Thermochemical Investigations in the System Cadmium-Praseodymium Relevant for Pyrometallurgical Fuel Reprocessing

Vapor pressure measurements, in terms of a (non-)isothermal isopiestic method, were carried out in the system Cd-Pr between 749 K and 1067 K (476 °C and 794 °C). Thermodynamic activities of cadmium as a function of temperature were obtained directly for the composition ranging from 50.0 to 85.7 at. pct Cd. From these results, partial molar enthalpies of mixing of Cd were derived for the corresponding composition range. The activity values of Cd were converted to an average sample temperature of 823 K (550 °C) by applying an integrated form of the Gibbs–Helmholtz equation. These data indicate that Cd₂Pr and Cd₅₈Pr₁₃ are probably the most stable intermetallic compounds in this system. Using an activity value of Pr from the literature as integration constant, Gibbs–Duhem integration was performed, and integral Gibbs energies are presented at 823 K (550 °C), referred to Cd(l) and α-Pr(s). Gibbs energies of formation at the stoichiometric compositions of the phases Cd₆Pr, Cd₅₈Pr₁₃, Cd₄₅Pr₁₁, Cd₃Pr, and Cd₂Pr were determined to be about ?18.8, ?23.5, ?24.8, ?28.7, and ?33.8 kJ g-atom^?1 at 823 K (550 °C), respectively.     

Efficient document image binarization using heterogeneous computing and parameter tuning

In the context of historical document analysis, image binarization is a first important step, which separates foreground from background, despite common image degradations, such as faded ink, stains, or bleed-through. Fast binarization has great significance when analyzing vast archives of document images, since even small inefficiencies can quickly accumulate to years of wasted execution time. Therefore, efficient binarization is especially relevant to companies and government institutions, who want to analyze their large collections of document images. The main challenge with this is to speed up the execution performance without affecting the binarization performance. We modify a state-of-the-art binarization algorithm and achieve on average a 3.5 times faster execution performance by correctly mapping this algorithm to a heterogeneous platform, consisting of a CPU and a GPU. Our proposed parameter tuning algorithm additionally improves the execution time for parameter tuning by a factor of 1.7, compared to previous parameter tuning algorithms. We see that for the chosen algorithm, machine learning-based parameter tuning improves the execution performance more than heterogeneous computing, when comparing absolute execution times.

     

Hydrogenation behavior on 30 nm vanadium thin films with two different adhesion conditions

The influence of a thin polycarbonate de-adhesion layer on the hydrogen concentration is studied on 30 nm vanadium films deposited on glass substrates, using electrochemical hydrogenography in an optical microscopy and scanning tunneling microscopy. It is shown that the optical reflection provides information about the de-adhesion morphology (buckles) while the optical transmission signal gives information about concentration and film thickness changes. Artificially patterned samples allow simultaneous studying adhered and de-adhered film parts, for similar mean concentrations. The optical data clearly show a different hydrogen behavior of the two parts. Data interpretation suggests higher local hydrogen content in the adhered film parts than for the detached films parts. Strong changes in the optical transmission of the adhered film parts can be attributed to strong morphological changes at the film surface. These changes are mainly attributed to grain sliding processes in the vanadium film.     

Discovery of Heterocyclic Nonacetamide Synaptic Vesicle Protein 2A (SV2A) Ligands with Single‐Digit Nanomolar Potency: Opening Avenues towards the First SV2A Positron Emission Tomography (PET) Ligands

The role of the synaptic vesicle protein 2A (SV2A) protein, target of the antiepileptic drug levetiracetam, is still mostly unknown. Considering its potential to provide in vivo functional insights into the role of SV2A in epileptic patients, the development of an SV2A positron emission tomography (PET) tracer has been undertaken. Using a 3D pharmacophore model based on close analogues of levetiracetam, we report the rationale design of three heterocyclic non‐acetamide lead compounds, UCB‐A, UCB‐H and UCB‐J, the first single‐digit nanomolar SV2A ligands with suitable properties for development as PET tracers.     

A methodology to benchmark flexible payload architectures in a megaconstellation use case

This paper proposes a methodology to benchmark satellite payload architectures and find the optimal trade‐offs between high flexibility and low complexity. High flexibility would enable the satellite to adapt to various distributions of user terminals on the ground and fulfill the data rate demand of these users. Besides, low complexity is required to keep satellite networks competitive in the context of emerging 5G networks. To estimate the flexibility of a payload, an indicator to characterize the non‐uniformity of user distributions is proposed. Each benchmarked payload may be characterized by a graph relating the throughput to this parameter further denoted . The payload provides the same throughput trends for different scenarios of user distributions with the same parameter. As a consequence, the average capacity of the system may be estimated by (a) calculating the probability distribution of over the orbit and (b) integrating the throughput based on this payload response. It thus results in a straightforward way for benchmarking payloads directly on an estimation of the averaged capacity, accounting for the user distribution over the earth. A simulation platform has been developed to characterize the payload throughput including the implementation of a resource allocation algorithm that accounts for constraints of various payloads. Using this definition and the developed tool, we benchmark a bent‐pipe architecture, a beam hopping architecture and a hybrid beam‐steering architecture for a LEO megaconstellation use case. The methodology showcases the interest for investigating different payload architectures depending on realistic traffic scenario analysis.