Conformal Prediction: a Unified Review of Theory and New Challenges

In this work we provide a review of basic ideas and novel developments about Conformal Prediction -- an innovative distribution-free, non-parametric forecasting method, based on minimal assumptions -- that is able to yield in a very straightforward way predictions sets that are valid in a statistical sense also in in the finite sample case. The in-depth discussion provided in the paper covers the theoretical underpinnings of Conformal Prediction, and then proceeds to list the more advanced developments and adaptations of the original idea.Comment: arXiv admin note: text overlap with arXiv:0706.3188, arXiv:1604.04173, arXiv:1709.06233, arXiv:1203.5422 by other author

Refractive index sensing by brillouin scattering in side-polished optical fibers

In this Letter, we demonstrate the possibility to measure the refractive index of a liquid, using the stimulating Brillouin scattering in a 3-cm-long side-polished optical fiber. In addition, we show that by depositing a high-refractive index layer on the polished surface the sensitivity of the Brillouin frequency shift (BFS) can be increased due to a higher penetration of the evanescent field in the outer medium. Experiments show a maximum BFS change of about 11 MHz when varying the refractive index of the external medium from 1 (air) to 1.402, and a BFS sensitivity to refractive index of about 293 MHz/RIU around 1.40

Automated image-based analysis unveils acute effects due to sub-lethal pesticide doses exposure

Pesticides are still abused in modern agriculture. The effects of their exposure to even sub-lethal doses can be detrimental to ecosystem stability and human health. This work aims to validate the use of machine learning techniques for recognizing motor abnormalities and to assess any effect post-exposure to a minimal dosage of these substances on a model organism, gaining insights into potential risks for human health. The test subject was the Mediterranean fruit fly, Ceratitis capitata (Wiedemann) (Diptera: Tephritidae), exposed to food contaminated with the LC 30 of Carlina acaulis essential oil. A deep learning approach enabled the pose estimation within an arena. Statistical analysis highlighted the most significant features between treated and untreated groups. Based on this analysis, two learning-based algorithms, Random Forest (RF) and XGBoost were employed. The results were compared through different metrics. RF algorithm generated a model capable of distinguishing treated subjects with an area under the receiver operating characteristic curve of 0.75 and an accuracy of 0.71. Through an image-based analysis, this study revealed acute effects due to minimal pesticide doses. So, even small amounts of these biocides drifted far from distribution areas may negatively affect the environment and humans

Surface Plasmon Resonance Sensor Based on Inkjet 3D Printing

A novel surface plasmon (SPR) sensor was designed, manufactured and experimentally tested. A novel approach was followed to fabricate the sensor. It is based on a combination of both the inkjet 3D printing process and the use of optical adhesives, which were used as an alternative solution to the use of plastic optical fibers (POFs). The obtained experimental results showed good performances, at least in terms of figure of merit (FOM), for the 3D-printed sensor, which were quite similar to those gained by an SPR–POF configuration. Next, through a cost analysis, the possibility of manufacturing the SPR sensor at a low cost was demonstrated, thus being economically advantageous towards conventional sensors