identification in dozens of human and animal forensic caseworks. Six representative forensic caseworks involving the specific identification of mixed animal samples are reported in this paper, in order to demonstrate the applicability and usefulness of the method.
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Asked to comment on a collective discussion paper by Jennifer L. Mnookin et al., this Commentary identifies difficulties the authors encountered in defining or agreeing on the subject matter "forensic science" and its perceived deficiencies. They conclude that there is a need for a research culture, whereas this Commentary calls for the development of a forensic science culture through the development of forensic science education fed by research dedicated to forensic science issues. It is a call for a change of emphasis and, perhaps, of paradigm.
Resumo:
OBJECTIVES: To evaluate whether adult specialists comply with the basic principles for a successful transition of adolescents with chronic disorders, and to determine whether the characteristics of the adult specialists have an influence on applying these principles. METHODS: Out of 299 adult specialists in four French-speaking Swiss cantons, 209 (70%) answered a paper-and-pencil mailed questionnaire between May and July 2007. Only those having received the transfer of at least one adolescent in the previous 2 years (N=102) were included in the analysis. We analyzed four dependent variables: discussing common concerns of adolescent patients, seeing the patient alone, having a transition protocol, and having a previous contact with the pediatric specialist. A logistic regression was performed for each dependent variable controlling for the physicians' characteristics (number of transfers, age, gender, workplace, and perceived experience). RESULTS: Fifty-four percent of the physicians did not spend time alone with their patients, and sensitive issues such as sexuality or substance use were not widely discussed with their young patients. Most respondents (59%) did not have an established protocol, and 54% did not have any contact with the pediatric specialist. In the multivariate analyses, the adult specialists' characteristics had little impact. CONCLUSIONS: For many adolescents with chronic disorders the transition from pediatric to adult healthcare seems to be limited to a simple transfer, often lacking adequate communication between physicians. Applying simple but basic principles such as a good coordination between providers would probably improve the quality of healthcare of adolescents with chronic illness.
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The first investigation of arthropods associated with carrion in Cameroon was carried out within the campus of the University of Yaounde I (Cameroon) from 17thJanuary to 3rd April 2008. Carcasses of rats (Rattus norvegicus Berkenhout, 1769 var WISTAR) were exposed to colonization by the local fauna of arthropods. The invading organisms were collected daily during the study period. 2287 individuals of arthropod belonging to 3 classes, 16 orders, 37 families and 7 subfamilies were identified. The insects assessed were mainly Diptera, Coleoptera and Acari. This study illustrates the high diversity of the necroentomofauna in Cameroon and provides an insight approximation into the succession pattern of invading insect and a weekly estimation of the time of death.
Resumo:
The flourishing number of publications on the use of isotope ratio mass spectrometry (IRMS) in forensic science denotes the enthusiasm and the attraction generated by this technology. IRMS has demonstrated its potential to distinguish chemically identical compounds coming from different sources. Despite the numerous applications of IRMS to a wide range of forensic materials, its implementation in a forensic framework is less straightforward than it appears. In addition, each laboratory has developed its own strategy of analysis on calibration, sequence design, standards utilisation and data treatment without a clear consensus.Through the experience acquired from research undertaken in different forensic fields, we propose a methodological framework of the whole process using IRMS methods. We emphasize the importance of considering isotopic results as part of a whole approach, when applying this technology to a particular forensic issue. The process is divided into six different steps, which should be considered for a thoughtful and relevant application. The dissection of this process into fundamental steps, further detailed, enables a better understanding of the essential, though not exhaustive, factors that have to be considered in order to obtain results of quality and sufficiently robust to proceed to retrospective analyses or interlaboratory comparisons.
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Today's approach to anti-doping is mostly centered on the judicial process, despite pursuing a further goal in the detection, reduction, solving and/or prevention of doping. Similarly to decision-making in the area of law enforcement feeding on Forensic Intelligence, anti-doping might significantly benefit from a more extensive gathering of knowledge. Forensic Intelligence might bring a broader logical dimension to the interpretation of data on doping activities for a more future-oriented and comprehensive approach instead of the traditional case-based and reactive process. Information coming from a variety of sources related to doping, whether directly or potentially, would feed an organized memory to provide real time intelligence on the size, seriousness and evolution of the phenomenon. Due to the complexity of doping, integrating analytical chemical results and longitudinal monitoring of biomarkers with physiological, epidemiological, sociological or circumstantial information might provide a logical framework enabling fit for purpose decision-making. Therefore, Anti-Doping Intelligence might prove efficient at providing a more proactive response to any potential or emerging doping phenomenon or to address existing problems with innovative actions or/and policies. This approach might prove useful to detect, neutralize, disrupt and/or prevent organized doping or the trafficking of doping agents, as well as helping to refine the targeting of athletes or teams. In addition, such an intelligence-led methodology would serve to address doping offenses in the absence of adverse analytical chemical evidence.
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Whether for investigative or intelligence aims, crime analysts often face up the necessity to analyse the spatiotemporal distribution of crimes or traces left by suspects. This article presents a visualisation methodology supporting recurrent practical analytical tasks such as the detection of crime series or the analysis of traces left by digital devices like mobile phone or GPS devices. The proposed approach has led to the development of a dedicated tool that has proven its effectiveness in real inquiries and intelligence practices. It supports a more fluent visual analysis of the collected data and may provide critical clues to support police operations as exemplified by the presented case studies.
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This paper reports on the purpose, design, methodology and target audience of E-learning courses in forensic interpretation offered by the authors since 2010, including practical experiences made throughout the implementation period of this project. This initiative was motivated by the fact that reporting results of forensic examinations in a logically correct and scientifically rigorous way is a daily challenge for any forensic practitioner. Indeed, interpretation of raw data and communication of findings in both written and oral statements are topics where knowledge and applied skills are needed. Although most forensic scientists hold educational records in traditional sciences, only few actually followed full courses that focussed on interpretation issues. Such courses should include foundational principles and methodology - including elements of forensic statistics - for the evaluation of forensic data in a way that is tailored to meet the needs of the criminal justice system. In order to help bridge this gap, the authors' initiative seeks to offer educational opportunities that allow practitioners to acquire knowledge and competence in the current approaches to the evaluation and interpretation of forensic findings. These cover, among other aspects, probabilistic reasoning (including Bayesian networks and other methods of forensic statistics, tools and software), case pre-assessment, skills in the oral and written communication of uncertainty, and the development of independence and self-confidence to solve practical inference problems. E-learning was chosen as a general format because it helps to form a trans-institutional online-community of practitioners from varying forensic disciplines and workfield experience such as reporting officers, (chief) scientists, forensic coordinators, but also lawyers who all can interact directly from their personal workplaces without consideration of distances, travel expenses or time schedules. In the authors' experience, the proposed learning initiative supports participants in developing their expertise and skills in forensic interpretation, but also offers an opportunity for the associated institutions and the forensic community to reinforce the development of a harmonized view with regard to interpretation across forensic disciplines, laboratories and judicial systems.
Resumo:
This article presents an experimental study about the classification ability of several classifiers for multi-classclassification of cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland lawenforcement authorities regularly ask forensic laboratories to determinate the chemotype of a seized cannabisplant and then to conclude if the plantation is legal or not. This classification is mainly performed when theplant is mature as required by the EU official protocol and then the classification of cannabis seedlings is a timeconsuming and costly procedure. A previous study made by the authors has investigated this problematic [1]and showed that it is possible to differentiate between drug type (illegal) and fibre type (legal) cannabis at anearly stage of growth using gas chromatography interfaced with mass spectrometry (GC-MS) based on therelative proportions of eight major leaf compounds. The aims of the present work are on one hand to continueformer work and to optimize the methodology for the discrimination of drug- and fibre type cannabisdeveloped in the previous study and on the other hand to investigate the possibility to predict illegal cannabisvarieties. Seven classifiers for differentiating between cannabis seedlings are evaluated in this paper, namelyLinear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Nearest NeighbourClassification (NNC), Learning Vector Quantization (LVQ), Radial Basis Function Support Vector Machines(RBF SVMs), Random Forest (RF) and Artificial Neural Networks (ANN). The performance of each method wasassessed using the same analytical dataset that consists of 861 samples split into drug- and fibre type cannabiswith drug type cannabis being made up of 12 varieties (i.e. 12 classes). The results show that linear classifiersare not able to manage the distribution of classes in which some overlap areas exist for both classificationproblems. Unlike linear classifiers, NNC and RBF SVMs best differentiate cannabis samples both for 2-class and12-class classifications with average classification results up to 99% and 98%, respectively. Furthermore, RBFSVMs correctly classified into drug type cannabis the independent validation set, which consists of cannabisplants coming from police seizures. In forensic case work this study shows that the discrimination betweencannabis samples at an early stage of growth is possible with fairly high classification performance fordiscriminating between cannabis chemotypes or between drug type cannabis varieties.