Morphogen gradients have been associated with differential gene expression and are implicated in the triggering and regulation of developmental biological processes. This study focused on creating morphogenic gradients through the thickness of hydrospun scaffolds. Specifically, electrospun poly(ε-caprolactone) fibers were loaded with all-trans-retinoic acid (ATRA), and designed to release ATRA at a predetermined rate. Multilayered scaffolds designed to present varied initial ATRA concentrations were then exposed to flow conditions in a bioreactor. Gradient formation was verified by a simple convection-diffusion mathematical model approving establishment of a continuous solute gradient across the scaffold. The biological value of the designed gradients in scaffolds was evaluated by monitoring the fate of murine embryonal carcinoma cells embedded within the scaffolds. Cell differentiation within the different layers matched the predictions set forth by the theoretical model, in accordance with the ATRA gradient formed across the scaffold. This tool bears powerful potential in establishing in vitro simulation models for better understanding the inner workings of the embryo.
Purpose
The purpose of this paper is to provide a framework to thinking and creating scenarios about future crimes and terror attacks relying on the Internet of Things (IoT), and to present a crowdsourcing research based on this thinking, which resulted in both high- and low-probability scenarios with dramatic impact.
Design/methodology/approach
The research relies on general morphological analysis for deconstructing wicked problems into core components, and on crowdsourcing 50 experts on Wikistrat’s commercial platform, allowing them to suggest core components, rank them by importance and develop scenarios together. This methodology allowed a wider view than usual, and allowed the experts to examine unorthodox combination of components, leading to the creation of wild-card scenarios.
Findings
Analysis of both the core components and the resulting scenarios indicates that the IoT is set to have a dramatic role in crime and terror attacks in the near future. High-impact high-probability scenarios include attacks on power plants, cyber wallets and personal assistants. High-impact low-probability scenarios include terrorist attacks by environmentalist groups, accidental attacks conducted by immature pranksters and having a computer worm propagating in a low-security but critical facility like a hospital.
Originality/value
This paper brings a standardized method which can be used to examine complex events like crime and terror attacks using a disruptive and emerging technology. The results can be used by practitioners to further study the issue and develop many other scenarios more tailored to their needs. The scenarios presented in this paper can also be of value to security bodies who wish to be better prepared for the future.
The Internet of Things is a paradigm in which everyday items are connected to the internet and share information with other devices. This new paradigm is rapidly becoming a reality in the developed world, and while it holds an immensely positive potential, it also means that criminals and terrorists would be able to influence the physical world from the comfort of their homes. We can expect that hackers, ransomwares, viruses, spywares and many of the other woes of the internet today will migrate to the internet of things as well. In this research we used General Morphological Analysis and brought together fifty experts on an online platform to develop novel scenarios about the crimes and terrorist acts of the future. The experts developed 21 scenarios, which were then ranked according to their plausibility. We provide a brief description of every scenario, and focus particularly on the four most plausible ones: blackmailing by connecting to smart homes, gaining insider information from wearable devices and using it for financial gains, assaulting a smart city through the internet, and performing sex crimes via connected items in the smart home.
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