Miracle-dz/UniFAR-FTUs huggingface dataset:
Decoupling the rotation of stars and gas – II. The link between black hole activity and simulated IFU kinematics in IllustrisTNG

We study the relationship between supermassive black hole (BH) feedback, BH luminosity, and the kinematics of stars and gas for galaxies in IllustrisTNG. We use galaxies with mock MaNGA observations to identify kinematic misalignment at z = 0 (difference in rotation of stars and gas), for which we follow the evolutionary history of BH activity and gas properties over the last 8 Gyr. Misaligned low-mass galaxies ($\mathrm{\mathit{ M}_{stel} \lt 10^{10.2}\, \mathrm{M}_{\odot }}$) typically have boosted BH luminosity and BH growth, and have had more energy injected by BHs into the gas over the last 8 Gyr in comparison to low-mass aligned galaxies. These properties likely lead to outflows and gas removal, in agreement with active low mass galaxies in observations. Splitting on BH luminosity at z = 0 produces consistent distributions of kinematic misalignment at z = 0; however, splitting on the maximum BH luminosity over the last 8 Gyr produces statistically significant different distributions. While instantaneous correlation at z = 0 is difficult due to misalignment persisting on longer time-scales, the relationship between BH activity and misalignment is clear. High-mass quenched galaxies ($\mathrm{\mathit{ M}_{stel} \gt 10^{10.2}\, \mathrm{M}_{\odot }}$) with misalignment typically have similar BH luminosities, show lower gas fractions, and have typically lower gas phase metallicity over the last 8 Gyr in comparison to the high mass aligned.
Analysing the Determinants of Household Pro-Environmental Behaviour: An Exploratory Study

What strongly influences or determines household pro-environmental behaviour (PEB) is a question of great curiosity across the globe. Solution to this research question investigating PEB has significant implications for researchers, strategic planners and public policymakers. Multidisciplinary research seems necessary to answer this complex question identifying variables that influence PEB at the individual level. In the light of recent work on environmental paradigms, the currents study attempts to explore and identify the relevant factors that contribute to PEB significantly. To achieve the stated objective, an in-depth literature review and qualitative analysis were carried out. A questionnaire was developed to measure the PEB construct and its determinants. Next, the reliability of the questionnaire was assessed using pilot study. Following this, exploratory factor analysis was conducted to identify the major determinants. The validation of constructs using exploratory factor analysis exhibited an interpretable latent structure consisting of determinants of PEB. Results indicate that PEB comprises of nine dimensions viz., behavioural intention, attitude, personal moral norms, subjective norms, situational factors, perceived behavioural control, community concern, internal attribution and perceived consequences. Finally, the study integrates the internal and external determinants in an understanding framework to predict different types of PEBs. The results of the study provide important insights for researchers, strategic planners and policymakers to help more people act in pro-environmental ways. From the theoretical perspective, the study results provide empirical evidence to researchers and a reliable and valid scale to measure PEBs.
Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps – validation on simulations

We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear two-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. The analysis is geared towards the third year (Y3) data from the Dark Energy Survey (DES), but the methodology can be applied to other weak lensing data sets. We present the formalism for obtaining the convergence maps from the measured shear and for obtaining the second and third moments of these maps given partial sky coverage. We estimate the covariance matrix from a large suite of numerical simulations. We test our pipeline through a simulated likelihood analyses varying 5 cosmological parameters and 10 nuisance parameters and identify the scales where systematic or modelling uncertainties are not expected to affect the cosmological analysis. Our simulated likelihood analysis shows that the combination of second and third moments provides a 1.5 per cent constraint on S8 ≡ σ8(Ωm/0.3)0.5 for DES Year 3 data. This is 20 per cent better than an analysis using a simulated DES Y3 shear two-point statistics, owing to the non-Gaussian information captured by the inclusion of higher order statistics. This paper validates our methodology for constraining cosmology with DES Year 3 data, which will be presented in a subsequent paper.
Circumbinary Disks: Accretion and Torque as a Function of Mass Ratio and Disk Viscosity

Using numerical hydrodynamics calculations and a novel method for densely sampling parameter space, we measure the accretion and torque on a binary system from a circumbinary disk. In agreement with some earlier studies, we find that the net torque on the binary is positive for mass ratios close to unity, and that accretion always drives the binary toward equal mass. Accretion variability depends sensitively on the numerical sink prescription, but the torque and relative accretion onto each component do not depend on the sink timescale. Positive torque and highly variable accretion occurs only for mass ratios greater than around 0.05. This means that for mass ratios below 0.05, the binary would migrate inward until the secondary accreted sufficient mass, after which it would execute a U-turn and migrate outward. We explore a range of viscosities, from α = 0.03 to α = 0.15, and find that this outward torque is proportional to the viscous torque, so that torque per unit accreted mass is independent of α. Dependence of accretion and torque on mass ratio is explored in detail, densely sampling mass ratios between 0.01 and unity. For mass ratio q > 0.2, accretion variability is found to exhibit a distinct sawtooth pattern, typically with a five-orbit cycle that provides a smoking gun prediction for variable quasars observed over long periods, as a potential means to confirm the presence of a binary.
Supernovae within Pre-existing Wind-blown Bubbles: Dust Injection versus Ambient Dust Destruction

By means of 3D hydrodynamical simulations, we evaluate here the impact that supernova (SN) explosions occurring within wind-driven bubbles have on the survival or destruction of dust grains. We consider both the dust generated within the ejecta and the dust initially present in the ambient gas and later locked up in the surrounding wind-driven shell (WDS). The collision of the SN blast wave with the WDS leads to a transmitted shock that moves into the shell and a reflected shock that moves into the ejecta. The transmitted shock is capable of destroying large amounts of the dust locked in the shell, but only if the mass of the WDS is small, less than a few tens the ejected mass. Conversely, massive WDSs, with several times the ejected mass, lead upon the interaction to strong radiative cooling, which inhibits the Sedov–Taylor phase and weakens the transmitted shock, making it unable to traverse the WDS. In such a case, the destruction/disruption of the ambient dust is largely inhibited. On the other hand, the SN remnants grow rapidly in the very tenuous region excavated by the stellar winds, and thus a large fraction of the dust generated within the ejecta is not efficiently destroyed by the SN reverse shock, nor by the reflected shock. Our calculations favor a scenario in which core-collapse SNe within sufficiently massive WDSs supply more dust to the interstellar medium than they are able to destroy.
Fair Adversarial Gradient Tree Boosting

Fair classification has become an important topic in machine learning research. While most bias mitigation strategies focus on neural networks, we noticed a lack of work on fair classifiers based on decision trees even though they have proven very efficient. In an up-to-date comparison of state-of-the-art classification algorithms in tabular data, tree boosting outperforms deep learning. For this reason, we have developed a novel approach of adversarial gradient tree boosting. The objective of the algorithm is to predict the output Y with gradient tree boosting while minimizing the ability of an adversarial neural network to predict the sensitive attribute S. The approach incorporates at each iteration the gradient of the neural network directly in the gradient tree boosting. We empirically assess our approach on 4 popular data sets and compare against state-of-the-art algorithms. The results show that our algorithm achieves a higher accuracy while obtaining the same level of fairness, as measured using a set of different common fairness definitions.
Beyond the ethic case: a value proposition of proactive human factors management

This paper is based on the work presented in Osterman, C. (2012), ‘Developing a value proposition of maritime ergonomics’, PhD thesis, Department of Shipping and Marinetechnology, Chalmers University of Technology, Gothenburg, Sweden.There is a large body of knowledge available on the role of human factors for successful (andunsuccessful) systems. Domain specific handbooks, guidelines and standards can be found alsofor the maritime industry. Yet, the deteriorating figure of maritime casualties and the highincidence of occupational accidents suggest this knowledge is not utilised to its full potential.The purpose of this paper is to present a value proposition of maritime human factors,positioning the potential core values that can be delivered to stakeholders within and outside themaritime transport system.The paper adopts an exploratory research approach, investigating thelink between human factors and operational performance from several different angles. Methods for data collection include literature studies, individual and focus group interviews, and a casestudy involving a shipping company.The synthesis of the results is presented in terms of a value proposition that describes the valuefor the employee in terms of improved health and well-being, learning, skill discretion andindependence in life. Values for the company include increased operational performance and flexibility, advantages in recruiting and retaining personnel. Values for the sector includecompetitive strength, attractiveness of work and increased learning across the industry. Values for the society include reduced costs for health care and social security, reduced environmentalimpact, and a sustainable working life.These results are a first step to make visible the effects of human factors management on overallsystems performance in the maritime domain.
Voltage-Mode CFTA-C Third-Order Elliptic Low-Pass Filter Design and Optimization Using Signal Flow Graph Approach

In this work, two active only grounded-C equivalents of third-order voltage-mode (VM) elliptic low-pass (LP) LC ladder prototype are proposed. As active building blocks (ABBs) the recently introduced current follower transconductance amplifier (CFTA) were used. The first active only grounded-C LP filter employing eight CFTAs was proposed by interconnecting CFTA-based active equivalent sub-blocks of passive components, where one of the low-impedance input terminals is not used. Since such feature may cause some noise injection into the proposed circuit, the proposed filter was optimized using Mason-Coates' signal flow graph approach. In several steps the number of ABBs was reduced by two and the unused input terminal was eliminated. The performance of the novel and optimized active only grounded-C third-order VM elliptic LP filter was tested experimentally using the readily available UCC-N1B integrated circuit. DOI: http://dx.doi. org/10.5755/j01.eee. 21.2. 11508
Real or Fake? Spoofing State-Of-The-Art Face Synthesis Detection Systems

The availability of large-scale facial databases, together with the remarkable progresses of deep learning technologies, in particular Generative Adversarial Networks (GANs), have led to the generation of extremely realistic fake facial content, which raises obvious concerns about the potential for misuse. These concerns have fostered the research of manipulation detection methods that, contrary to humans, have already achieved astonishing results in some scenarios. In this study, we focus on the entire face synthesis, which is one specific type of facial manipulation. The main contributions of this study are: i) a novel strategy to remove GAN "fingerprints" from synthetic fake images in order to spoof facial manipulation detection systems, while keeping the visual quality of the resulting images, ii) an in-depth analysis of state-of-the-art detection approaches for the entire face synthesis manipulation, iii) a complete experimental assessment of this type of facial manipulation considering state-of-the-art detection systems, remarking how challenging is this task in unconstrained scenarios, and finally iv) a novel public database named FSRemovalDB produced after applying our proposed GAN-fingerprint removal approach to original synthetic fake images. The observed results led us to conclude that more efforts are required to develop robust facial manipulation detection systems against unseen conditions and spoof techniques such as the one proposed in this study.
On the deformation of the Lamina Cribrosa under intraocular pressure

The deformation of the Lamina Cribrosa under intraocular pressure is studied by means of the linear and nonlinear Ambartsumyan's theory of plate and the refined theory proposed by Rodionova, Titaev and Chernykh. Lamina Cribrosa is modelled as a continuos nonuniform transversal isotropic plate.
Evaluating the Impact of Bank Specific Determinants of Non-performing Loans in Namibia

This paper aimed at assessing the bank-specific determinants for non-performing loans in commercial banks in Namibia. The study employed time-series econometric techniques of unit root, co-integration, impulse response functions and forecast error variance decomposition on the quarterly data covering the period 2001 to 2014. Two models were estimated in which return on assets and return on equity were alternating as profitability measures, among other variables that explain non-performing loans. The results reveal that return on assets, return on equity, loan to total asset ratio, log of total assets are the main determinants of nonperforming loans. In specific terms, a negative relationship between non-performing loans and return on assets as well as return on equity was found. Furthermore, a positive relationship between non-performing loans and loan to total asset ratio was found. Lastly, the results revealed a positive relationship between non-performing loans and log of total assets.
Portfolio rebalancing experiments using the Quantum Alternating Operator Ansatz

This paper investigates the experimental performance of a discrete portfolio optimization problem relevant to the financial services industry on the gate-model of quantum computing. We implement and evaluate a portfolio rebalancing use case on an idealized simulator of a gate-model quantum computer. The characteristics of this exemplar application include trading in discrete lots, non-linear trading costs, and the investment constraint. We design a novel problem encoding and hard constraint mixers for the Quantum Alternating Operator Ansatz, and compare to its predecessor the Quantum Approximate Optimization Algorithm. Experimental analysis demonstrates the potential tractability of this application on Noisy Intermediate-Scale Quantum (NISQ) hardware, identifying portfolios within 5% of the optimal adjusted returns and with the optimal risk for a small eight-stock portfolio.
Live fast, die young: GMC lifetimes in the FIRE cosmological simulations of Milky Way mass galaxies

We present the first measurement of the lifetimes of giant molecular clouds (GMCs) in cosmological simulations at z = 0, using the Latte suite of FIRE-2 simulations of Milky Way (MW) mass galaxies. We track GMCs with total gas mass ≳105 M⊙ at high spatial (∼1 pc), mass (7100 M⊙), and temporal (1 Myr) resolution. Our simulated GMCs are consistent with the distribution of masses for massive GMCs in the MW and nearby galaxies. We find GMC lifetimes of 5–7 Myr, or 1–2 freefall times, on average, with less than 2 per cent of clouds living longer than 20 Myr. We find decreasing GMC lifetimes with increasing virial parameter, and weakly increasing GMC lifetimes with galactocentric radius, implying that environment affects the evolutionary cycle of GMCs. However, our GMC lifetimes show no systematic dependence on GMC mass or amount of star formation. These results are broadly consistent with inferences from the literature and provide an initial investigation into ultimately understanding the physical processes that govern GMC lifetimes in a cosmological setting.
The dust effects on galaxy scaling relations

Accurate galaxy scaling relations are essential for a successful model of galaxy formation and evolution as they provide direct information about the physical mechanisms of galaxy assembly over cosmic time. We present here a detailed analysis of a sample of nearby spiral galaxies taken from the KINGFISH survey. The photometric parameters of the morphological components are obtained from bulge–disc decompositions using galfit data analysis algorithm, with surface photometry of the sample done beforehand. Dust opacities are determined using a previously discovered correlation between the central face-on dust opacity of the disc and the stellar mass surface density. The method and the library of numerical results previously obtained in Pastrav et al. (2013a,b) are used to correct the measured photometric and structural parameters for projection (inclination), dust, and decomposition effects in order to derive their intrinsic values. Galaxy disc scaling relations are then presented, both the measured (observed) and the intrinsic (corrected) ones, in the optical regime, to show the scale of the biases introduced by the aforementioned effects. The slopes of the size–luminosity relations and the dust versus stellar mass are in agreement with values found in other works. We derive mean dust optical depth and dust/stellar mass ratios of the sample, which we find to be consistent with previous studies of nearby spiral galaxies. While our sample is rather small, it is sufficient to quantify the influence of galaxy environment (dust, in this case) when deriving scaling relations.
CHEETAH: An Ultra-Fast, Approximation-Free, and Privacy-Preserved Neural Network Framework based on Joint Obscure Linear and Nonlinear Computations

Machine Learning as a Service (MLaaS) is enabling a wide range of smart applications on end devices. However, such convenience comes with a cost of privacy because users have to upload their private data to the cloud. This research aims to provide effective and efficient MLaaS such that the cloud server learns nothing about user data and the users cannot infer the proprietary model parameters owned by the server. This work makes the following contributions. First, it unveils the fundamental performance bottleneck of existing schemes due to the heavy permutations in computing linear transformation and the use of communication intensive Garbled Circuits for nonlinear transformation. Second, it introduces an ultra-fast secure MLaaS framework, CHEETAH, which features a carefully crafted secret sharing scheme that runs significantly faster than existing schemes without accuracy loss. Third, CHEETAH is evaluated on the benchmark of well-known, practical deep networks such as AlexNet and VGG-16 on the MNIST and ImageNet datasets. The results demonstrate more than 100x speedup over the fastest GAZELLE (Usenix Security'18), 2000x speedup over MiniONN (ACM CCS'17) and five orders of magnitude speedup over CryptoNets (ICML'16). This significant speedup enables a wide range of practical applications based on privacy-preserved deep neural networks.
Adversarial Examples in Modern Machine Learning: A Review

Recent research has found that many families of machine learning models are vulnerable to adversarial examples: inputs that are specifically designed to cause the target model to produce erroneous outputs. In this survey, we focus on machine learning models in the visual domain, where methods for generating and detecting such examples have been most extensively studied. We explore a variety of adversarial attack methods that apply to image-space content, real world adversarial attacks, adversarial defenses, and the transferability property of adversarial examples. We also discuss strengths and weaknesses of various methods of adversarial attack and defense. Our aim is to provide an extensive coverage of the field, furnishing the reader with an intuitive understanding of the mechanics of adversarial attack and defense mechanisms and enlarging the community of researchers studying this fundamental set of problems.
Modeling of the Variable Circumstellar Absorption Features of WD 1145+017

We present an eccentric precessing gas disk model designed to study the variable circumstellar absorption features detected for WD 1145+017, a metal polluted white dwarf with an actively disintegrating asteroid around it. This model, inspired by one recently proposed by Cauley et al., calculates explicitly the gas opacity for any predetermined physical conditions in the disk, predicting the strength and shape of all absorption features, from the UV to the optical, at any given phase of the precession cycle. The successes and failures of this simple model provide valuable insight on the physical characteristics of the gas surrounding the star, notably its composition, temperature, and density. This eccentric disk model also highlights the need for supplementary components, most likely circular rings, in order to explain the presence of zero velocity absorption as well as highly ionized Si iv lines. We find that a precession period of 4.6 ± 0.3 yr can successfully reproduce the shape of the velocity profile observed at most epochs from 2015 April to 2018 January, although minor discrepancies at certain times indicate that the assumed geometric configuration may not be optimal yet. Finally, we show that our model can quantitatively explain the change in morphology of the circumstellar features during transiting events.
Effect of Varying Cadmium Stress on Chickpea (Cicer arietinum L) Seedlings: An Ultrastructural Study

Seed germination, one of the most important phase in the life cycle of a plant, is highly responsive to the existing environment. High levels of heavy metals significantly change the structural orientation of leaf, root and shoot. This paper reports on the effect of Cd toxicity on seed germination, seedling growth, photosynthetic pigment content and structural orientation of vascular tissues in chickpea ( Cicer arietinum L) seedlings. Results showed that inhibition of seed germination and root growth started at 0.10 mM cadmium treatment solution and the highest inhibitive effect was found at 50.0 mM concentration. The accumulation of cadmium in plant parts are in the order root > stem > leaf. From the SEM study it was found that normal orientation of the vascular tissues as well as associated tissues are disrupted and the stomatal complexes with guard cells were highly affected in the leaves. Permanent URL: http://hdl.handle. net/2047/d20018674