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Recent developments in online communication and their usage in everyday life have caused an explosion in the amount of a new genre of text data, short text. Thus, the need to classify this type of text based on its content has a significant implication in many areas. Online debates are no exception, once these provide access to information about opinions, positions and preferences of its users. This paper aims to use data obtained from online social conversations in Portuguese schools (short text) to observe behavioural trends and to see if students remain engaged in the discussion when stimulated. This project used the state of the art (SoA) Machine Learning (ML) algorithms and methods, through BERT based models to classify if utterances are in or out of the debate subject. Using SBERT embeddings as a feature, with supervised learning, the proposed model achieved results above 0.95 average accuracy for classifying online messages. Such improvements can help social scientists better understand human communication, behaviour, discussion and persuasion.

Several domains of society will be disrupted once millions of high-quality qubits can be brought together to perform fault-tolerant quantum computing (FTQC). All quantum computing hardware available today is many orders of magnitude removed from the requirements for FTQC. The intimidating challenges associated with integrating such complex systems have already been addressed by the semiconductor industry -hence many qubit makers have retrofitted their technology to be CMOS-compatible. This compatibility, however, can have varying degrees ranging from the mere ability to fabricate qubits using a silicon wafer as a substrate, all the way to the co-integration of qubits with high-yield, low-power advanced electronics to control these qubits. Extrapolating the evolution of quantum processors to future systems, semiconductor spin qubits have unique advantages in this respect, making them one of the most serious contenders for large-scale FTQC. In this review, we focus on the overlap between state-of-the-art semiconductor spin qubit systems and CMOS industry Very Large-Scale Integration (VLSI) principles. We identify the main differences in spin qubit operation, material, and system requirements compared to well-established CMOS industry practices. As key players in the field are looking to collaborate with CMOS industry partners, this review serves to accelerate R&D towards the industrial scale production of FTQC processors., Comment: 36 pages, 5 figures

This paper introduces a reinforcement learning (RL) platform that enhances end-to-end user journeys in healthcare digital tools through personalization. We explore a case study with SwipeRx, the most popular all-in-one app for pharmacists in Southeast Asia, demonstrating how the platform can be used to personalize and adapt user experiences. Our RL framework is tested through a series of experiments with product recommendations tailored to each pharmacy based on real-time information on their purchasing history and in-app engagement, showing a significant increase in basket size. By integrating adaptive interventions into existing mobile health solutions and enriching user journeys, our platform offers a scalable solution to improve pharmaceutical supply chain management, health worker capacity building, and clinical decision and patient care, ultimately contributing to better healthcare outcomes., Comment: Presented at the Third Workshop on End-to-End Customer Journey Optimization at KDD 2024 (KDD CJ Workshop '24), August 26, Barcelona, Spain

Pharmacies are critical in healthcare systems, particularly in low- and middle-income countries. Procuring pharmacists with the right behavioral interventions or nudges can enhance their skills, public health awareness, and pharmacy inventory management, ensuring access to essential medicines that ultimately benefit their patients. We introduce a reinforcement learning operational system to deliver personalized behavioral interventions through mobile health applications. We illustrate its potential by discussing a series of initial experiments run with SwipeRx, an all-in-one app for pharmacists, including B2B e-commerce, in Indonesia. The proposed method has broader applications extending beyond pharmacy operations to optimize healthcare delivery., Comment: Presented at The First Workshop on AI Behavioral Science (AIBS'24) at KDD 2024, August 25, Barcelona, Spain

We exhibit an example of a discontinuity point for the Lyapunov exponents as a function of the cocycle in the H\"older topology. The linear cocycle taking values in SL$(2,\mathbb{R})$ is locally constant and defined over a Bernoulli shift. Our example extends Bocker-Viana's and Butler's results., Comment: 6 pages

Superior computational power promised by quantum computers utilises the fundamental quantum mechanical principle of entanglement. However, achieving entanglement and verifying that the generated state does not follow the principle of local causality has proven difficult for spin qubits in gate-defined quantum dots, as it requires simultaneously high concurrence values and readout fidelities to break the classical bound imposed by Bell's inequality. Here we employ heralded initialization and calibration via gate set tomography (GST), to reduce all relevant errors and push the fidelities of the full 2-qubit gate set above 99 %, including state preparation and measurement (SPAM). We demonstrate a 97.17 % Bell state fidelity without correcting for readout errors and violate Bell's inequality with a Bell signal of S = 2.731 close to the theoretical maximum of $2\sqrt{2}$. Our measurements exceed the classical limit even at elevated temperatures of 1.1 K or entanglement lifetimes of 100 $\mu s$., Comment: 19 pages, 5 main figures, 9 extended data figures

A new readout technique was developed with the primary aim of keeping the number of channels in the front-end electronics as low as possible when scaling up the sensitive area of a Resistive Plate Chamber (RPC). The readout method here presented significantly reduces the dependence between the detector area and the number of electronic channels, without substantial reduction of its performance: a 30 cm x 30 cm double stack multi-gap timing RPC was operated during weeks with cosmic rays, achieving a 2D spatial resolution well below 1 mm and time resolution lower than 100 ps, while its efficiency was kept above 98%., Comment: 16th Pisa Meeting on Advanced Detectors

Silicon quantum computing has the potential to revolutionize technology with capabilities to solve real-life problems that are computationally complex or even intractable for modern computers [1] by offering sufficient high quality qubits to perform complex error-corrected calculations. Silicon metal-oxide-semiconductor based quantum dots present a promising pathway for realizing practical quantum computers. To improve certain qubit properties, it is a common strategy to incorporate multiple electrons in the same dot in order to form qubits in higher confined orbital states. Theoretical modelling is an essential part of understanding the quantum behaviour of these electrons, providing a basis for validating the physical working of device models as well as providing insights into experimental data. Hartree-Fock theory is an imperative tool for the electronic structure modelling of multi-electron quantum dots due to its ability to simulate a large number of electrons with manageable computation load. However, an efficient calculation of the self-consistent field becomes hard because dot formations in silicon are characterized by strong electron-electron interactions and conduction band valleys, besides the relatively high comparative effective mass, which add to create a behaviour dominated by repulsion between electrons rather than a well established shell structure. In this paper, we present a Hartree-Fock-based method that accounts for these complexities for the modelling of silicon quantum dots. With this method, we first establish the significance of including electron-electron interactions and valley degree of freedom and their implications. We then explore a simple case of anisotropic dots and observe the impact of anisotropy on dot formations.

Recently we have proposed a new concept of a thermal neutron detector based on resistive plate chambers and 10B4C solid neutron converters, enabling to readout with high resolution in both the 3D position of neutron capture and the neutron time of flight (ToF). In this paper, we report the results of the first beam tests conducted with a new neutron RPC detection module, coupled to the position readout units of a new design. The main focus is on the measurements of the neutron ToF and identification of the converter layer where the neutron is captured, giving the position along the beam direction.

Most paints contain pigments that absorb light and fade over time. A robust alternative can be found in nature, where structural coloration arises from the interference of light with submicron features. Plant-derived, cellulose nanocrystals (CNCs) mimic these features by self-assembling into a cholesteric liquid crystal that exhibits structural coloration when dried. While much research has been done on CNCs in aqueous solutions, less is known about transferring CNCs to apolar solvents that are widely employed in paints. This study uses a common surfactant in agricultural and industrial products to suspend CNCs in toluene that are then dried into structurally colored films. Surprisingly, a stable liquid crystal phase is formed within hours, even with concentrations of up to 50 wt.-%. Evaporating the apolar CNC suspensions results in photonic films with peak wavelengths ranging from 660 to 920 nm. The resulting flexible films show increased mechanical strength, enabling a blue-shift into the visible spectrum with applied force. The films also act as humidity sensors, with increasing relative humidity yielding a red-shift. With the addition of a single surfactant, CNCs can be made compatible with existing production methods of industrial coatings, while improving the strength and responsiveness of structurally-colored films to external stimuli., Comment: 11 pages, 4 figures

Coherently dressed spins have shown promising results as building blocks for future quantum computers owing to their resilience to environmental noise and their compatibility with global control fields. This mode of operation allows for more amenable qubit architecture requirements and simplifies signal routing on the chip. However, multi-qubit operations, such as qubit addressability and two-qubit gates, are yet to be demonstrated to establish global control in combination with dressed qubits as a viable path to universal quantum computing. Here we demonstrate simultaneous on-resonance driving of degenerate qubits using a global field while retaining addressability for qubits with equal Larmor frequencies. Furthermore, we implement SWAP oscillations during on-resonance driving, constituting the demonstration of driven two-qubit gates. Significantly, our findings highlight the fragility of entangling gates between superposition states and how dressing can increase the noise robustness. These results represent a crucial milestone towards global control operation with dressed qubits. It also opens a door to interesting spin physics on degenerate spins.

The Option Keyboard (OK) was recently proposed as a method for transferring behavioral knowledge across tasks. OK transfers knowledge by adaptively combining subsets of known behaviors using Successor Features (SFs) and Generalized Policy Improvement (GPI). However, it relies on hand-designed state-features and task encodings which are cumbersome to design for every new environment. In this work, we propose the "Successor Features Keyboard" (SFK), which enables transfer with discovered state-features and task encodings. To enable discovery, we propose the "Categorical Successor Feature Approximator" (CSFA), a novel learning algorithm for estimating SFs while jointly discovering state-features and task encodings. With SFK and CSFA, we achieve the first demonstration of transfer with SFs in a challenging 3D environment where all the necessary representations are discovered. We first compare CSFA against other methods for approximating SFs and show that only CSFA discovers representations compatible with SF&GPI at this scale. We then compare SFK against transfer learning baselines and show that it transfers most quickly to long-horizon tasks., Comment: NeurIPS 2023

Silicon hole quantum dots have been the subject of considerable attention thanks to their strong spin-orbit coupling enabling electrical control. The physics of silicon holes is qualitatively different from germanium holes and requires a separate theoretical description. In this work, we theoretically study the electrical control and coherence properties of silicon hole dots with different magnetic field orientations. We discuss possible experimental configurations to optimize the electric dipole spin resonance (EDSR) Rabi time, the phonon relaxation time, and the dephasing due to random telegraph noise. Our main findings are: (i) The in-plane $g$-factor is strongly influenced by the presence of the split-off band, as well as by any shear strain. The $g$-factor is a non-monotonic function of the top gate electric field, in agreement with recent experiments. This enables coherence sweet spots at specific values of the top gate field and specific magnetic field orientations. (ii) Even a small ellipticity (aspect ratios $\sim 1.2$) causes significant anisotropy in the in-plane $g$-factor, which can vary by $50\% - 100\%$ as the magnetic field is rotated in the plane. (iii) EDSR Rabi frequencies are comparable to Ge, and the ratio between the relaxation time and the EDSR Rabi time $\sim 10^5$. For an out-of-plane magnetic field the EDSR Rabi frequency is anisotropic with respect to the orientation of the driving electric field, varying by $\approx 20\%$ as the driving field is rotated in the plane. Our work aims to stimulate experiments by providing guidelines on optimizing configurations and geometries to achieve robust, fast and long-lived hole spin qubits in silicon., Comment: 22 Pages, 11 figures