Caracterización integral de las propiedades fisicoquímicas, térmicas, composicionales y sensoriales del aceite de semilla de rosa mosqueta prensado en frío

In this study, cold-pressed rosehip seed oil was fully characterized. Acidity and oxidation levels were near the limit values or slightly exceeded them and improvement in the storage conditions was suggested. The oil started to crystallize at -45.25 °C, and melt at -25.56 °C. Linoleic acid (51.1%), β-sitosterol (84.6%), γ-tocopherol (773.76 µg/g) and rosmarinic acid (31.38 µg/g) were determined as major fatty acid, sterol, tocopherol and phenolic compound, respectively. For the first time, aromatic volatile compounds and sensory descriptive terms were determined for cold-pressed rosehip seed oil. Sixty-seven volatile compounds were detected and L-limonene was found to be a major volatile compound. According to the sensory analysis, timber/kindling and raw vegetable tastes/aromas were found to be relatively dominant. Consequently, it is thought that rosehip seeds can be used as a raw material for edible and nutritionally-rich cold-pressed oil production and/or as source oil for functional food preparations.En este estudio se caracterizó completamente el aceite de semilla de rosa mosqueta prensado en frío. Los niveles de acidez y oxidación estaban cerca de los valores límite o los excedían ligeramente y se sugirió mejorar las condiciones de almacenamiento. El aceite comenzó a cristalizar a -45,25°C y a fundirse a -25,56°C. Se determinó el ácido linoleico (51,1%), β-sitosterol (84,6%), γ-tocoferol (773,76 µg/g) y ácido rosmarínico (31,38 µg/g) como principal ácido graso, esterol, tocoferol y compuesto fenólico, respectivamente. Por primera vez, se determinaron compuestos aromáticos volátiles y términos descriptivos sensoriales para el aceite de semilla de rosa mosqueta prensado en frío. Se detectaron sesenta y siete compuestos volátiles y se descubrió que el L-limoneno era un compuesto volátil importante. Según el análisis sensorial, se encontró que los sabores/aromas de madera/astillas y vegetales crudos eran relativamente dominantes. En consecuencia, se cree que las semillas de rosa mosqueta pueden usarse como materia prima para la producción de aceite prensado en frío comestible y nutritivo y/o como aceite fuente para preparaciones de alimentos funcionales

An Alternative Approach to Network Demand Estimation: Implementation and Application in Multi-Agent Transport Simulation (MATSim)

AbstractThis paper introduces a novel network demand estimation framework consistent with the input data structure requirements of Multi-Agent Transport Simulation (MATSim). The sources of data are the American Community Survey, US Census Bureau, National Household Travel Surveys, travel surveys from South East Florida Regional Planning Authority, OpenStreetMap and Florida Statewide Transportation Engineering Warehouse for Archived Regional Database. The developed framework employs mathematical and statistical methods to derive probability density functions and multinomial logit models for activity and location choices. The implementation of demand estimation process resulted into the creation of 1,200,889 agents (only those using cars). The scenario for the estimated agents was configured and simulated in MATSim. The results from the simulated scenario resulted in the expected morning, afternoon and evening traffic patterns as well as the desirable level of agreement between simulated and observed traffic volumes

Flux Correlators and Semiclassics

We consider correlators for the flux of energy and charge in the background of operators with large global $U(1)$ charge in conformal field theory (CFT). It has recently been shown that the corresponding Euclidean correlators generically admit a semiclassical description in terms of the effective field theory (EFT) for a conformal superfluid. We adapt the semiclassical description to Lorentzian observables and compute the leading large charge behavior of the flux correlators in general $U(1)$ symmetric CFTs. We discuss the regime of validity of the large charge EFT for these Lorentzian observables and the subtleties in extending the EFT approach to subleading corrections. We also consider the Wilson-Fisher fixed point in $d=4-\epsilon$ dimensions, which offers a specific weakly coupled realization of the general setup, where the subleading corrections can be systematically computed without relying on an EFT.Comment: 33 pages, 8 figure

The Effect of Geometrical Factors on the Surface Pressure Distribution on a Human Phantom Model Following Shock Exposure: A Computational and Experimental Study

Experimental data and finite element simulations of an anthropometric surrogate headform was used to evaluate the effect of specimen location and orientation on surface pressures following shock exposures of varying intensity. It was found that surface pressure distributions changed with local flow field disturbances, making it necessary to use data reduction strategies to facilitate comparisons between test locations, shock wave intensities and headform orientations. Non-dimensional parameters, termed amplification factors, were developed to permit direct comparisons of pressure waveform characteristics between incident shock waves differing in intensity, irrespective of headform location and orientation. This approach proved to be a sensitive metric, highlighting the flow field disturbances which exist in different locations and indicating how geometric factors strongly influence the flow field and surface pressure distribution

Understanding and responding to danger from climate change: the role of key risks in the IPCC AR5

The IPCC’s Fifth Assessment Report (AR5) identifies key risks in a changing climate to inform judgments about danger from climate change and to empower responses. In this article, we introduce the innovations and implications of its approach, which extends analysis across sectors and regions, and consider relevance for future research and assessment. Across key risks in the AR5, we analyze the changing risk levels and potential for risk reduction over the next few decades, an era with some further committed warming, and in the second half of the 21st century and beyond, a longer-term era of climate options determined by the ambition of global mitigation. The key risk assessment underpins the IPCC’s conclusion that increasing magnitudes of warming increase the likelihood of severe, pervasive, and irreversible impacts. Here, we emphasize central challenges in understanding and communicating risks. These features include the importance of complex interactions in shaping risks, the need for rigorous expert judgment in evaluating risks, and the centrality of values, perceptions, and goals in determining both risks and responses

proovframe: frameshift-correction for long-read (meta)genomics

Long-read sequencing technologies hold big promises for the genomic analysis of complex samples such as microbial communities. Yet, despite improving accuracy, basic gene prediction on long-read data is still often impaired by frameshifts resulting from small indels. Consensus polishing using either complementary short reads or to a lesser extent the long reads themselves can mitigate this effect but requires universally high sequencing depth, which is difficult to achieve in complex samples where the majority of community members are rare. Here we present proovframe, a software implementing an alternative approach to overcome frameshift errors in long-read assemblies and raw long reads. We utilize protein-to-nucleotide alignments against reference databases to pinpoint indels in contigs or reads and correct them by deleting or inserting 1-2 bases, thereby conservatively restoring reading-frame fidelity in aligned regions. Using simulated and real-world benchmark data we show that proovframe performs comparably to short-read-based polishing on assembled data, works well with remote protein homologs, and can even be applied to raw reads directly. Together, our results demonstrate that protein-guided frameshift correction significantly improves the analyzability of long-read data both in combination with and as an alternative to common polishing strategies. Proovframe is available from https://github.com/thackl/proovframe

Reusable and Flexible Heterogeneous Catalyst for Reduction of TNT by Pd Nanocube Decorated ZnO Nanolayers onto Electrospun Polymeric Nanofibers

An effective method for the fabrication of well designed nanocomposite for the catalytic reduction of 2,4,6-trinitrotoluene (TNT) was developed. Here, cubic palladium (Pd) nanoparticles were utilized for enhancing the interface properties, attachment quality, catalytic yield and stability after the catalysis reactions. Ligand controlled facet growth by the Br- anions during thermal decomposition of the palladium-precursor resulted with cubic shaped average ∼13 nm palladium nanocubes (Pd NC). The anisotropic Pd NC were utilized to decorate the surface of the zinc oxide (ZnO) nanolayers deposited by atomic layer deposition (ALD) technique on the electrospun polyacrylonitrile (PAN) nanofibers. Due to the polymeric nature of the electrospun PAN nanofibers, Pd NC decorated nanoweb is highly flexible and has a high surface area. For the sustainable Pd NC decoration on the ZnO surfaces coated on PAN nanofibers, anchor points were formed by the functional thiol groups which can facilitate the Pd NC attachment and stability on the ZnO surface. The -OH and alkyl thiol groups obtained via sol-gel reactions positioned on the ZnO layer providing a better interface between ZnO and Pd NC which cannot be obtained by pristine PAN nanofibers. Additionally, due to the increased surface interaction, geometrical positioning on fibers for a better intermediate complex formation and stability via soft-soft interaction, Pd NC decorated flexible polymeric electrospun nanoweb provided enhanced catalytic reduction of TNT in aqueous medium. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinhei

Dynamic connectivity algorithms for Monte Carlo simulations of the random-cluster model

We review Sweeny's algorithm for Monte Carlo simulations of the random cluster model. Straightforward implementations suffer from the problem of computational critical slowing down, where the computational effort per edge operation scales with a power of the system size. By using a tailored dynamic connectivity algorithm we are able to perform all operations with a poly-logarithmic computational effort. This approach is shown to be efficient in keeping online connectivity information and is of use for a number of applications also beyond cluster-update simulations, for instance in monitoring droplet shape transitions. As the handling of the relevant data structures is non-trivial, we provide a Python module with a full implementation for future reference.Comment: Contribution to the "XXV IUPAP Conference on Computational Physics" proceedings; Corrected equation 3 and error in the maximal number of edge level

Calomplification — the power of generative calorimeter models

Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn the underlying distribution, such that a generated sample outperforms a training sample of limited size. This kind of GANplification has been observed for simple Gaussian models. We show the same effect for a physics simulation, specifically photon showers in an electromagnetic calorimeter

Statistical Analysis of Paradigmatic Class Richness Supports Greater Paleoindian Projectile-Point Diversity in the Southeast

Ronald Mason\u27s hypothesis from the 1960s that the southeastern United States possesses greater Paleoindian projectile-point diversity than other regions is regularly cited, and often assumed to be true, but in fact has never been quantitatively tested. Even if valid, however, the evolutionary meaning of this diversity is contested. Point diversity is often linked to Clovis origins, but point diversity could also arise from group fissioning and drift, admixture, adaptation, or multiple founding events, among other possibilities. Before archaeologists can even begin to discuss these scenarios, it is paramount to ensure that what we think we know is representative of reality. To this end, we tested Mason\u27s hypothesis for the first time, using a sample of 1,056 Paleoindian points from eastern North America ami employing paradigmatic classification and rigorous statistical tools used in the quantification of ecological biodiversity. Our first set of analyses, which compared the Southeast to the Northeast, showed that the Southeast did indeed possess significantly greater point-class richness. Although this result was consistent with Mason\u27s hypothesis, our second set of analyses, which compared the Upper Southeast to the Lower Southeast and the Northeast showed that in terms of point-class richness the Upper Southeast \u3e Lower Southeast \u3e Northeast. Given current chronometric evidence, we suggest that this latter result is consistent with the suggestion that the area of the Ohio, Cumberland, and Tennessee River valleys, as well as the mid-Atlantic coastal plain, were possible initial and secondary staging areas for colonizing Paleoindian foragers moving from western to eastern North America