Observation of a nanophase segregation in LiCl aqueous solutions from Transient Grating Experiments

Transient Grating experiments performed on supercooled LiCl, RH2O solutions with R>6 reveal the existence of a strong, short time, extra signal which superposes to the normal signal observed for the R=6 solution and other glass forming systems. This extra signal shows up below 190 K, its shape and the associated timescale depend only on temperature, while its intensity increases with R. We show that the origin of this signal is a phase separation between clusters with a low solute concentration and the remaining, more concentrated, solution. Our analysis demonstrates that these clusters have a nanometer size and a composition which are rather temperature independent, while increasing R simply increases the number of these clusters.Comment: 19 pages+ 8 figures+ 2 table

PM10 source apportionment applying PMF and chemical tracer analysis to ship-borne measurements in the Western Mediterranean

A PM10 sampling campaign was carried out on board the cruise ship Costa Concordia during three weeks in summer 2011. The ship route was Civitavecchia-Savona-Barcelona-Palma de Mallorca-Malta (Valletta)-Palermo-Civitavecchia. The PM10 composition was measured and utilized to identify and characterize the main PM10 sources along the ship route through receptor modelling, making use of the Positive Matrix Factorization (PMF) algorithm. A particular attention was given to the emissions related to heavy fuel oil combustion by ships, which is known to be also an important source of secondary sulphate aerosol. Five aerosol sources were resolved by the PMF analysis. The primary contribution of ship emissions to PM10 turned out to be (12 ± 4)%, while secondary ammonium sulphate contributed by (35 ± 5)%. Approximately, 60% of the total sulphate was identified as secondary aerosol while about 20% was attributed to heavy oil combustion in ship engines. The measured concentrations of methanesulphonic acid (MSA) indicated a relevant contribution to the observed sulphate loading by biogenic sulphate, formed by the atmospheric oxidation of dimethyl sulphide (DMS) emitted by marine phytoplankton

Ergodicity breaking in strong and network-forming glassy system

The temperature dependence of the non-ergodicity factor of vitreous GeO$_2$, $f_{q}(T)$, as deduced from elastic and quasi-elastic neutron scattering experiments, is analyzed. The data are collected in a wide range of temperatures from the glassy phase, up to the glass transition temperature, and well above into the undercooled liquid state. Notwithstanding the investigated system is classified as prototype of strong glass, it is found that the temperature- and the $q$-behavior of $f_{q}(T)$ follow some of the predictions of Mode Coupling Theory. The experimental data support the hypothesis of the existence of an ergodic to non-ergodic transition occurring also in network forming glassy systems

Angiographic demonstration of spontaneous diffuse three vessel coronary artery spasm

AbstractThe spontaneous occurrence of diffuse three vessel coronary artery spasm was documented during routine coronary angiography in three patients with a history of variant angina. Quantitative angiographic analysis of 18 arterial segments demonstrated that the mean luminal diameter of 1.47 mm during spasm increased to 2.47 mm after the administration of nitroglycerin (p < 0.0001). The underlying coronary arteries were normal or near normal.Although multivessel spasm has previously been considered to be uncommon and its spontaneous occurrence during angiography only rarely documented, these cases suggest that it may be more common than previously recognized. In addition to important diagnostic considerations, this phenomenon may have important implications regarding the pathophysiologic role of endothelium in coronary artery spasm

Estimating hidden fishing activity hotspots from vessel transmitted data

Monitoring fishery activity is essential for resource planning and guaranteeing fisheries sustainability. Large fishing vessels constantly and continuously communicate their positions via Automatic Identification System (AIS) or Vessel Monitoring Systems (VMSs). These systems can use radio or Global Positioning System (GPS) devices to transmit data. Processing and integrating these big data with other fisheries data allows for exploring the relations between socio-economic and ecosystem assets in marine areas, which is fundamental in fishery monitoring. In this context, estimating actual fishing activity from time series of AIS and VMS data would enhance the correct identification of fishing activity patterns and help assess regulations' effectiveness. However, these data might contain gaps because of technical issues such as limited coverage of the terrestrial receivers or saturated transmission bands. Other sources of data gaps are adverse meteorological conditions and voluntary switch-offs. Gaps may also include hidden (unreported) fishing activity whose quantification would improve actual fishing activity estimation. This paper presents a workflow for AIS/VMS big-data analysis that estimates potential unreported fishing activity hotspots in a marine area. The workflow uses a statistical spatial analysis over vessel speeds and coordinates and a multi-source data integration approach that can work on multiple areas and multiple analysis scales. Specifically, it (i) estimates fishing activity locations and rebuilds data gaps, (ii) estimates the potential unreported fishing hour distribution and the unreported-over-total ratio of fishing hours at a 0.01 degrees spatial resolution, (iii) identifies potential unreported fishing activity hotspots, (iv) extracts the stocks involved in these hotspots (using global-scale repositories of stock and species observation data) and raises an alert about their possible endangered, threatened, and protected (ETP) status. The workflow is also a free-to-use Web Service running on an open science-compliant cloud computing platform with a Web Processing Service (WPS) standard interface, allowing efficient big data processing. As a study case, we focussed on the Adriatic Sea. We reconstructed the monthly reported and potential unreported trawling activity in 2019, using terrestrial AIS data with a 5-min sampling period, containing similar to 50 million records transmitted by similar to 1,600 vessels. The results highlight that the unreported fishing activity hotspots especially impacted Italian coasts and some forbidden and protected areas. The potential unreported activity involved 33 stocks, four of which were ETP species in the basin. The extracted information agreed with expert studies, and the estimated trawling patterns agreed with those produced by the Global Fishing Watch

A feasibility assessment of a retrofit Molten Carbonate Fuel Cell coal-fired plant for flue gas CO₂ segregation

This work considers the use of a Molten Carbonate Fuel Cell (MCFC) system as a power generation and CO2 concentrator unit downstream of the coal burner of an existing production plant. In this way, the capability of MCFCs for CO2 segregation, which today is studied primarily in reference to large-scale plants, is applied to an intermediate-size plant highlighting the potential for MCFC use as a low energy method of carbon capture. A technical feasibility analysis was performed using an MCFC system-integrated model capable of determining steady-state performance across varying feed composition. The MCFC user model was implemented in Aspen Custom Modeler and integrated into the reference plant in Aspen Plus. The model considers electrochemical, thermal, and mass balance effects to simulate cell electrical and CO2 segregation performance. Results obtained suggest a specific energy requirement of 1.41 MJ kg CO2 121 significantly lower than seen in conventional Monoethanolamine (MEA) capture processes

Distance Estimation of an Unknown Person from a Portrait

We propose the first automated method for estimating distance from frontal pictures of unknown faces. Camera calibration is not necessary, nor is the reconstruction of a 3D representation of the shape of the head. Our method is based on estimating automatically the position of face and head landmarks in the image, and then using a regressor to estimate distance from such measurements. We collected and annotated a dataset of frontal portraits of 53 individuals spanning a number of attributes (sex, age, race, hair), each photographed from seven distances. We find that our proposed method outperforms humans performing the same task. We observe that different physiognomies will bias systematically the estimate of distance, i.e. some people look closer than others. We expire which landmarks are more important for this task