Abstract
The original version of this Article contained an error in the Acknowledgements section. “This work was partially funded by the Project TAMI—Transparent Artificial Medical Intelligence (NORTE- 01-0247-FEDER-045905) financed by ERDF—European Regional Fund through the North Portugal Regional Operational Program—NORTE 2020 and by the Portuguese Foundation for Science and Technology—FCT under the CMU—Portugal International Partnership, and also by the Portuguese Foundation for Science and Technology—FCT within PhD grants SFRH/BD/139468/2018 and 2020.06434.BD. The authors thank the Swiss National Science Foundation grant number 198388, as well as the Lindenhof foundation for their grant support.” now reads: “This work was supported by National Funds through the Portuguese Funding Agency, FCT–Foundation for Science and Technology Portugal, under Project LA/P/0063/2020, and also by the Portuguese Foundation for Science and Technology - FCT within PhD grants SFRH/BD/139468/2018 and 2020.06434.BD. The authors thank the Swiss National Science Foundation grant number 198388, as well as the Lindenhof foundation for their grant support.” The original Article has been corrected. © The Author(s) 2023.

Abstract
Automatic Lip-Reading (ALR), also known as Visual Speech Recognition (VSR), is the technological process to extract and recognize speech content, based solely on the visual recognition of the speaker’s lip movements. Besides hearing-impaired people, regular hearing people also resort to visual cues for word disambiguation, every time one is in a noisy environment. Due to the increasingly interest in developing ALR systems, a considerable number of research articles are being published. This article selects, analyses, and summarizes the main papers from 2018 to early 2022, from traditional methods with handcrafted feature extraction algorithms to end-to-end deep learning based ALR which fully take advantage of learning the best features, and of the evergrowing publicly available databases. By providing a recent state-of-the-art overview, identifying trends, and presenting a conclusion on what is to be expected in future work, this article becomes an efficient way to update on the most relevant ALR techniques. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
In Walrasian markets, an auctioneer proposes a price to the market participants, who react by revealing the quantities they are willing to buy or sell at this price. The auctioneer then proposes new prices to improve the demand and supply match until the equilibrium is reached. This market, common for stock exchanges, has also been proposed for electricity markets like power electricity exchanges, where iterations among auctioneer and market participants take place before the interval settlement period (ISP) until supply and demand match and a stable price is reached. We propose a Walrasian design for local electricity markets where the iterations between auctioneer and market participants happen in real time, so previous imbalances are used to correct the proposed price for the next ISP. The designs are simulated to test convergence and their capability of achieving efficient dynamic prices.

Abstract
Dissipative quartic solitons have gained interest in the field of mode-locked lasers for their energy-width scaling which allows the generation of ultrashort pulses with high energies. Pursuing the characterization of such pulses, here we found soliton solutions of a distributed model for mode locked lasers in the presence of either positive or negative fourth-order dispersion (4OD). We studied the impact the laser parameters may have on the profiles, range of existence, and energy-width relation of the output pulses. The most energetic and narrowest solutions occur for negative 4OD, with the energy having an inverse cubic dependence with the width in most cases. Our simulations showed that the spectral filtering has the biggest contribution in the generation of short (widths as low as 39 fs) and very energetic (391 nJ) optical pulses.(c) 2023 Optica Publishing Group

Abstract
The motion of S2, one of the stars closest to the Galactic Centre, has been measured accurately and used to study the compact object at the centre of the Milky Way. It is commonly accepted that this object is a supermassive black hole, but the nature of its environment is open to discussion. Here, we investigate the possibility that dark matter in the form of an ultralight scalar field 'cloud' clusters around Sgr A*. We use the available data for S2 to perform a Markov Chain Monte Carlo analysis and find the best-fit estimates for a scalar cloud structure. Our results show no substantial evidence for such structures. When the cloud size is on the order of the size of the orbit of S2, we are able to constrain its mass to be smaller than 0.1 % of the central mass, setting a strong bound on the presence of new fields in the galactic centre.

Abstract
Greenland ice core records display abrupt transitions, designated as Dansgaard-Oeschger (DO) events, characterised by episodes of rapid warming (typically decades) followed by a slower cooling. The identification of abrupt transitions is hindered by the typical low resolution and small size of paleoclimate records, and their significant temporal variability. Furthermore, the amplitude and duration of the DO events varies substantially along the last glacial period, which further hinders the objective identification of abrupt transitions from ice core records Automatic, purely data-driven methods, have the potential to foster the identification of abrupt transitions in palaeoclimate time series in an objective way, complementing the traditional identification of transitions by visual inspection of the time series.In this study we apply an algorithmic time series method, the Matrix Profile approach, to the analysis of the NGRIP Greenland ice core record, focusing on:- the ability of the method to retrieve in an automatic way abrupt transitions, by comparing the anomalies identified by the matrix profile method with the expert-based identification of DO events;- the characterisation of DO events, by classifying DO events in terms of shape and identifying events with similar warming/cooling temporal patternThe results for the NGRIP time series show that the matrix profile approach struggles to retrieve all the abrupt transitions that are identified by experts as DO events, the main limitation arising from the diversity in length of DO events and the method’s dependence on fixed-size sub-sequences within the time series. However, the matrix profile method is able to characterise the similarity of shape patterns between DO events in an objective and consistent way.