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Aharonov-Bohm conductance oscillations emerge as a result of gapless surface states in topological insulator nanowires. This quantum interference accompanies a change in the number of transverse one-dimensional modes in transport, and the density of states of such nanowires is also expected to show Aharonov-Bohm oscillations. Here, we demonstrate a novel characterization of topological phase in Bi2Se3 nanowire via nanomechanical resonance measurements. The nanowire is configured as an electromechanical resonator such that its mechanical vibration is associated with its quantum capacitance. In this way, the number of one-dimensional transverse modes is reflected in the resonant frequency, thereby revealing Aharonov-Bohm oscillations. Simultaneous measurements of DC conductance and mechanical resonant frequency shifts show the expected oscillations, and our model based on the gapless Dirac fermion with impurity scattering explains the observed quantum oscillations successfully. Our results suggest that the nanomechanical technique would be applicable to a variety of Dirac materials.

Quantum technologies utilize photons in a wide range of spectra, from microwave to visible light. Interactions between photons at different frequencies can be mediated by the collective excitation of spins in a ferromagnetic material. Here, we present optic-to-microwave conversions using the spin mode. In the conversion system, we observe that the generation of microwaves can be controlled by the polarization of the infrared input. Furthermore, we miniaturize the system and demonstrate conversion in a cryogenic environment, where microwave photons can be manipulated in the quantum regime. We show that the conversion efficiency scales with the intensity of the infrared illumination. [ABSTRACT FROM AUTHOR]

Mass movements and delta collapses are significant sources of tsunamis in lacustrine environments, impacting human societies enormously. Paleotsunamis studies play an essential role in understanding historical events and their consequences, along with their return periods. This study investigates a paleotsunami induced by a subaqueous mass movement during the Younger Dryas to Early Holocene transition, ca. 11,700 years ago in Lake Aiguebelette (NW Alps, France). Utilizing high‐resolution seismic and bathymetric surveys associated with sedimentological, geochemical, and magnetic analyses, we uncovered a paleotsunami triggered by a seismically induced mass transport deposit. Numerical simulations of mass movement have been conducted using a visco‐plastic Herschel‐Bulkley rheological model and corresponding tsunami wave modeled with dispersive and nondispersive models. Our findings reveal for the first time that dispersive effects may be negligible for subaqueous landslides in a relatively small lake. This research reconstructs a previously unreported paleotsunami event and enhances our understanding of tsunami dynamics in lacustrine environments. Plain Language Summary: This study explores an ancient landslide and its ability to potentially generate a tsunami. This event took place in Lake Aiguebelette, located in the NW Alps, France. By applying advanced underwater mapping techniques and computer modeling, we were able to reconstruct the origins and impact of this underwater prehistoric landslide. Our work revealed that this underwater landslide may have triggered a significant tsunami wave. These findings are crucial as they provide new insights into the dynamics of such geological events in lake environments, enhancing our understanding of their potential impacts and aiding in the preparation for future similar hazards. Key Points: Uncovered a 11,700‐year‐old subaqueous landslide‐induced paleotsunami in Lake Aiguebelette (NW Alps, France)Numerical model is constrained to reproduce the available geological dataFound dispersion effects to be of minimal importance in the modeling of this historical tsunami event [ABSTRACT FROM AUTHOR]

This paper delves into the advantages of authentication algorithms employing self-sovereign identity, highlighting a reduced communication overhead and the elimination of single points of failure. However, it acknowledges the vulnerability of digital wallets to real-world issues like loss or theft. To address these challenges, we propose an efficient key backup and recovery protocol based on the FROST threshold signature algorithm. This protocol involves trusted third parties and backup devices, ensuring secure secret key sharing and rapid key recovery. Performance evaluations, including key recovery time, demonstrate the protocol's efficiency and reliability, bolstering the overall robustness of self-sovereign identity systems. [ABSTRACT FROM AUTHOR]

The violent explosion of the Hunga Tonga-Hunga Ha'apai volcano on January 15, 2022, was the origin of an atmospheric wave and a volcano-meteorological tsunami (VMT), both of which were recorded worldwide. The Tonga tsunami event caused resonance effects, leading to wave amplification in some far-field coastal areas like La Pampilla port in Callao, Peru, 10,000 km away from the volcano, where the rupture of the Vessel mooring lines occurred 15 hours after the eruption, resulting the spill of over 11,000 barrels of crude oil. This study aims to better understand the coastal effects of the Tonga tsunami, focusing on mooring loads in marine port environments. We examine how the VMT affected the safety of vessel moorings, hypothesising that atmosphere-induced acoustic ocean waves exerted hydrodynamic loading that endangered ships in port areas. A tsunami propagation obtained with a validated Boussinesq model at the local scale in Callao Bay provides the input to the mooring system model applied to a vessel with similar characteristics to the one docked at La Pampilla Port on the day of the Tonga event. This allows to study the effect of the VMT on overstressing and the potential mooring breakage. The results suggest that the Tonga tsunami event could be responsible for the movement and loss of positioning of the vessel. Furthermore, atmospheric waves significantly increased mooring stresses, particularly on the starboard quarter moorings. This event showed the need to prepare Tsunami Early Warning Systems and port authorities for detecting and managing VMTs induced by atmospheric acoustic waves. The work provides new insights into the far-field effects of the Tonga 2022 tsunami and discusses the lessons learned from such an uncommon event. [ABSTRACT FROM AUTHOR]

The Black Lake rockslide is located on the east wall of an open-pit mine initially operated by LAB Chrysotile near Thetford Mines, Quebec. Movements were observed in July 2012 when a volume of 2.0 x [10.sup.7] [m.sup.3] was mobilized, destroying a large portion of Highway 112. Mining operations ceased in 2012, causing the complete shutdown of the pumping system whose goal was to prevent the rise of water level in the pit. As the water level increases in the pit, it is essential to determine the potential of tsunami generation by possible partially submerged rockslides and to understand the potential impacts. A series of possible scenarios have been analysed with regard to velocity and acceleration of the potential rockslide as well as the corresponding wave generation and inundation. Results from the simulation show that when the factor of safety of the global slope is less than unity, inundation would not reach the potentially vulnerable infrastructures. Maximum wave height will vary as a function of the filling of the lake, and the lower wave height relative to water depth will happen when the lake is completely filled.Key words: landslide-generated tsunami, partially submerged landslide, numerical modeling, open-pit mine, active rockslide.Le glissement de Black Lake est situe sur la paroi est d'une ancienne mine a ciel ouvert exploitee par la compagnie LAB Chrysotile, a Thetford Mines, Quebec. Ce glissement actif a connu un fort episode de glissements en juillet 2012, ou un volume de 2,0 x [10.sup.7] [m.sup.3] a ete mobilise, emportant une large portion de la Route 112. Les operations minieres ont cesse en 2012, causant l'arret complet du systeme de pompage lequel visait a prevenir la montee du niveau d'eau dans la fosse. Comme le niveau d'eau augmente dans la fosse il devient primordial de determiner le potentiel tsunamigenique genere par des glissements rocheux partiellement submerges possibles afin de comprendre le phenomene et de reagir efficacement a celui-ci. Plusieurs modelisations numeriques ont ete realisees a partir de scenarios probables concernant les vitesses et les accelerations de glissement rocheux potentiel ainsi que la formation de vagues et l'inondation correspondantes. Les modelisations effectuees ont permis de montrer que, lorsque le facteur de securite de la pente globale est inferieur a 1, aucune infrastructure potentiellement vulnerable ne serait touchee par un eventuel tsunami. La hauteur maximale de la vague generee sera fonction de la hauteur d'eau dans le bassin. Les hauteurs de vagues minimales, relatives au niveau d'eau dans le bassin, seront generees lorsque le bassin sera completement rempli.Mots-cles: tsunami genere par un glissement de terrain, glissement partiellement submerge, modelisation numerique, mine a ciel ouvert, glissement rocheux actif., 1. IntroductionApproximately 90 km south of Quebec City, on the border between Black Lake sector to the north (part of Thetford Mines) and the municipality of Saint-Joseph-de-Coleraine to the south, [...]

Stock price prediction has been a subject of significant interest in the financial mathematics field. Recently, interest in natural language processing models has increased, and among them, transformer models, such as BERT and FinBERT, are attracting attention. This study uses a mathematical framework to investigate the effects of human sentiment on stock movements, especially in text data. In particular, FinBERT, a domain-specific language model based on BERT tailored for financial language, was employed for the sentiment analysis on the financial texts to extract sentiment information. In this study, we use "summary" text data extracted from The New York Times, representing concise summaries of news articles. Accordingly, we apply FinBERT to the summary text data to calculate sentiment scores. In addition, we employ the LSTM (Long short-term memory) methodology, one of the machine learning models, for stock price prediction using sentiment scores. Furthermore, the LSTM model was trained by stock price data and the estimated sentiment scores. We compared the predictive power of LSTM models with and without sentiment analysis based on error measures such as MSE, RMSE, and MAE. The empirical results demonstrated that including sentiment scores through the LSTM model led to improved prediction accuracy for all three measures. These findings indicate the significance of incorporating news sentiment into stock price predictions, shedding light on the potential impact of psychological factors on financial markets. By using the FinBERT transformer model, this study aimed to investigate the interplay between sentiment and stock price predictions, contributing to a deeper understanding of mathematical-based sentiment analysis in finance and its role in enhancing forecasting in financial mathematics. Furthermore, we show that using summary data instead of entire news articles is a useful strategy for mathematical-based sentiment analysis. [ABSTRACT FROM AUTHOR]

Pressure sensors made on a mechanically deformable substrates are widely available for health monitoring systems, tactile sensors, and human–machine interfaces. While their sensitivity typically exceeds that of the human skin, it is highly challenging to perceive multiple kinds of mechanical inputs, such as normal, stretching, bending, and/or twisting forces, in a decoupled manner. For example, the interpretation of the specific pressure‐related distortion requires differentiation of such pressure stimuli from the simultaneously measured mixed deformation. This report proposes a sensor with an engineered geometrical configuration that dramatically reduces its mechanical distortion made by non‐pressure related stimuli. Such decoupled‐sensing capability for normal force is characterized by a linear response of fractional resistance change at 2.07 kPa−1 and negligible responses to other deformations such as stretching and bending. An in vitro sensor demonstration for the diagnosis of stress urinary incontinence presents one mode of practical application of the sensor. Facile fabrication allows an interconnected array and wireless network to capture the spatial distribution of normal force and to record the data with consumer devices, respectively. [ABSTRACT FROM AUTHOR]

In digital identity authentication, credentials are typically stored in a digital wallet and authenticated through a single key-based signature and public key verification. However, ensuring compatibility between systems and credentials can be challenging and the existing architecture can create a single point of failure, which can hinder system stability and prevent data interchange. To address this problem, we propose a multiparty distributed signature structure using FROST, a Schnorr signature-based threshold signature algorithm, applied to the WACI protocol framework for credential interaction. This approach eliminates a single point of failure and secures the signer's anonymity. Additionally, by following standard interoperability protocol procedures, we can ensure interoperability during the exchange of digital wallets and credentials. This paper presents a method that combines a multiparty distributed signature algorithm and an interoperability protocol, and discusses the implementation results. [ABSTRACT FROM AUTHOR]