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Towards stable nickel catalysts for selective hydrogenation of biomass-based BHMF into THFDM
Full text linkSelective transformation of BHMF (2,5-bis(hydroxymethyl)furan) to THFDM (tetrahydrofuran-2,5-dimethanol) over a variety of structured Ni/Sx-Z1−x catalysts was investigated. The effects of support, Ni loading, solvent, temperature, pressure, and particle size on the conversion and selectivity were studied. Among them, the 10 wt% Ni catalyst supported on the SiO2:ZrO2 weight ratio of 90:10 (10NiS90Z10) exhibits the best performance in terms of BHMF conversion and THFDM selectivity. Its good performance was attributed to its well-balanced properties, that depend upon the ZrO2 content of the support in combination with SiO2, the active Ni sites-support interaction, and acidity/basicity ratio of each catalyst resulting in different Ni dispersions. Importantly, the 10NiS90Z10 catalyst showed a stable selectivity to THFDM (>94%), with 99.4% conversion of BHMF during 2 h reaction time. Poor catalytic activity resulted from excessive ZrO2 content (>10 wt%). The structural, textural, and acidity properties of NiSi100−y-Zry catalysts, tuned by selectively varying the Ni amount from 5 to 15 wt%, were critically investigated using numerous material characterization techniques. Catalyst recycling experiments revealed that the catalyst could be recycled several times without any measurable loss of catalytic activity
Combining rule- and SMT-based reasoning for verifying floating-point Java programs in KeY
Full text linkDeductive verification has been successful in verifying interesting properties of real-world programs. One notable gap is the limited support for floating-point reasoning. This is unfortunate, as floating-point arithmetic is particularly unintuitive to reason about due to rounding as well as the presence of the special values infinity and ‘Not a Number’ (NaN). In this article, we present the first floating-point support in a deductive verification tool for the Java programming language. Our support in the KeY verifier handles floating-point arithmetics, transcendental functions, and potentially rounding-type casts. We achieve this with a combination of delegation to external SMT solvers on the one hand, and KeY-internal, rule-based reasoning on the other hand, exploiting the complementary strengths of both worlds. We evaluate this integration on new benchmarks and show that this approach is powerful enough to prove the absence of floating-point special values—often a prerequisite for correct programs—as well as functional properties, for realistic benchmarks
Detection of magnetic fields in the circumgalactic medium of nearby galaxies using Faraday rotation
Full text linkContext. The existence of magnetic fields in the circumgalactic medium (CGM) is largely unconstrained. Their detection is important as magnetic fields can have a significant impact on the evolution of the CGM, and, in turn, the fields can serve as tracers for dynamical processes in the CGM. Aims. Using the Faraday rotation of polarised background sources, we aim to detect a possible excess of the rotation measure in the surrounding area of nearby galaxies. Methods. We used 2461 residual rotation measures (RRMs) observed with the LOw Frequency ARray (LOFAR), where the foreground contribution from the Milky Way is subtracted. The RRMs were then studied around a subset of 183 nearby galaxies that was selected by apparent B-band magnitude. Results. We find that, in general, the RRMs show no significant excess for small impact parameters (i.e., the perpendicular distance to the line of sight). However, if we only consider galaxies at higher inclination angles and sightlines that pass close to the minor axis of the galaxies, we find significant excess at impact parameters of less than 100 kpc. The excess in |RRM| is 3.7 rad m-2 with an uncertainty between \ub10.9 rad m-2 and \ub11.3 rad m-2 depending on the statistical properties of the background (2.8σ - 4.1σ). With electron densities of ∼10-4 cm-3, this suggests magnetic field strengths of a few tenths of a microgauss. Conclusions. Our results suggest a slow decrease in the magnetic field strength with distance from the galactic disc, as expected if the CGM is magnetised by galactic winds and outflows
Biomarkers of seafood intake during pregnancy – Pollutants versus fatty acids and micronutrients
Full text linkIntake of fish and seafood during pregnancy may have certain beneficial effects on fetal development, but measurement of intake using questionnaires is unreliable. Here, we assessed several candidate biomarkers of seafood intake, including long-chain omega 3 fatty acids (n-3 LCPUFA), selenium, iodine, methylmercury, and different arsenic compounds, in 549 pregnant women (gestational week 29) in the prospective birth cohort NICE (Nutritional impact on Immunological maturation during Childhood in relation to the Environment). Proportions of the fatty acids eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) in erythrocytes were measured using gas chromatography with flame ionization detector. Selenium was measured in blood plasma and erythrocytes, mercury and arsenic in erythrocytes, and iodine and several arsenic compounds in urine, using inductively coupled plasma mass spectrometry, arsenic compounds after first being separated by ion exchange high-performance liquid chromatography (HPLC). Each biomarker was related to intake of total seafood and to intake of fatty and lean fish, and shellfish in third trimester, estimated from a semi-quantitative food frequency questionnaire filled out in gestational week 34. The pregnant women reported a median total seafood intake of 184 g/week (5th-95th percentiles: 34–465 g/week). This intake correlated most strongly with erythrocyte mercury concentrations (rho = 0.49, p < 0.001), consisting essentially of methylmercury, followed by total arsenic in erythrocytes (rho = 0.34, p < 0.001), and arsenobetaine in urine (rho = 0.33, p < 0.001), the main form of urinary arsenic. These biomarkers correlated well with intake of both fatty fish, lean fish, and shellfish. Erythrocyte DHA and plasma selenium correlated, although weakly, mainly with fatty fish (rho = 0.25 and 0.22, respectively, both p < 0.001). In conclusion, elevated concentrations of erythrocyte mercury and urinary arsenobetaine can be useful indicators of seafood intake, more so than the n-3 LCPUFAs. However, the relative importance of the biomarkers may differ depending on the type and amount of seafood consumed
Radiolytic degradation of dimethyl telluride in aqueous solutions
Full text linkThe formation of volatile radioactive species is a major concern in severe nuclear reactor accident scenarios. Release of radioactive material to the environment is highly governed by the volatility of the species and therefore it its crucial to understand the behavior of any such species during the accident and the days and weeks following. One of the volatile, yet highly understudied fission products is tellurium. Although tellurium has been released in significant amounts during the major nuclear accidents that have occurred, the knowledge of the behavior is still lacking. Here we present results on the radiolysis of dimethyl telluride, a highly volatile species shown to form in accident conditions. The behavior of dimethyl telluride was investigated under gamma irradiation in various aqueous solutions and conditions representative to severe nuclear reactor accident conditions. The results suggest that dimethyl telluride is relatively stable towards gamma irradiation and its degradation is highly affected by the amount of dissolved oxygen and competing species. It was found that dimethyl telluride degrades via oxidative processes by reacting with oxidizing radiolysis products e.g. •OH, O.-. In the absence of oxygen, several volatile telluride dimers were observed. The results presented here increase the interest in organic tellurides in severe accident conditions and highlight the need for further investigation of the re-volatilization and mitigation of volatile tellurium species
Utilization of convolutional neural networks for HI source finding: Team FORSKA-Sweden approach to SKA Data Challenge 2
Full text linkContext. The future deployment of the Square Kilometer Array (SKA) will lead to a massive influx of astronomical data and the automatic detection and characterization of sources will therefore prove crucial in utilizing its full potential. Aims. We examine how existing astronomical knowledge and tools can be utilized in a machine learning-based pipeline to find 3D spectral line sources. Methods. We present a source-finding pipeline designed to detect 21-cm emission from galaxies that provides the second-best submission of SKA Science Data Challenge 2. The first pipeline step was galaxy segmentation, which consisted of a convolutional neural network (CNN) that took an HI cube as input and output a binary mask to separate galaxy and background voxels. The CNN was trained to output a target mask algorithmically constructed from the underlying source catalog of the simulation. For each source in the catalog, its listed properties were used to mask the voxels in its neighborhood that capture plausible signal distributions of the galaxy. To make the training more efficient, regions containing galaxies were oversampled compared to the background regions. In the subsequent source characterization step, the final source catalog was generated by the merging and dilation modules of the existing source-finding software SOFIA, and some complementary calculations, with the CNN-generated mask as input. To cope with the large size of HI cubes while also allowing for deployment on various computational resources, the pipeline was implemented with flexible and configurable memory usage. Results. We show that once the segmentation CNN has been trained, the performance can be fine-Tuned by adjusting the parameters involved in producing the catalog from the mask. Using different sets of parameter values offers a trade-off between completeness and reliability
Enabling Factors and Durations Data Analytics for Dynamic Freight Parking Limits
Full text linkFreight parking operations occur amid conflicting conditions of public space scarcity, competition with other users, and the inefficient management of loading zones (LZ) at cities’ curbside. The dynamic nature of freight operations, and the static LZ provision and regulation, accentuate these conflicting conditions at specific peak times. This generates supply–demand mismatches of parking infrastructure. These mismatches have motivated the development of Smart LZ that bring together technology, parking infrastructure, and data analytics to allocate space and define dynamic duration limits based on users’ needs. Although the dynamic duration limits unlock the possibility of a responsive LZ management, there is a narrow understanding of factors and analytical tools that support their definition. Therefore, the aim of this paper is twofold. Firstly, to identify factors for enabling dynamic parking durations policies. Secondly, to assess data analytics tools that estimate freight parking durations and LZ occupation levels based on operational and locational features. Semi-structured interviews and focus group analyses showed that public space use assessment, parking demand estimation, enforcement capabilities, and data sharing strategies are the most relevant factors when defining dynamic parking limits. This paper used quantitative models to assess different analytical tools that study LZ occupation and parking durations using tracked freight parking data from the City of Vic (Spain). CatBoost outperformed other machine learning (ML) algorithms and queuing models in estimating LZ occupation and parking durations. This paper contributes to the freight parking field by understanding how data analytics support dynamic parking limits definition, enabling responsive curbside management
The complex organic molecular content in the L1517B starless core
Full text linkRecent observations of the pre-stellar core L1544 and the younger starless core L1498 have revealed that complex organic molecules (COMs) are enhanced in the gas phase towards their outer and intermediate-density shells. Our goal is to determine the level of chemical complexity towards the starless core L1517B, which seems younger than L1498, and compare it with the other two previously studied cores to see if there is a chemical evolution within the cores. We have carried out 3 mm high-sensitivity observations towards two positions in the L1517B starless core: the core\u27s centre and the position where the methanol emission peaks (at a distance of similar to 5000 au from the core\u27s centre). Our observations reveal that a lower number of COMs and COM precursors are detected in L1517B with respect to L1498 and L1544, and also show lower abundances. Besides methanol, we only detected CH3O, H2CCO, CH3CHO, CH3CN, CH3NC, HCCCN, and HCCNC. Their measured abundances are similar to 3 times larger towards the methanol peak than towards the core\u27s centre, mimicking the behaviour found towards the more evolved cores L1544 and L1498. We propose that the differences in the chemical complexity observed between the three studied starless cores are a consequence of their evolution, with L1517B being the less evolved one, followed by L1498 and L1544. Chemical complexity in these cores seems to increase over time, with N-bearing molecules forming first and O-bearing COMs forming at a later stage as a result of the catastrophic depletion of CO
Space-Dependent Calculation of the Multiplicity Moments for Shells With the Inclusion of Scattering
Full text linkIn recent work, we extended the methodology of multiplicity counting in nuclear safeguards by elaborating the one-speed stochastic transport theory of the calculation of the so-called multiplicity moments, i.e., the factorial moments of the number of neutrons emitted from a fissile item, following a source event from an internal neutron source [spontaneous fission and ((Formula presented.)) reactions]. Calculations were made for solid spheres and cylinders, with the source being homogeneously distributed within the item. Recent measurements of the Rocky Flats Shells during the Measurement of Uranium Subcritical and Critical (MUSIC) campaign conducted by Los Alamos National Laboratory and assisted by the University of Michigan inspired us to extend the model to spherical shell geometry with a point source in the middle of the central cavity. Comparison of the calculated results with the experimental ones indicated that accounting for fission as the only neutron reaction (the standard procedure in the point model, adapted also in our work so far) was not sufficient for reaching good agreement with measurements. The model was therefore extended to include elastic scattering into the one-speed formalism, whereas the effect of inelastic scattering was accounted for in an empirical way. After these extensions, good agreement was found between the calculated and the measured values. The paper describes the extension of the theory and provides concrete quantitative results
Influence of stent-induced vessel deformation on hemodynamic feature of bloodstream inside ICA aneurysms
Full text linkOne of the effective treatment options for intracranial aneurysms is stent-assisted coiling. Though, previous works have demonstrated that stent usage would result in the deformation of the local vasculature. The effect of simple stent on the blood hemodynamics is still uncertain. In this work, hemodynamic features of the blood stream on four different ICA aneurysm with/without interventional are investigated. To estimate the relative impacts of vessel deformation, four distinctive ICA aneurysm is simulated by the one-way FSI technique. Four hemodynamic factors of aneurysm blood velocity, wall pressure and WSS are compared in the peak systolic stage to disclose the impact of defamation by the stent in two conditions. The stent usage would decrease almost all of the mentioned parameters, except for OSI. Stenting reduces neck inflow rate, while the effect of interventional was not consistent among the aneurysms. The deformation of an aneurysm has a strong influence on the hemodynamics of an aneurysm. This outcome is ignored by most of the preceding investigations, which focused on the pre-interventional state for studying the relationship between hemodynamics and stents. Present results show that the application of stent without coiling would improve most hemodynamic factors, especially when the deformation of the aneurysm is high enough