Miracle-dz/UniFAR-FTUs huggingface dataset:
Quasar continuum spectrum disfavors black holes with a magnetic monopole charge

Black holes carrying a magnetic monopole charge are a subject of interest for a long time. In this work we explore the possibility of an observational evidence of such black holes carrying a magnetic monopole, namely the Bardeen rotating black holes. We derive the theoretical spectrum from the accretion disk surrounding a Bardeen black hole using the thin-disk approximation. We compare the theoretically derived spectrum with the optical data of eighty Palomar Green quasars to constrain the monopole charge parameter g and the spin parameter a of the quasars. From our analysis we note that the Kerr-scenario in general relativity is observationally more favored than black holes with a monopole charge. We arrive at such a conclusion using error estimators like χ, the Nash-Sutcliffe efficiency, the index of agreement and their modified forms. In particular, black holes with g ≥ 0.03 are outside 99% confidence interval. The implications are discussed.
Self-interacting dark scalar spikes around black holes via relativistic Bondi accretion

We consider the spike mass density profile in a dark halo by self-consistently solving the relativistic Bondi accretion of dark matter onto a non-spining black hole of mass M. We assume that the dominant component of the dark matter in the halo is a Standard model gauge-singlet scalar. Its mass m ≃ 10-5 eV and quartic self-coupling λ ≲ 1019 are constrained to be compatible with the properties of galactic dark halos. In the hydrodynamic limit, we find that the accretion rate is bounded from below, M min = 96πG 2 M 2 m 4/λħ 3. Therefore, for M = 106 M⊙ we have M min ≃ 1.41 × 10-9 M ⊙ yr-1, which is subdominant compared to the Eddington accretion of baryons. The spike density profile ρ 0(r) within the self-gravitating regime cannot be fitted well by a single-power law but a double-power one. Despite that, we can fit ρ 0(r) piecewise and find that ρ 0(r) ∝ r -1.20 near the sound horizon, ρ 0(r) ∝ r -1.00 towards the Bondi radius and ρ 0(r) ∝ r -1.08 for the region in between. This contrasts with more cuspy ρ 0(r) ∝ r -1.75 for dark matter with Coulomb-like self-interaction.
Explainable Artiﬁcial Intelligence for Customer Churning Prediction in Banking

In banking industry, customer churn prediction plays important role in business success due to the fact that the cost of attracting new customers is much more than that of retaining ones. Several Machine Learning (ML) models are being employed to make predictions in customer churn and achieve excellent performance. However, the problem with these models is a lack of transparency and interpretability. The goal of this work is developing explanations for customer churn prediction model using Shapley Additive exPlanations (SHAP) method.
A REVIEW ON SENTIMENT ANALYSIS: SOCIAL MEDIA ABUSE TO WOMEN

: Internet being the basic necessity for humans, plays a significant role in all walks of life as it has become a platform for online learning, exchanging ideas and sharing opinions. The surge in social networking applications has allowed people to use these platforms to voice their opinions for daily issues. This has resulted into in depth work in the field of sentiment analysis of twitter data. Sentiment analysis also referred to as opinion mining is a general form of dialogue preparation task that aims at discovering the sentiments behind opinions in texts on varying topics. Many recent studies in the field of sentiment analysis have also diverted the mind of researches towards daily societal issues. The Social Networking application Twitter is considered to be a popular microblog. This platform allows users to comment or tweet their opinions on a topic of their choice. Much attention is being given to Research on Opinion Investigation or Sentiment Analysis of Twitter data over the last decade which involves dissecting “tweets” (comments) and the content of these expressions by multiusers on varied topics. This review paper emphasises on how women are abused on social networking platforms. The levels of sentiment analysis and approaches of sentiment analysis are also discussed.
Dispersive qubit readout with machine learning

Open quantum systems can undergo dissipative phase transitions, and their critical behavior can be exploited in sensing applications. For example, it can be used to enhance the fidelity of superconducting qubit readout measurements, a central problem toward the creation of reliable quantum hardware. A recently introduced measurement protocol, named ``critical parametric quantum sensing'', uses the parametric (two-photon driven) Kerr resonator's driven-dissipative phase transition to reach single-qubit detection fidelity of 99.9\% [arXiv:2107.04503]. In this work, we improve upon the previous protocol by using machine learning-based classification algorithms to \textit{efficiently and rapidly} extract information from this critical dynamics, which has so far been neglected to focus only on stationary properties. These classification algorithms are applied to the time series data of weak quantum measurements (homodyne detection) of a circuit-QED implementation of the Kerr resonator coupled to a superconducting qubit. This demonstrates how machine learning methods enable a faster and more reliable measurement protocol in critical open quantum systems.
Effect of emitters on quantum state transfer in coupled cavity arrays

Over the last decade, conditions for perfect state transfer in quantum spin chains have been discovered, and their experimental realizations addressed. In this paper, we consider an extension of such studies to quantum state transfer in a coupled cavity array including the effects of atoms in the cavities which can absorb and emit photons as they propagate down the array. Our model is equivalent to previously examined spin chains in the one-excitation sector and in the absence of emitters. We introduce a Monte Carlo approach to the inverse eigenvalue problem which allows the determination of the inter-cavity and cavity-emitter couplings resulting in near-perfect quantum state transfer fidelity, and examine the time dependent polariton wave function through exact diagonalization of the resulting Tavis-Cummings-Hubbard Hamiltonian. The effect of inhomogeneous emitter locations is also evaluated.
A Validation Tool for Designing Reinforcement Learning Environments

Reinforcement learning (RL) has gained increasing attraction in the academia and tech industry with launches to a variety of impactful applications and products. Although research is being actively conducted on many fronts (e.g., offline RL, performance, etc.), many RL practitioners face a challenge that has been largely ignored: determine whether a designed Markov Decision Process (MDP) is valid and meaningful. This study proposes a heuristic-based feature analysis method to validate whether an MDP is well formulated. We believe an MDP suitable for applying RL should contain a set of state features that are both sensitive to actions and predictive in rewards. We tested our method in constructed environments showing that our approach can identify certain invalid environment formulations. As far as we know, performing validity analysis for RL problem formulation is a novel direction. We envision that our tool will serve as a motivational example to help practitioners apply RL in real-world problems more easily.
Compositional Test Generation of Industrial Synchronous Systems

Synchronous systems provide a basic model of embedded systems and industrial systems are modeled as Simulink diagrams and/or Lustre programs. Although the test generation problem is critical in the development of safe systems, it often fails because of the spatial and temporal complexity of the system descriptions. This paper presents a compositional test generation method to address the complexity issue. We regard a test case as a counterexample in safety verification, and represent a test generation process as a deductive proof tree built with dedicated inference rules; we conduct both spatial- and temporal-compositional reasoning along with a modular system structure. A proof tree is generated using our semi-automated scheme involving manual effort on contract generation and automatic processes for counterexample search with SMT solvers. As case studies, the proposed method is applied to four industrial examples involving such features as enabled/triggered subsystems, multiple execution rates, filter components, and nested counters. In the experiments, we successfully generated test cases for target systems that were difficult to deal with using the existing tools.
4H-SiC avalanche photodiode with multistep junction extension termination

4H-SiC avalanche photodiodes (APDs) are fabricated with a multistep junction termination extension. The leakage current density has been dramatically reduced to as low as 1 /spl mu/A/cm/sup 2/ and photo-responsivity up to 10/sup 5/ A/W has been achieved. The 4H-SiC APDs can run very stably at power densities up to 10/sup 4/ W/cm/sup 2/.
UNIST: Unpaired Neural Implicit Shape Translation Network

We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains. Our model is built on autoencoding implicit fields, rather than point clouds which represents the state of the art. Furthermore, our translation network is trained to perform the task over a latent grid representation which combines the merits of both latent-space processing and position awareness, to not only enable drastic shape transforms but also well preserve spatial features and fine local details for natural shape translations. With the same network architecture and only dictated by the input domain pairs, our model can learn both style-preserving content alteration and content-preserving style transfer. We demonstrate the generality and quality of the translation results, and compare them to well-known baselines. Code is available at https://qiminchen.github. io/unist/.
Bundles over Connected Sums

A principal bundle over the connected sum of two manifolds need not be diffeomorphic or even homotopy equivalent to a non-trivial connected sum of manifolds. We show however that the homology of the total space of a bundle formed as a pullback of a bundle over one of the summands is the same as if it had that bundle as a summand. See Theorem 3.3. An application appears in [2]. Examples are given, including one where the total space of the pullback is not homotopy equivalent to a connected sum with that as a summand and some in which it is. Finally, we describe the homology of the total space of a principal U(1) bundle over a 6-manifold of the type described by Wall’s theorem. It is a connected sum of an even number of copies of S×S with a 7-manifold whose homology is Z/k in degree 4 (and Z in degrees 0 and 7, and zero in all other degrees).
Regularity theory and numerical algorithm for the fractional Klein-Kramers equation

Fractional Klein-Kramers equation can well describe subdiffusion in phase space. In this paper, we develop the fully discrete scheme for fractional Klein-Kramers equation based on the backward Euler convolution quadrature and local discontinuous Galerkin methods. Thanks to the obtained sharp regularity estimates in temporal and spatial directions after overcoming the hypocoercivity of the operator, the complete error analyses of the fully discrete scheme are built. % , the main challenge of which comes from the hypocoercivity of the operator. It's worth mentioning that the convergence of the provided scheme is independent of the temporal regularity of the exact solution. Finally, numerical results are proposed to verify the correctness of the theoretical results.
The Many Faces of Anger: A Multicultural Video Dataset of Negative Emotions in the Wild (MFA-Wild)

The portrayal of negative emotions such as anger can vary widely between cultures and contexts, depending on the acceptability of expressing full-blown emotions rather than suppression to maintain harmony. The majority of emotional datasets collect data under the broad label “anger”, but social signals can range from annoyed, contemptuous, angry, furious, hateful, and more. In this work, we curated the first in-the-wild multicultural video dataset of emotions, and deeply explored anger-related emotional expressions by asking culture-fluent annotators to label the videos with 6 labels and 13 emojis in a multi-label framework. We provide a baseline multi-label classifier on our dataset, and show how emojis can be effectively used as a language-agnostic tool for annotation.
TOPOLOGICAL RIGIDITY OF TORI AND FINITE GROUP ACTIONS ON HYPERTORAL MANIFOLDS

Let X be a closed, connected and oriented topological n-dimensional manifold. Suppose that: (1) X supports an effective action of (Z/r) for arbitrarily large values of r, (2) the fundamental group π1(X) is virtually solvable, and (3) there exists a map X → T n of nonzero degree. We then prove that X is homeomorphic to T . Without using the assumption on π1(X) we prove that the cohomology ring H ∗(X ;Z) is isomorphic to H∗(T ;Z). We also prove that any closed connected and oriented n-dimensional manifold X admitting a map to T n of nonzero degree has Jordan homeomorphism group, and we study for such manifolds the maximal number k such that X admits effective actions of (Z/r) for arbitrarily large r. Finally, we prove that if X is a compact and connected Kaehler manifold of real dimension n and X supports effective holomorphic actions of (Z/r) for arbitrarily large r, then m ≤ n, and if m = n then X is biholomorphic to a complex torus.
Attention-based Transformation from Latent Features to Point Clouds

In point cloud generation and completion, previous methods for transforming latent features to point clouds are generally based on fully connected layers (FC-based) or folding operations (Folding-based). However, point clouds generated by FC-based methods are usually troubled by outliers and rough surfaces. For folding-based methods, their data flow is large, convergence speed is slow, and they are also hard to handle the generation of non-smooth surfaces. In this work, we propose AXform, an attention-based method to transform latent features to point clouds. AXform first generates points in an interim space, using a fully connected layer. These interim points are then aggregated to generate the target point cloud. AXform takes both parameter sharing and data flow into account, which makes it has fewer outliers, fewer network parameters, and a faster convergence speed. The points generated by AXform do not have the strong 2-manifold constraint, which improves the generation of non-smooth surfaces. When AXform is expanded to multiple branches for local generations, the centripetal constraint makes it has properties of self-clustering and space consistency, which further enables unsupervised semantic segmentation. We also adopt this scheme and design AXformNet for point cloud completion. Considerable experiments on different datasets show that our methods achieve state-of-the-art results.
Can mass change the diffusion coefficient of DNA-coated colloids?

Inertia does not generally affect the long time diffusion of passive overdamped particles in fluids. Yet we have discovered a surprising property of particles coated with ligands, that bind reversibly to surface receptors – heavy particles diffuse more slowly than light ones of the same size. We show this by simulation and by deriving an analytic formula for the mass-dependent diffusion coefficient in the overdamped limit. We estimate the magnitude of this effect for a range of biophysical ligand-receptor systems, and find it is potentially observable for micronscale DNA-coated colloids.
Hybrid stars from a constrained equation of state

We determine, within a meta-model, the properties of the nuclear matter equation of state (EoS) that allow for a phase transition to deconfinement matter. It is shown that the properties that define the isoscalar channel are the ones that are affected, in particular, a phase transition implies much larger values of the skewness and kurtosis. The effect of multi-quark interaction channels in the description of the quark phase in hybrid stars is also studied. NS properties, such as the mass and radius of the quark core, show an interplay dependence between the 8-quark vector and the 4-quark isovector-vector interactions. We show that low mass NS, M ~ 1.4M⊙, may already contain a quark core, and satisfy all existing NS observational constraints. We discuss the strangeness content of the quark core and its influence on the speed of sound.
Investigation of Temperature at Tool-Chip Interface in Turning Using Two-Color Pyrometer

A technique for measuring temperature at the interface between a cutting tool and a chip is developed. A two-color pyrometer with fused fiber coupler is applied to the temperature measurement of the tool-chip interface in dry and wet turning. By using this pyrometer, it is possible to measure the temperature of a very small object without emissivity affecting the results. A translucent alumina sintered under HIP is used as the cutting tool, and an annealed carbon steel AISI 1045 is used as the workpiece. Water-soluble coolant is introduced onto the rake surface of the tool. The technique developed is suitable for measuring temperature at tool-chip interface, either in dry or wet cutting conditions. The effect of coolant on the temperature is small, since temperature reduction is only about 3 percent compared with the temperature in dry cutting. The temperature distributions on the cutting tool and the work material are analyzed using the finite element method. Good agreement is obtained between the analytical results and experimental ones.
A novel instrumentation amplifier with reduced magnitude and phase errors

A novel, simple, low-cost modification in the conventional instrumentation amplifier structure is suggested to minimize the magnitude and phase errors. Necessary analytical conditions are obtained to realize maximally flat magnitude and phase responses over a wide frequency range. The effect of the second pole of the op-amps on the circuit stability is presented. The proposed design has the advantage of flat magnitude and phase responses over an extended frequency range. Simulation and experimental results are given to support the theoretical conclusions. >
A Puzzle-Based Dataset for Natural Language Inference

We provide here a dataset for tasks related to natural language understanding and natural language inference. The dataset contains logical puzzles in natural language from three domains: comparing puzzles, knighs and knaves, and zebra puzzles. Each puzzle is associated with the entire set of atomic questions that can be generated based on the relations and individuals occurring in the text. For each question we provide the correct answer: entailment, contradiction or ambiguity. The answer's correctness is verified against theorem provers. Good puzzles have two properties: (i) each piece of information is necessary and (ii) no unnecessary information is provided. These properties make puzzles interesting candidates for machine comprehension tasks.
Modeling and performance analysis of a fiber Bragg grating interrogation system using an acousto-optic tunable filter

The performance of a fiber grating interrogation system using an acousto-optic tunable filter (AOTF) is analyzed. An equivalent linear circuit is presented to describe the system, which tracks the wavelength of a fiber Bragg grating (FBG) sensor in a FBG sensor array. From the model, the tracking resolution of a shot-noise-limited system has been determined for both transmissive and reflective interrogation of FBGs. An optimum ratio between the bandwidths of the FBG and the AOTF has been derived. Experimental results of a tracking system are presented to validate the theoretical predictions. The theory should also be suitable for interrogation systems using other forms of tunable bandpass filters for tracking the FBG wavelength.
Reduction of Hyperelliptic Curves in Characteristic $\not=2$

Let $K$ be the quotient field of a discrete valuation ring $R$ with residue characteristic $\not=2$, and let $C$ be a hyperelliptic curve over $K$. We assume that all geometric branch points of the double covering $C\twoheadrightarrow{\mathbb P}^1_K$ are rational and mark both $C$ and ${\mathbb P}^1_K$ with these branch points. After possibly replacing $R$ by a ramified extension of degree $2$, we give a direct construction for the stable model of $C$ as a marked curve over $R$. We deduce that the closed fiber of this stable model is determined completely by the closed fiber of the stable model of the marked ${\mathbb P}^1_K$. In particular, the dual graph and other information for the former can be read off directly from the corresponding information for the latter.
Human cumulative culture and the exploitation of natural phenomena

Cumulative cultural evolution (CCE)—defined as the process by which beneficial modifications are culturally transmitted and progressively accumulated over time—has long been argued to underlie the unparalleled diversity and complexity of human culture. In this paper, I argue that not just any kind of cultural accumulation will give rise to human-like culture. Rather, I suggest that human CCE depends on the gradual exploitation of natural phenomena, which are features of our environment that, through the laws of physics, chemistry or biology, generate reliable effects which can be exploited for a purpose. I argue that CCE comprises two distinct processes: optimizing cultural traits that exploit a given set of natural phenomena (Type I CCE) and expanding the set of natural phenomena we exploit (Type II CCE). I argue that the most critical features of human CCE, including its open-ended dynamic, stems from Type II CCE. Throughout the paper, I contrast the two processes and discuss their respective socio-cognitive requirements. This article is part of a discussion meeting issue ‘The emergence of collective knowledge and cumulative culture in animals, humans and machines’.
Translating ordinary language into symbolic logic

The paper describes a computer program, written in COMIT, for translating ordinary English into the notation of propositional logic and first-order functional logic. The program is designed to provide an ordinary language input to a COMIT program for the David-Putnam proof-procedure algorithm. The entire set of operations which are performed on an input sentence or argument are divided into three stages. In Stage I, an input sentence ‘S’, such as “The composer who wrote ‘Alcina’ wrote some operas in English,” is rewritten in a quasi-logical notation, “The X/A such that X/A is a composer and X/A wrote Alcina wrote some X/B such that X/B is an opera and X/B is in English. ” The quasi-logical notation serves as an intermediate language between logic and ordinary English. In Stage II, S is translated into the logical notation of propositional functions and quantifiers, or of propositional logic, whichever is appropriate. In Stage III, S is run through the proof-procedure program and evaluated. (The sample sentence quoted is of course ‘invalid’, i.e. nontautological.) The COMIT program for Stage III is complete, that for Stage II is almost complete, and that for Stage I is incomplete. The paper describes the work done to date on the programs for Stages I and II.
Theoretical and experimental study of feed network effects on the radiation pattern of series-fed microstrip antenna arrays

Microstrip series-fed arrays are often utilised for compact array designs. This type of feed structure minimises feedline lengths and feedline radiation. However, in practice, the radiation from the feed network still can be significant and it can have a noticeable effect on the array radiation pattern. Analysis is performed using the advantageous full-wave discrete image technique. Theoretical and experimental analysis of the radiation from a four-element series-fed microstrip array antenna, which fully includes the effect of the feed network, is presented. General conclusions are made for the purpose of practical designs.