18,077 research outputs found
Revisão taxonómica do género Calendula L. (Asteraceae - Calenduleae) na Península Ibérica e Marrocos
The genus Calendula L. (Asteraceae - Calenduleae) includes, depending on the author, 10 to 25 species, distributed mainly in the Mediterranean basin. The taxonomy of this genus is considered to be extremely difficult, due to a great morphological variability, doubtfull relevance of some of the characters used to distinguish its species (e.g. the life form: annual or perennial; the habit: erect or diffuse, shape of the leaves, indumentum, relative size of the capitula and colour of disc or ray florets, achene morphology), but also due to the hybridization and polyploidization. Despite the numerous studies that have been published, no agreement on the classification and characters used to discriminate between taxa has been reached. A taxonomic study of the genus Calendula was conducted for the Iberian Peninsula and Morocco, aiming at (1) access the morphological variability between and within taxa, (2) confirm the chromosome numbers, (3) increase the nuclear DNA content estimations, (4) re-evaluate taxa delimitations and circumscription, and (5) reassess, and redefine, the
descriptions and characters useful to distinguish taxa. In order to achieve a satisfying taxonomic core, extensive fieldwork, detailed morphometric analysis,
chorological, karyological and genome size studies were conducted. For the Iberian Peninsula, four species were recognized, including nine subspecies (between these two new subspecies were described). For Morocco, including some taxa from Algeria and Tunisia 13 species were recognized (two new species and a nomenclatural change), including 15 subspecies (among these eight new subspecies were described). To corroborate the results obtained and to evaluate the evolutionary relationships among taxa, phylogenetic studies using molecular methods, such as ITS, microsatellites or other molecular markers, should be used.O género Calendula L. (Asteraceae - Calenduleae) inclui, dependendo do autor, 10 a 25 espécies, distribuídas essencialmente na bacia do Mediterrâneo. A taxonomia deste género é considerada extremamente difícil, devido à grande variabilidade morfológica, discutivel relevância de alguns dos caracteres utilizados para distinguir suas espécies (por exemplo, a forma de vida: anual ou perene, o hábito: erecto ou difuso, a forma das folhas, o indumento, o tamanho e a cor dos capítulos e a morfologia dos aquénios), mas também devido à
hibridização e poliploidização. Apesar dos inúmeros estudos que foram publicados, não foi alcançado um acordo sobre a classificação e os caracteres utilizados para discriminar as suas espécies. Um estudo taxonómico do género Calendula foi realizado para a Península Ibérica e Marrocos, com o objectivo de (1) verificar a variabilidade morfológica, (2) confirmar o número de cromossomas, (3) aumentar as estimativas de conteúdo em ADN, (4) reavaliar a delimitação e a circunscrição dos taxa, e (5) reavaliar e redefinir as descrições e caracteres úteis para os distinguir. Para alcançar uma robustês taxonómica satisfatória, foram realizados extensos trabalhos de campo, análise morfométrica detalhada, abordagens corológicas, cariológicas e quanto ao conteúdo em ADN. Para a Península Ibérica, quatro espécies foram reconhecidas, incluindo nove subespécies (entre essas duas novas subespécies foram descritas). Para Marrocos, incluindo alguns taxa da Argelia e Tunisia, foram reconhecidas 13 espécies (duas novas e uma mudança nomenclatural), incluindo 15 subespécies (entre essas oito novas subespécies foram descritas). Para corroborar os resultados obtidos e avaliar as relações evolutivas e filogenéticas entre os taxa, estudos que utilizem diferentes métodos
moleculares, tais como ITS, microsatélites ou outros marcadores moleculares, devem ser utilizados.Apoio financeiro do Laboratório Associado CESAM - Centro de Estudos do Ambiente e do Mar (AMB/50017) financiado por fundos nacionais através da FCT/MCTES e cofinanciado pelo FEDER (POCI-01-0145-FEDER-007638), no âmbito do Acordo de Parceria PT2020, e Compete 2020Programa Doutoral em Biologi
Cosmology with one galaxy? -- The ASTRID model and robustness
Recent work has pointed out the potential existence of a tight relation
between the cosmological parameter , at fixed ,
and the properties of individual galaxies in state-of-the-art cosmological
hydrodynamic simulations. In this paper, we investigate whether such a relation
also holds for galaxies from simulations run with a different code that made
use of a distinct subgrid physics: Astrid. We find that also in this case,
neural networks are able to infer the value of with a
precision from the properties of individual galaxies while
accounting for astrophysics uncertainties as modeled in CAMELS. This tight
relationship is present at all considered redshifts, , and the stellar
mass, the stellar metallicity, and the maximum circular velocity are among the
most important galaxy properties behind the relation. In order to use this
method with real galaxies, one needs to quantify its robustness: the accuracy
of the model when tested on galaxies generated by codes different from the one
used for training. We quantify the robustness of the models by testing them on
galaxies from four different codes: IllustrisTNG, SIMBA, Astrid, and
Magneticum. We show that the models perform well on a large fraction of the
galaxies, but fail dramatically on a small fraction of them. Removing these
outliers significantly improves the accuracy of the models across simulation
codes.Comment: 16 pages, 12 figure
Testing the nomological network for the Personal Engagement Model
The study of employee engagement has been a key focus of management for over three decades. The academic literature on engagement has generated multiple definitions but there are two primary models of engagement: the Personal Engagement Model of Kahn (1990), and the Work Engagement Model (WEM) of Schaufeli et al., (2002). While the former is cited by most authors as the seminal work on engagement, research has tended to focus on elements of the model and most theoretical work on engagement has predominantly used the WEM to consider the topic.
The purpose of this study was to test all the elements of the nomological network of the PEM to determine whether the complete model of personal engagement is viable. This was done using data from a large, complex public sector workforce. Survey questions were designed to test each element of the PEM and administered to a sample of the workforce (n = 3,103). The scales were tested and refined using confirmatory factor analysis and then the model was tested determine the structure of the nomological network. This was validated and the generalisability of the final model was tested across different work and organisational types.
The results showed that the PEM is viable but there were differences from what was originally proposed by Kahn (1990). Specifically, of the three psychological conditions deemed necessary for engagement to occur, meaningfulness, safety, and availability, only meaningfulness was found to contribute to employee engagement. The model demonstrated that employees experience meaningfulness through both the nature of the work that they do and the organisation within which they do their work. Finally, the findings were replicated across employees in different work types and different organisational types.
This thesis makes five contributions to the engagement paradigm. It advances engagement theory by testing the PEM and showing that it is an adequate representation of engagement. A model for testing the causal mechanism for engagement has been articulated, demonstrating that meaningfulness in work is a primary mechanism for engagement. The research has shown the key aspects of the workplace in which employees experience meaningfulness, the nature of the work that they do and the organisation within which they do it. It has demonstrated that this is consistent across organisations and the type of work. Finally, it has developed a reliable measure of the different elements of the PEM which will support future research in this area
Evolutionary Multi-Objective Aerodynamic Design Optimization Using CFD Simulation Incorporating Deep Neural Network
An evolutionary multi-objective aerodynamic design optimization method using
the computational fluid dynamics (CFD) simulations incorporating deep neural
network (DNN) to reduce the required computational time is proposed. In this
approach, the DNN infers the flow field from the grid data of a design and the
CFD simulation starts from the inferred flow field to obtain the steady-state
flow field with a smaller number of time integration steps. To show the
effectiveness of the proposed method, a multi-objective aerodynamic airfoil
design optimization is demonstrated. The results indicate that the
computational time for design optimization is suppressed to 57.9% under 96
cores processor conditions
Subspecies limits based on morphometry and mitochondrial DNA genomics in a polytypic species, the common grackle, Quiscalus quiscula
Nearctic migratory songbirds have demonstrated low levels of genetic differentiation and weak phylogeographical structure in mitochondrial DNA lineages compared with resident species. The common grackle, Quiscalus quiscula, is a widespread, partially migratory, North American icterid composed of three currently recognized subspecies. In this study, mensural characters (external and skeletal measurements) and the complete mitochondrial genome together with two mitochondrial genes, Cytb and ND2, were used to investigate subspecific differentiation and demographic history of the common grackle. The results showed substantial variation in body size among subspecies, mostly distributed between the ‘Florida grackle’, Quiscalus quiscula quiscula, and the two other subspecies. Analysis of mitochondrial DNA indicated low levels of genetic variation, but we found distinct haplotypes in Florida that form a clade in the phylogenetic tree. This suggests that the nominate subspecies in Florida is a distinct evolutionary unit. The sharing of haplotypes among the other subspecies (Quiscalus quiscula versicolor and Quiscalus quiscula stonei) in the north suggests high levels of gene flow, making the status of these two subspecies equivocal. Gene f low between nominate Q. q. quiscula, Q. q. versicolor and putative Q. q. stonei is probably attributable to historical changes in distribution and abundance following climate change events. We therefore recognize only two subspecies in the common grackle complex
Model-Independent Determination of and using Time-Delay Galaxy Lenses and Gamma-Ray Bursts
Combining the `time-delay distance' () measurements from galaxy
lenses and other distance indicators provides model-independent determinations
of the Hubble constant () and spatial curvature (), only
based on the validity of the Friedmann-Lema\^itre-Robertson-Walker (FLRW)
metric and geometrical optics. To take the full merit of combining measurements in constraining , we use gamma-ray burst (GRB) distances
to extend the redshift coverage of lensing systems much higher than that of
Type Ia Supernovae (SNe Ia) and even higher than quasars, whilst the general
cosmography with a curvature component is implemented for the GRB distance
parametrizations. Combining Lensing+GRB yields ~km
sMpc and (1). A
flat-universe prior gives slightly an improved ~km
sMpc. When combining Lensing+GRB+SN Ia, the error bar falls by 25\%, whereas is not improved due to the
degeneracy between SN Ia absolute magnitude, , and along with the
mismatch between the SN Ia and GRB Hubble diagrams at . Future
increment of GRB observations can help to moderately eliminate the
degeneracy in SN Ia distances and ameliorate the restrictions on cosmographic
parameters along with when combining Lensing+SN Ia+GRB. We
conclude that there is no evidence of significant deviation from a (an) flat
(accelerating) universe and is currently determined at 3\% precision. The
measurements show great potential to arbitrate the tension between the
local distance ladder and cosmic microwave background measurements and provide
a relevant consistency test of the FLRW metric.Comment: Accepted for publication in MNRA
Vegetation responses to variations in climate: A combined ordinary differential equation and sequential Monte Carlo estimation approach
Vegetation responses to variation in climate are a current research priority in the context of accelerated shifts generated by climate change. However, the interactions between environmental and biological factors still represent one of the largest uncertainties in projections of future scenarios, since the relationship between drivers and ecosystem responses has a complex and nonlinear nature. We aimed to develop a model to study the vegetation’s primary productivity dynamic response to temporal variations in climatic conditions as measured by rainfall, temperature and radiation. Thus, we propose a new way to estimate the vegetation response to climate via a non-autonomous version of a classical growth curve, with a time-varying growth rate and carrying capacity parameters according to climate variables. With a Sequential Monte Carlo Estimation to account for complexities in the climate-vegetation relationship to minimize the number of parameters. The model was applied to six key sites identified in a previous study, consisting of different arid and semiarid rangelands from North Patagonia, Argentina. For each site, we selected the time series of MODIS NDVI, and climate data from ERA5 Copernicus hourly reanalysis from 2000 to 2021. After calculating the time series of the a posteriori distribution of parameters, we analyzed the explained capacity of the model in terms of the linear coefficient of determination and
the parameters distribution variation. Results showed that most rangelands recorded changes in their sensitivity over time to climatic factors, but vegetation responses were heterogeneous and influenced by different drivers. Differences in this climate-vegetation relationship were recorded among different cases: (1) a marginal and decreasing sensitivity to temperature and radiation, respectively, but a high sensitivity to water availability; (2) high and increasing sensitivity to temperature and water availability, respectively; and (3) a case with an abrupt shift in vegetation dynamics driven by a progressively decreasing sensitivity to water availability, without any
changes in the sensitivity either to temperature or radiation. Finally, we also found that the time scale, in which the ecosystem integrated the rainfall phenomenon in terms of the width of the window function used to convolve the rainfall series into a water availability variable, was also variable in time. This approach allows us to estimate the connection degree between ecosystem productivity and climatic variables. The capacity of the model to identify changes over time in the vegetation-climate relationship might inform decision-makers about ecological transitions and the differential impact of climatic drivers on ecosystems.Estación Experimental Agropecuaria BarilocheFil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Perri, Daiana Vanesa. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; ArgentinaFil: Perri, Daiana Vanesa. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Easdale, Marcos Horacio. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; ArgentinaFil: Easdale, Marcos Horacio. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentin
Inferring networks from time series: a neural approach
Network structures underlie the dynamics of many complex phenomena, from gene
regulation and foodwebs to power grids and social media. Yet, as they often
cannot be observed directly, their connectivities must be inferred from
observations of their emergent dynamics. In this work we present a powerful and
fast computational method to infer large network adjacency matrices from time
series data using a neural network. Using a neural network provides uncertainty
quantification on the prediction in a manner that reflects both the
non-convexity of the inference problem as well as the noise on the data. This
is useful since network inference problems are typically underdetermined, and a
feature that has hitherto been lacking from network inference methods. We
demonstrate our method's capabilities by inferring line failure locations in
the British power grid from observations of its response to a power cut. Since
the problem is underdetermined, many classical statistical tools (e.g.
regression) will not be straightforwardly applicable. Our method, in contrast,
provides probability densities on each edge, allowing the use of hypothesis
testing to make meaningful probabilistic statements about the location of the
power cut. We also demonstrate our method's ability to learn an entire cost
matrix for a non-linear model from a dataset of economic activity in Greater
London. Our method outperforms OLS regression on noisy data in terms of both
speed and prediction accuracy, and scales as where OLS is cubic. Since
our technique is not specifically engineered for network inference, it
represents a general parameter estimation scheme that is applicable to any
parameter dimension
A Finite Element-Inspired Hypergraph Neural Network: Application to Fluid Dynamics Simulations
An emerging trend in deep learning research focuses on the applications of
graph neural networks (GNNs) for mesh-based continuum mechanics simulations.
Most of these learning frameworks operate on graphs wherein each edge connects
two nodes. Inspired by the data connectivity in the finite element method, we
present a method to construct a hypergraph by connecting the nodes by elements
rather than edges. A hypergraph message-passing network is defined on such a
node-element hypergraph that mimics the calculation process of local stiffness
matrices. We term this method a finite element-inspired hypergraph neural
network, in short FEIH()-GNN. We further equip the proposed network with
rotation equivariance, and explore its capability for modeling unsteady fluid
flow systems. The effectiveness of the network is demonstrated on two common
benchmark problems, namely the fluid flow around a circular cylinder and
airfoil configurations. Stabilized and accurate temporal roll-out predictions
can be obtained using the -GNN framework within the interpolation
Reynolds number range. The network is also able to extrapolate moderately
towards higher Reynolds number domain out of the training range
The cosmic waltz of Coma Berenices and Latyshev 2 (Group X). Membership, phase-space structure, mass, and energy distributions
Context. Open clusters (OCs) are fundamental benchmarks where theories of
star formation and stellar evolution can be tested and validated. Coma Ber and
Latyshev 2 (Group X) are the second and third OCs closest to the Sun, making
them excellent targets to search for low-mass stars and ultra-cool dwarfs. In
addition, this pair will experience a flyby in 10-16 Myr which makes it a
benchmark to test OCs pair interactions. Aims. We aim at analysing the
membership, luminosity, mass, phase-space (i.e., positions and velocities), and
energy distributions for Coma Ber and Latyshev 2 and test the hypothesis of the
mixing of their populations at the encounter time. Methods. We develop a new
phase-space membership methodology and apply it to Gaia data. With the
recovered members we infer the phase-space, luminosity and mass distributions
using publicly available Bayesian inference codes. Then, with a publicly
available orbit integration code and members' positions and velocities, we
integrate their orbits 20 Myr into the future. Results. In Coma Ber, we
identify 302 candidate members distributed in the core and tidal tails. The
tails are dynamically cold and asymmetrically populated. The stellar system
called Group X is made of two structures: the disrupted OC Latyshev 2 (186
candidate members) and a loose stellar association called Mecayotl 1 (146
candidate members), both of them will fly by Coma Ber in Myr and
Myr, respectively, and each other in Myr. Conclusions.
We study the dynamical properties of the core and tails of Coma Ber and also
confirm the existence of the OC Latyshev 2 and its neighbour stellar
association Mecayotl 1. Although these three systems will experience encounters
we find no evidence supporting the mixing of their populations.Comment: 25 pages, 19 figures, accepted for publication in Astronomy &
Astrophysic
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