Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical Antennas: Aperture optical antennas

This contribution reviews the studies on subwavelength aperture antennas in the optical regime, paying attention to both the fundamental investigations and the applications. Section 2 reports on the enhancement of light-matter interaction using three main types of aperture antennas: single subwavelength aperture, single aperture surrounded by shallow surface corrugations, and subwavelength aperture arrays. A large fraction of nanoaperture applications is devoted to the field of biophotonics to improve molecular sensing, which are reviewed in Section 3. Lastly, the applications towards nano-optics (sources, detectors and filters) are discussed in Section 4.
Feature Engineering for Mid-Price Prediction With Deep Learning

Mid-price movement prediction based on the limit order book data is a challenging task due to the complexity and dynamics of the limit order book. So far, there have been very limited attempts for extracting relevant features based on the limit order book data. In this paper, we address this problem by designing a new set of handcrafted features and performing an extensive experimental evaluation on both liquid and illiquid stocks. More specifically, we present an extensive set of econometric features that capture the statistical properties of the underlying securities for the task of mid-price prediction. The experimental evaluation consists of a head-to-head comparison with other handcrafted features from the literature and with features extracted from a long short-term memory autoencoder by means of a fully automated process. Moreover, we develop a new experimental protocol for online learning that treats the task above as a multi-objective optimization problem and predicts: 1) the direction of the next price movement and; 2) the number of order book events that occur until the change takes place. In order to predict the mid-price movement, features are fed into nine different deep learning models based on multi-layer perceptrons, convolutional neural networks, and long short-term memory neural networks. The performance of the proposed method is then evaluated on liquid and illiquid stocks (i.e., TotalView-ITCH US and Nordic stocks). For some stocks, results suggest that the correct choice of a feature set and a model can lead to the successful prediction of how long it takes to have a stock price movement.
Chronic liver disease and hepatic encephalopathy patients with new-onset focal motor status epilepticus: Indicates herpetic encephalitis

Seizures are not common in cases with chronic liver disease. Overall seizures have been reported in 20–30% of cases in chronic liver disease associated with hepatic encephalopathy. We report two cases of chronic liver disease patients who presented with new-onset refractory focal status epilepticus (SE). Both patients had encephalitis and seizures which responded only when acyclovir was added to the treatment with antiepileptic medication. Herpes encephalitis should be considered as a possible diagnosis in new-onset focal seizures or focal SE in patients with chronic liver disease with or without hepatic encephalopathy, pending further investigations.
HST/COS observations of a new population of associated QSO absorbers

(Abridged) We present a sample of new population of associated absorbers, detected through Ne VIII \lambda\lambda 770,780 absorption, in HST/COS spectra of intermediate redshift (0.45 7,000 km/s) systems in our sample. All these systems show very high N(Ne VIII) (i.e. > 10^{15.6} cm^{-2}), high ionization parameter (i.e. log U > 0.5), high metallicity (i.e. Z > Z_{\odot}), and ionization potential dependent f_c values. The observed column density ratios of different ions are reproduced by multiphase photoionization (PI) and/or collisional ionization (CI) equilibrium models. While solar abundance ratios are adequate in CIE, enhancement of Na relative to Mg is required in PI models to explain our observations.
GRB 100219A with X-shooter – abundances in a galaxy at z =4.7

Context. Abundances of galaxies at redshifts z > 4 are di cult to obtain from damped Ly (DLA) systems in the sightlines of quasars (QSOs) due to the Ly forest blanketing and the low number of high-redshift quasars detected. Gamma-ray bursts (GRBs) with their higher luminosity are well suited to study galaxies out to the formation of the first stars at z > 10. Its large wavelength coverage makes the X-shooter spectrograph an excellent tool to study the interstellar medium (ISM) of high redshift galaxies, in particular if the redshift is not known beforehand. Aims. We want to determine the properties of a GRB host at z = 4:66723 from absorption lines. This is one of the highest redshifts where a detailed analysis with medium-resolution data is possible. Furthermore, we determine the dust extinction using the spectral energy distribution from X-rays to near infrared. Finally, we put the results in context to other GRBs at z > 4 and properties of (high redshift) QSO absorbers. Methods. The velocity components of the resonant and fine-structure absorption lines are fitted with Voigt-profiles and the metallicity determined from S, Si, Fe and O. Si II* together with the energy released in the UV restframe as determined from GROND photometric data gives us the distance of the absorbing material from the GRB. The extinction is determined from the spectral slope using X-ray spectral information and the flux calibrated X-shooter spectrum, cross calibrated with photometric data from GROND. We also collect information on all GRB hosts with z > 4. Results. We measure a relatively high metallicity of [M/H] = 1:0 0:1 from S, the distance of the material showing fine-structure lines is 0.3 to 1.0 kpc. The extinction is moderate with AV = 0:24 0:06 mag. Low- and high ionization as well as fine-structure lines show a complicated kinematic structure probably pointing to a merger in progress. We detect one intervening system at z = 2:18. Conclusions. GRB-DLAs have a shallower evolution of metallicity with redshift than QSO absorbers and no evolution in their HI column density or ionization fraction. GRB hosts at high redshift seem to continue the trend of the metallicity-luminosity relation towards lower metallicities but the sample is still too small to draw a definite conclusion. While the detection of GRBs at z > 4 with current satellites is still di cult, they are very important for our understanding of the early epochs of star- and galaxy-formation in the Universe.
Political Text Scaling Meets Computational Semantics

During the past 15 years, automatic text scaling has become one of the key tools of the Text as Data community in political science. Prominent text-scaling algorithms, however, rely on the assumption that latent positions can be captured just by leveraging the information about word frequencies in documents under study. We challenge this traditional view and present a new, semantically aware text-scaling algorithm, SemScale, which combines recent developments in the area of computational linguistics with unsupervised graph-based clustering. We conduct an extensive quantitative analysis over a collection of speeches from the European Parliament in five different languages and from two different legislative terms, and we show that a scaling approach relying on semantic document representations is often better at capturing known underlying political dimensions than the established frequency-based (i.e., symbolic) scaling method. We further validate our findings through a series of experiments focused on text preprocessing and feature selection, document representation, scaling of party manifestos, and a supervised extension of our algorithm. To catalyze further research on this new branch of text-scaling methods, we release a Python implementation of SemScale with all included datasets and evaluation procedures.
On Kirchhoff's Model of Parabolic Type

ABSTRACT In this article, the existence of a global strong solution for all finite time is derived for the Kirchhoff's model of parabolic type. Based on exponential weight function, some new regularity results which reflect the exponential decay property are obtained for the exact solution. For the related dynamics, the existence of a global attractor is shown to hold for the problem when the non-homogeneous forcing function is either independent of time or in L∞(L2). With the finite element Galerkin method applied in spatial direction keeping time variable continuous, a semidiscrete scheme is analyzed, and it is also established that the semidiscrete system has a global discrete attractor. Optimal error estimates in L∞(H1) norm are derived which are valid uniformly in time. Further, based on a backward Euler method, a completely discrete scheme is analyzed and error estimates are derived. It is also further, observed that in cases where f = 0 or f = O(e−γ0t) with γ0 > 0, the discrete solutions and error estimates decay exponentially in time. Finally, some numerical experiments are discussed which confirm our theoretical findings.
Bilinear equations and Bäcklund transformation for a generalized ultradiscrete soliton solution

Ultradiscrete soliton equations and Bäcklund transformation for a generalized soliton solution are presented. The equations include the ultradiscrete Korteweg–de Vries (KdV) equation or the ultradiscrete Toda equation in a special case. We also express the solution by the ultradiscrete permanent, which is defined by ultradiscretizing the signature-free determinant, that is, the permanent. Moreover, we discuss a relation between Bäcklund transformations for discrete and ultradiscrete KdV equations.
The Relationship between Career Decision-Making Self-Efficacy, Career Preparation Behaviour and Career Decision Difficulties among South Korean College Students

Few studies have continuously examined the relationship between career decision-making self-efficacy variables and career-related variables in South Korea’s specific cultural context. Accordingly, this study aims to analyse (using Pearson’s correlations and structural equation modelling) the relationships between South Korean college students’ career decision-making self-efficacy, career preparation behaviour, and career decision difficulties. There were positive and negative relationships between career decision-making self-efficacy and career preparation behaviour career decision difficulties, respectively. In addition, we found a positive effect between career preparation behaviour and career decision-making self-efficacy, while career decision difficulties negatively affected career decision-making self-efficacy. Considering the standardised coefficient of the specific direct effect, the effect on career decision-making self-efficacy of career preparation behaviour was larger than that of career decision difficulties. It is recommended that career programmes are developed that help college students to independently set their career goals, actively search for career information, and promote career preparation behaviour while considering their majors. It is also recommended career counselling programmes be designed that can help them establish their self-concept and identity. These findings could provide the necessary basic data for the construction of an effective college career guidance system and inform strategies for improving college students’ career decision-making self-efficacy.
Vectorizing Images of Any Size

We propose a novel algorithm for converting quantized raster color images to resolution-independent scalable vector graphics (SVG). Starting from the discontinuity set of the input image, the algorithm connects the pieces of curves separating two constant regions to reconstruct the apparent contours of objects and interpret T-junctions and saddle points. This structure is depixelized by curve affine shortening, which requires maintaining the topology of the discontinuity set during filtering. The resulting Hierarchical Curve-based Vectorization (HCV) algorithm compares favorably to several state-of-art vectorization algorithms and software for color-quantized photos and pixel art1.
On isomorphisms of generalized multifold extensions of algebras without nonzero oriented cycles

Abstract Assume that a basic algebra A over an algebraically closed field with a basic set A 0 of primitive idempotents has the property that for all Let n be a nonzero integer, and and two automorphisms of the repetitive category of A with jump n (namely, they send to where is the i-th copy of A in for all ). If and coincide on the objects and if there exists a map such that for all morphisms then the orbit categories and are isomorphic as -graded categories.
A non-LTE spectral analysis of the 3 He and 4 He isotopes in the HgMn star κ Cancri ,

Aims. We present a pilot study on non-local thermodynamic equilibrium (NLTE) line-formation computations for the isotopes 3 He and 4 He in the mercury-manganese star κ Cancri. The impact of NLTE effects on the determination of isotopic abundances and the vertical stratification of helium in the atmosphere is investigated. Methods. Modern NLTE line-formation computations were employed to analyse a high-resolution and high signal-to-noise ratio ESO-VLT/UVES spectrum of κ Cnc. The atmospheric parameters were determined from fitting the hydrogen Balmer lines and the spectral energy distribution. Multiple He i lines were investigated, including He i λ4921 A and λ6678 A, which show the widest isotopic splits. Results. Half of the observed He i lines in the spectrum of κ Cnc show significant NLTE strengthening, the effects are strongest in the red lines He i λ5875 A and He i λ6678 A. NLTE abundances from individual He i lines are up to a factor of ∼3 lower than LTE values. Helium is found to be stratified in the atmosphere of κ Cnc. While the LTE analysis indicates a step-like profile of the helium abundance, a gradual decrease with height is indicated by the NLTE analysis. A 3 He/ 4 He ratio of ∼0.25–0.30 is found. With the available data it cannot be decided whether the two isotopes follow the same stratification profile, or not. Conclusions. This work implies that NLTE effects may be ubiquitous in the atmospheres of HgMn stars and may have a significant impact on abundance determinations and the interpretation of the vertical abundance stratification of elements.
Magnetic field-induced quantum criticality via new asymptotically AdS5 solutions

Using analytical methods, we derive and extend previously obtained numerical results on the low temperature properties of holographic duals to four-dimensional gauge theories at finite density in a nonzero magnetic field. We find a new asymptotically AdS5 solution representing the system at zero temperature. This solution has vanishing entropy density, and the charge density in the bulk is carried entirely by fluxes. The dimensionless magnetic field to charge density ratio for these solutions is bounded from below, with a quantum critical point appearing at the lower bound. Using matched asymptotic expansions, we extract the low temperature thermodynamics of the system. Above the critical magnetic field, the low temperature entropy density takes a simple form, linear in the temperature, and with a specific heat coefficient diverging at the critical point. At the critical magnetic field, we derive the scaling law s ∼ T1/3 inferred previously from the numerical analysis. We also compute the full scaling function describing the region near the critical point and identify the dynamical critical exponent: z = 3. These solutions are expected to holographically represent boundary theories in which strongly interacting fermions are filling up a Fermi sea. They are fully top–down constructions in which both the bulk and boundary theories have well-known embeddings in the string theory. Communicated by S F Ross
Two-Timescale Dynamic Energy and Reserve Dispatch With Wind Power and Energy Storage

The integration of volatile renewable resources and energy storage entails making dispatch decisions for conventional coal-fired units and fast-response devices in different timescales. This paper studies intraday dynamic energy-reserve dispatch following a two-timescale setting. The coarse timescale determines the hourly reference output and reserve allocation, which offers a sufficient backup for the fine-timescale operation; the fine timescale determines the adjustment of gas-fired units and energy storage system every 15 minutes in response to the actual wind power. A stochastic dynamic programming method is proposed to make decisions at the coarse timescale while guaranteeing the robust feasibility of the fast process via vertex scenarios of uncertainty set and bounding the state-of-charge intervals for energy storage; the fast-response actions at the fine timescale are updated using a truncated rolling-horizon optimization, which incorporates the cost-to-go functions calculated at the coarse timescale to prevent the fast decisions from being myopic. Case studies on the modified IEEE 5-bus system and 118-bus system validate the proposed framework.
Layer-Aware Containerized Service Orchestration in Edge Networks

Edge computing provides computational resources in the vicinity of end-users to reduce delay compared to traditional remote clouds. However, the capacity of edge resources usually is not sufficient for the required computational demands. Therefore, it is necessary to design methods for employing these resources in an efficient manner. On the other hand, network function virtualization (NFV) is a promising solution to use the network resources in a more flexible way than traditional schemes. Although more focus has been on realization of NFV systems via virtual machines so far, recent studies show that container-based solutions can improve efficiency thanks to lightweight implementation and layered structure of containers. Nonetheless, to the best of our knowledge, there is no comprehensive study on the problem of orchestrating services composed of a chain of containerized network functions in edge networks. In this paper, we consider this scenario when service requests are submitted to the system and address important aspects of this problem such as downloading and sharing container layers and steering traffic among network functions. We present the formulation of the problem as an integer linear program (ILP) and prove its NP-hardness. Then, to handle this problem, we propose RCCO, a polynomial-time algorithm based on ideas from deterministic and randomized rounding framework. Our results from extensive evaluations show that the bandwidth consumption of the proposed algorithm compared to the optimal algorithm is higher by only about 4% while it can outperform baselines from literature by more than 37%.
Federated Learning Approach for Measuring the Response of Brain Tumors to Chemotherapy

—Brain tumor is a fatal disease and one of the major causes of rising death rates in adults. Predicting methylation of the O6-Methylguanine-DNA Methyltransferase (MGMT) gene status utilizing Magnetic resonance imaging (MRI) imaging is highly important since it is a predictor of brain tumor responses to chemotherapy, which reduces the number of needed surgeries. Deep Learning (DL) approaches became powerful in extracting meaningful relationships and making accurate predictions. DL-based models require a large database and accessing or transferring patient data to train the model. Federated machine learning has recently gained popularity, as it offers practical solutions for data privacy, centralized computation, and high computing power. This study aims to investigate the feasibility of federated learning (FL) by developing a FL-based approach to predict MGMT promoter methylation status using the BraTs2021 dataset for the four sequence types, (Fluid Attenuated Inversion Recovery (FLAIR), T1-weighted (T1w), T1-weighted Gadolinium Post Contrast (T1wCE/T1Gd), and T2-weighted (T2w)) MRI images. The FL model compared to the DL-based and the experimental results show that even with imbalanced and heterogeneous datasets, the FL approach reached the training model to 99.99% of the model quality achieved with centralized data after 300 communication rounds between 10 institutions using OpenFl framework and the improved EfficentNet-B3 neural network architecture.
Measuring AGN Feedback with the Sunyaev-Zel’dovich Effect

One of the most important and poorly understood issues in structure formation is the role of outflows driven by active galactic nuclei (AGNs). Using large-scale cosmological simulations, we compute the impact of such outflows on the small-scale distribution of the cosmic microwave background (CMB). Like gravitationally heated structures, AGN outflows induce CMB distortions through both thermal motions and peculiar velocities, by processes known as the thermal and kinetic Sunyaev-Zel’dovich (SZ) effects, respectively. For AGN outflows the thermal SZ effect is dominant, doubling the angular power spectrum on arcminute scales. But the most distinct imprint of AGN feedback is a substantial increase in the thermal SZ distortions around elliptical galaxies, poststarburst elliptical galaxies, and quasars that is linearly proportional to the outflow energy. While point-source subtraction is difficult for quasars, we show that by appropriately stacking microwave measurements around early-type galaxies, the new generation of small-scale microwave telescopes will be able to directly measure AGN feedback at the level that is important for current theoretical models.
Atomic and electronic structure of the $\sqrt{3}$$\times$$\sqrt{3}$ silicene phase on Ag(111): density-functional calculations

Density-functional theory calculations are used to verify the atomic structure of the $\sqrt{3}$$\times$$\sqrt{3}$ silicene phase grown on the Ag(111) surface. Recent experimental studies strongly suggested that the previous double-layer silicene model should be replaced with a Ag-mixed double-layer model resembling the top layers of the Ag/Si(111)-($\sqrt{3}$$\times$$\sqrt{3}$) surface. In our calculations, the Ag-mixed double-layer model is indeed energetically favored over the double-layer silicene model and well reproduces the reported scanning-tunneling microscopy and spectroscopy data. Especially, the structural origin of the experimental band structure is clarified as the top Ag-Si mixed layer, unlike the experimental interpretations as either a silicene layer or the Ag(111) substrate.