Pre-travel consultations quality criteria: a Delphi consensus

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Properties and Biodegradability of Thermoplastic Starch Obtained from Granular Starches Grafted with Polycaprolactone

Granular starches grafted with polycaprolactone (St-g-PCL) were obtained using N-methylimidazole (NMI) as a catalyst. The effect of the starch/monomer ratio and catalyst content was studied to obtain different levels of grafted PCL. The highest grafting percentage (76%) and addition (43%) were achieved for reactions with a starch/monomer ratio of 50/50 and 25% catalyst. The grafting of PCL on the starch granule was verified by the emergence of the carbonyl group in the FTIR spectra and the increased diameter of the grafted starch granule. Thermoplastic starch from ungrafted starch (TPS) and grafted starch (TPGS) was obtained by mixing ungrafted or grafted starch granules with water, glycerol, or sorbitol in a mixer. TPS and TPGS behave as plastic materials, and their mechanical properties depend on the type of plasticizer used. Materials with glycerol as the plasticizer exhibited less rigidity. The presence of starch-g-PCL results in a dramatic increase in the elongation of the thermoplastic material. The starch present in the TPS or TPGS was completely biodegraded while the grafted PCL was partially biodegraded after the enzymatic degradation of the materials

Airborne Prokaryote and Virus Abundance Over the Red Sea

Aeolian dust exerts a considerable influence on atmospheric and oceanic conditions negatively impacting human health, particularly in arid and semi-arid regions like Saudi Arabia. Aeolian dust is often characterized by its mineral and chemical composition; however, there is a microbiological component of natural aerosols that has received comparatively little attention. Moreover, the amount of materials suspended in the atmosphere is highly variable from day to day. Thus, understanding the variability of atmospheric dust loads and suspended microbes throughout the year is essential to clarify the possible effects of dust on the Red Sea ecosystem. Here, we present the first estimates of dust and microbial loads at a coastal site on the Red Sea over a 2-year period, supplemented with measurements from dust samples collected along the Red Sea basin in offshore waters. Weekly average dust loads from a coastal site on the Red Sea ranged from 4.6 to 646.11 μg m−3, while the abundance of airborne prokaryotic cells and viral-like particles (VLPs) ranged from 77,967 to 1,203,792 cells m−3 and from 69,615 to 3,104,758 particles m−3, respectively. To the best of our knowledge, these are the first estimates of airborne microbial abundance in this region. The elevated concentrations of resuspended dust particles and suspended microbes found in the air indicate that airborne microbes may potentially have a large impact on human health and on the Red Sea ecosystem.En prens

Stochastic Electrical Detection of Single Ion-Gated Semiconducting Polymers

Semiconducting polymer chains constitute the building blocks for a wide range of electronic materials and devices. However, most of their electrical characteristics at the single-molecule level have received little attention. Elucidating these properties can help understanding performance limits and enable new applications. Here, coupled ionic–electronic charge transport is exploited to measure the quasi-1D electrical current through long single conjugated polymer chains as they form transient contacts with electrodes separated by ≈10 nm. Fluctuations between internal conformations of the individual polymers are resolved as abrupt, multilevel switches in the electrical current. This behavior is consistent with the theoretical simulations based on the worm-like-chain (WLC) model for semiflexible polymers. In addition to probing the intrinsic properties of single semiconducting polymer chains, the results provide an unprecedented window into the dynamics of random-coil polymers and enable the use of semiconducting polymers as electrical labels for single-molecule (bio)sensing assays.</p

Efficient co-templating roles of amines and amides admixed with alkylammonium salts for the stabilisation of new AlPO4-n topologies

Two different aluminophosphate structures were synthesised in aqueous media using as main template methylamine (MA), directly added, or generated in situ from methylformamide (MF). Both involve novel AlPO4-n topologies that undergo structural transformations upon template removal, yielding above 350°C microporous thermostable materials with interesting properties. Tetraalkylammonium (TEA) cations were used optionally as co-templates along with MA. Only non protonated MA was found incorporated into the pore volume of both structures, in relatively strong interaction with the framework oxygens. TEA appeared to stabilise one of the phases at defined stages of nucleation and/or growth processes, without playing any specific structure-directing role

Optimal network reconfiguration for congestion management optimization in active distribution networks

Recently, the distribution networks are working close to their physical device limits. When congestion takes place, distributed switches can be controlled to change their status in order to find a new optimal network configuration that solves that congestion. In this paper, a new methodology for congestion management by means of distributed network reconfiguration is presented. Switches and controllable voltage units such as PV units were used in the optimization process. The optimization process is guided by a weighted objective function that takes into account real power losses as well as operational limits of the power system under study. The methodology is tested in an Italian real power distribution system.The research leading to these results has received funding from the European Union seventh framework program FP7-SMARTCITIES-2013 under grant agreement 608860 IDE4L – Ideal grid for all

Momentum-resolved resonant inelastic soft X-ray scattering (qRIXS) endstation at the ALS

A momentum resolved resonant inelastic X-ray scattering (qRIXS) experimental station with continuously rotatable spectrometers and parallel detection is designed to operate at different beamlines at synchrotron and free electron laser (FEL) facilities. This endstation, currently located at the Advanced Light Source (ALS), has five emission ports on the experimental chamber for mounting the high-throughput modular soft X-ray spectrometers (MXS) [24]. Coupled to the rotation from the supporting hexapod, the scattered X-rays from 27.5° (forward scattering) to 152.5° (backward scattering) relative to the incident photon beam can be recorded, enabling the momentum-resolved RIXS spectroscopy. The components of this endstation are described in details, and the preliminary RIXS measurements on highly oriented pyrolytic graphite (HOPG) reveal the low energy vibronic excitations from the strong electron-phonon coupling at C K edge around σ* band. The grating upgrade option to enhance the performance at low photon energies is presented and the potential of this spectroscopy is discussed in summary

Charged quark stars in metric f(R)f(R) gravity

We provide the modified TOV equations for the hydrostatic equilibrium of charged compact stars within the metric $f(R)$ gravitational background. We adopt the MIT bag model EoS for the dense matter and assume a charge distribution where the electric charge density $\rho_{\rm ch}$ is proportional to the standard energy density $\rho$. Using the Starobinsky model, we explore the role of the $\alpha R^2$ term, where $\alpha$ is a free constant and $R$ the Ricci scalar, on the global properties of charged stars such as radius, mass and total charge. We present the dependence of the structure of the star for several values of $\alpha$ and for different values of the constant parameter $\beta\equiv \rho_{\rm ch}/\rho$. Remarkably, we find that the radius decreases with respect to its GR value for low central densities, while the opposite occurs in the high-central-density region. The mass measured at the surface always decreases and the maximum-total charge undergoes a substantial increase as the parameter $\alpha$ increases. We also illustrate the variations of the asymptotic mass as a consequence of the electric charge and the extra quadratic term.Comment: 11 pages, 7 figures. To appear in JCA

An ontology for failure interpretation in automated planning and execution

This is a post-peer-review, pre-copyedit version of an article published in ROBOT - Iberian Robotics Conference. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-35990-4_31”.Autonomous indoor robots are supposed to accomplish tasks, like serve a cup, which involve manipulation actions, where task and motion planning levels are coupled. In both planning levels and execution phase, several source of failures can occur. In this paper, an interpretation ontology covering several sources of failures in automated planning and also during the execution phases is introduced with the purpose of working the planning more informed and the execution prepared for recovery. The proposed failure interpretation ontological module covers: (1) geometric failures, that may appear when e.g. the robot can not reach to grasp/place an object, there is no free-collision path or there is no feasible Inverse Kinematic (IK) solution. (2) hardware related failures that may appear when e.g. the robot in a real environment requires to be re-calibrated (gripper or arm), or it is sent to a non-reachable configuration. (3) software agent related failures, that may appear when e.g. the robot has software components that fail like when an algorithm is not able to extract the proper features. The paper describes the concepts and the implementation of failure interpretation ontology in several foundations like DUL and SUMO, and presents an example showing different situations in planning demonstrating the range of information the framework can provide for autonomous robotsPeer ReviewedPostprint (author's final draft

Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A \emph{shapelet} is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselve