A game theoretical semantics for a logic of formal inconsistency

This paper introduces a game theoretical semantics for a particular logic of formal inconsistency called mbC

Correction to:A two million year record of low-latitude aridity linked to continental weathering from the Maldives (Progress in Earth and Planetary Science, (2018), 5, 1, (86), 10.1186/s40645-018-0238-x)

In the original version of this article (Kunkelova et al. 2018), published on 18 December 2018, there was 1 error in the author name of Dr. Yu

A two million year record of low-latitude aridity linked to continental weathering from the Maldives

Tem uma correção em http://hdl.handle.net/10400.1/12390Indian-Asian monsoon has oscillated between warm/wet interglacial periods and cool/dry glacial periods with periodicities closely linked to variations in Earth’s orbital parameters. However, processes that control wet versus dry, i.e. aridity cyclical periods on the orbital time-scale in the low latitudes of the Indian-Asian continent remain poorly understood because records over millions of years are scarce. The sedimentary record from International Ocean Discovery Program (IODP) Expedition 359 provides a well-preserved, high-resolution, continuous archive of lithogenic input from the Maldives reflecting on low-latitude aridity cycles. Variability within the lithogenic component of sedimentary deposits of the Maldives results from changes in monsoon-controlled sedimentary sources. Here, we present X-ray fluorescence (XRF) core-scanning results from IODP Site U1467 for the past two million years, allowing full investigation of orbital periodicities. We specifically use the Fe/K as a terrestrial climate proxy reflecting on wet versus dry conditions in the source areas of the Indian-Asian landmass, or from further afield. The Fe/K record shows orbitally forced cycles reflecting on changes in the relative importance of aeolian (stronger winter monsoon) during glacial periods versus fluvial supply (stronger summer monsoon) during interglacial periods. For our chronology, we tuned the Fe/K cycles to precessional insolation changes, linking Fe/K maxima/minima to insolation minima/maxima with zero phase lag. Wavelet and spectral analyses of the Fe/K record show increased dominance of the 100 kyr cycles after the Mid Pleistocene Transition (MPT) at 1.25 Ma in tandem with the global ice volume benthic δ18O data (LR04 record). In contrast to the LR04 record, the Fe/K profile resolves 100-kyr-like cycles around the 130 kyr frequency band in the interval from 1.25 to 2 million years. These 100-kyr-like cycles likely form by bundling of two or three obliquity cycles, indicating that low-latitude Indian-Asian climate variability reflects on increased tilt sensitivity to regional eccentricity insolation changes (pacing tilt cycles) prior to the MPT. The implication of appearance of the 100 kyr cycles in the LR04 and the Fe/K records since the MPT suggests strengthening of a climate link between the low and high latitudes during this period of climate transition.SFRH/BPD/96960/2013; PTDC/MAR-PRO/3396/2014info:eu-repo/semantics/publishedVersio

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, thanks to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. Treatment plans obtained considering the optimized noncoplanar arc trajectories, for a pool of twelve difficult head-and-neck tumor cases, present a remarkable quality improvement when compared with treatment plans obtained considering coplanar equispaced beam directions, still commonly used in clinical practice. Furthermore, significant quality improvements were obtained for some of the cases when compared to coplanar VMAT treatment plans. Automated procedures like the one proposed in this paper will simplify the current treatment workflow, making better use of human resources and allowing for unbiased comparisons between different treatment techniques. As running the proposed automated framework will not waste any human resources, it can be assessed as being a valuable tool in clinical practice even if it only benefits specific patients

Flow neutralisation of sulfur-containing chemical warfare agents with Oxone: packed bed vs. aqueous solution

peer reviewedThe oxidative neutralisation of sulfur-containing CWAs (yperite and VX simulants) with Oxone has been developed in flow systems. In order to reach full selectivity towards harmless decomposition products, Oxone has to be used either in solid form (blister agent detoxification) or aqueous form (nerve agent detoxification)

An automated bi‐level optimization approach for IMRT

Intensity-modulated radiation therapy is used worldwide to treat cancer patients. The objective of this treatment is to deliver a prescribed radiation dose to the tumor while sparing, as much as possible, all the healthy tissues, especially organs at risk (OAR). This means that the planning of a radiotherapy treatment should take into consideration conflicting objectives: to be able to spare as much as possible the OAR guaranteeing, at the same time, that the desired radiation is delivered to the volumes to treat. While the volumes to treat can be adequately irradiated from almost any set of directions, the radiation directions that are chosen have a determinant impact on the OAR. This means that those directions that provide an improved OAR sparing should be selected. The choice of radiation directions (beam angles) can thus be interpreted as being fundamentally determined by the OAR, with the radiation intensities associated with each of these directions being determined by the needed radiation to be delivered to the volumes to treat. In this work, we interpret the radiotherapy treatment planning problem as a bi-level optimization problem. At the upper level, OAR control the choice of the beam angles, which are selected aiming at OAR sparing. At the lower level, the optimal radiation intensities are decided by the volumes to treat, considering the beam angle ensemble obtained at the upper level. The proposed bi-level approach was tested using 10 clinical head-and-neck cancer cases already treated at the Portuguese Institute of Oncology in Coimbra

Static and Dynamic Algorithms for Terrain Classification in UAV Aerial Imagery

The ability to precisely classify different types of terrain is extremely important for Unmanned Aerial Vehicles (UAVs). There are multiple situations in which terrain classification is fundamental for achieving a UAV’s mission success, such as emergency landing, aerial mapping, decision making, and cooperation between UAVs in autonomous navigation. Previous research works describe different terrain classification approaches mainly using static features from RGB images taken onboard UAVs. In these works, the terrain is classified from each image taken as a whole, not divided into blocks; this approach has an obvious drawback when applied to images with multiple terrain types. This paper proposes a robust computer vision system to classify terrain types using three main algorithms, which extract features from UAV’s downwash effect: Static textures- Gray-Level Co-Occurrence Matrix (GLCM), Gray-Level Run Length Matrix (GLRLM) and Dynamic textures- Optical Flow method. This system has been fully implemented using the OpenCV library, and the GLCM algorithm has also been partially specified in a Hardware Description Language (VHDL) and implemented in a Field Programmable Gate Array (FPGA)-based platform. In addition to these feature extraction algorithms, a neural network was designed with the aim of classifying the terrain into one of four classes. Lastly, in order to store and access all the classified terrain information, a dynamic map, with this information was generated. The system was validated using videos acquired onboard a UAV with an RGB camera