Miracle-dz/UniFAR-FTUs huggingface dataset:
A spatio-kinematic model for jets in post-AGB stars,

Aims. We aim to determine the geometry, density gradient, and velocity structure of jets in post-asymptotic giant branch (post-AGB) binaries. Methods. Our high cadence time series of high-resolution optical spectra of jet-creating post-AGB binary systems provide us with a unique tomography of the jet. We determine the spatio-kinematic structure of the jets based on these data by fitting the synthetic spectral line profiles created by our model to the observed, orbital phase-resolved, Hα-line profiles of these systems. The fitting routine is provided with an initial spectrum and is allowed to test three configurations, derived from three specific jet launching models: a stellar jet launched by the star, an X-wind, and a disk wind configuration. We apply a Markov-chain Monte Carlo routine in order to fit our model to the observations. Our fitting code is tested on the post-AGB binary IRAS 19135+3937. Results. We find that a model using the stellar jet configuration gives a marginally better fit to our observations. The jet has a wide half-opening angle of about 76° and reaches velocities up to 870 km s−1. Conclusions. Our methodology is successful in determining some parameters for jets in post-AGB binaries. The model for IRAS 19135+3937 includes a transparent, low density inner region (for a half-opening angle < 40°). The source feeding the accretion disk around the companion is most likely the circumbinary disk. We will apply this jet fitting routine to other jet-creating post-AGB stars in order to provide a more complete description of these objects.
Detailed study of the Milky Way globular cluster Laevens 3

We present a photometric and spectroscopic study of the Milky Way satellite Laevens 3. Using MegaCam/Canada–France–Hawaii Telescope $g$ and $i$ photometry and Keck II/DEIMOS multi-object spectroscopy, we refine the structural and stellar properties of the system. The Laevens 3 colour–magnitude diagram shows that it is quite metal-poor, old ($13.0 \pm 1.0$ Gyr), and at a distance of $61.4 \pm 1.0$ kpc, partly based on two RR Lyrae stars. The system is faint ($M_V = -2.8^{+0.2}_{-0.3}$ mag) and compact ($r_h = 11.4 \pm 1.0$ pc). From the spectroscopy, we constrain the systemic metallicity (${\rm [Fe/H]}_\mathrm{spectro} = -1.8 \pm 0.1$ dex) but the metallicity and velocity dispersions are both unresolved. Using Gaia DR2, we infer a mean proper motion of $(\mu _\alpha ^*,\mu _\delta)=(0.51 \pm 0.28,-0.83 \pm 0.27)$ mas yr−1, which, combined with the system’s radial velocity ($\langle v_r\rangle = -70.2 \pm 0.5 {\rm \, km \,\, s^{-1}}$), translates into a halo orbit with a pericenter and apocenter of $40.7 ^{+5.6}_{-14.7}$ and $85.6^{+17.2}_{-5.9}$ kpc, respectively. Overall, Laevens 3 shares the typical properties of the Milky Way’s outer halo globular clusters. Furthermore, we find that this system shows signs of mass segregation that strengthens our conclusion that Laevens 3 is a globular cluster.
Improves Monetization Using Big Data Analytics

Vungle Inc. Improves Monetization Using Big Data Analytics Bert De Reyck UCL School of Management, University College London, London, United Kingdom, bdereyck@ucl.ac. uk Ioannis Fragkos Department of Technology and Operations Management, Rotterdam School of Management, Rotterdam, The Netherlands, fragkos@rsm.nl Yael Grushka-Cockayne, Casey Lichtendahl Darden School of Business, University of Virginia, Charlottesville, Virginia 22903, {grushkay@darden.virginia. edu, lichtendahlc@darden.virginia. edu} Hammond Guerin Data Science Team, Vungle Inc., San Francisco, California 94107, hammond.guerin@vungle.com Andrew Kritzer BookMD, Los Angeles, California 90081, akritzer@gmail.com
Title Nonparametric Bayesina Sparse Factor Analysis for Frequency Doain Blind Source Separation without

Blind source separation (BSS) and sound activity detection (SAD) from a sound source mixture with minimum prior information are two major requirements for computational auditory scene analysis that recognizes auditory events in many environments. In daily environments, BSS suffers from many problems such as reverberation, a permutation problem in frequency-domain processing, and uncertainty about the number of sources in the observed mixture. While many conventional BSS methods resort to a cascaded combination of subprocesses, e.g., frequency-wise separation and permutation resolution, to overcome these problems, their outcomes may be affected by the worst subprocess. Our aim is to develop a unified framework to cope with these problems. Our method, called permutationfree infinite sparse factor analysis (PF-ISFA), is based on a nonparametric Bayesian framework that enables inference without a pre-determined number of sources. It solves BSS, SAD and the permutation problem at the same time. Our method has two key ideas: unified source activities for all the frequency bins and the activation probabilities of all the frequency bins of all the sources. Experiments were carried out to evaluate the separation performance and the SAD performance under four reverberant conditions. For separation performance in the BSS EVAL criteria, our method outperformed conventional complex ISFA under all conditions. For SAD performance, our method outperformed the conventional method by 5.9–0.5% in F-measure under the condition RT20 = 30–600 [ms], respectively.
PHYSICALLY EFFECTIVE FIBER FOR DAIRY COWS : CURRENT PERSPECTIVES

In 1997, a series of papers were published in the Journal of Dairy Science from a symposium entitled “Meeting the Fiber Requirements of Dairy Cows. ” In this symposium, the term physically effective NDF (peNDF) was first defined and a system for using peNDF in ration formulation was proposed (Mertens, 1997). Since then, this measurement has become widely used (and misused) in applied dairy nutrition. The purpose of this paper is to present some current perspectives on how peNDF is used in the field today, discuss current limitations in our ability to measure peNDF particularly on-farm, and challenges for measuring and using peNDF in the future.
Image Denoising by Bayesian Regression

We present a kernel based approach for image de-noising in the spatial domain. The crux of evaluation for the kernel weights is addressed by a Bayesian regression. This approach introduces an adaptive filter, well preserving edges and thin structures in the image. The hyper-parameters in the model as well as the predictive distribution functions are estimated through an efficient iterative scheme. We evaluate our method on common test images, contaminated by white Gaussian noise. Qualitative results show the capability of our method to smooth out the noise while preserving the edges and fine texture. Quantitative comparison with the celebrated total variation (TV) and several wavelet methods ranks our approach among state-of-the-art denoising algorithms. Further advantages of our method include the capability of direct and simple integration of the noise PDF into the de-noising framework. The suggested method is fully automatic and can equally be applied to other regression problems.
Autobiographical memory and social skills of men and women

This study investigated gender-specific relationships between autobiographical memory (AM) performance and two social skills, namely empathy and assertiveness. One hundred and fourteen male and female students were tested with a questionnaire on AM and two test scales for empathy and assertiveness. The results revealed positive correlations between AM performance and both social skills, thus underscoring the social function of AM. In addition we found several gender differences. Women showed superior AM performance and also scored higher in empathy, while men scored higher in assertiveness. We propose that AM, empathy, and assertiveness develop in gender-specific mutual dependencies reflecting parental socialization. Copyright © 2005 John Wiley & Sons, Ltd.
You Can : Matchmaking Encryption and its Applications

We introduce a new form of encryption that we name matchmaking encryption (ME). Using ME, sender S and receiver R (each with its own attributes) can both specify policies the other party must satisfy in order for the message to be revealed. The main security guarantee is that of privacy-preserving policy matching: During decryption nothing is leaked beyond the fact that a match occurred/did not occur. ME opens up new ways of secretly communicating, and enables several new applications where both participants can specify fine-grained access policies to encrypted data. For instance, in social matchmaking, S can encrypt a file containing his/her personal details and specify a policy so that the file can be decrypted only by his/her ideal partner. On the other end, a receiver R will be able to decrypt the file only if S corresponds to his/her ideal partner defined through a policy. On the theoretical side, we define security for ME, as well as provide generic frameworks for constructing ME from functional encryption. These constructions need to face the technical challenge of simultaneously checking the policies chosen by S and R, to avoid any leakage. On the practical side, we construct an efficient scheme for the identity-based setting, with provable security in the random oracle model under the standard BDH assumption. We implement and evaluate our scheme and provide experimental evidence that our construction is practical. We also apply identity-based ME to a concrete use case, in particular for creating an anonymous bulletin board over a Tor network.
Using Evowave for Logical Coupling Analysis of a Long-lived Software System

Logical coupling reveals implicit dependencies between program entities, by measuring how often they changed together during development. The comprehension of how the logical coupling property manifests itself in the project is a key activity. Software Evolution Visualization (SEV) has been a promising approach to this end. However, this is not trivial, since SEV has to handle different software entities and attributes, and still deals with the temporal dimension of evolution. In this sense, we have been working on the specification, development and evaluation of a novel SEV tool, called EVOWAVE. This novel visualization metaphor is able to visualize different types of data generated in software evolution using both overview-based and detail-based approaches. It can be applied to different software engineering tasks and domains. In this paper, we present a logical coupling study we conducted in order to evaluate this tool in this important domain.
How Transparency Affects Distributional Politics: A Field Experiment among Elected Incumbents in Malawi

How does transparency affect distributional politics? We theorize that transparency conditions how officials choose among recipient communities, compelling them to allocate to needy communities rather than those with political supporters. We present the results of a field experiment in which 333 locally elected incumbents in Malawi made a series of real and meaningful choices about the allocation of NGO-provided development goods to schools in their constituency. Prior to allocating goods to recipient school communities, half of the incumbents were informed that letters about their allocation decisions would be sent to local oversight committees who are formally empowered to liaise between citizens and the government to foster development. We find evidence suggesting that this transparency treatment caused incumbents to allocate goods to recipient school communities with greater economic need, and to allocate less to schools in politically pivotal areas; though these effects are only observed among incumbents who are knowledgeable about their communities. To our knowledge, this is the first experimental evaluation of theoretical claims about the role of transparency in distributional politics using in-office elected leaders as participants and observing real distributional decisions.
Modern Trends in Imaging XII Advanced methods in fluorescence microscopy

It requires a good deal of will power to resist hyperbole in considering the advances that have been achieved in fluorescence microscopy in the last 25 years. Our effort has been to survey the modalities of microscopic fluorescence imaging available to cell biologists and perhaps useful for diagnostic pathologists. The gamut extends from established confocal laser scanning through multiphoton and TIRF to the emerging technologies of super-resolution microscopy that breech the Abbé limit of resolution. Also considered are the recent innovations in structured and light sheet illumination, the use of FRET and molecular beacons that exploit specific characteristics of designer fluorescent proteins, fluorescence speckles, and second harmonic generation for native anisometric structures like collagen, microtubules and sarcomeres.
A 3 D analytical modeling of tri-gate tunneling field-effect transistors

In this paper, a three-dimensional (3D) analytical solution of the electrostatic potential is derived for the trigate tunneling field-effect transistors (TG TFETs) based on the perimeter-weighted-sum approach. The model is derived by separating the device into a symmetric and an asymmetric double-gate (DG) TFETs and then solving the 2D Poisson’s equation for these structures. The subthreshold tunneling current expression is extracted by numerical integrating the band-to-band tunneling generation rate over the volume of the device. It is shown that the potential distributions, the electric field profile, and the tunneling current predicted by the analytical model are in close agreement with the 3D device simulation results without the need of fitting parameters. Additionally, the dependence of the tunneling current on the device parameters in terms of the gate oxide thickness, gate dielectric constant, channel length, and applied drain bias is investigated and also demonstrated its agreement with the device simulations.
Conjunctive Visual Forms

Visual exploration of multidimensional data is a process of isolating and extracting relationships within and between dimensions. Coordinated multiple view approaches are particularly effective for visual exploration because they support precise expression of heterogeneous multidimensional queries using simple interactions. Recent visual analytics research has made significant progress in identifying and understanding patterns of composed views and coordinations that support fast, flexible, and open-ended data exploration. What is missing is formalization of the space of expressible queries in terms of visual representation and interaction. This paper introduces the Conjunctive Visual Form model in which visual exploration consists of interactively-driven sequences of transitions between visual states that correspond to conjunctive normal forms in boolean logic. The model predicts several new and useful ways to extend the space of rapidly expressible queries through addition of simple interactive capabilities to existing compositional patterns. Two recent related visual tools offer a subset of these capabilities, providing a basis for conjecturing about such extensions.
Chapter 3 Description and Preliminary Analysis of New Hominid Craniodental Fossils from the Swartkrans Formation

Nearly 100 hominid craniodental fossils have been recovered from the Swartkrans Formation through recent excavations by C. K. Brain. Specimens derive from the Member 1 Hanging Remnant breccia, as well as from in situ deposits that constitute Member 1 Lower Bank, Member 2 and Member 3. The remains of some six individuals are attributable to Homo, while the remainder of the fossils that can be identified taxonomically are ascribable to Paranthropus. The Paranthropus specimens from the various lithostratigraphic units within the Swartkrans cave are morphologically and metrically very similar to one another. It is proposed that all are attributable to a single species. Comparisons between the Swartkrans and Kromdraai Paranthropus samples reveal differences in tooth Size and shape that may attest to their taxonomic distinctiveness.
Acute myeloid leukemia LSD 1 inhibition by tranylcypromine derivatives interferes with GFI 1-mediated repression of PU . 1 target genes and induces differentiation in AML

LSD1 has emerged as a promising epigenetic target in the treatment of acute myeloid leukemia (AML). We used two murine AML models based on retroviral overexpression of Hoxa9/Meis1 (H9M) or MN1 to study LSD1 loss of function in AML. The conditional knockout of Lsd1 resulted in differentiation with both granulocytic and monocytic features and increased ATRA sensitivity and extended the survival of mice with H9M-driven AML. The conditional knockout led to an increased expression of multiple genes regulated by the important myeloid transcription factors GFI1 and PU.1. These include the transcription factors GFI1B and IRF8. We also compared the effect of different irreversible and reversible inhibitors of LSD1 in AML and could show that only tranylcypromine derivatives were capable of inducing a differentiation response. We employed a conditional knock-in model of inactive, mutant LSD1 to study the effect of only interfering with LSD1 enzymatic activity. While this was sufficient to initiate differentiation, it did not result in a survival benefit in mice. Hence, we believe that targeting both enzymatic and scaffolding functions of LSD1 is required to efficiently treat AML. This finding as well as the identified biomarkers may be relevant for the treatment of AML patients with LSD1 inhibitors.
CHAPTER 1 Modeling the Vascular System and Its Capillary Networks

Modeling of the vascular system and its capillary networks is considered within the context of associated scaling laws relating measurements of cardiovascular variables of mammals ranging in size from the mouse to the human and onward to the elephant. Topics include competing effects of viscous and inertial resistances to blood flow in the system and their appropriate separation for modeling purposes. Adequacy of the separation is confirmed by the demonstrated success of the scaling theory in consolidating size-dependent measurements into a single underlying description. Applications of the work include scaling of form and function for different-size systems directly to the human for confirmation of physiological descriptions and for practical matters such as the projection of safe drug dosage from small mammals to humans. Specific topics of form include discussion of detailed scaling laws for radius and length of arterial and venous vessel and for the radius, length, and number of capillary vessels. Topics of function include discussion of underlying physiological processes responsible for heart rate, ventricular outflow, blood circulation time, and kidney operation. The scaling of therapeutic drug concentrations from mouse to human is considered as an illustration of practical matters of interest.
On importance-weighted autoencoders

The importance weighted autoencoder (IWAE) (Burda et al., 2016) is a popular variational-inference method which achieves a tighter evidence bound (and hence a lower bias) than standard variational autoencoders by optimising a multi-sample objective, i.e. an objective that is expressible as an integral over $K > 1$ Monte Carlo samples. Unfortunately, IWAE crucially relies on the availability of reparametrisations and even if these exist, the multi-sample objective leads to inference-network gradients which break down as $K$ is increased (Rainforth et al., 2018). This breakdown can only be circumvented by removing high-variance score-function terms, either by heuristically ignoring them (which yields the 'sticking-the-landing' IWAE (IWAE-STL) gradient from Roeder et al. (2017)) or through an identity from Tucker et al. (2019) (which yields the 'doubly-reparametrised' IWAE (IWAE-DREG) gradient). In this work, we argue that directly optimising the proposal distribution in importance sampling as in the reweighted wake-sleep (RWS) algorithm from Bornschein & Bengio (2015) is preferable to optimising IWAE-type multi-sample objectives. To formalise this argument, we introduce an adaptive-importance sampling framework termed adaptive importance sampling for learning (AISLE) which slightly generalises the RWS algorithm. We then show that AISLE admits IWAE-STL and IWAE-DREG (i.e. the IWAE-gradients which avoid breakdown) as special cases.
Human Rhinovirus at Naturally Occurring COPD Exacerbation

Chronic obstructive pulmonary disease (COPD) is an inflammatory condition of the lung caused by an abnormal response to particles and noxious gases, primarily cigarette smoke. Patients suffer daily symptoms and can have episodes of worsening symptoms termed acute exacerbations. Exacerbations are associated with impaired quality of life, faster lung function decline, higher mortality and increased risk of hospitalisation. The aetiology of COPD exacerbations is controversial; however respiratory viral and bacterial infections are an important feature of exacerbations. This study utilised real-time qPCR to measure prevalence and load of human rhinovirus (HRV) in stable COPD and during the time-course of naturally occurring exacerbations and their recovery. HRV was assessed in association with upper respiratory tract (URT) symptoms namely cold symptoms and sore throats, secondary bacterial infection, patient reported outcomes and exacerbation frequency. Additionally, respiratory syncytial virus (RSV) was semi-quantitatively examined in stable COPD and at exacerbation. The original contribution of this work to the field is that HRV prevalence and load are highest at exacerbation presentation and decrease during recovery. HRV load is higher in the presence of URT symptoms compared to the load without, and the load remains higher for longer with both symptoms compared to only one. This study described novel evidence for the development of secondary bacterial infection after HRV infection in natural exacerbations, and demonstrated that HRV infection is associated with patient reported outcomes. Patients with HRV had higher exacerbation frequencies compared to those without HRV. RSV prevalence did not change significantly between stable COPD and exacerbation. The findings from this thesis have important implications in terms of exacerbation therapy. The evidence provided may allow appropriate targeting of therapeutic interventions therefore reducing exacerbation severity and frequency. These findings emphasise the importance of rapid development of therapeutic targets for the prevention and treatment of HRV infection in COPD patients.