Miracle-dz/UniFAR-FTUs huggingface dataset:
Ionized haloes in planetary nebulae: new discoveries, literature compilation and basic statistical properties

We present a comprehensive observational study of haloes around planetary nebulae (PNe). Deep Hα+[N ii] and/or [O iii] narrow-band images have been obtained for 35 PNe, and faint extended haloes have been newly discovered in the following 10 objects: Cn 1-5, IC 2165, IC 2553, NGC 2792, NGC 2867, NGC 3918, NGC 5979, NGC 6578, PB 4, and possibly IC 1747. New deep images have also been obtained of other known or suspected haloes, including the huge extended emission around NGC 3242 and Sh 2-200. In addition, the literature was searched, and together with the new observations an improved data base containing some 50 PN haloes has been compiled. The halo sample is illustrated in an image atlas contained in this paper, and the original images are made available for use by the scientific community at http://www.ing. iac.es/rcorradi/HALOES/. The haloes have been classified following the predictions of modern radiation-hydrodynamical simulations that describe the formation and evolution of ionized multiple shells and haloes around PNe. According to the models, the observed haloes have been divided into the following groups: (i) circular or slightly elliptical asymptotic giant branch (AGB) haloes, which contain the signature of the last thermal pulse on the AGB; (ii) highly asymmetrical AGB haloes; (iii) candidate recombination haloes, i.e. limb-brightened extended shells that are expected to be produced by recombination during the late post-AGB evolution, when the luminosity of the central star drops rapidly by a significant factor; (iv) uncertain cases which deserve further study for a reliable classification; (v) non-detections, i.e. PNe in which no halo is found to a level of ≲10−3 the peak surface brightness of the inner nebulae. We discuss the properties of the haloes: detection rate, morphology, location of the central stars in the Hertzsprung–Russell diagram, sizes, surface brightness profiles, and kinematical ages. Among the most notable results, we find that, as predicted by models, ionized AGB haloes are a quite common phenomenon in PNe, having been found in 60 per cent of elliptical PNe for which adequately deep images exist. Another 10 per cent show possible recombination haloes. In addition, using the kinematical ages of the haloes and inner nebulae, we conclude that most of the PNe with observed AGB haloes have left the AGB far from a thermal pulse, at a phase when hydrogen burning is the dominant energy source. We find no significant differences between the AGB haloes of hydrogen-poor and hydrogen-rich central stars.
Comet Siding Spring's influence on the Mars' ionosphere

On October 19th 2014, Mars experienced a close encounter with Comet C/2013 A1 (Siding Spring), at a distance of ~138,000 km. The coma washed over Mars and the planet passed directly through the cometary debris stream, producing significant effects in Mars' upper atmosphere. We present here an overview of ionospheric measurements performed during the comet encounter with Mars Express, MAVEN, and Mars Reconnaissance Orbiter. We discuss the comet's influence on the ionosphere through different processes that work at different altitudes: magnetospheric disturbances, impact of cometary pickup ions, and deposition of cometary dust.
Biologically-Constrained Graphs for Global Connectomics Reconstruction

Most current state-of-the-art connectome reconstruction pipelines have two major steps: initial pixel-based segmentation with affinity prediction and watershed transform, and refined segmentation by merging over-segmented regions. These methods rely only on local context and are typically agnostic to the underlying biology. Since a few merge errors can lead to several incorrectly merged neuronal processes, these algorithms are currently tuned towards over-segmentation producing an overburden of costly proofreading. We propose a third step for connectomics reconstruction pipelines to refine an over-segmentation using both local and global context with an emphasis on adhering to the underlying biology. We first extract a graph from an input segmentation where nodes correspond to segment labels and edges indicate potential split errors in the over-segmentation. In order to increase throughput and allow for large-scale reconstruction, we employ biologically inspired geometric constraints based on neuron morphology to reduce the number of nodes and edges. Next, two neural networks learn these neuronal shapes to further aid the graph construction process. Lastly, we reformulate the region merging problem as a graph partitioning one to leverage global context. We demonstrate the performance of our approach on four real-world connectomics datasets with an average variation of information improvement of 21.3%.
Rational Modeling of Narrow Band Antenna by Vector Fitting

This paper proposes a new methodology in rational modeling of narrow band antenna. Through the analysis for the measured Z-parameter of the antenna via vector fitting method (VFM), the rational fraction polynomial can fit the Z-parameter accurately. By comparing the basic models with the polynomial, the rational model of the antenna and parameters can be derived. The model has high accuracy in characterizing the antenna, and plays a guiding role in narrow band antenna design. Introduction Narrow band antenna is a new type of antenna, which is gradually developed in the last 30 years. Compared with the common microwave antenna, narrow band antenna has the advantages of miniaturization, ease of integration, good directivity, etc. It has been widely used in Terahertz research [1], Wireless Local Area Network (WLAN) research, Global Positioning System (GPS), etc. In the design of the narrow band antenna, developing a rational model for the antenna is one of the most common and practical way to characterize the electromagnetic characteristics of the antenna [2]. In general, the rational model is closely related to the physics and geometry of the antenna, which can provide a good reference for the design of the antenna through simulating the parameters of the rational model [3]. There are two basic requirements to propose the rational model [4]. The first one is the impedance requirement: the input impedance Zin and admittances Yin of the rational model should be matched to those of the modeled antenna. The second is the radiated behavior requirement: the load resistor RL should be equal to the resistor of the antenna’s radiation Rrad. In order to meet the requirements, the numerical curve fitting is one of the most common ways to extract parameters in the development of the rational model [5]. However, the numerical fitting method has an assignable problem. It often has a large amount of computation and is difficult to converge and get stable solutions. This paper adopts a rational function approximation approach called vector-fitting [6, 7] to construct the rational model which have advantages in lower computation, better stability over traditional numerical simulation. Model parameters can be computed through the poles and residues of VF method results. Through using the vector fitting method to fit the measured data of the Zparameters of the narrow band
AFFECTIVE COMPUTING AND SENTIMENT ANALYSIS Sentiment and Sarcasm Classification with Multitask Learning

The surge of Internet has enabled large-scale text-based opinion sharing on a wide range of topics. This has led to the opportunity of mining user sentiment on various subjects from the data publicly available over the Internet. The most important task in the analysis of users’ opinions is sentiment classification: determining whether a given text, such as a user review, comment, or tweet, carries positive or negative polarity.
Relationship of loss, mean age of air and the distribution of CFCs to stratospheric circulation and implications for atmospheric lifetimes

[1] Projections of the recovery of the ozone layer are made with global atmospheric models using a specified time series of mixing ratios of ozone depleting substances (ODSs) at the lower boundary. This time series is calculated using atmospheric mixing ratio observations, emission rates, and an estimate for the atmospheric lifetime. ODS destruction and simulated atmospheric-lifetime vary among models because they depend on the simulated stratospheric transport and mixing. We investigate the balance between the annual change in ODS burden, its atmospheric loss, and the annual ODS input to the atmosphere using several models. Some models produce realistic distributions for the mean age of air and some do not. Back trajectory calculations relate the fractional release (one minus the amount of ODS at a location relative to its stratospheric entry value) to the mean age through the age spectrum, showing that, for the individual spectrum elements, the maximum altitude and loss increase with age. Models with faster circulations produce ‘‘young’’ distributions for the age of air and fail to reproduce the observed relationship between the mean age of air and the fractional release. Models with realistic mean age of air reproduce the observed relationship. These models yield a lifetime for CFCl3 of � 56 years, longer than the 45 year lifetime currently used to project future mixing ratios. Use of flux boundary conditions in assessment models would have several advantages, including consistency between the ODS evolution and simulated loss even if the simulated residual circulation changes due to climate change.
Periodic X-ray Modulation and its Possible Relation with Orbital Elements in Compact Binaries

Stellar companion of a black hole orbiting in an eccentric orbit will experience modulating tidal force with a periodicity same as that of the orbital period. This, in turn, is expected to modulate accretion rates, and thus the seed photon flux which are inverse Comptonized to produce harder X-rays are expected to be modulated. However, there could be several other effects, such as eclipses, reflection from winds, superhump phenomena etc., which could also modulate the radiation at about the same frequency. By analyzing complete all sky monitor (ASM) data (1.5−12 keV) of RXTE and all sky survey data (15 − 50 keV) of Swift/BAT satellites, we find presence of this periodicity in several objects. If we assume that this modulation is solely due to tidal effects, the RMS-value of the peak in power density spectrum allows us to estimate eccentricities of these orbits. Surprisingly, these agree with eccentricities measured by independent means for some of these objects. For the rest, our estimate of eccentricities may be taken as the upper limit.
A methodology and model for the pull-in parameters of electrostatic actuators

This paper presents a generalized model for the pull-in phenomenon in electrostatic actuators with a single input, either charge or voltage. The pull-in phenomenon of a general electrostatic actuator with a single input is represented by an algebraic equation referred to as the pull-in equation. This equation directly yields the pull-in parameters, namely, the pull-in voltage or pull-in charge and the pull-in displacement. The model presented here permits the analysis of a wide range of cases, including nonlinear mechanical effects as well as various nonlinear, nonideal, and parasitic electrical effects. In some of the cases, an analytic solution is derived, which provides physical insight into how the pull-in parameters depend upon the design and properties of the actuator. The pull-in equation can also yield rapid numerical solutions, allowing interactive and optimal design. The model is then utilized to analyze analytically the case of a Duffing spring, previously analyzed numerically by Hung and Senturia, and captures the variations of the pull-in parameters in the continuum between a perfectly linear spring and a cubic spring. Several other case studies are described and analyzed using the pull-in equation, including parallel-plate and tilted-plate (torsion) actuators taking into account the fringing field capacitance, feedback and parasitic capacitance, trapped charges, an external force, and large displacements.
An Analyzing of different Techniques and Tools to Recover Data from Volatile Memory

— Computer forensics has recently gained significant popularity with many local law enforcement agencies. It is currently employed in fraud, theft, drug enforcement and almost every other enforcement activity. There are many relatively new tools available that have been developed in order to recover and dissect the information that can be gleaned from data storage area like hard-disk, pen drive, etc. it’s all like a volatile memory, but because this is a relatively new and fast-growing field many forensic analysts do not know or take advantage of these assets. Memory like Volatile memory may contain many pieces of information relevant to a forensic investigation, such as passwords, cryptographic keys, and other data. Having the knowledge which type of method use and tools needed to recover that data is essential, and this capability is becoming increasingly more relevant as hard drive encryption and other security mechanisms make traditional hard disk forensics more challenging. This research will cover the theory behind volatile memory analysis, including why it is important, what kinds of data can be recovered, and the potential pitfalls of this type of analysis, as well as techniques for recovering and analyzing volatile data and currently available toolkits that have been developed for this purpose.
ELUCIDATING THE STRUCTURE OF SOLID / ELECTROLYTE INTERFACES Force probe experiments at hydrophilic , hydrophobic and electri ed aqueous

Solid electrolyte interfaces are central to reactivity, stability and self-organization in a large range of complementary  elds and disciplines. It is widely appreciated, that solid|solution interfaces are central to processes involving cell-to-substrate interaction[1-3], self-assembly and self-organization in biological and biomaterials4, stability of colloidal dispersions and electrochemical energy storage and electro-catalysis [5-6] as well as corrosion[7].
Adapted Appearance ( c ) Student Model Output ( a ) Baseline Appearance ( b ) Teacher Adaptation Target Adaptation Target Interactive Video Object Segmentation using Teacher-Student Adaptation

Video object segmentation is an essential task in robot manipulation to facilitate grasping and learning affordances. Incremental learning is important for robotics in unstructured environments, since the total number of objects and their variations can be intractable. Inspired by the children learning process, human robot interaction (HRI) can be utilized to teach robots about the world guided by humans similar to how children learn from a parent or a teacher. A human teacher can show potential objects of interest to the robot, which is able to self adapt to the teaching signal without providing manual segmentation labels. We propose a novel teacher-student learning paradigm to teach robots about their surrounding environment. A two-stream motion and appearance “teacher“ network provides pseudo-labels to adapt an appearance “student“ network. The student network is able to segment the newly learned objects in other scenes, whether they are static or in motion. We also introduce a carefully designed dataset that serves the proposed HRI setup, denoted as (I)nteractive (V)ideo (O)bject (S)egmentation. Our IVOS dataset contains teaching videos of different objects, and manipulation tasks. Unlike previous datasets, IVOS provides manipulation tasks sequences with segmentation annotation along with the waypoints for the robot trajectories. It also provides segmentation annotation for the different transformations such as translation, scale, planar rotation, and out-of-plane rotation. Our proposed adaptation method outperforms the state-of-the-art on DAVIS and FBMS with 6.8% and 1.2% in F-measure respectively. It improves over the baseline on IVOS dataset with 46.1% and 25.9% in mIoU.
Bulk diamond optical waveguides fabricated by focused femtosecond laser pulses

Diamond’s nitrogen-vacancy (NV) centers show great promise in sensing applications and quantum computing due to their long electron spin coherence time and their ability to be located, manipulated and read out using light. The electrons of the NV center, largely localized at the vacancy site, combine to form a spin triplet, which can be polarized with 532- nm laser light, even at room temperature. The NV's states are isolated from environmental perturbations making their spin coherence comparable to trapped ions. An important breakthrough would be in connecting, using waveguides, multiple diamond NVs together optically. However, the inertness of diamond is a significant hurdle for the fabrication of integrated optics similar to those that revolutionized silicon photonics. In this work we show the possibility of buried waveguide fabrication in diamond, enabled by focused femtosecond high repetition rate laser pulses. We use μRaman spectroscopy to gain better insight into the structure and refractive index profile of the optical waveguides.
Matrix product operators for sequence-to-sequence learning

The method of choice to study one-dimensional strongly interacting many body quantum systems is based on matrix product states and operators. Such method allows to explore the most relevant, and numerically manageable, portion of an exponentially large space. Here we show how to construct a machine learning model in which matrix product operators are trained to implement sequence to sequence prediction, i.e. given a sequence at a time step, it allows one to predict the next sequence. We then apply our algorithm to cellular automata (for which we show exact analytical solutions in terms of matrix product operators), and to nonlinear coupled maps. We show advantages of the proposed algorithm when compared to conditional random fields and bidirectional long short-term memory neural network. To highlight the flexibility of the algorithm, we also show how it can perform classification tasks.
Nonlinear dynamics induced by linear wave interactions in multilayered flows

Using simple kinematics, we propose a general theory of linear wave interactions between the interfacial waves of a two-dimensional (2D), inviscid, multilayered fluid system. The strength of our formalism is that one does not have to specify the physics of the waves in advance. Wave interactions may lead to instabilities, which may or may not be of the familiar ‘normal-mode’ type. Contrary to intuition, the underlying dynamical system describing linear wave interactions is found to be nonlinear. Specifically, a saw-tooth jet profile with three interfaces possessing kinematic and geometric symmetry is explored. Fixed points of the system for different ranges of a Froude number like control parameter $\unicode[STIX]{x1D6FE}$ are derived, and their stability evaluated. Depending upon the initial condition and $\unicode[STIX]{x1D6FE}$ , the dynamical system may reveal transient growth, weakly positive Lyapunov exponents, as well as different nonlinear phenomena such as the formation of periodic and pseudo-periodic orbits. All these occur for those ranges of $\unicode[STIX]{x1D6FE}$ where normal-mode theory predicts neutral stability. Such rich nonlinear phenomena are not observed in a 2D dynamical system resulting from the two-wave problem, which reveals only stable and unstable nodes.
Research and development of a PV converter-based stand-alone power supply system for technical security equipment power supply

The purpose of the work is to develop a methodology for designing a stand-alone power supply system based on photovoltaic (PV) converters for technical security equipment power supply. The object of the study is a PV converter - based stand-alone power supply system. Energy storage units, which are widely used in the designing of power supply systems for power supply of technical security equipment are presented. A methodology for designing a power supply system is used, which takes into account the integral effect of solar insolation, ambient temperature in the range from - 40°C to +50°C, temperature of a PV module and a storage battery; PV module capacity; requirements for independent operation of technical security equipment; electrical characteristics of the solar charge controller (rated open-circuit voltage and rated charge current). To calculate the total solar insolation arriving at the surface of a photovoltaic module, the Kastrov model is used for calculating direct solar radiation; the Berlage model is used for calculating the scattered solar energy and the Berland model is used for calculating insolation in cloudy conditions. The studies of lithium-titanate storage batteries have been carried out in the climate chamber and a corresponding mathematical model has been developed for the temperature-dependent capacity of the battery. To determine solar insolation falling on the tilted surface of the PV module the software has been developed in the C# programming language. The designed PV module-based power supply system provides an independent uninterrupted continuous power supply of equipment under constant consumption of no more than 115.2 Wh per day by technical security equipment. The results of the work can be used in the development of a stand-alone power supply system for power supply of technical security equipment, security and control.
UvA-DARE ( Digital Academic Repository ) A Physical Explanation for Natural Image Statistics

The statistics of texture operators on natural images are empirically determined to conform to a Weibull process. We explain these findings from the physical principles of fragmentation processes. The Weibull parameters are known to indicate the fractal dimension of the underlying system. Hence, we show the Weibull process to have a physical foundation for describing natural image statistics. Keywords— Texture, Natural image statistics, Sequential fragmentation, Fractals.
Insight into non-linearly shaped superconducting whiskers via a synchrotron nanoprobe

We were successful in synthesizing non-linear YBa2Cu3Ox whiskers, i.e. half loops or kinked shapes, which are promising candidates for solid-state devices based on the intrinsic Josephson effect and with improved electrical connections. We report on a complete characterization of their structural properties via a synchrotron nanoprobe as well as laboratory single-crystal diffraction techniques. This investigation allowed us to fully disclose the growth mechanism, which leads to the formation of curved whiskers. The superconducting properties are evaluated in comparison with their straight counterpart, revealing a strong functional analogy and confirming their potential applicability in superconducting electronic devices.
A Comprehensive IS-Enabled Framework and IS Research Agenda to Improve Contributions to Environmental Sustainability by Universities

For more than 25 years, universities have been acknowledged as having the potential to make crucial contributions to addressing the challenges of environmental sustainability. During this time, many universities have undertaken activities in support of sustainability, although few have succeeded in realizing their potential to make significant contributions in research and education or as adopters of sustainable practices within their institutions. This paper aims to assist universities to improve their contributions to the challenges of environmental sustainability by: reviewing current literature guiding universities to support sustainability; identifying gaps in the literature; and, proposing a composite framework to facilitate contributions by IS-enabled innovations that significantly improve the level of sustainability behaviours and practices in universities. An IS research agenda integrated with the Composite Framework is proposed.