Miracle-dz/UniFAR-FTUs huggingface dataset:
Composition of Interstellar Clouds in the Disk and Halo. IV. HD 215733

In this paper we continue our investigation of diffuse clouds in the interstellar medium with an analysis of the line of sight toward the star HD 215733, located in the Galactic halo some 1700 pc below the plane. As in our previous papers, we utilize the component-fitting technique to determine velocities, velocity widths, and column densities for a variety of ions in each of the absorbing regions detected. Our data include a large number of ultraviolet absorption lines observed with the Goddard High Resolution Spectrograph and ground-based observations of Ca II K absorption and H I 21 cm emission. We detect 23 components (absorbing regions) in the low-ionization species toward HD 215733 and seven components in the highly ionized species (i.e., Si3+, C3+, and N4+). The low-ion components arise in H I gas. Gas-phase abundances measured for these components follow the pattern seen for halo stars in our previous studies. These have been interpreted as indicating either that a nearly indestructible population of interstellar grains is present or that the intrinsic abundances of a number of elements in the ISM are significantly subsolar. Kinetic temperatures are estimated for 16 low-ion components. Of these, four (with the highest values of |vLSR|) are warm, with T > 1000 K; six are cold, with T < 300 K. Extensive diagnostic information includes data on the excited atoms C+ and C0, showing that in the cold clouds n(H0) ≃ 25 cm-3, with n(H0)T ≃ 2500 K cm-3. The ionization equilibrium of C0, Mg0, S0, and Ca+ gives log ne values differing systematically by up to 1 dex between these different species. Correction for these differences, together with a somewhat uncertain overall calibration with excited C+, gives values of log ne in the range from -2.1 to -2.7 for the cold clouds in the four best determined cases, and from -1.2 to -1.8 for the 3 warm clouds with measured ne. The cold cloud values yield ne/n(H0) ≃ 2 × 10-4, which suggests ionization of the heavier elements only (with all H neutral), but values higher by half a dex would also be consistent with the data. Strong absorption features of Si3+ and C3+ both appear in three components. For two of these, the ratio of b values between these two species equals the square root of the mass ratio, suggesting thermal broadening at temperatures of 6 × 105 K and 5 × 104 K. The column density ratios would require a temperature of ~8 × 104 K in collisional equilibrium.
Learning a Pedestrian Social Behavior Dictionary

Understanding pedestrian behavior patterns is a key component to building autonomous agents that can navigate among humans. We seek a learned dictionary of pedestrian behavior to obtain a semantic description of pedestrian trajectories. Supervised methods for dictionary learning are impractical since pedestrian behaviors may be unknown a priori and the process of manually generating behavior labels is prohibitively time consuming. We instead utilize a novel, unsupervised framework to create a taxonomy of pedestrian behavior observed in a specific space. First, we learn a trajectory latent space that enables unsupervised clustering to create an interpretable pedestrian behavior dictionary. We show the utility of this dictionary for building pedestrian behavior maps to visualize space usage patterns and for computing the distributions of behaviors. We demonstrate a simple but effective trajectory prediction by conditioning on these behavior labels. While many trajectory analysis methods rely on RNNs or transformers, we develop a lightweight, low-parameter approach and show results comparable to SOTA on the ETH and UCY datasets.
Polaron with quadratic electron-phonon interaction

We present the first numerically exact study of a polaron with quadratic coupling to the oscillator displacement, using two alternative methodological developments. Our results cover both anti-adiabatic and adiabatic regimes and the entire range of electron-phonon coupling $g_2$, from the system's stability threshold at attractive $g_2=-1$ to arbitrary strong repulsion at $g_2 \gg 1$. Key properties of quadratic polarons prove dramatically different from their linear counterparts. They (i) are insensitive even to large quadratic coupling except in the anti-adiabatic limit near the threshold of instability at attraction; (ii) depend only on the adiabatic ratio but are insensitive to the electron dispersion and dimension of space; (iii) feature weak lattice deformations even at the instability point. Our results are of direct relevance to properties of electrons at low densities in polar materials, including recent proposals for their superconducting states.
Improving Zero-shot Generalization and Robustness of Multi-Modal Models

Multi-modal- image-text models such as CLIP and LiT have demonstrated impressive performance on image classification benchmarks and their zero-shot generalization ability is particularly exciting. While the top-5 zero-shot accuracies of these models are very high, the top-1 accuracies are much lower (over 25% gap in some cases). We investigate the reasons for this performance gap and find that many of the failure cases are caused by ambiguity in the text prompts. First, we develop a simple and efficient zero-shot post-hoc method to identify images whose top-1 prediction is likely to be incorrect, by measuring consistency of the predictions w.r. t. multiple prompts and image transformations. We show that our procedure better predicts mistakes, outperforming the popular max logit baseline on selective prediction tasks. Next, we propose a simple and efficient way to improve accuracy on such uncertain images by making use of the WordNet hierarchy; specifically we augment the original class by incorporating its parent and children from the semantic label hierarchy, and plug the augmentation into text prompts. We conduct experiments on both CLIP and LiT models with five different ImageNet-based datasets. For CLIP, our method improves the top-1 accuracy by 17.13% on the uncertain subset and 3.6% on the entire ImageNet validation set. We also show that our method improves across ImageNet shifted datasets, four other datasets, and other model architectures such as LiT. The proposed method11Work carried out mainly at Google is hyperparameter-free, requires no additional model training and can be easily scaled to other large multi-modal architectures. Code is available at https://github.com/gyhandy/Hierarchy-CLIP.
FRAME: Evaluating Rationale-Label Consistency Metrics for Free-Text Rationales

Following how humans communicate, free-text rationales aim to use natural language to explain neural language model (LM) behavior. However, free-text rationales' unconstrained nature makes them prone to hallucination, so it is important to have metrics for free-text rationale quality. Existing free-text rationale metrics measure how consistent the rationale is with the LM's predicted label, but there is no protocol for assessing such metrics' reliability. Thus, we propose FRAME, a framework for evaluating rationale-label consistency (RLC) metrics for free-text rationales. FRAME is based on three axioms: (1) good metrics should yield highest scores for reference rationales, which maximize RLC by construction; (2) good metrics should be appropriately sensitive to semantic perturbation of rationales; and (3) good metrics should be robust to variation in the LM's task performance. Across three text classification datasets, we show that existing RLC metrics cannot satisfy all three FRAME axioms, since they are implemented via model pretraining which muddles the metric's signal. Then, we introduce a non-pretraining RLC metric that greatly outperforms baselines on (1) and (3), while performing competitively on (2). Finally, we discuss the limitations of using RLC to evaluate free-text rationales.
Melody transcription via generative pre-training

Despite the central role that melody plays in music perception, it remains an open challenge in music information retrieval to reliably detect the notes of the melody present in an arbitrary music recording. A key challenge in melody transcription is building methods which can handle broad audio containing any number of instrument ensembles and musical styles - existing strategies work well for some melody instruments or styles but not all. To confront this challenge, we leverage representations from Jukebox (Dhariwal et al. 2020), a generative model of broad music audio, thereby improving performance on melody transcription by $20$% relative to conventional spectrogram features. Another obstacle in melody transcription is a lack of training data - we derive a new dataset containing $50$ hours of melody transcriptions from crowdsourced annotations of broad music. The combination of generative pre-training and a new dataset for this task results in $77$% stronger performance on melody transcription relative to the strongest available baseline. By pairing our new melody transcription approach with solutions for beat detection, key estimation, and chord recognition, we build Sheet Sage, a system capable of transcribing human-readable lead sheets directly from music audio. Audio examples can be found at https://chrisdonahue.com/sheetsage and code at https://github.com/chrisdonahue/sheetsage .
Evolution of the Angular Momentum of Molecular Cloud Cores Formed from Filament Fragmentation

The angular momentum of molecular cloud cores plays an important role in the process of star formation. However, the time evolution of the angular momentum of molecular cloud cores is still unclear. In this paper, we perform three-dimensional simulations to investigate the time evolution of the angular momentum of molecular cloud cores formed through filament fragmentation. As a result, we find that most of the cores rotate perpendicular to the filament axis. The mean angular momentum of the cores changes by only around 30% during the initial stage of their formation process and then remains almost constant. In addition, we analyze the internal angular momentum structure of the cores. Although the cores gain angular momentum with various directions from the initial turbulent velocity fluctuations of their parent filaments, the angular momentum profile in each core converges to the self-similar solution. We also show that the degree of complexity of the angular momentum structure in a core decreases slightly with time. Moreover, we perform synthetic observations and show that the angular momentum profile measured from the synthetic mean velocity map is compatible with the observations when the filament inclination is taken into account. The present study suggests a theory of core formation from filament fragmentation where the angular momentum structures of the cores are determined by the velocity fluctuation along the filaments and both are compatible with the observations. This theory also provides new insights into the core properties that could be tested observationally.
Twisted Magnetic Fields in Conducting Fluids

The formation of loops in the lines of force of a twisted magnetic field confined within a cylinder of radius R, first suggested by AIfven (1950a), is discussed by the method of normal modes. The model first becomes unstable with respect to modes which do not lead to the formation of loops. Ignoring this, the condition obtained for loop formation is that the pitch of the twisted field be less than pR.
Pion and nucleon relativistic electromagnetic four-current distributions

The quantum phase-space approach allows one to deﬁne relativistic spatial distributions inside a target with arbitrary spin and arbitrary average momentum. We apply this quasiprobabilistic formalism to the whole electromagnetic four-current operator in the case of spin-0 and spin- 12 targets, study in detail the frame dependence of the corresponding spatial distributions, and compare our results with those from the light-front formalism. While former works focused on the charge distributions, we extend here the investigations to the current distributions. We clarify the role played by the Wigner rotation and argue that electromagnetic properties are most naturally understood in terms of Sachs form factors, contrary to what the light-front formalism previously suggested. Finally, we illustrate our results using the pion and nucleon electromagnetic form factors extracted from experimental data.
Observation errors in all‐sky data assimilation

This article examines the first‐guess (FG) departures of microwave imager radiances assimilated in all‐sky conditions (i.e. clear, cloudy and precipitating). Agreement between FG and observations is good in clear skies, with error standard deviations around 2 K, but in heavy cloud or precipitation errors increase to 20 K. The forecast model is not good at predicting cloud and precipitation with exactly the right intensity or location. This leads to apparently non‐Gaussian behaviour, both heteroscedasticity, i.e. an increase in error with cloud amount, and boundedness, i.e. the size of errors is close to the geophysical range of the observations, which runs from clear to fully cloudy. However, the dependence of FG departure standard deviations on the mean cloud amount is predictable. Using this dependence to normalise the FG departures gives an error distribution that is close to Gaussian. Thus if errors are treated correctly, all‐sky observations can be assimilated successfully under the assumption of Gaussianity on which assimilation systems are based. This ‘symmetric’ error model can be used to provide a robust threshold quality‐control check and to determine the size of observation errors for all‐sky assimilation. In practice, however, this ‘observation’ error is being used to account for the model's difficulty in forecasting cloud, which really comes from errors in the background and in the forecast model. Hence in future it will be necessary to improve the representation of background and model error. Separately, symmetric cloud amount is recommended as a predictor for bias correction schemes, avoiding the sampling problems associated with ‘asymmetric’ predictors like the FG cloud amount. Copyright © 2011 Royal Meteorological Society
Pressure and temperature stabilization of an existing Echelle spectrograph III

The Echelle spectrograph FOCES1 is currently located at the laboratories of Munich University Observatories under pressure and temperature stabilized conditions. It is being used as a test bed for a number of different stability issues related to high precision radial velocity spectroscopy. We utilize FOCES to study spectrograph stability, illumination stability and fiber transport stability. With this work we continue the series of papers that present our efforts to obtain temperature and pressure stabilization in the spectrograph environment. In particular we present first optical measurement results and compare them to simulations previously published. We show the movement of the image on the CCD with changes of pressure and temperature and the stability of the spot positions in the stabilized system using measurements done by a ThAr gas discharge source.
Negative Pressures and Cavitation in Liquid Helium

Cavitation—the formation of bubbles—is a familiar phenomenon. Whenever a liquid is agitated violently, there is a possibility that cavitation will occur (see, for example, figure 1). In the case of boat propellers or hydraulic machines, cavitation is a problem that engineers try to avoid. In other contexts, however, cavitation can be useful—as, for example, in ultrasonic cleaning devices.
Dynamics of non-coalescence in unequal sized, conducting multi-droplet system suspended in an insulating medium under an electric field

Abstract An intriguing experimental observation in electrocoalescence of water-in-oil emulsions is the occurrence of a very low critical electric field, beyond which chaining of droplets and shorting of electrodes is observed, as compared with the experimental and theoretical predictions based on two equal sized water droplets in oil. Motivated by these observations, a numerical, analytical and experimental study on the interaction between multiple, unequal sized, perfectly conducting droplets in a perfectly dielectric medium under an electric field is presented here. We show that the critical capillary number ($Ca_c$), based on the bigger droplet, in a two droplet system, reduces as the radius ratio of the smaller to bigger drop decreases. Secondly, in a system of three equally sized droplets, it is expected that the $Ca_c$ will be smaller than a two equal sized droplet system, since the electric field experienced by the central droplet is higher when surrounded by two droplets instead of one. Our results show that nonlinearity in the system due to both the asymmetric shape deformation and the electrostatic interaction between the multiple droplets, leads to significant reduction in $Ca_c$ for onset of non-coalescence in an unequal sized two droplet system or for equal and unequal sized three droplet systems, as compared with $Ca_c$ for two equal sized droplets. This is possibly one of the underlying mechanisms for observing much smaller $Ca_c$ in emulsions as compared with a system of two equal sized droplets, and could be responsible for a polydisperse water-in-oil emulsion being exceptionally susceptible to chaining under an electric field.
Magnetic reconnection within rolled‐up MHD‐scale Kelvin‐Helmholtz vortices: Two‐fluid simulations including finite electron inertial effects

We have performed two‐dimensional two‐fluid simulations including finite electron inertial effects to investigate the cross‐scale coupling in the evolution of MHD‐scale Kelvin‐Helmholtz (KH) mode. We focus on the model in which density is uniform and only the in‐plane magnetic field component is present. The effects of the velocity jump across the shear layer and those of the variation of the magnetic field intensity across the shear layer are considered. When the shear is strong enough to make a KH vortex highly rolled‐up, within‐the‐vortex reconnection is seen to play crucial roles in determining the structure of the large‐scale vortex itself. Especially when the magnetic field intensity is significantly unbalanced across the shear layer, injection of a magnetic bubble is seen to result from the reconnection process.
Exploring Web-based Translation Resources Applied to Hindi-English Cross-Lingual Information Retrieval

Internet users perceive a multilingual web but are unfamiliar with it due to communication in their regional language called Cross-Lingual Information Retrieval (CLIR). In CLIR, a translation technique is used to translate the user queries into the target documents language. Conventional translation techniques are based on either a manual dictionary or a parallel corpus. While the trending Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) techniques are trained on a parallel corpus. NMT is not so mature for Hindi-English translation, according to the literature, SMT performs better than the NMT. SMT provides a static translation due to the limited vocabularies in the available parallel corpus. It may not provide the translations for missing or unseen words while the web provides a dynamic interface where multiple users are updating information at the same time. The web may provide the translations for missing or unseen words, therefore, the web is effectively used for technically developed languages like English, German, Spanish, Russian, and Chinese. In this paper, different web resources such as Wikipedia, Hindi WordNet & Indo WordNet, ConceptNet, and online dictionary-based translation techniques are proposed and applied to Hindi-English CLIR. Wikipedia-based translation approach incorporates three modules, i.e., exactly matched, partially matched, and disambiguation to address the issues of wrong inter-wiki links, partially matched terms, and ambiguous articles. Hindi WordNet & Indo WorNet attribute ”English synset” and ConceptNet attributes ”Related term” & ”Synonymy” are used for obtaining translations. Further, WordNet path similarity is used to disambiguate translations. Various online dictionaries are available that return multiple relevant and irrelevant translations. The proposed approaches are compared to the SMT where the Wikipedia-based approach achieves approximately similar mean average precision to SMT.
Competency Models for Information Security and Cybersecurity Professionals: Analysis of Existing Work and a New Model

Competency models are widely adopted frameworks that are used to improve human resource functions and education. However, the characteristics of competency models related to the information security and cybersecurity domains are not well understood. To bridge this gap, this study investigates the current state of competency models related to the security domain through qualitative content analysis. Additionally, based on the competency model analysis, an evidence-based competency model is proposed. Examining the content of 27 models, we found that the models can benefit target groups in many different ways, ranging from policymaking to performance management. Owing to their many uses, competency models can arguably help to narrow the skills gap from which the profession is suffering. Nonetheless, the models have their shortcomings. First, the models do not cover all of the topics specified by the Cybersecurity Body of Knowledge (i.e., no model is complete). Second, by omitting social, personal, and methodological competencies, many models reduce the competency profile of a security expert to professional competencies. Addressing the limitations of previous work, the proposed competency model provides a holistic view of the competencies required by security professionals for job achievement and can potentially benefit both the education system and the labor market. To conclude, the implications of the competency model analysis and use cases of the proposed model are discussed.
Option Pricing Trees

This article provides a selective description of numerical techniques for option valuation when the underlying model is based on certain kinds of diffusion processes. It emphasizes models based on discretizing the underlying process on a finite state space at discrete points in time and describes techniques for building both path-dependent and path-independent discrete-time models that can approximate a given continuous-time process for the underlying state variables. Monte Carlo methods or numerical methods for solving partial differential equations are almost completely ignored. In the interest of clarity, the focus is on specific processes to illustrate the basic principles, forgoing technical details that may cloud the basic concepts. The major focus is on describing models that can be realistically implemented in practice.
Discrete-time complementary models and smoothing

Abstract The fact that the smoothing error is a (wide sense) Markov process is somehow surprising since smoothed estimates depend upon both past and future data. In this paper we first give a simple and general proof of this fact. Then we use the so-called complementary models introduced by Weinert and Desai to derive forwards and backwards markovian models for the smoothing error in state-space models. By exploring the structure of the complementary models we show that, under certain restrictions, only two simple structured models exist, one that runs forwards in time and the other that runs backwards in time. The forwards complementary model leads to the forward Rauch-Tung-Striebel (RTS) smoothing formula and to a backwards markovian model for the error, whereas the backwards model leads to the backward RTS formula and to a forwards error model. The two models for the smoothing error can be derived one from the other by a forward-backward transformation that preserves the sample paths. Finally, by using.