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    The History of Quantum Games
    (IEEE, 2023) Piispanen, Laura; Morrell, Edward; Park, Solip; Pfaffhauser, Marcell; Kultima, Annakaisa; Department of Computer Science; Department of Art and Media; IBM Research Zurich; Department of Computer Science; Department of Art and Media
    In this paper, we explore the historical development of playable quantum physics related games (“quantum games”). For the purpose of this examination, we have collected over 260 quantum games ranging from commercial games, applied and serious games, and games that have been developed at quantum themed game jams and educational courses. We provide an overview of the journey of quantum games across three dimensions: the perceivable dimension of quantum physics, the dimension of scientific purposes, and the dimension of quantum technologies. We then further reflect on the definition of quantum games and its implications. While motivations behind developing quantum games have typically been educational or academic, themes related to quantum physics have begun to be more broadly utilised across a range of commercial games. In addition, as the availability of quantum computer hardware has grown, entirely new variants of quantum games have emerged to take advantage of these machines' inherent capabilities, Quantum Computer Games.
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    Machine Learning Applications for Smart Building Energy Utilization: A Survey
    (Springer, 2024-02-05) Huotari, Matti; Främling, Kary; Malhi, Avleen; Department of Electrical Engineering and Automation; Department of Industrial Engineering and Management; Department of Electrical Engineering and Automation; Department of Industrial Engineering and Management; Department of Computer Science
    The United Nations launched sustainable development goals in 2015 that include goals for sustainable energy. From global energy consumption, households consume 20–30% of energy in Europe, North America and Asia; furthermore, the overall global energy consumption has steadily increased in the recent decades. Consequently, to meet the increased energy demand and to promote efficient energy consumption, there is a persistent need to develop applications enhancing utilization of energy in buildings. However, despite the potential significance of AI in this area, few surveys have systematically categorized these applications. Therefore, this paper presents a systematic review of the literature, and then creates a novel taxonomy for applications of smart building energy utilization. The contributions of this paper are (a) a systematic review of applications and machine learning methods for smart building energy utilization, (b) a novel taxonomy for the applications, (c) detailed analysis of these solutions and techniques used for the applications (electric grid, smart building energy management and control, maintenance and security, and personalization), and, finally, (d) a discussion on open issues and developments in the field.
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    Nanoscopic spin-wave channeling along programmable magnetic domain walls in a CoFeB/BaTiO3 multiferroic heterostructure
    (American Institute of Physics, 2024-01-22) Zhu, Weijia; Qin, Huajun; van Dijken, Sebastiaan; Nanomagnetism and Spintronics; Wuhan University; Department of Applied Physics
    We report a micromagnetic study on spin-wave propagation along magnetic domain walls in a ferromagnetic/ferroelectric bilayer. In our system, strain coupling between the two ferroic materials and inverse magnetostriction produce a fully correlated domain pattern wherein straight and narrow ferroelectric domain walls pin the magnetic domain walls. Consequently, an external magnetic field does tailor the spin structure of the magnetic domain walls instead of moving them. We use experimental parameters from a previously studied CoFeB/BaTiO3 material system to investigate the potential of artificial multiferroics for programmable nanoscopic spin-wave channeling. We show that spin waves are transported along the pinned magnetic domain walls at zero magnetic field and low frequency due to a local demagnetizing field. Further, switching of the domain wall spin structure from a head-to-tail to a head-to-head configuration abruptly changes the propagating spin-wave mode. We study the effect of magnetic field strength on the localized modes and discuss reversible control of spin-wave channeling via electric-field-driven magnetic domain wall motion. Nanoscopic guiding of propagating spin waves by an electric field, in combination with positional robustness to and mode programming by an external magnetic field, offers prospects for low-power and reconfigurable domain-wall-based magnonic devices.
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    Bodily maps of musical sensations across cultures
    (National Academy of Sciences, 2024-01-25) Putkinen, Vesa; Zhou, Xinqi; Gan, Xianyang; Yang, Linyu; Becker, Benjamin; Sams, Mikko; Nummenmaa, Lauri; University of Turku; Sichuan Normal University; University of Electronic Science and Technology of China; Sichuan University; The University of Hong Kong; Department of Neuroscience and Biomedical Engineering; Department of Neuroscience and Biomedical Engineering
    Emotions, bodily sensations and movement are integral parts of musical experiences. Yet, it remains unknown i) whether emotional connotations and structural features of music elicit discrete bodily sensations and ii) whether these sensations are culturally consistent. We addressed these questions in a cross-cultural study with Western (European and North American, n = 903) and East Asian (Chinese, n = 1035). We precented participants with silhouettes of human bodies and asked them to indicate the bodily regions whose activity they felt changing while listening to Western and Asian musical pieces with varying emotional and acoustic qualities. The resulting bodily sensation maps (BSMs) varied as a function of the emotional qualities of the songs, particularly in the limb, chest, and head regions. Music-induced emotions and corresponding BSMs were replicable across Western and East Asian subjects. The BSMs clustered similarly across cultures, and cluster structures were similar for BSMs and self-reports of emotional experience. The acoustic and structural features of music were consistently associated with the emotion ratings and music-induced bodily sensations across cultures. These results highlight the importance of subjective bodily experience in music-induced emotions and demonstrate consistent associations between musical features, music-induced emotions, and bodily sensations across distant cultures.
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    Detecting virtual photons in ultrastrongly coupled superconducting quantum circuits
    (American Physical Society, 2024-01) Giannelli, L.; Paladino, E.; Grajcar, M.; Paraoanu, G. S.; Falci, G.; National Research Council of Italy; Comenius University Bratislava; Centre of Excellence in Quantum Technology, QTF; Department of Applied Physics
    Light-matter interaction and understanding the fundamental physics behind is essential for emerging quantum technologies. Solid-state devices may explore new regimes where coupling strengths are "ultrastrong", i.e., comparable to the energies of the subsystems. New exotic phenomena occur the common root of many of them being the fact that the entangled vacuum contains virtual photons. They herald the lack of conservation of the number of excitations which is the witness of ultrastrong coupling breaking the U(1) symmetry. Despite more than a decade of research, the detection of ground-state virtual photons still awaits demonstration. In this work, we recognize the "conspiring"set of experimental challenges and show how to overcome them, thus providing a solution to this long-standing problem. We find that combining a superinductor-based unconventional "light fluxonium"qudit and coherent control yields a highly efficient, faithful, and selective conversion of virtual photons into real ones. This enables their detection with resources available to present-day quantum technologies.
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    Developing eHealth for Home Dialysis : Clinicians' Needs for a Digital Patient Engagement Platform
    (IOS Press, 2024-01-25) Hölsä, Sini; Viitanen, Johanna; Valkonen, Paula; Lääveri, Tinja; Rauta, Virpi; Department of Computer Science; Computer Science Professors; Professorship Viitanen Johanna; University of Helsinki; Department of Computer Science
    eHealth solutions such as digital patient engagement platforms (DPEPs) aim at enhancing communication and collaboration between patients and clinicians. From the clinicians' viewpoint, concerns exist about new information systems (IS) leading to increased workload and interoperability problems. This article aims to support the development and implementation of DPEPs from the end-users' perspective. We studied clinicians' needs for a new DPEP developed to support home dialysis (HD) care. Eight clinicians participated in remote semi-structured interviews. Clinicians had positive expectations for the new DPEP as it could provide an overall picture of patients' status, support patients' self-care, and save time during patient visits. However, they had concerns about successful implementation, changes to workflows, and integration issues. To conclude, it is important to design and agree on changes in work practices, patient care, and complex IS environments when implementing new DPEP solutions in clinics.
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    Locality in Online, Dynamic, Sequential, and Distributed Graph Algorithms
    (2023-07-05) Akbari, Amirreza; Eslami, Navid; Lievonen, Henrik; Melnyk, Darya; Särkijärvi, Joona; Suomela, Jukka; Department of Computer Science; Professorship Suomela J.; Computer Science Professors; Department of Computer Science; Etessami, Kousha; Feige, Uriel; Puppis, Gabriele
    In this work, we give a unifying view of locality in four settings: distributed algorithms, sequential greedy algorithms, dynamic algorithms, and online algorithms. We introduce a new model of computing, called the online-LOCAL model: the adversary presents the nodes of the input graph one by one, in the same way as in classical online algorithms, but for each node we get to see its radius-T neighborhood before choosing the output. Instead of looking ahead in time, we have the power of looking around in space. We compare the online-LOCAL model with three other models: the LOCAL model of distributed computing, where each node produces its output based on its radius-T neighborhood, the SLOCAL model, which is the sequential counterpart of LOCAL, and the dynamic-LOCAL model, where changes in the dynamic input graph only influence the radius-T neighborhood of the point of change. The SLOCAL and dynamic-LOCAL models are sandwiched between the LOCAL and online-LOCAL models. In general, all four models are distinct, but we study in particular locally checkable labeling problems (LCLs), which is a family of graph problems extensively studied in the context of distributed graph algorithms. We prove that for LCL problems in paths, cycles, and rooted trees, all four models are roughly equivalent: the locality of any LCL problem falls in the same broad class – O(log∗ n), Θ(log n), or nΘ(1) – in all four models. In particular, this result enables one to generalize prior lower-bound results from the LOCAL model to all four models, and it also allows one to simulate e.g. dynamic-LOCAL algorithms efficiently in the LOCAL model. We also show that this equivalence does not hold in two-dimensional grids or general bipartite graphs. We provide an online-LOCAL algorithm with locality O(log n) for the 3-coloring problem in bipartite graphs – this is a problem with locality Ω(n1/2) in the LOCAL model and Ω(n1/10) in the SLOCAL model.
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    Designing Quantum Games and Quantum Art for Exploring Quantum Physics
    (IEEE, 2023) Piispanen, Laura; Department of Computer Science; Department of Computer Science
    In this paper, the design processes of five games, simulations, and interactive art installations involving quantum physics is reported and reflected. These projects were developed between 2019 and 2022 and include smaller game jam projects and longer-term collaborations with a professional game company. The design reflections explore the issues that can influence the success of serious and applied games, as well as art pieces used in science communication, research, or educational roles. Based on these experiences, it is evident that design constraints, design values, effective communication, and the valuation of each other’s expertise are at the center of successful quantum game development.
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    Creating Digital LAM Content for Schools : Modelling User Involvement in Multi-organisational Context
    (Springer, 2023) Peltonen, Riitta; Nieminen, Marko; National Library of Finland; Department of Computer Science; Department of Computer Science; Goh, Dion H.; Chen, Shu-Jiun; Tuarob, Suppawong
    Public services are usually created in a network of organisations, meta-organisations that consist multiple actors with variety of capacities. Managing work in meta-organisations face unique challenges due to multiple stakeholders with different understandings of the tasks. Management of the work requires shared base understanding of contributions needed from multiple stakeholders and for many tasks, this is not yet properly understood and modelled. User-centred design, even it supports well multi-disciplinary development of systems and services with multiple actors and can be applied to ascertain a balanced outcome from the design work, is one of these areas that lacks this understanding and requires further modelling. Typically, user-centred design responsibilities are set in a public organisation who creates the digital service platform. Through our case on creating digital library, archive, and museum (LAM) content service for schools, we study how user centred design activities happen outside the platform provider organisation. More specifically, we study how the content creation organisations can utilise the expertise of a teacher and identify how this expertise can be incorporated in content creation organisations. Based on our findings we form a tentative model for user involvement in meta-organisations (UIMO) which aims to formulate a structure for the user-centred design responsibilities in networked environment.
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    Horseshoe prior Bayesian quantile regression
    (Wiley-Blackwell, 2024-01) Kohns, D; Szendrei, Tibor; Department of Computer Science; Heriot-Watt University; Department of Computer Science
    This paper extends the horseshoe prior to Bayesian quantile regression and provides a fast sampling algorithm for computation in high dimensions. Compared to alternative shrinkage priors, our method yields better performance in coefficient bias and forecast error, especially in sparse designs and in estimating extreme quantiles. In a high-dimensional growth-at-risk forecasting application, we forecast tail risks and complete forecast densities using a database covering over 200 macroeconomic variables. Quantile specific and density calibration score functions show that our method provides competitive performance compared to competing Bayesian quantile regression priors, especially at short- and medium-run horizons.
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    Electronic structure and lattice dynamics of 1T-VSe2 : Origin of the three-dimensional charge density wave
    (American Physical Society, 2024-01-15) Diego, Josu; Subires, D.; Said, A. H.; Chaney, D. A.; Korshunov, A.; Garbarino, G.; Diekmann, F.; Mahatha, S. K.; Pardo, V.; Wilkinson, J. M.; Lord, J. S.; Strempfer, J.; Perez, Pablo J.Bereciartua; Francoual, S.; Popescu, C.; Tallarida, M.; Dai, J.; Bianco, Raffaello; Monacelli, Lorenzo; Calandra, Matteo; Bosak, A.; Mauri, Francesco; Rossnagel, K.; Fumega, Adolfo O.; Errea, Ion; Blanco-Canosa, S.; University of the Basque Country; Donostia International Physics Center; Argonne National Laboratory; European Synchrotron Radiation Facility; German Electron Synchrotron; University of Santiago de Compostela; Rutherford Appleton Laboratory; Autonomous University of Barcelona; University of Modena and Reggio Emilia; Swiss Federal Institute of Technology Lausanne; BEC-INFM; Italian Institute of Technology; Correlated Quantum Materials (CQM); Department of Applied Physics
    To characterize in detail the charge density wave (CDW) transition of 1T-VSe2, its electronic structure and lattice dynamics are comprehensively studied by means of x-ray diffraction, muon spectroscopy, angle resolved photoemission (ARPES), diffuse and inelastic x-ray scattering, and state-of-the-art first-principles density functional theory calculations. Resonant elastic x-ray scattering does not show any resonant enhancement at either V or Se, indicating that the CDW peak at the K edges describes a purely structural modulation of the electronic ordering. ARPES experiments identify (i) a pseudogap at T>TCDW, which leads to a depletion of the density of states in the ML-M'L' plane at T
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    Generative AI for graph-based drug design: Recent advances and the way forward
    (Elsevier, 2024) Garg, Vikas; Computer Science Professors; Department of Computer Science
    Discovering new promising molecule candidates that could translate into effective drugs is a key scientific pursuit. However, factors such as the vastness and discreteness of the molecular search space pose a formidable technical challenge in this quest. AI-driven generative models can effectively learn from data, and offer hope to streamline drug design. In this article, we review state of the art in generative models that operate on molecular graphs. We also shed light on some limitations of the existing methodology and sketch directions to harness the potential of AI for drug design tasks going forward.
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    A comparative study of clinical trial and real-world data in patients with diabetic kidney disease
    (Nature Publishing Group, 2024-01-19) Kurki, Samu; Halla-aho, Viivi; Haussmann, Manuel; Lähdesmäki, Harri; Leinonen, Jussi V.; Koskinen, Miika; Bayer Oy; University of Helsinki; Department of Computer Science; Computer Science Professors; Department of Computer Science
    A growing body of research is focusing on real-world data (RWD) to supplement or replace randomized controlled trials (RCTs). However, due to the disparities in data generation mechanisms, differences are likely and necessitate scrutiny to validate the merging of these datasets. We compared the characteristics of RCT data from 5734 diabetic kidney disease patients with corresponding RWD from electronic health records (EHRs) of 23,523 patients. Demographics, diagnoses, medications, laboratory measurements, and vital signs were analyzed using visualization, statistical comparison, and cluster analysis. RCT and RWD sets exhibited significant differences in prevalence, longitudinality, completeness, and sampling density. The cluster analysis revealed distinct patient subgroups within both RCT and RWD sets, as well as clusters containing patients from both sets. We stress the importance of validation to verify the feasibility of combining RCT and RWD, for instance, in building an external control arm. Our results highlight general differences between RCT and RWD sets, which should be considered during the planning stages of an RCT-RWD study. If they are, RWD has the potential to enrich RCT data by providing first-hand baseline data, filling in missing data or by subgrouping or matching individuals, which calls for advanced methods to mitigate the differences between datasets.
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    Microwave quantum diode
    (Nature Publishing Group, 2024-01-20) Upadhyay, Rishabh; Golubev, Dmitry S.; Chang, Yu Cheng; Thomas, George; Guthrie, Andrew; Peltonen, Joonas T.; Pekola, Jukka P.; Quantum Phenomena and Devices; Centre of Excellence in Quantum Technology, QTF; Department of Applied Physics
    The fragile nature of quantum circuits is a major bottleneck to scalable quantum applications. Operating at cryogenic temperatures, quantum circuits are highly vulnerable to amplifier backaction and external noise. Non-reciprocal microwave devices such as circulators and isolators are used for this purpose. These devices have a considerable footprint in cryostats, limiting the scalability of quantum circuits. As a proof-of-concept, here we report a compact microwave diode architecture, which exploits the non-linearity of a superconducting flux qubit. At the qubit degeneracy point we experimentally demonstrate a significant difference between the power levels transmitted in opposite directions. The observations align with the proposed theoretical model. At − 99 dBm input power, and near the qubit-resonator avoided crossing region, we report the transmission rectification ratio exceeding 90% for a 50 MHz wide frequency range from 6.81 GHz to 6.86 GHz, and over 60% for the 250 MHz range from 6.67 GHz to 6.91 GHz. The presented architecture is compact, and easily scalable towards multiple readout channels, potentially opening up diverse opportunities in quantum information, microwave read-out and optomechanics.
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    Euclid preparation : XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong-lensing events
    (EDP Sciences, 2024-01-01) Leuzzi, L.; Meneghetti, M.; Angora, G.; Metcalf, R. B.; Moscardini, L.; Rosati, P.; Bergamini, P.; Calura, F.; Clément, B.; Gavazzi, R.; Gentile, F.; Lochner, M.; Grillo, C.; Vernardos, G.; Aghanim, N.; Amara, A.; Amendola, L.; Auricchio, N.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Capobianco, V.; Carbone, C.; Carretero, J.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; Dinis, J.; Dubath, F.; Dupac, X.; Dusini, S.; Farrens, S.; Niemi, S. M.; Schneider, P.; Wang, Y.; Gozaliasl, G.; Sánchez, A. G.; , Euclid Collaboration; Universita di Bologna; Istituto di Astrofisica Spaziale e Fisica Cosmica di Bologna; University of Ferrara; Swiss Federal Institute of Technology Lausanne; Aix-Marseille Université; University of the Western Cape; University of Milano; Université Paris-Saclay; University of Portsmouth; Heidelberg University ; Max Planck Institute for Extraterrestrial Physics; National Institute for Astrophysics (INAF); University of Genoa; Osservatorio Astronomico di Capodimonte; Universidade do Porto; Istituto Nazionale di Astrofisica (INAF); Institute for High Energy Physics; Osservatorio Astronomico di Roma; Centre national d'études spatiales; University of Edinburgh; University of Manchester; ESRIN - ESA Centre for Earth Observation; Université Claude Bernard Lyon 1; University College London; University of Lisbon; University of Geneva; Urbanización Villafranca Del Castillo; National Institute for Nuclear Physics; European Space Research and Technology Centre; University of Bonn; California Institute of Technology; Department of Computer Science
    Forthcoming imaging surveys will increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of billions of galaxies will have to be inspected to identify potential candidates. In this context, deep-learning techniques are particularly suitable for finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong-lensing systems on the basis of their morphological characteristics. In particular, we implemented a classical CNN architecture, an inception network, and a residual network. We trained and tested our networks on different subsamples of a data set of 40 000 mock images whose characteristics were similar to those expected in the wide survey planned with the ESA mission Euclid, gradually including larger fractions of faint lenses. We also evaluated the importance of adding information about the color difference between the lens and source galaxies by repeating the same training on single- and multiband images. Our models find samples of clear lenses with 90% precision and completeness. Nevertheless, when lenses with fainter arcs are included in the training set, the performance of the three models deteriorates with accuracy values of ~0.87 to ~0.75, depending on the model. Specifically, the classical CNN and the inception network perform similarly in most of our tests, while the residual network generally produces worse results. Our analysis focuses on the application of CNNs to high-resolution space-like images, such as those that the Euclid telescope will deliver. Moreover, we investigated the optimal training strategy for this specific survey to fully exploit the scientific potential of the upcoming observations. We suggest that training the networks separately on lenses with different morphology might be needed to identify the faint arcs. We also tested the relevance of the color information for the detection of these systems, and we find that it does not yield a significant improvement. The accuracy ranges from ~0.89 to ~0.78 for the different models. The reason might be that the resolution of the Euclid telescope in the infrared bands is lower than that of the images in the visual band.
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    Electromagnetic effects in anti-Hermitian media with gain and loss
    (American Physical Society, 2024-01) Freter, L.; Mirmoosa, M. S.; Sihvola, A.; Simovski, C. R.; Tretyakov, S. A.; Quantum Dynamics; University of Eastern Finland; Department of Electronics and Nanoengineering; Department of Applied Physics; Department of Electronics and Nanoengineering
    Incorporating both gain and loss into electromagnetic systems provides possibilities to engineer effects in unprecedented ways. Concerning electromagnetic effects in isotropic media that have concurrently electric and magnetic responses, there is, in fact, a degree of freedom to distribute the gain and loss in different effective material parameters. In this paper, we analytically scrutinize wave interactions with those media, and, most importantly, we contemplate the extreme scenario where such media are anti-Hermitian. Considering various conditions for excitation, polarization, and geometry, we uncover important effects and functionalities such as lasing into both surface waves and propagating waves, conversion of evanescent source fields to transmitted propagating waves, full absorption, and enhancing backward to forward scattering ratio. We hope that these findings explicitly show the potential of anti-Hermiticity to be used in optical physics as well as microwave engineering for creating and using unconventional wave phenomena.
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    Self-Supervised Forecasting in Electronic Health Records with Attention-Free Models
    (IEEE, 2024) Kumar, Yogesh; Ilin, Alexander; Salo, Henri; Kulathinal, Sangita; Leinonen, Maarit K.; Marttinen, Pekka; Department of Computer Science; National Institute for Health and Welfare; University of Helsinki; Computer Science Professors; Department of Computer Science
    Despite the proven effectiveness of Transformer neural networks across multiple domains, their performance with Electronic Health Records (EHR) can be nuanced. The unique, multidimensional sequential nature of EHR data can sometimes make even simple linear models with carefully engineered features more competitive. Thus, the advantages of Transformers, such as efficient transfer learning and improved scalability are not always fully exploited in EHR applications. In this work, we aim to forecast the demand for healthcare services, by predicting the number of patient visits to healthcare facilities. The challenge amplifies when dealing with divergent patient subgroups, like those with rare diseases, which are characterized by unique health trajectories and are typically smaller in size. To address this, we employ a self-supervised pretraining strategy, Generative Summary Pretraining (GSP), which predicts future summary statistics based on past health records of a patient. Our models are pretrained on a health registry of nearly one million patients, then fine-tuned for specific subgroup prediction tasks, showcasing the potential to handle the multifaceted nature of EHR data. In evaluation, SANSformer consistently surpasses robust EHR baselines, with our GSP pretraining method notably amplifying model performance, particularly within smaller patient subgroups. Our results illuminate the promising potential of tailored attention-free models and self-supervised pretraining in refining healthcare utilization predictions across various patient demographics.
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    Measuring digital intervention user experience with a novel ecological momentary assessment (EMA) method, CORTO
    (Elsevier, 2024-03) Lukka, Lauri; Karhulahti, Veli Matti; Bergman, Vilma Reetta; Palva, J. Matias; Department of Neuroscience and Biomedical Engineering; University of Jyväskylä; Department of Neuroscience and Biomedical Engineering
    Digital interventions often suffer from low usage, which may reflect insufficient attention to user experience. Moreover, the existing evaluation methods have limited applicability in the remote study of user experience of complex interventions that have expansive content and that are used over an extensive period of time. To alleviate these challenges, we describe here a novel qualitative Ecological Momentary Assessment (EMA) method: the CORTO method (Contextual, One-item, Repeated, Timely, Open-ended). We used it to gather digital intervention user experience data from Finnish adults (n = 184) who lived with interview-confirmed major depressive disorder (MDD) and took part in a randomized controlled trial (RCT) that studied the efficacy of a novel 12-week game-based digital intervention for depression. A second dataset on user experience was gathered with retrospective interviews (n = 22). We inductively coded the CORTO method and retrospective interview data, which led to four user experience categories: (1) contextual use, (2) interaction-elicited emotional experience, (3) usability, and (4) technical issues. Then, we used the created user experience categories and Template Analysis to analyze both datasets together, and reported the results qualitatively. Finally, we compared the two datasets with each other. We found that the data generated with the CORTO method offered more insights into usability and technical categories than the interview data that particularly illustrated the contextual use. The emotional valence of the interview data was more positive compared with the CORTO data. Both the CORTO and interview data detected 55 % of the micro-level categories; 20 % of micro-level categories were only detected by the CORTO data and 25 % only by the interview data. We found that the during-intervention user experience measurement with the CORTO method can provide intervention-specific insights, and thereby further the iterative user-centered intervention development. Overall, these findings highlight the impact of evaluation methods on the categories and qualities of insights acquired in intervention research.
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    Elevating Business Models to the Ecosystem Level: Evidence from Web3 and Beyond
    (2024-01-03) Bengts, Annika; Eloranta, Ville; Hakanen, Esko; Turunen, Taija; Tullney, Valeska; Department of Management Studies; Department of Industrial Engineering and Management; Department of Management Studies; Department of Industrial Engineering and Management
    Business models integrate activities for value creation and capture. While ecosystems have emerged as potent catalysts for value creation through collaborative innovation, the common understanding is that value capture occurs within individual firms. This paper challenges this dichotomy. In an empirical study using a polar types case approach, we first illustrate how two ecosystems employ decentralization technology, specifically blockchain-based Web3 platforms, to elevate value capture to the ecosystem level. We then outline the implications beyond the blockchain domain using two non-Web3 cases. Specifically, we show — from the perspectives of value proposition, value constellation, and profit equation — how business models can rise to the ecosystem level.
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    Socio-economic pandemic modelling : case of Spain
    (Nature Publishing Group, 2024-01) Snellman, Jan E.; Barreiro, Nadia L.; Barrio, Rafael A.; Ventura, Cecilia I.; Govezensky, Tzipe; Kaski, Kimmo K.; Korpi-Lagg, Maarit J.; Department of Computer Science; Instituto de Investigaciones Científicas y Técnicas para la Defensa (CITEDEF); Universidad Nacional Autónoma de México; Comisión Nacional de Energía Atómica; Department of Computer Science
    A global disaster, such as the recent Covid-19 pandemic, affects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities. We apply the model to the specific case of Spain, since there are accurate data available about these three features. We focused on tourism as an example of the economic activity, since this sector of economy is one ofthe most likely to be affected by the restrictions imposed by the authorities, and because it represents an important part of Spanish economy. The results of numerical calculations agree with the empirical data in such a way that we can acquire a better insight of the different processes at play in such a complex situation, and also in other different circumstances.