Expressing the value of forensic science in policing

© 2016 Australian Academy of Forensic Sciences. Only a small part of forensic science activities scattered across criminal justice systems is the object of scientific scrutiny, and is taken into account when evaluating the added-value brought by this discipline. Even in its more restricted definition, forensic science faces many embarrassing questions about its capacity to provide valid and reliably interpreted information in court. The inflation of control mechanisms increases costs and reduces the scope or availability of forensic information. The viability of forensic science, viewed through this lens, is questioned. To address this challenge, it is imperative to validly express forensic science contributions that are otherwise diluted across earlier processes. These include abductive and inductive species of inferences used in crime investigation, crime analysis and criminal intelligence. The ‘scientificity’ of these processes may be questioned, but it is not contested that they largely determine the global outcome of justice systems. As a result, they cannot be ignored. To unlock the debate, it is proposed to turn the forensic science focus from means (instruments, techniques, methods) to ends (what is the problem, what are the objectives?). This perspective naturally leads to proactive models of policing. It also provides possible frameworks to express various uses of the information conveyed by traces for solving problems. Reframed forensic science contributions are more validly expressed and the current debate can ultimately be transcended

Parameterized Littlewood-Paley operators with variable kernels on Hardy spaces and weak Hardy spaces

In this paper, by using the atomic decomposition theory of Hardy space and weak Hardy space, we discuss the boundedness of parameterized Littlewood-Paley operator with variable kernel on these spaces.Comment: 15 pages. arXiv admin note: text overlap with arXiv:1711.0961

Forensic-led regulation strategies: are they fit for security problem-solving purposes?

The dominant conception of forensic sciences is as a patchwork of disciplines assisting the criminal justice system, but the 2009 NAS report questioned the robustness of the scientific foundations of essentially all the forensic science disciplines. Yet, solutions intended to counter this disturbing assessment have mainly focused on methodology upgrades epitomized by quality management strategies that are crowned by accreditation of laboratories and certification of individual forensic scientists.While a forensic science world without quality management is senseless, its reported and observed implementation begs the question whether it has developed from a necessary tool to a constraint contributing to frame a mistaken view of experimental sciences dedicated to responding to criminal and litigation matters. This article questions the adequacy of forensic-led regulation strategies for security problem-solving, calling for a better understanding of its original link with criminological concerns. © 2018 selection and editorial matter, Quentin Rossy, David Décary-Hétu, Olivier Delémont and Massimiliano Mulone; individual chapters, the contributors

Experimental design trade-offs for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle

Time-series of high throughput gene sequencing data intended for gene regulatory network (GRN) inference are often short due to the high costs of sampling cell systems. Moreover, experimentalists lack a set of quantitative guidelines that prescribe the minimal number of samples required to infer a reliable GRN model. We study the temporal resolution of data vs quality of GRN inference in order to ultimately overcome this deficit. The evolution of a Markovian jump process model for the Ras/cAMP/PKA pathway of proteins and metabolites in the G1 phase of the Saccharomyces cerevisiae cell cycle is sampled at a number of different rates. For each time-series we infer a linear regression model of the GRN using the LASSO method. The inferred network topology is evaluated in terms of the area under the precision-recall curve AUPR. By plotting the AUPR against the number of samples, we show that the trade-off has a, roughly speaking, sigmoid shape. An optimal number of samples corresponds to values on the ridge of the sigmoid

Staphylococcus aureus gene expression in a rat model of infective endocarditis

Background: Diabetes mellitus is a frequent underlying comorbidity in patients with Staphylococcus aureus endocarditis, and it represents a risk factor for complications and a negative outcome. The pathogenesis of staphylococcal endocardial infections in diabetic hosts has been poorly characterized, and little is known about S. aureus gene expression in endocardial vegetations. Methods: We utilized a rat model of experimental S. aureus endocarditis to compare the pathogenesis of staphylococcal infection in diabetic and nondiabetic hosts and to study the global S. aureus transcriptome in endocardial vegetations in vivo. Results: Diabetic rats had higher levels of bacteremia and larger endocardial vegetations than nondiabetic control animals. Microarray analyses revealed that 61 S. aureus genes were upregulated in diabetic rats, and the majority of these bacterial genes were involved in amino acid and carbohydrate metabolism. When bacterial gene expression in vivo (diabetic or nondiabetic endocardial vegetations) was compared to in vitro growth conditions, higher in vivo expression of genes encoding toxins and proteases was observed. Additionally, genes involved in the production of adhesins, capsular polysaccharide, and siderophores, as well as in amino acid and carbohydrate transport and metabolism, were upregulated in endocardial vegetations. To test the contribution of selected upregulated genes to the pathogenesis of staphylococcal endocarditis, isogenic deletion mutants were utilized. A mutant defective in production of the siderophore staphyloferrin B was attenuated in the endocarditis model, whereas the virulence of a surface adhesin (ΔsdrCDE) mutant was similar to that of the parental S. aureus strain. Conclusions: Our results emphasize the relevance of diabetes mellitus as a risk factor for infectious endocarditis and provide a basis for understanding gene expression during staphylococcal infections in vivo. Electronic supplementary material The online version of this article (doi:10.1186/s13073-014-0093-3) contains supplementary material, which is available to authorized users

Conductivity Exponent and Backbone Dimension in 2-d Percolation

We present high statistics simulations for 2-d percolation clusters in the "bus bar" geometry at the critical point, for site and for bond percolation. We measured their backbone sizes and electrical conductivities. For all sets of measurements we find large corrections to scaling, most of which do not seem to be described by single powers. Using single power terms for the corrections to scaling of the backbone masses, we would obtain fractal dimensions which are different for site and bond percolation, while the correct result is $D_b = 1.6432(8)$ for both. For the conductivity, the corrections to scaling are strongly non-monotonic for bond percolation. The exponent $t' = t/\nu$ is measured as 0.9826(8), in disagreement with the Alexander-Orbach and other conjectures.Comment: 15 pages, including 5 figures and 2 tables; minor change

An algorithm to calculate the transport exponent in strip geometries

An algorithm for solving the random resistor problem by means of the transfer-matrix approach is presented. Preconditioning by spanning clusters extraction both reduces the size of the conductivity matrix and speed up the calculations.Comment: 17 pages, RevTeX2.1, HLRZ - 97/9

Shearing of loose granular materials: A statistical mesoscopic model

A two-dimensional lattice model for the formation and evolution of shear bands in granular media is proposed. Each lattice site is assigned a random variable which reflects the local density. At every time step, the strain is localized along a single shear-band which is a spanning path on the lattice chosen through an extremum condition. The dynamics consists of randomly changing the `density' of the sites only along the shear band, and then repeating the procedure of locating the extremal path and changing it. Starting from an initially uncorrelated density field, it is found that this dynamics leads to a slow compaction along with a non-trivial patterning of the system, with high density regions forming which shelter long-lived low-density valleys. Further, as a result of these large density fluctuations, the shear band which was initially equally likely to be found anywhere on the lattice, gets progressively trapped for longer and longer periods of time. This state is however meta-stable, and the system continues to evolve slowly in a manner reminiscent of glassy dynamics. Several quantities have been studied numerically which support this picture and elucidate the unusual system-size effects at play.Comment: 11 pages, 15 figures revtex, submitted to PRE, See also: cond-mat/020921