Energy efficiency of information transmission by electrically coupled neurons

The generation of spikes by neurons is energetically a costly process. This paper studies the consumption of energy and the information entropy in the signalling activity of a model neuron both when it is supposed isolated and when it is coupled to another neuron by an electrical synapse. The neuron has been modelled by a four dimensional Hindmarsh-Rose type kinetic model for which an energy function has been deduced. For the isolated neuron values of energy consumption and information entropy at different signalling regimes have been computed. For two neurons coupled by a gap junction we have analyzed the roles of the membrane and synapse in the contribution of the energy that is required for their organized signalling. Computational results are provided for cases of identical and nonidentical neurons coupled by unidirectional and bidirectional gap junctions. One relevant result is that there are values of the coupling strength at which the organized signalling of two neurons induced by the gap junction takes place at relatively low values of energy consumption and the ratio of mutual information to energy consumption is relatively high. Therefore, communicating at these coupling values could be energetically the most efficient option

Detecting natural disasters, damage, and incidents in the wild

Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emerged as a low-latency data source to quickly understand disaster situations. While most studies on social media are limited to text, images offer more information for understanding disaster and incident scenes. However, no large-scale image datasets for incident detection exists. In this work, we present the Incidents Dataset, which contains 446,684 images annotated by humans that cover 43 incidents across a variety of scenes. We employ a baseline classification model that mitigates false-positive errors and we perform image filtering experiments on millions of social media images from Flickr and Twitter. Through these experiments, we show how the Incidents Dataset can be used to detect images with incidents in the wild. Code, data, and models are available online at http://incidentsdataset.csail.mit.edu.Comment: ECCV 202

Choice of the initial antiretroviral treatment for HIV-positive individuals in the era of integrase inhibitors

BACKGROUND: We aimed to describe the most frequently prescribed initial antiretroviral therapy (ART) regimens in recent years in HIV-positive persons in the Cohort of the Spanish HIV/AIDS Research Network (CoRIS) and to investigate factors associated with the choice of each regimen. METHODS: We analyzed initial ART regimens prescribed in adults participating in CoRIS from 2014 to 2017. Only regimens prescribed in >5% of patients were considered. We used multivariable multinomial regression to estimate Relative Risk Ratios (RRRs) for the association between sociodemographic and clinical characteristics and the choice of the initial regimen. RESULTS: Among 2874 participants, abacavir(ABC)/lamivudine(3TC)/dolutegavir(DTG) was the most frequently prescribed regimen (32.1%), followed by tenofovir disoproxil fumarate (TDF)/emtricitabine (FTC)/elvitegravir(EVG)/cobicistat(COBI) (14.9%), TDF/FTC/rilpivirine (RPV) (14.0%), tenofovir alafenamide (TAF)/FTC/EVG/COBI (13.7%), TDF/FTC+DTG (10.0%), TDF/FTC+darunavir/ritonavir or darunavir/cobicistat (bDRV) (9.8%) and TDF/FTC+raltegravir (RAL) (5.6%). Compared with ABC/3TC/DTG, starting TDF/FTC/RPV was less likely in patients with CD4100.000 copies/mL. TDF/FTC+DTG was more frequent in those with CD4100.000 copies/mL. TDF/FTC+RAL and TDF/FTC+bDRV were also more frequent among patients with CD4<200 cells//muL and with transmission categories other than men who have sex with men. Compared with ABC/3TC/DTG, the prescription of other initial ART regimens decreased from 2014-2015 to 2016-2017 with the exception of TDF/FTC+DTG. Differences in the choice of the initial ART regimen were observed by hospitals' location. CONCLUSIONS: The choice of initial ART regimens is consistent with Spanish guidelines' recommendations, but is also clearly influenced by physician's perception based on patient's clinical and sociodemographic variables and by the prescribing hospital location

UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level

UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level

Synergistic Exploitation of Geoinformation Methods for Post-earthquake 3D Mapping and Damage Assessment

This paper presents a methodological framework, which establishes links among the: i. 3D mapping, ii. 3D model creation and iii. damage classification grades of masonry buildings by European Macroseismic Scale-98 and the application of geoinformation methods towards 3D mapping and damage assessment after a catastrophic earthquake event. We explore the synergistic exploitation of a Real Time Kinematics system, terrestrial photogrammetry, Unmanned Aircraft Systems and terrestrial laser scanner for collecting accurate and high-resolution geospatial information. The proposed workflow was applied at the catastrophic earthquake of June 12th, 2017 on the traditional settlement of Vrisa on the island of Lesvos, Greece. The Structure from Motion method has been applied on the high-resolution terrestrial and aerial photographs, for producing accurate and very detailed 3D point clouds of the damaged buildings of the Vrisa settlement. Additionally, two Orthophoto maps and two Digital Surface Models have been created, with a spatial resolution of 5 cm and 3 cm, respectively. The first orthophoto map has been created just one day after the earthquake, while the second one, a month later. The significant advantages of the proposed methodology are: (a) the production of reliable and accurate 2D and 3D information at both village and building scales, (b) the ability to support scientists during building damage assessment phase and (c) the proposed damage documentation provides all the appropriate information which can augment all experts and stakeholders, national and local organizations focusing on the post-earthquake management and reconstruction processes of the Vrisa traditional village

The Polarimetric and Helioseismic Imager on Solar Orbiter

Aims. This paper describes the Polarimetric and Helioseismic Imager on the Solar Orbiter mission (SO/PHI), the first magnetograph and helioseismology instrument to observe the Sun from outside the Sun-Earth line. It is the key instrument meant to address the top-level science question: How does the solar dynamo work and drive connections between the Sun and the heliosphere? SO/PHI will also play an important role in answering the other top-level science questions of Solar Orbiter, while hosting the potential of a rich return in further science. Methods. SO/PHI measures the Zeeman effect and the Doppler shift in the Fe