Optimal Blends of History and Intelligence for Robust Antiterrorism Policy

Abstract Antiterrorism analysis requires that security agencies blend evidence on historical patterns of terrorist behavior with incomplete intelligence on terrorist adversaries to predict possible terrorist operations and devise appropriate countermeasures. We model interactions between reactive, adaptive and intelligent adversaries embedded in minimally sufficient organizational settings to study the optimal analytic mixture, expressed as historical memory reach-back and the number of anticipatory scenarios, that should be used to design antiterrorism policy. We show that history is a valuable source of information when the terrorist organization evolves and acquires new capabilities at such a rapid pace that makes optimal strategies advocated by game-theoretic reasoning unlikely to succeed

Cohort profile: the British Columbia COVID-19 Cohort (BCC19C)—a dynamic, linked population-based cohort

PurposeThe British Columbia COVID-19 Cohort (BCC19C) was developed from an innovative, dynamic surveillance platform and is accessed/analyzed through a cloud-based environment. The platform integrates recently developed provincial COVID-19 datasets (refreshed daily) with existing administrative holdings and provincial registries (refreshed weekly/monthly). The platform/cohort were established to inform the COVID-19 response in near “real-time” and to answer more in-depth epidemiologic questions.ParticipantsThe surveillance platform facilitates the creation of large, up-to-date analytic cohorts of people accessing COVID-19 related services and their linked medical histories. The program of work focused on creating/analyzing these cohorts is referred to as the BCC19C. The administrative/registry datasets integrated within the platform are not specific to COVID-19 and allow for selection of “control” individuals who have not accessed COVID-19 services.Findings to dateThe platform has vastly broadened the range of COVID-19 analyses possible, and outputs from BCC19C analyses have been used to create dashboards, support routine reporting and contribute to the peer-reviewed literature. Published manuscripts (total of 15 as of July, 2023) have appeared in high-profile publications, generated significant media attention and informed policy and programming. In this paper, we conducted an analysis to identify sociodemographic and health characteristics associated with receiving SARS-CoV-2 laboratory testing, testing positive, and being fully vaccinated. Other published analyses have compared the relative clinical severity of different variants of concern; quantified the high “real-world” effectiveness of vaccines in addition to the higher risk of myocarditis among younger males following a 2nd dose of an mRNA vaccine; developed and validated an algorithm for identifying long-COVID patients in administrative data; identified a higher rate of diabetes and healthcare utilization among people with long-COVID; and measured the impact of the pandemic on mental health, among other analyses.Future plansWhile the global COVID-19 health emergency has ended, our program of work remains robust. We plan to integrate additional datasets into the surveillance platform to further improve and expand covariate measurement and scope of analyses. Our analyses continue to focus on retrospective studies of various aspects of the COVID-19 pandemic, as well as prospective assessment of post-acute COVID-19 conditions and other impacts of the pandemic

Axelrod’s metanorm games on networks

Metanorms is a mechanism proposed to promote cooperation in social dilemmas. Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation. We generalize Axelrod’s analysis of metanorms dynamics to interactions unfolding on networks through simulation and mathematical modeling. Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation. In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperationSpanish MICINN projects CSD2010-00034 (CONSOLIDER-INGENIO 2010) and DPI2010-16920, and by the Junta de Castilla y Leo´ n, references BU034A08 and GREX251-2009

Dynamic Treatment Regimes and Interference in Dyadic Networks: A Joint Optimization Approach

Identifying interventions that are optimally tailored to each individual is of significant interest in various fields, in particular precision medicine. Dynamic treatment regimes (DTRs) employ sequences of decision rules that utilize individual patient information to recommend treatments. However, the assumption that an individual's treatment does not impact the outcomes of others, known as the no interference assumption, is often challenged in practical settings. For example, in infectious disease studies, the vaccine status of individuals in close proximity can influence the likelihood of infection. Imposing this assumption when it, in fact, does not hold, may lead to biased results and impact the validity of our resulting DTR optimization. In this thesis, we extend the estimation method of dynamic weighted ordinary least squares (dWOLS), a doubly robust and easily implemented approach for estimating optimal DTRs, to incorporate the presence of interference. Specifically, we develop new methodologies to optimize DTRs in the presence of interference for both binary and continuous treatments. Through comprehensive simulations and analysis of the Population Assessment of Tobacco and Health (PATH) data, we demonstrate the performance of the proposed joint optimization strategy compared to the current state-of-the-art conditional optimization methods. Furthermore, we extend the dWOLS method to accommodate multiple outcomes and patient-specific costs, enhancing its flexibility and applicability in complex health contexts

Advances in Bioresorbable phosphate ‎glass optical fiber fabrication

L'abstract è presente nell'allegato / the abstract is in the attachmen

Phosphate glass-based microstructured optical fibers with hole and core for biomedical applications

Bioresorbable phosphate glasses are an excellent alternative to conventional silicate-based glass systems for biomedical applications. These glasses can have tailorable bioresorbability and mechanical properties, a wide range of transparency windows (from 300 to 2600 nm), and are of great interest for biophotonic devices. The present work investigates the feasibility of fabricating a microstructured bioresorbable optical fiber combined with a microfluidic channel. Extrusion and stack-and-draw techniques are used to manufacture the microstructured optical fiber capable of guiding light and liquid simultaneously. An optimized extrusion procedure allowed fabricating preforms with the lowest bending and tapering possible. The preform was drawn to 130 and 230 μm diameter fibers. Light guide and attenuation loss were characterized, and the microfluidic channel was tested for liquid delivery. The proposed approach demonstrates the vast potentiality of such microstructured fiber that could be used as a theranostics device to be employed in specific areas inside the body without needing a removal procedure

Bioresorbable phosphate glass microstructured optical fibers with hole and core for biomedicine

Over the last decades, there has been a growing interest towards optical fiber technology for biomedical field. Several applications that require insertion of optical fibers into the human body will take advantage of the availability of bioresorbable fibers able to be gradually resorbed by the tissue eliminating the need for follow-up explant surgery. Calcium-phosphate glasses have been designed and synthesized in our laboratory to be dissolvable in biological fluids while showing a wide range of transparency, mechanical reliability, and suitability for both preform extrusion and fiber drawing. Step index single-mode and multi-mode optical fibers have been drawn from these glasses using a custom-made induction heated drawing tower. In this work we report the fabrication of a microstructured bioresorbable optical fiber featuring a multi-mode core and a microfluidic channel. The preform was drawn to 130 and 230 μm diameter fibers. Light guide and attenuation loss were characterized, and the microfluidic channel was tested for liquid delivery. The proposed fiber shows a vast potentiality in theragnostic applications where the ability of delivery liquid and light simultaneously could enable novel devices to be employed in specific areas inside the body without needing a removal procedure

Proportion of time spent in the emergence and collapse zones.

<p>Proportion of time that the simulation spends in the norm collapse and emergence zones as a function of key network statistics using similar projections as those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020474#pone-0020474-g005" target="_blank">Figure 5</a>. Color codes the fraction of simulation time spent in each zone computed for each bin. Time spent outside either zone is insignificant.</p

Legend for gradient maps.

<p>The map applies to both analytic and simulated gradient landscapes. The axes represent the average boldness and vengefulness of the population as its strategic characteristics. For each point, we measure the direction and speed of population drift. For analytical landscapes, we will also pinpoint the expected location of the evolutionary stable states. For simulation landscapes, we will be measuring the time that the simulation spends in each of the two key regions: norm emergence and norm collapse zones. Sample maps for different network topologies are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020474#pone-0020474-g007" target="_blank">Figure 7</a>.</p

Minimal interconnectedness necessary for a cooperative evolutionary stable state.

<p>Minimal interconnectedness necessary for a cooperative evolutionary stable state to exist in the simplified analytical model for any given average degree of the network, compared to the expected interconnectedness of different network topologies with radius 1. Default metanorms parameters are assumed.</p