Study of isotopic variations in black powder: reflections on the use of stable isotopes in forensic science for source inference.

Isotope ratio mass spectrometry (IRMS) has recently made its appearance in the forensic community. This high-precision technology has already been applied to a broad range of forensic fields such as illicit drugs, explosives and flammable liquids, where current, routinely used techniques have limited powers of discrimination. The conclusions drawn from the majority of these IRMS studies appear to be very promising. Used in a comparative process, as in food or drug authentication, the measurement of stable isotope ratios is a new and remarkable analytical tool for the discrimination or the identification of a substance with a definite source or origin. However, the research consists mostly of preliminary studies. The significance of this 'new' piece of information needs to be evaluated in light of a forensic framework to assess the actual potential and validity of IRMS, considering the characteristics of each field. Through the isotopic study of black powder, this paper aims at illustrating the potential of the method and the limitations of current knowledge in stable isotopes when facing forensic problems.

Surrogate science: The idol of a universal method for scientific inference

The application of statistics to science is not a neutral act. Statistical tools have shaped and were also shaped by its objects. In the social sciences, statistical methods fundamentally changed research practice, making statistical inference its centerpiece. At the same time, textbook writers in the social sciences have transformed rivaling statistical systems into an apparently monolithic method that could be used mechanically. The idol of a universal method for scientific inference has been worshipped since the "inference revolution" of the 1950s. Because no such method has ever been found, surrogates have been created, most notably the quest for significant p values. This form of surrogate science fosters delusions and borderline cheating and has done much harm, creating, for one, a flood of irreproducible results. Proponents of the "Bayesian revolution" should be wary of chasing yet another chimera: an apparently universal inference procedure. A better path would be to promote both an understanding of the various devices in the "statistical toolbox" and informed judgment to select among these.

Isotope ratio mass spectrometry as a tool for source inference in forensic science: a critical review

Isotope ratio mass spectrometry (IRMS) has been used in numerous fields of forensic science in a source inference perspective. This review compiles the studies published on the application of isotope ratio mass spectrometry (IRMS) to the traditional fields of forensic science so far. It completes the review of Benson et al. [1] and synthesises the extent of knowledge already gathered in the following fields: illicit drugs, flammable liquids, human provenancing, microtraces, explosives and other specific materials (packaging tapes, safety matches, plastics, etc.). For each field, a discussion assesses the state of science and highlights the relevance of the information in a forensic context. Through the different discussions which mark out the review, the potential and limitations of IRMS, as well as the needs and challenges of future studies are emphasized. The paper elicits the various dimensions of the source which can be obtained from the isotope information and demonstrates the transversal nature of IRMS as a tool for source inference.

Inference of Evolutionary Forces Acting on Human Biological Pathways.

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald-Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

Hire me: Computational inference of hirability in employment interviews based on nonverbal behavior

Understanding the basis on which recruiters form hirability impressions for a job applicant is a key issue in organizational psychology and can be addressed as a social computing problem. We approach the problem from a face-to-face, nonverbal perspective where behavioral feature extraction and inference are automated. This paper presents a computational framework for the automatic prediction of hirability. To this end, we collected an audio-visual dataset of real job interviews where candidates were applying for a marketing job. We automatically extracted audio and visual behavioral cues related to both the applicant and the interviewer. We then evaluated several regression methods for the prediction of hirability scores and showed the feasibility of conducting such a task, with ridge regression explaining 36.2% of the variance. Feature groups were analyzed, and two main groups of behavioral cues were predictive of hirability: applicant audio features and interviewer visual cues, showing the predictive validity of cues related not only to the applicant, but also to the interviewer. As a last step, we analyzed the predictive validity of psychometric questionnaires often used in the personnel selection process, and found that these questionnaires were unable to predict hirability, suggesting that hirability impressions were formed based on the interaction during the interview rather than on questionnaire data.