Heuristic-based approaches for (CP)-nets in negotiation

CP-Nets have proven to be an effective representation for capturing preferences. However, their use in multiagent negotiation is not straightforward. The main reason for this is that CP-Nets capture partial ordering of preferences, whereas negotiating agents are required to compare any two outcomes based on the request and offers. This makes it necessary for agents to generate total orders from their CP-Nets. We have previously proposed a heuristic to generate total orders from a given CP-Net. This paper proposes another heuristic based on Borda count, applies it in negotiation, and compares its performance with the previous heuristic

Case Report: Gastric Carcinoma Diagnosed at the Second Trimester of Pregnancy

We report a rare case of gastric cancer in pregnancy. A 26-year-old woman presented at the 20th week of pregnancy complaining of nausea and vomiting. Although the patient considered the condition to be related with pregnancy and underestimated its importance, her complaints persisted over the following weeks and she was hospitalized for investigation. The diagnostic workup revealed a metastatic gastric cancer. Gastric cancer is very rare in pregnancy, and therefore it may be left out of differential diagnosis by physicians. Diagnosis may be further delayed because of overlapping symptoms occurring during normal pregnancy (nausea, vomiting, and fatigue). All these factors may contribute to a very high mortality of this malignancy during pregnancy

Neural network-based image reconstruction in swept-source optical coherence tomography using undersampled spectral data

Optical Coherence Tomography (OCT) is a widely used non-invasive biomedical imaging modality that can rapidly provide volumetric images of samples. Here, we present a deep learning-based image reconstruction framework that can generate swept-source OCT (SS-OCT) images using undersampled spectral data, without any spatial aliasing artifacts. This neural network-based image reconstruction does not require any hardware changes to the optical set-up and can be easily integrated with existing swept-source or spectral domain OCT systems to reduce the amount of raw spectral data to be acquired. To show the efficacy of this framework, we trained and blindly tested a deep neural network using mouse embryo samples imaged by an SS-OCT system. Using 2-fold undersampled spectral data (i.e., 640 spectral points per A-line), the trained neural network can blindly reconstruct 512 A-lines in ~6.73 ms using a desktop computer, removing spatial aliasing artifacts due to spectral undersampling, also presenting a very good match to the images of the same samples, reconstructed using the full spectral OCT data (i.e., 1280 spectral points per A-line). We also successfully demonstrate that this framework can be further extended to process 3x undersampled spectral data per A-line, with some performance degradation in the reconstructed image quality compared to 2x spectral undersampling. This deep learning-enabled image reconstruction approach can be broadly used in various forms of spectral domain OCT systems, helping to increase their imaging speed without sacrificing image resolution and signal-to-noise ratio.Comment: 20 Pages, 7 Figures, 1 Tabl

New Mediterranean Biodiversity Records (July 2015)

The Collective Article ‘New Mediterranean Biodiversity Records’ of the Mediterranean Marine Science journal offers the means to publish biodiversity records in the Mediterranean Sea. The current article is divided in two parts, for records of native and alien species respectively. The new records of native species include: the neon flying squid Ommastrephes bartramii in Capri Island, Thyrrenian Sea; the bigeye thresher shark Alopias superciliosus in the Adriatic Sea; a juvenile basking shark Cetorhinus maximus caught off Piran (northern Adriatic); the deep-sea Messina rockfish Scorpaenodes arenai in the National Marine Park of Zakynthos (East Ionian Sea, Greece); and the oceanic puffer Lagocephalus lagocephalus in the Adriatic Sea.The new records of alien species include: the red algae Antithamnionella elegans and Palisada maris-rubri, found for the first time in Israel and Greece respectively; the green alga Codium parvulum reported from Turkey (Aegean Sea); the first record of the alien sea urchin Diadema setosum in Greece; the nudibranch Goniobranchus annulatus reported from South-Eastern Aegean Sea (Greece); the opisthobranch Melibe viridis found in Lebanon; the new records of the blue spotted cornetfish Fistularia commersonii in the Alicante coast (Eastern Spain); the alien fish Siganus luridus and Siganus rivulatus in Lipsi Island, Dodecanese (Greece); the first record of Stephanolepis diaspros from the Egadi Islands Marine Protected Area (western Sicily); a northward expansion of the alien pufferfish Torquigener flavimaculosus along the southeastern Aegean coasts of Turkey; and data on the occurrence of the Lessepsian immigrants Alepes djedaba, Lagocephalus sceleratus and Fistularia commersonii in Zakynthos Island (SE Ionian Sea, Greece)

Reactive Molecular Dynamics study on the first steps of DNA-damage by free hydroxyl radicals

We employ a large scale molecular simulation based on bond-order ReaxFF to simulate the chemical reaction and study the damage to a large fragment of DNA-molecule in the solution by ionizing radiation. We illustrate that the randomly distributed clusters of diatomic OH-radicals that are primary products of megavoltage ionizing radiation in water-based systems are the main source of hydrogen-abstraction as well as formation of carbonyl- and hydroxyl-groups in the sugar-moiety that create holes in the sugar-rings. These holes grow up slowly between DNA-bases and DNA-backbone and the damage collectively propagate to DNA single and double strand break.Comment: 6 pages and 8 figures. movies and simulations are available at: http://qmsimulator.wordpress.com

Roadmap on label-free super-resolution imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label-free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field

Roadmap on Label-Free Super-resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label-free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.Peer reviewe