Monitoring the Agung (Indonesia) ash plume of November 2017 by means of infrared Himawari 8 data

The Agung volcano (Bali; Indonesia) erupted in later November 2017 after several years of quiescence. Because of ash emissions, hundreds of flights were cancelled, causing an important air traffic disruption in Indonesia. We investigate those ash emissions from space by applying the RSTASH algorithm for the first time to Himawari-8 data and using an ad hoc implementation scheme to reduce the time of the elaboration processes. Himawari-8 is a new generation Japanese geostationary meteorological satellite, whose AHI (Advanced Himawari Imager) sensor offers improved features, in terms of spectral, spatial and temporal resolution, in comparison with the previous imagers of the MTSAT (Multi-Functional Transport Satellite) series. Those features should guarantee further improvements in monitoring rapidly evolving weather/environmental phenomena. Results of this work show that RSTASH was capable of successfully detecting and tracking the Agung ash plume, despite some limitations (e.g., underestimation of ash coverage under certain conditions; generation of residual artefacts). Moreover, estimates of ash cloud-top height indicate that the monitored plume extended up to an altitude of about 9.3 km above sea level during the period 25 November at 21:10 UTC-26 November at 00:50 UTC. The study demonstrates that RSTASH may give a useful contribution for the operational monitoring of ash clouds over East Asia and the Western Pacific region, well exploiting the 10 min temporal resolution and the spectral features of the Himawari-8 data

The FoodCast research image database (FRIDa)

In recent years we have witnessed an increasing interest in food processing and eating behaviors. This is probably due to several reasons. The biological relevance of food choices, the complexity of the food-rich environment in which we presently live (making food-intake regulation difficult), and the increasing health care cost due to illness associated with food (food hazards, food contamination, and aberrant food-intake). Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for non-commercial purposes to independent researchers who aim at developing their own research program. The FoodCast Research Image Database (FRIDa) we present here includes 877 images belonging to eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., french fries), rotten-food (e.g., moldy banana), natural-non-food items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport). FRIDa has been validated on a sample of healthy participants (N = 73) on standard variables (e.g., valence, familiarity, etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power, etc.). FRIDa is a well-controlled, flexible, validated, and freely available (http://foodcast.sissa.it/neuroscience/) tool for researchers in a wide range of academic fields and industry. \ua9 2013 Foroni, Pergola, Argiris and Rumiati

Advanced Satellite Technique for Volcanic Activity Monitoring and Early Warning.

Nowadays, satellite remote sensing is an important tool for volcanic activity monitoring, thanks to several operational satellite platforms providing data everywhere with high observational frequencies and generally at low cost. Among different techniques available, an advanced satellite method, named RST (Robust Satellite Technique). based on the multitemporal analysis of satellite data, has shown a high capability in volcanic activity monitoring. This approach has proved capable of identifyimg and tracking volcanic ash Cloud and of correctly detecting and monitoring volcanic thermal anomalies. This paper analyzes some recent results, obtained applying this approach to the last eruptive events of Mt. Etna using both polar and geostationary satellites. In particular, for the first time, this approach is implemented on the present geostationary platform MSG-SEVIRI, with 15 min of temporal resolution. Preliminary results, together with a future potential of this implementation, are shown and discussed. Moreover, a differential RST index in time domain is also proposed for near real-time application, as a possible contribution to the development of an efficient early warning satellite system for volcanic hazard mitigation

Advanced satellite technique for volcanic activity monitoring and early warning

Nowadays, satellite remote sensing is an important tool for volcanic activity monitoring, thanks to several operational satellite platforms providing data everywhere with high observational frequencies and generally at low cost. Among different techniques available, an advanced satellite method, named RST (Robust Satellite Technique), based on the multitemporal analysis of satellite data, has shown a high capability in volcanic activity monitoring. This approach has proved capable of identifying and tracking volcanic ash cloud and of correctly detecting and monitoring volcanic thermal anomalies. This paper analyzes some recent results, obtained applying this approach to the last eruptive events of Mt. Etna using both polar and geostationary satellites. In particular, for the first time, this approach is implemented on the present geostationary platform MSG-SEVIRI, with 15 min of temporal resolution. Preliminary results, together with a future potential of this implementation, are shown and discussed. Moreover, a differential RST index in time domain is also proposed for near real-time application, as a possible contribution to the development of an efficient early warning satellite system for volcanic hazard mitigation

Cyclooxygenase-2 inhibitors. 1,5-diarylpyrrol-3-acetic esters with enhanced inhibitory activity toward cyclooxygenase-2 and improved cyclooxygenase-2/cyclooxygenase-1 selectivity.

he important role of cyclooxygenase-2 (COX-2) in the pathogenesis of inflammation and side effect limitations of current COX-2 inhibitor drugs illustrates a need for the design of new compounds based on alternative structural templates. We previously reported a set of substituted 1,5-diarylpyrrole derivatives, along with their inhibitory activity toward COX enzymes. Several compounds proved to be highly selective COX-2 inhibitors and their affinity data were rationalized through docking simulations. In this paper, we describe the synthesis of new 1,5-diarylpyrrole derivatives that were assayed for their in vitro inhibitory effects toward COX isozymes. Among them, the ethyl-2-methyl-5-[4-(methylsulfonyl)phenyl]-1-[3-fluorophenyl]-1H-pyrrol-3- acetate (1d), which was the most potent and COX-2 selective compound, also showed a very interesting in vivo anti-inflammatory and analgesic activity, laying the foundations for developing new lead compounds that could be effective agents in the armamentarium for the management of inflammation and pain

Volcanic ash cloud detection from space: a preliminary comparison between RST approach and water vapour corrected BTD procedure

Volcanic eruptions can inject large amounts (Tg) of gas and particles into the troposphere and, sometimes, into the stratosphere. Besides the main gases (H2O, CO2 , SO2 and HCl), volcanic clouds contain a mix of silicate ash particles in the size range 0.1μm to mm or larger. Interest in the ash presence detection is high in particular because it represents a serious hazard for air traffic. Particles with dimension of several millimeters can damage the aircraft structure (windows, wings, ailerons), while particles less than 10μm may be extremely dangerous for the jet engines and are undetectable by the pilots during night or in low visibility conditions. Satellite data are useful for measuring volcanic clouds because of the large vertical range of these emissions and their likely large horizontal spread. Moreover, since volcanoes are globally distributed and inherently dangerous, satellite measurements offer a practical and safe platform from which to make observations. Two different techniques used to detect volcanic clouds from satellite data are considered here for a preliminary comparison, with possible implications on quantitative retrievals of plume parameters. In particular, the Robust Satellite Techniques (RST) approach and a water vapour corrected version of the Brightness Temperature Difference (BTD) procedure, will be compared. The RST approach is based on the multi-temporal analysis of historical, long-term satellite records, devoted to a former characterization of the measured signal, in terms of expected value and natural variability and a further recognition of signal anomalies by an automatic, unsupervised change detection step. The BTD method is based on the difference between the brightness temperature measured in two channels centered around 11 and 12 mm. To take into account the atmospheric water vapour differential absorption in the 11–12 μm spectral range that tends to reduce (and in some cases completely mask) the BTD signal, a water vapor correction procedure, based on measured or synthetic atmospheric profiles, has been applied. Results independently achieved by both methods during recent Mt. Etna eruptions are presented, compared and discussed also in terms of further implications for quantitative retrievals of plume parameters

Assessing the potential of <i>SWVI</i> (Soil Wetness Variation Index) for hydrological risk monitoring by means of satellite microwave observations

International audienceIn the last years satellite remote sensing applications in hydrology have considerably progressed. A new multi-temporal satellite data-analysis approach has been recently suggested in order to estimate space-time changes of geophysical parameters possibly related to the increase of environmental and hydro-geological hazards. Such an approach has been already used both for flooded area mapping (using AVHRR data) and for soil wetness index estimation (using AMSU data). In this work, a preliminary sensitivity analysis of the proposed Soil Wetness Variation Index (SWVI) is made in the case of low intensity meteorological events by the comparison with hydrological (precipitation) data. This analysis, as a first step of a more complex work in progress, is targeted to a first evaluation of the reliability of the SWVI in describing soil response to precipitations of different duration and intensity