Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying surface probe images in strongly correlated electronic systems via machine learning

Scanning probe experiments such as scanning tunneling microscopy (STM) and atomic force microscopy (AFM) on strongly correlated electronic systems often reveal complex pattern formation on multiple length scales. By studying the universal scaling in these images, we have shown in several distinct correlated electronic systems that the pattern formation is driven by proximity to a disorder-driven critical point, revealing a unification of the pattern formation in these materials. As an alternative approach to this image classification problem of novel materials, here we report the first investigation of the machine learning method to determine which underlying physical model is driving pattern formation in a system. Using a neural network architecture, we are able to achieve 97% accuracy on classifying configuration images from three models with Ising symmetry. This investigation also demonstrates that machine learning can capture the implicit universal behavior of a physical system. This broadens our understanding of what machine learning can do, and we expect more synergy between machine learning and condensed matter physics in the future.
Transition to detonation in a model problem

We show, within the context of a model problem, how an initial low Mach number combustion wave develops into a detonation when subjected to an externally applied gasdynamic disturbance. We give explicit criteria that the external disturbance must satisfy in order for transition to be achieved On montre, dans le contexte d'un probleme modele, comment un front initial a faible nombre de Mach se change en detonation quand il est expose a une perturbation d'origine exterieure. On donne sous forme explicite un critere que la perturbation exterieure doit satisfaire pour que la transition soit effective
Short-Term Meaning Shift: A Distributional Exploration

We present the first exploration of meaning shift over short periods of time in online communities using distributional representations. We create a small annotated dataset and use it to assess the performance of a standard model for meaning shift detection on short-term meaning shift. We find that the model has problems distinguishing meaning shift from referential phenomena, and propose a measure of contextual variability to remedy this.
The Development of Funding Schemes at Finnish Universities of Applied Sciences

 This article examines the development of funding schemes at Finnish universities of applied sciences (UASs) between 2012 and 2018. During that period, the rudiments of the financing of Finnish UASs changed from cost-based to performance-based funding schemes. In a performancebased funding scheme, the state allocates funding based on the achievement of predefined objectives. The reform was intended to improve the processes and structures of UASs and to increase their effectiveness. This study explores the development of funding schemes from simple cost-based funding schemes towards more complex performance-based funding schemes with many indicators of performance. The results of the study offer empirical evidence on the impact of funding schemes on the measures of the performance of UASs, interpretations of the research object in context and causal connections between the above-mentioned elements.
The Axial Rotation and Variable Macroturbulence of RR Lyrae and Red Horizontal Branch Stars

We have derived relations between FWHMs and equivalent widths of metallic absorption lines in the spectra of RR Lyrae stars to estimate new upper limits on the axial equatorial rotational velocities of RR Lyrae and metal-poor red horizontal branch (RHB) stars. We have also derived the variations of RR Lyrae macroturbulent velocities during the pulsation cycles. In RRab cycles, the line widths are dominated by phase-dependent convolutions of axial rotation and macroturbulence, which we designate as Vmacrot. The behavior of Vmacrot is remarkably uniform among the RRab stars, but the behavior of Vmacrot among RRc stars varies strongly from star to star. The RRab stars exhibit an upper limit on Vmacrot of 5 ± 1 km s−1 with weak evidence of an anticorrelation with Teff. The RRc minima range from 2 to 12 km s−1. The abrupt decline in large rotations with decreasing Teff at the blue boundary of the instability strip and the apparently smooth continuous variation among the RRab and RHB stars suggests that HB stars gain/lose surface angular momentum on timescales that are short compared to HB lifetimes. The Vmacrot values for our metal-poor RHB stars agree well with those derived by Fourier analysis of an independent but less metal-poor sample of Carney et al.; they conform qualitatively to the expectations of Tanner et al. A general conclusion of our investigation is that surface angular momentum as measured by Vrot sin (i) is not a reliable indicator of total stellar angular momentum anywhere along the HB.
LSST Target-of-opportunity Observations of Gravitational-wave Events: Essential and Efficient

We present simulated observations to assess the ability of the Large Synoptic Survey Telescope (LSST) and the wide-fast-deep (WFD) survey to detect and characterize kilonovae—the optical emission associated with binary neutron star (and possibly black hole–neutron star) mergers. We expand on previous studies in several critical ways by exploring a range of kilonova models and several choices of cadence, as well as by evaluating the information content of the resulting light curves. We find that, depending on the precise choice of cadence, the WFD survey will achieve an average kilonova detection efficiency of ≈1.6%–2.5% and detect only ≈3–6 kilonovae per year. The detected kilonovae will be within the detection volume of the Advanced LIGO/Virgo (ALV). By refitting the best resulting LSST light curves with the same model used to generate them, we find that the model parameters are generally weakly constrained, and are accurate to at best a factor of 2–3. Motivated by the finding that the WFD will yield a small number of kilonova detections, with poor light curves and marginal information content, and that the detections are in any case inside the ALV volume, we argue that target-of-opportunity follow-up of gravitational-wave triggers is a much more effective approach for kilonova studies. We outline the qualitative foundation for such a program with the goal of minimizing the impact on LSST operations. We argue that observations in the gz-bands with a total time investment per event of ≈1.5 hr per 10 deg2 of a search area is sufficient to rapidly detect and identify kilonovae with ≳90% efficiency. For an estimated event rate of ∼20 per year visible to LSST, this accounts for ∼1.5% of the total survey time. In this regime, LSST has the potential to be a powerful tool for kilonovae discovery, with detected events handed off to other narrow-field facilities for further monitoring.
Multi-objective day-ahead scheduling of microgrids using modified grey wolf optimizer algorithm

Investigation of the environmental/economic optimal operation management of a microgrid (MG) as a case study for applying a novel modified multi-objective grey wolf optimizer (MMOGWO) algorithm is presented in this paper. MGs can be considered as a fundamental solution in order for distributed generators’ (DGs) management in future smart grids. In the multi-objective problems, since the objective functions are conflict, the best compromised solution should be extracted through an efficient approach. Accordingly, a proper method is applied for exploring the best compromised solution. Additionally, a novel distance-based method is proposed to control the size of the repository within an aimed limit which leads to a fast and precise convergence along with a well-distributed Pareto optimal front. The proposed method is implemented in a typical grid-connected MG with non-dispatchable units including renewable energy sources (RESs), along with a hybrid power source (micro-turbine, fuel-cell and battery) as dispatchable units, to accumulate excess energy or to equalize power mismatch, by optimal scheduling of DGs and the power exchange between the utility grid and storage system. The efficiency of the suggested algorithm in satisfying the load and optimizing the objective functions is validated through comparison with different methods, including PSO and the original GWO. Modified grey wolf optimizer, Micro-grid, Renewable energy sources
Exploring the Very Extended Low-surface-brightness Stellar Populations of the Large Magellanic Cloud with SMASH

We present the detection of very extended stellar populations around the Large Magellanic Cloud (LMC) out to R ∼ 21°, or ∼18.5 kpc at the LMC distance of 50 kpc, as detected in the Survey of the Magellanic Stellar History (SMASH) performed with the Dark Energy Camera on the NOAO Blanco 4 m Telescope. The deep (g ∼ 24) SMASH color–magnitude diagrams (CMDs) clearly reveal old (∼9 Gyr), metal-poor ([Fe/H] ≈ −0.8 dex) main-sequence stars at a distance of ∼50 kpc. The surface brightness of these detections is extremely low with our most distant detection at Σg ≈ 34 mag arcsec−2. The SMASH radial density profile breaks from the inner LMC exponential decline at ∼13°–15° and a second component at larger radii has a shallower slope with power-law index α = −2.2 that contributes ∼0.4% of the LMC’s total stellar mass. In addition, the SMASH densities exhibit large scatter around our best-fit model of ∼70% indicating that the envelope of stellar material in the LMC periphery is highly disturbed. We also use data from the NOAO Source catalog to map the LMC main-sequence populations at intermediate radii and detect a steep dropoff in density on the eastern side of the LMC (at R ≈ 8°) as well as an extended structure to the far northeast. These combined results confirm the existence of a very extended, low-density envelope of stellar material with a disturbed shape around the LMC. The exact origin of this structure remains unclear, but the leading options include an accreted halo or tidally stripped outer disk material.
A 19–48.3-GHz 6th-Order Transformer-Based Injection-Locked Frequency Divider With 87.1% Locking Range in 40-nm CMOS

This brief presents a 19–48.3-GHz fully-on-chip divided-by-2 injection-locked frequency divider (ILFD) based on a 6th-order transformer for a wide locking range in 40-nm CMOS technology. The proposed 6th-order transformer extends the resonator’s locking range by introducing more zeros and poles that could widen the frequency range satisfying the locking conditions. Furthermore, an inductive gain peaking technique is adopted to ensure start-up conditions and achieve low power consumption. The measurement results demonstrate a locking range of 29.3 GHz from 19 GHz to 48.3 GHz, which satisfies most applications for different nations’ 5G standards. The chip occupies a core area of 0.0518 mm2 and dissipates 2.88 mW from a 0.6-V voltage supply.
Learning Clinical Outcomes from Heterogeneous Genomic Data Sources

Translating the vast data generated by genomic platforms into reliable predictions of clinical outcomes remains a critical challenge in realizing the promise of genomic medicine largely due to small number of independent samples. In this paper, we show that neural networks can be trained to predict clinical outcomes using heterogeneous genomic data sources via multi-task learning and adversarial representation learning, allowing one to combine multiple cohorts and outcomes in training. We compare our proposed method to two baselines and demonstrate that it can be used to help mitigate the data scarcity and clinical outcome censorship in cancer genomics learning problems.
Hubble Space Telescope photometry of multiple stellar populations in the inner parts of NGC 2419

We present new deep imaging of the central regions of the remote globular cluster NGC 2419, obtained with the F343N and F336W filters of the Wide Field Camera 3 on board the Hubble Space Telescope. The new data are combined with archival imaging to constrain nitrogen and helium abundance variations within the cluster. We find a clearly bimodal distribution of the nitrogen-sensitive F336W–F343N colours of red giants, from which we estimate that about 55% of the giants belong to a population with about normal (field-like) nitrogen abundances (P1), while the remaining 45% belong to a nitrogen-rich population (P2). On average, the P2 stars are more He-rich than the P1 stars, with an estimated mean difference of ΔY ≃ 0.05, but the P2 stars exhibit a significant spread in He content and some may reach ΔY ≃ 0.13. A smaller He spread may also be present for the P1 stars. Additionally, stars with spectroscopically determined low Mg abundances ([Mg/Fe] < 0) are generally associated with P2. We find the P2 stars to be slightly more centrally concentrated in NGC 2419 with a projected half-number radius of about 10% less than for the P1 stars, but the difference is not highly significant (p ≃ 0.05). Using published radial velocities, we find evidence of rotation for the P1 stars, whereas the results are inconclusive for the P2 stars, which are consistent with no rotation as well as the same average rotation found for the P1 stars. Because of the long relaxation time scale of NGC 2419, the radial trends and kinematic properties of the populations are expected to be relatively unaffected by dynamical evolution. Hence, they provide constraints on formation scenarios for multiple populations, which must account not only for the presence of He spreads within sub-populations identified via CNO variations, but also for the relatively modest differences in the spatial distributions and kinematics of the populations.
Multivariate Newton Interpolation

For $m,n \in \mathbb{N}$, $m\geq 1$ and a given function $f : \mathbb{R}^m\longrightarrow \mathbb{R}$, the polynomial interpolation problem (PIP) is to determine a unisolvent node set $P_{m,n} \subseteq \mathbb{R}^m$ of $N(m,n):=|P_{m,n}|=\binom{m+n}{n}$ points and the uniquely defined polynomial $Q_{m,n,f}\in \Pi_{m,n}$ in $m$ variables of degree $\mathrm{deg}(Q_{m,n,f})\leq n \in \mathbb{N}$ that fits $f$ on $P_{m,n}$, i.e., $Q_{m,n,f}(p) = f(p)$, $\forall\, p \in P_{m,n}$. For $m=1$ the solution to the PIP is well known. In higher dimensions, however, no closed framework was available. We here present a generalization of the classic Newton interpolation from one-dimensional to arbitrary-dimensional spaces. Further we formulate an algorithm, termed PIP-SOLVER, based on a multivariate divided difference scheme that computes the solution $Q_{m,n,f}$ in $\mathcal{O}\big(N(m,n)^2\big)$ time using $\mathcal{O}\big(mN(m,n)\big)$ memory. Further, we introduce unisolvent Newton-Chebyshev nodes and show that these nodes avoid Runge's phenomenon in the sense that arbitrary periodic Sobolev functions $f \in H^k(\Omega,\mathbb{R}) \subsetneq C^0(\Omega,\mathbb{R})$, $\Omega =[-1,1]^m$ of regularity $k >m/2$ can be uniformly approximated, i.e., $ \lim_{n\rightarrow \infty}||\,f -Q_{m,n,f} \,||_{C^0(\Omega)}= 0$. Numerical experiments demonstrate the computational performance and approximation accuracy of the PIP-SOLVER in practice. We expect the presented results to be relevant for many applications, including numerical solvers, quadrature, non-linear optimization, polynomial regression, adaptive sampling, Bayesian inference, and spectral analysis.
Focused Electron and X-ray Beam Crosslinking in Liquids for Nanoscale Hydrogels 3D Printing and Encapsulation

Additive fabrication of biocompatible 3D structures out of liquid hydrogel solutions has become pivotal technology for tissue engineering, soft robotics, biosensing, drug delivery, etc. Electron and X-ray lithography are well suited to pattern nanoscopic features out of dry polymers, however, the direct additive manufacturing in hydrogel solutions with these powerful tools is hard to implement due to vacuum incompatibility of hydrated samples. In this work, we resolve this principal impediment and demonstrate a technique for in-liquid hydrogel 3D-sculpturing separating high vacuum instrumentation and volatile sample with ultrathin molecularly impermeable membranes transparent to low-energy electrons and soft X-rays. Using either scanning focused electron or synchrotron soft X-ray beams, the principle of the technique, particularities of the in-liquid crosslinking mechanism and factors affecting the ultimate gel feature size are described and validated through the comparison of experiments and simulations. The potential of this technique is demonstrated on a few practical examples such as encapsulation of nanoparticles and live-cell as well as fabrication of mesoscopic 3D-hydrogel structures via modulation of the beam energy
Automated Fact Checking in the News Room

Fact checking is an essential task in journalism; its importance has been highlighted due to recently increased concerns and efforts in combating misinformation. In this paper, we present an automated fact checking platform which given a claim, it retrieves relevant textual evidence from a document collection, predicts whether each piece of evidence supports or refutes the claim, and returns a final verdict. We describe the architecture of the system and the user interface, focusing on the choices made to improve its user friendliness and transparency. We conduct a user study of the fact-checking platform in a journalistic setting: we integrated it with a collection of news articles and provide an evaluation of the platform using feedback from journalists in their workflow. We found that the predictions of our platform were correct 58% of the time, and 59% of the returned evidence was relevant.
SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search

The $k$-Nearest Neighbor Search ($k$-NNS) is the backbone of several cloud-based services such as recommender systems, face recognition, and database search on text and images. In these services, the client sends the query to the cloud server and receives the response in which case the query and response are revealed to the service provider. Such data disclosures are unacceptable in several scenarios due to the sensitivity of data and/or privacy laws. In this paper, we introduce SANNS, a system for secure $k$-NNS that keeps client's query and the search result confidential. SANNS comprises two protocols: an optimized linear scan and a protocol based on a novel sublinear time clustering-based algorithm. We prove the security of both protocols in the standard semi-honest model. The protocols are built upon several state-of-the-art cryptographic primitives such as lattice-based additively homomorphic encryption, distributed oblivious RAM, and garbled circuits. We provide several contributions to each of these primitives which are applicable to other secure computation tasks. Both of our protocols rely on a new circuit for the approximate top-$k$ selection from $n$ numbers that is built from $O(n + k^2)$ comparators. We have implemented our proposed system and performed extensive experimental results on four datasets in two different computation environments, demonstrating more than $18-31\times$ faster response time compared to optimally implemented protocols from the prior work. Moreover, SANNS is the first work that scales to the database of 10 million entries, pushing the limit by more than two orders of magnitude.
Diffusive versus Free-streaming Cosmic-Ray Transport in Molecular Clouds

Understanding the cosmic-ray (CR) ionization rate is crucial in order to simulate the dynamics of molecular clouds, and interpret the chemical species observed in these objects. Calculating the CR ionization rate requires both accurate knowledge of the spectrum of MeV to GeV protons at the edge of the cloud as well as a model for the propagation of CRs into molecular clouds. Some models for the propagation of CRs in molecular clouds assume them to stream freely along magnetic field lines, while in others they propagate diffusively due to resonant scattering off of magnetic disturbances excited by MHD turbulence present in the medium. We discuss the conditions under which CR diffusion can operate in a molecular cloud, calculate the local CR spectrum and ionization rate in both a free-streaming and diffusive propagation model, and highlight the different results from the two models. We also apply these two models to the propagation through the ISM to obtain the proton spectrum seen by Voyager 1, and show that such a spectrum favors a diffusive propagation model.
A study to assess the water sanitation and hygiene (WASH) Practices among school children aged between 11 – 15 years in a private school in TVS Nagar, Madurai, Tamil Nadu

Background Water Sanitation and Hygiene (WASH) is an essential set of activities practiced among people of all age group to maintain their personal health standards and for environmental well being. Poor sanitation and hygiene practices have increased the burden of spread of communicable disease in the community . Hygiene education was found to be highly integrated in children who have more accessibility to adequate water, sanitary and hygienic practices . This study is done to assess the practices regarding WASH among school children. Methods A study was conducted among school going children in a private school in TVS Nagar, Madurai from January 2020 to June 2020. Simple random sampling was employed and 213 children were identified for the study. Descriptive statistics was calculated for background variables and variables related to water, sanitation and hygiene (WASH) practices. Results: In this study, all the subjects 213 (100%) reported safe piped water supply, adequate sanitary facilities and hand washing facilities were provided to them. Chlorination 165 (77.5%) was major method of disinfection of the drinking water supply. It was found 98 (46%) reported that water was available throughout the year, 192 (90.1%) reported that water was accessible to those with special needs. Separate toilet facilities for boys and girls were provided to all 213 (100%) the subjects. Menstrual hygiene management (MHM) materials like sanitary napkins were provided to all 96 (100%) the female subjects. Covered bins 79 (82.2%) were provided for sanitary disposal of menstrual waste. Hand washing facilities 185 (86.8%) were accessible to those with special needs. Group activities on hand washing 152 (71.3%) was conducted twice a week. Conclusion: Provision of functional water, sanitary and hand washing facilities were found to be adequately provided by the school management and the facilities were sufficiently utilized by the subjects. It is pivotal to focus and adhere to WASH practices as it improves health and environmental safety. Therefore, it is necessary to create awareness and organize health education sessions and implement WASH programs to obtain favorable outcomes.
Impact of disclosure and assurance quality of corporate sustainability reports on access to finance

This paper investigates the impact of corporate social responsibility (CSR) disclosure quantity, quality, and external validation concerning assurance on capital constraints. We examine if these disclosure characteristics matter to the investors in the financial market, then they should be positively evaluated by financial market participants. More specifically, we study the effects of disclosure quantity, quality, and assurance on the access to financial resources for reporting firms. Analysis of data of an interna- tional sample for the period of 2007–2016 significantly supports the value relevance idea of CSR disclosure quality. We document that availability of more information about the firm's CSR initiatives eases the financial access. Furthermore, the quality and external assurance of CSR disclosure further strengthen the relationship between disclosure and access to finance. Our paper not only provides support for buying assurance but also argue for better assurance quality.