The aim of this work is to analyze the effects of ionizing radiation and radionuclides (like ¹³⁷Cs) in several higher plants located around the Fukushima Dai-ichi Nuclear Power Plant (FNPP), evaluating both their adaptive processes and evolution. After the FNPP accident in March 2011 much attention was focused to the biological consequences of ionizing radiation and radionuclides released in the area surrounding the nuclear plant. This unexpected mishap led to the emission of radionuclides in aerosol and gaseous forms from the power plant, which contaminated a large area, including wild forest, cities, farmlands, mountains, and the sea, causing serious problems. Large quantities of ¹³¹I, ¹³⁷Cs, and ¹³⁴Cs were detected in the fallout. People were evacuated but the flora continued to be affected by the radiation exposure and by the radioactive dusts’ fallout. The response of biota to FNPP irradiation was a complex interaction among radiation dose, dose rate, temporal and spatial variation, varying radiation sensitivities of the different plants’ species, and indirect effects from other events. The repeated ionizing radiations, acute or chronic, guarantee an adaptation of the plant species, demonstrating a radio-resistance. Consequently, ionizing radiation affects the genetic structure, especially during chronic irradiation, reducing genetic variability. This reduction is associated with the different susceptibility of plant species to chronic stress. This would confirm the adaptive theory associated with this phenomenon. The effects that ionizing radiation has on different life forms are examined in this review using the FNPP disaster as a case study focusing the attention ten years after the accident.

Conventional and non-conventional emergencies are among the most important safety and security concerns of the new millennium. Nuclear power and research plants, high-energy particle accelerators, radioactive substances for industrial and medical uses are all considered credible sources of threats both in warfare and in terror scenarios. Estimates of potential radiation releases of radioactive contamination related to these threats are therefore essential in order to prepare and respond to such scenarios. The goal of this paper is to demonstrate that computational modeling codes to simulate transport of radioactivity are extremely valuable to assess expected radiation levels and to improve risk analysis during emergencies helping the emergency planner and the first responders in the first hours of an occurring emergency.

Biosecurity and biosafety are key concerns of modern society. Although nanomaterials are improving the capacities of point detectors, standoff detection still appears to be an open issue. Laser-induced fluorescence of biological agents (BAs) has proved to be one of the most promising optical techniques to achieve early standoff detection, but its strengths and weaknesses are still to be fully investigated. In particular, different BAs tend to have similar fluorescence spectra due to the ubiquity of biological endogenous fluorophores producing a signal in the UV range, making data analysis extremely challenging. The Universal Multi Event Locator (UMEL), a general method based on support vector regression, is commonly used to identify characteristic structures in arrays of data. In the first part of this work, we investigate fluorescence emission spectra of different simulants of BAs and apply UMEL for their automatic classification. In the second part of this work, we elaborate a strategy for the application of UMEL to the discrimination of different BAs’ simulants spectra. Through this strategy, it has been possible to discriminate between these BAs’ simulants despite the high similarity of their fluorescence spectra. These preliminary results support the use of SVR methods to classify BAs’ spectral signatures.