Forest fires are still a large concern in several countries due to the social, environmental and economic damages caused. This paper aims to show the design and validation of a proposed system for the classification of smoke columns with object detection and a deep learning-based approach. This approach is able to detect smoke columns visible below or above the horizon. During the dataset labelling, the smoke object was divided into three different classes, depending on its distance to the horizon, a cloud object was also added, along with images without annotations. A comparison between the use of RetinaNet and Faster R-CNN was also performed. Using an independent test set, an F1-score around 80%, a G-mean around 80% and a detection rate around 90% were achieved by the two best models: both were trained with the dataset labelled with three different smoke classes and with augmentation; Faster R-CNNN was the model architecture, re-trained during the same iterations but following different learning rate schedules. Finally, these models were tested in 24 smoke sequences of the public HPWREN dataset, with 6.3 min as the average time elapsed from the start of the fire compared to the first detection of a smoke column.

Large forest fires have repeatedly affected Europe, in particular the Mediterranean countries. It is now crucial to continue the effort to feed the several layers of prediction models and understand how wildfire spreads in order to develop modern preventative and mitigation methods. The present study evaluates the performance of Sentinel 5-P TROPOMI for the monitoring of carbon monoxide (CO) and methane (CH₄) during extreme fire events in Portugal, focusing on the Monchique (2018) and Vila de Rei/Mação (2019) wildfires, which devastated 27,154 ha and 9249 ha, respectively. The spatial distribution and trend of CO and CH₄ prior to, during, and following the fire event were accessed and linked with in situ data in a qualitative and quantitative exploration. Large CO plumes were observed with CO columns exceeding 4.5 × 10¹⁸ and 6 × 10¹⁸ molecules/cm² on 21 July 2019, and 7 August 2018, respectively. CO distribution profiles after consecutive digital processing steps showed the ability to follow CO fluctuations according to the fire spread. Furthermore, statistically significant differences were found between CO emissions inside and outside the burning area in both fire events. Finally, the CO₂ estimated through CO column data presented an emission of 7.6 × 10¹⁹ molecules/cm² for the uppermost emission day on 7 August 2018. Although CH₄ monitoring is still unwavering to draw exact conclusions, the CO patterns during extreme fire events show promising and consistent data when compared with in situ data.

The aim of this research is to carry out a systematic review of the use of technological gaming platforms with serious games in the upper limb rehabilitation of patients with neuromotor disorders. Through a systematic review, the first two authors defined the inclusion criteria and extracted the data, resulting in 38 studies collected from B-On, PubMed and Medline. Ninety-two per cent of the selected articles were published since 2010. This review documents 35 different gaming platforms types. Twenty-one of the 38 articles included in this review conducted a clinical trial and of those only eight report improvements in the target population following the use of the games and platforms. This review concludes that a new paradigm is emerging in the rehabilitation field, characterized by the systematic use of technological gaming platforms with serious games in/for rehabilitation. The use of this approach seems to be beneficial. However, to facilitate the full integration of these platforms, it is necessary to conduct more research in this area, explore new approaches and carry out in-depth clinical studies into the benefits of these platforms. Implications for rehabilitation This review states that the use serious games and gaming platforms for upper limb rehabilitation are starting a new paradigm in the rehabilitation. For a full integration of this technologies in the rehabilitation field more studies are needed.

Drusen are common features in the ageing macula associated with exudative Age-Related Macular Degeneration (ARMD). They are visible in retinal images and their quantitative analysis is important in the follow up of the ARMD. However, their evaluation is fastidious and difficult to reproduce when performed manually. This article proposes a methodology for Automatic Drusen Deposits Detection and quantification in Retinal Images (AD3RI) by using digital image processing techniques. It includes an image pre-processing method to correct the uneven illumination and to normalize the intensity contrast with smoothing splines. The drusen detection uses a gradient based segmentation algorithm that isolates drusen and provides basic drusen characterization to the modelling stage. The detected drusen are then fitted by Modified Gaussian functions, producing a model of the image that is used to evaluate the affected area. Twenty two images were graded by eight experts, with the aid of a custom made software and compared with AD3RI. This comparison was based both on the total area and on the pixel-to-pixel analysis. The coefficient of variation, the intraclass correlation coefficient, the sensitivity, the specificity and the kappa coefficient were calculated. The ground truth used in this study was the experts' average grading. In order to evaluate the proposed methodology three indicators were defined: AD3RI compared to the ground truth (A2G); each expert compared to the other experts (E2E) and a standard Global Threshold method compared to the ground truth (T2G). The results obtained for the three indicators, A2G, E2E and T2G, were: coefficient of variation 28.8 %, 22.5 % and 41.1 %, intraclass correlation coefficient 0.92, 0.88 and 0.67, sensitivity 0.68, 0.67 and 0.74, specificity 0.96, 0.97 and 0.94, and kappa coefficient 0.58, 0.60 and 0.49, respectively. The gradings produced by AD3RI obtained an agreement with the ground truth similar to the experts (with a higher reproducibility) and significantly better than the Threshold Method. Despite the higher sensitivity of the Threshold method, explained by its over segmentation bias, it has lower specificity and lower kappa coefficient. Therefore, it can be concluded that AD3RI accurately quantifies drusen, using a reproducible method with benefits for ARMD evaluation and follow-up.

Background: Photothermal response of plasmonic nanomaterials can be utilized for a number of therapeutic applications such as the ablation of solid tumors. Methods & results: Gold nanoparticles were prepared using different methods. After optimization, we applied an aqueous plant extract as the reducing and capping agent of gold and maximized the near-infrared absorption (650–900 nm). Resultant nanoparticles showed good biocompatibility when tested in vitro in human keratinocytes and yeast Saccharomyces cerevisiae. Gold nanoparticles were easily activated by controlled temperature with an ultrasonic water bath and application of a pulsed laser. Conclusion: These gold nanoparticles can be synthesized with reproducibility, modified with seemingly limitless chemical functional groups, with adequate controlled optical properties for laser phototherapy of tumors and targeted drug delivery.

Currently retinal imaging is performed with the fundus camera. This has a number of limitations, in particular the high level of illuminations required for imaging. The scanning laser ophthalmoscope (SLO) has been proposed as an alternative imaging device but to date one of its main limitations has been that it gives only monochromatic images. In this paper we describe an SLO which uses low power red, green and blue lasers to image the human fundus. Using three lasers simultaneously to produce a colour image will increase the fundus exposure by a factor of three. To overcome this problem, a technique has been developed for multiplexing the lasers so that each point on the retina is imaged by the three lasers pulsed rapidly in sequence. The total exposure is thus kept to the same level as for a single laser and total imaging time is not increased. An example is shown of the image from a patient with diabetic retinopathy.