Detecting Trends in Job Advertisements

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The Affleck-Kennedy-Lieb-Tasaki (AKLT) point of the bilinear-biquadratic spin-1 chain is a cornerstone example of a disorder point where short-range correlations become incommensurate, and correlation lengths and momenta are nonanalytic. While the presence ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

The methanol-to-olefins (MTO) process on zeolite-based catalysts enables the production of olefins from green methanol. Selectivity control requires an understanding of the nature and evolution of hydrocarbon species that act as catalytically active center ...

This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine ...

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing s ...

Mapping the technology landscape is crucial for market actors to take informed investment decisions. However, given the large amount of data on the Web and its subsequent information overload, manually retrieving information is a seemingly ineffective and ...

Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods. However, such methods tend to come with caveats, such as no integration of ...

In this paper, the new mathematical correlation of two quantum systems that were initially allowed to interact and then separated is being formulated and analyzed. These correlations are illustrated by many examples and are also connected with fractals at ...

After the spread of COVID-19, surgical masks became highly recommended to the public. They tend to be handled and used multiple times, which may impact their performance. To evaluate this risk, surgical masks of Type IIR were submitted to four simulated tr ...

This paper characterizes the correlation of simultaneous measurements with different fast-ion H-alpha (FIDA) spectroscopy sightlines on Wendelstein 7-X. Using a collisionless guiding-center code, it is shown that, for two investigated volumes in the bulk o ...

BackgroundTinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a be ...

Novel forms of light beams carrying orbital angular momentum (OAM) have recently gained interest, especially due to some of their intriguing propagation features. Here, we experimentally demonstrate the generation of near-diffraction-free two-dimensional ( ...

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

Entity linking is an important problem with many applications. Most previous solutions were designed for settings where annotated training data is available, which is, however, not the case in numerous domains. We propose a light-weight and scalable entity ...

Purpose Although several MRI methods have been explored to achievein vivomyelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the ...

Large-scale models for learning fixed-dimensional cross-lingual sentence representations like LASER (Artetxe and Schwenk, 2019b) lead to significant improvement in performance on downstream tasks. However, further increases and modifications based on such ...

This paper compares predictions of metabolic energy expenditure in gait using seven metabolic energy expenditure models to assess their correlation with experimental data. Ground reaction forces, marker data, and pulmonary gas exchange data were recorded f ...

Machine Translation (MT) has made considerable progress in the past two decades, particularly after the introduction of neural network models (NMT). During this time, the research community has mostly focused on modeling and evaluating MT systems at the se ...

Detecting Trends in Job Advertisements

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Singularity with and without disorder at Affleck-Kennedy-Lieb-Tasaki points

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Correlating the Nature of Carbenium Ions in Zeolites to the Product Distribution in the Methanol-to-Olefins Process

Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Towards a multiscale point cloud structural similarity metric

Correlated-photon imaging at 10 volumetric images per second

From scattered sources to comprehensive technology landscape : A recommendation-based retrieval approach

Strong Heuristics for Named Entity Linking

Mathematical Approach to Distant Correlations of Physical Observables and Its Fractal Generalisation

On the durability of surgical masks after simulated handling and wear

Characterization of correlations of fast-ion H-alpha measurement volumes in Wendelstein 7-X by particle tracking

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

Synthesis of near-diffraction-free orbital-angular-momentum space-time wave packets having a controllable group velocity using a frequency comb

ExprADA: Adversarial domain adaptation for facial expression analysis

Low-Rank Subspaces for Unsupervised Entity Linking

Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA

Lightweight Cross-Lingual Sentence Representation Learning

Metabolic cost calculations of gait using musculoskeletal energy models, a comparison study

Discourse Phenomena in Machine Translation