Abstract
The classic classification scheme for active galactic nuclei (AGNs) was recently challenged by the discovery of the so-called changing-state (changing-look) AGNs. The physical mechanism ...behind this phenomenon is still a matter of open debate and the samples are too small and of serendipitous nature to provide robust answers. In order to tackle this problem, we need to design methods that are able to detect AGNs right in the act of changing state. Here we present an anomaly-detection technique designed to identify AGN light curves with anomalous behaviors in massive data sets. The main aim of this technique is to identify CSAGN at different stages of the transition, but it can also be used for more general purposes, such as cleaning massive data sets for AGN variability analyses. We used light curves from the Zwicky Transient Facility data release 5 (ZTF DR5), containing a sample of 230,451 AGNs of different classes. The ZTF DR5 light curves were modeled with a Variational Recurrent Autoencoder (VRAE) architecture, that allowed us to obtain a set of attributes from the VRAE latent space that describes the general behavior of our sample. These attributes were then used as features for an Isolation Forest (IF) algorithm that is an anomaly detector for a “one class” kind of problem. We used the VRAE reconstruction errors and the IF anomaly score to select a sample of 8809 anomalies. These anomalies are dominated by bogus candidates, but we were able to identify 75 promising CSAGN candidates.
Microalgae is constituted by different compounds, interesting for the production of a wide range of end-products by using different technologies. Many potential possibilities have been developed ...under the context of a biorefinery. The aim of this work is to evaluate the environmental performance of biogas production from Spirulina (Arthrospira maxima) through LCA using experimental and simulation results. For this purpose, kinetic models for batch cultivation and anaerobic digestion (AD) were determined from experimental data. Thus, Monod kinetic model and a first order model describe well microalgal biomass growth and AD, respectively. This model was used to simulate growth of Spirulina in a continuous system by using SuperPro Designer 9.5. Calculated results were compared to continuous experimental ones, obtaining good agreement in all cases. On the other hand, the whole process (cultivation, dewatering and AD of Spirulina biomass) was also simulated and the obtained results (material and energy balances) were used to construct LCA inventory data. Thereafter, environmental impacts were quantified through CML-2001 methodology using software Gabi 6.0. LCA results show that abiotic depletion of fossil resources (ADFR) category presents the highest impact, being biomass cultivation the most important contributor (about 56%). This result is directly related to the high energy consumption required for nutrient production, which also leads to increase remarkably the global warming potential (GWP) category. Main conclusion of the work is that the total/partial substitution of mineral fertilizers as nutrient source is the key to improve the environmental performance of the studied process. In this sense, a potential alternative could be the use of nutrients from wastewater or other wastes.
•Spirulina growth is experimentally studied in both batch and continuous systems.•Monod kinetic model describes well Spirulina growth.•First order kinetic model is used to describe anaerobic digestion of Spirulina.•Scaling up of biogas production from Spirulina is carried out by simulation.•Nutrient production processes present the highest environmental impacts.
Our understanding of stellar systems depends on the adopted interpretation of the initial mass function, IMF phi(m). Unfortunately, there is not a common interpretation of the IMF, which leads to ...different methodologies and diverging analysis ofobservational data. We study the correlation between the most massive star that a cluster would host, msubmax, and its total mass into stars, M, as an example where different views of the IMF lead to different results. We conclude that a random sampling IMF is not in contradiction to a possible msubmax - Mphysical law. However, such a law cannot be obtained from IMF algebraic manipulation or included analytically in the IMF functional form. The possible physical information that would be obtained from the N (or M) -- msubmax correlation is closely linked with the phisubM(M) and phisubN(N) distributions; hence it depends on the star formation process and the assumed definition of stellar cluster.
Context. Our understanding of stellar systems depends on the adopted interpretation of the initial mass function, IMF φ(m). Unfortunately, there is not a common interpretation of the IMF, which leads ...to different methodologies and diverging analysis of observational data. Aims. We study the correlation between the most massive star that a cluster would host, mmax, and its total mass into stars, ℳ, as an example where different views of the IMF lead to different results. Methods. We assume that the IMF is a probability distribution function and analyze the mmax − ℳ correlation within this context. We also examine the meaning of the equation used to derive a theoretical ℳ − \hbox{$\hat{m}_\mathrm{max}$} ℳ − m̂max relationship, \hbox{${\cal N} \times \int_{\hat{m}_\mathrm{max}}^{m_{\rm up}} \phi(m)\,\mathrm{d}m = 1$} 𝒩×∫m̂maxmupφ(m) dm=1 with N the total number of stars in the system, according to different interpretations of the IMF. Results. We find that only a probabilistic interpretation of the IMF, where stellar masses are identically independent distributed random variables, provides a self-consistent result. Neither ℳ nor the total number of stars in the cluster, N, can be used as IMF scaling factors. In addition, \hbox{$\hat{m}_\mathrm{max}$}m̂max is a characteristic maximum stellar mass in the cluster, but not the actual maximum stellar mass. A ⟨ℳ⟩ − \hbox{$\hat{m}_\mathrm{max}$}⟨ℳ⟩ − m̂max correlation is a natural result of a probabilistic interpretation of the IMF; however, the distribution of observational data in the N (or ℳ) − mmax plane includes a dependence on the distribution of the total number of stars, N (and ℳ), in the system, ΦN(N), which is not usually taken into consideration. Conclusions. We conclude that a random sampling IMF is not in contradiction to a possible mmax − ℳ physical law. However, such a law cannot be obtained from IMF algebraic manipulation or included analytically in the IMF functional form. The possible physical information that would be obtained from the N (or ℳ) − mmax correlation is closely linked with the Φℳ(ℳ) and ΦN(N) distributions; hence it depends on the star formation process and the assumed definition of stellar cluster.
Context. In a probabilistic framework of the interpretation of the initial mass function (IMF), the IMF cannot be arbitrarily normalized to the total mass, M, or number of stars, N, of the system. ...Hence, the inference of M and N when partial information about the studied system is available must be revised (i.e., the contribution to the total quantity cannot be obtained by simple algebraic manipulations of the IMF). Aims. We study how to include constraints in the IMF to make inferences about different quantities characterizing stellar systems. It is expected that including any particular piece of information about a system would constrain the range of possible solutions. However, different pieces of information might be irrelevant depending on the quantity to be inferred. In this work we want to characterize the relevance of the priors in the possible inferences. Methods. Assuming that the IMF is a probability distribution function, we derive the sampling distributions of M and N of the system constrained to different types of information available. Results. We show that the value ofMthat would be inferred must be described as a probability distribution PhiMM; m sub(a), N sub(a),Phi sub( N)(N) that depends on the completeness limit of the data, m sub(a), the number of stars observed down to this limit, Na, and the prior hypothesis made on the distribution of the total number of stars in clusters, Phi sub(N)(N).
Summary Bronchiectasis is a heterogeneous disease in terms of its clinical and functional presentation. Some isolated parameters have been used to assess the severity of bronchiectasis or its ...response to treatment. A study was undertaken to evaluate whether lung function, dyspnea and extension of the disease are separate entities in the impact of bronchiectasis upon patients using factor analysis. Patients with bronchiectasis diagnosed by high-resolution computed tomography (HRCT) and airflow obstruction defined by FEV1 /FVC<70% were included. Data were collected relating to clinical history, three different clinical ratings of dyspnea (Medical Research Council (MRC), Borg scale and Basal Dyspnea Index), the extent of bronchiectasis and functional variables. A total of 81 patients (mean age (SD): 69.5 (8.7)) years were included. The degree of dyspnea (MRC) was 1.9 (0.8). Mean FEV1 was 1301 ml (56.9% pred.). Four factors were found that accounted for 84.1% of the total data variance. Factor 1 (45.6% of the data variance) included the three measurements of dyspnea. Factor 2 (16% variance) comprised airflow obstruction parameters (FEV1 , FEV1 /FVC and PEF). Factor 3 (13.8% variance) included RV/TLC and RV (lung hyperinflation). Factor 4 (8.6% variance) included bronchiectasis extent. Dyspnea was more closely correlated with lung hyperinflation (r:0.33–0.54) than with airflow obstruction parameters ( r :0.17–0.26). Conclusions Airflow obstruction, dyspnea, lung hyperinflation and the lung extent of the bronchiectasis are four independent entities in the impact of bronchiectasis upon patients.
Aims.
We present a variability-, color-, and morphology-based classifier designed to identify multiple classes of transients and persistently variable and non-variable sources from the Zwicky ...Transient Facility (ZTF) Data Release 11 (DR11) light curves of extended and point sources. The main motivation to develop this model was to identify active galactic nuclei (AGN) at different redshift ranges to be observed by the 4MOST Chilean AGN/Galaxy Evolution Survey (ChANGES). That being said, it also serves as a more general time-domain astronomy study.
Methods.
The model uses nine colors computed from CatWISE and Pan-STARRS1 (PS1), a morphology score from PS1, and 61 single-band variability features computed from the ZTF DR11
g
and
r
light curves. We trained two versions of the model, one for each ZTF band, since ZTF DR11 treats the light curves observed in a particular combination of field, filter, and charge-coupled device (CCD) quadrant independently. We used a hierarchical local classifier per parent node approach-where each node is composed of a balanced random forest model. We adopted a taxonomy with 17 classes: non-variable stars, non-variable galaxies, three transients (SNIa, SN-other, and CV/Nova), five classes of stochastic variables (lowz-AGN, midz-AGN, highz-AGN, Blazar, and YSO), and seven classes of periodic variables (LPV, EA, EB/EW, DSCT, RRL, CEP, and Periodic-other).
Results.
The macro-averaged precision, recall, and F1-score are 0.61, 0.75, and 0.62 for the
g
-band model, and 0.60, 0.74, and 0.61, for the
r
-band model. When grouping the four AGN classes (lowz-AGN, midz-AGN, highz-AGN, and Blazar) into one single class, its precision-recall, and F1-score are 1.00, 0.95, and 0.97, respectively, for both the
g
and
r
bands. This demonstrates the good performance of the model in classifying AGN candidates. We applied the model to all the sources in the ZTF/4MOST overlapping sky (−28 ≤ Dec ≤ 8.5), avoiding ZTF fields that cover the Galactic bulge (|
gal_b
| ≤ 9 and
gal_l
≤ 50). This area includes 86 576 577 light curves in the
g
band and 140 409 824 in the
r
band with 20 or more observations and with an average magnitude in the corresponding band lower than 20.5. Only 0.73% of the
g
-band light curves and 2.62% of the
r
-band light curves were classified as stochastic, periodic, or transient with high probability (
P
init
≥ 0.9). Even though the metrics obtained for the two models are similar, we find that, in general, more reliable results are obtained when using the
g
-band model. With it, we identified 384 242 AGN candidates (including low-, mid-, and high-redshift AGN and Blazars), 287 156 of which have
P
init
≥ 0.9.
The early-type galaxy SDSS J133519.91+072807.4 (hereafter SDSS1335+0728), which had exhibited no prior optical variations during the preceding two decades, began showing significant nuclear ...variability in the Zwicky Transient Facility (ZTF) alert stream from December 2019 (as ZTF19acnskyy). This variability behaviour, coupled with the host-galaxy properties, suggests that SDSS1335+0728 hosts a $ odot $ black hole (BH) that is currently in the process of `turning on'. We present a multi-wavelength photometric analysis and spectroscopic follow-up performed with the aim of better understanding the origin of the nuclear variations detected in SDSS1335+0728. We used archival photometry (from WISE, 2MASS, SDSS, GALEX, eROSITA) and spectroscopic data (from SDSS and LAMOST) to study the state of SDSS1335+0728 prior to December 2019, and new observations from Swift SOAR/Goodman, VLT/X-shooter, and Keck/LRIS taken after its turn-on to characterise its current state. We analysed the variability of SDSS1335+0728 in the X-ray/UV/optical/mid-infrared range, modelled its spectral energy distribution prior to and after December 2019, and studied the evolution of its UV/optical spectra. From our multi-wavelength photometric analysis, we find that: (a) since 2021, the UV flux (from Swift /UVOT observations) is four times brighter than the flux reported by GALEX in 2004 ; (b) since June 2022, the mid-infrared flux has risen more than two times, and the W1$-$W2 WISE colour has become redder; and (c) since February 2024, the source has begun showing X-ray emission. From our spectroscopic follow-up, we see that (i) the narrow emission line ratios are now consistent with a more energetic ionising continuum; (ii) broad emission lines are not detected; and (iii) the OIII line increased its flux $ 3.6$ years after the first ZTF alert, which implies a relatively compact narrow-line-emitting region. We conclude that the variations observed in SDSS1335+0728 could be either explained by a $ odot $ AGN that is just turning on or by an exotic tidal disruption event (TDE). If the former is true, SDSS1335+0728 is one of the strongest cases of an AGN observed in the process of activating. If the latter were found to be the case, it would correspond to the longest and faintest TDE ever observed (or another class of still unknown nuclear transient). Future observations of SDSS1335+0728 are crucial to further understand its behaviour.
The classic classification scheme for active galactic nuclei (AGNs) was recently challenged by the discovery of the so-called changing-state (changing-look) AGNs. The physical mechanism behind this ...phenomenon is still a matter of open debate and the samples are too small and of serendipitous nature to provide robust answers. In order to tackle this problem, we need to design methods that are able to detect AGNs right in the act of changing state. Here we present an anomaly-detection technique designed to identify AGN light curves with anomalous behaviors in massive data sets. The main aim of this technique is to identify CSAGN at different stages of the transition, but it can also be used for more general purposes, such as cleaning massive data sets for AGN variability analyses. We used light curves from the Zwicky Transient Facility data release 5 (ZTF DR5), containing a sample of 230,451 AGNs of different classes. The ZTF DR5 light curves were modeled with a Variational Recurrent Autoencoder (VRAE) architecture, that allowed us to obtain a set of attributes from the VRAE latent space that describes the general behavior of our sample. These attributes were then used as features for an Isolation Forest (IF) algorithm that is an anomaly detector for a "one class" kind of problem. We used the VRAE reconstruction errors and the IF anomaly score to select a sample of 8809 anomalies. These anomalies are dominated by bogus candidates, but we were able to identify 75 promising CSAGN candidates.
Context. In a probabilistic framework of the interpretation of the initial mass function (IMF), the IMF cannot be arbitrarily normalized to the total mass, ℳ, or number of stars, N, of the system. ...Hence, the inference of ℳ and N when partial information about the studied system is available must be revised (i.e., the contribution to the total quantity cannot be obtained by simple algebraic manipulations of the IMF). Aims. We study how to include constraints in the IMF to make inferences about different quantities characterizing stellar systems. It is expected that including any particular piece of information about a system would constrain the range of possible solutions. However, different pieces of information might be irrelevant depending on the quantity to be inferred. In this work we want to characterize the relevance of the priors in the possible inferences. Methods. Assuming that the IMF is a probability distribution function, we derive the sampling distributions of ℳ and N of the system constrained to different types of information available. Results. We show that the value of ℳ that would be inferred must be described as a probability distribution Φℳℳ;ma,Na,ΦN(N) that depends on the completeness limit of the data, ma, the number of stars observed down to this limit, Na, and the prior hypothesis made on the distribution of the total number of stars in clusters, ΦN(N).
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