[article-cris] Perustieteiden korkeakoulu / SCI

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Physicians' Experiences of EHR Technical Quality : Results from Four Large Cross-Sectional Surveys in 2010-2021
(2024-08-22) Lääveri, Tinja; Viitanen, Johanna; Reponen, Jarmo; Renko, Jari; Department of Computer Science; Professorship Viitanen Johanna; Computer Science Professors; Computer Science - Digital Ethics, Society and Policy (Digital-ESP); Computer Science - Software and Service Engineering (SSE); Computer Science - Human-Computer Interaction and Design (HCID); University of Oulu; Oy Apotti Ab
Unexpected downtime and long response times of electronic health record (EHR) systems not only impact user satisfaction and clinicians' work efficiency but also bring about potential harm for patients. Despite improvements in the performance of EHR systems' architecture, hardware, and networks, technical challenges continue to cause problems. We explored the end-user experiences of EHR technical functionality and quality from four large national cross-sectional surveys conducted among Finnish physicians in 2010-21. The results were analyzed by healthcare sector/specialty groups. In most groups, the experiences of stability and reaction speed became worse in 2010-17, which is readily explained by the implementation of the national patient data repository services, but improvements were seen in 2021, suggesting that EHR vendors have solved at least some of the slowness problems. The proportion of physicians reporting having experienced faulty system function with potential or actualized harm for the patient had decreased in operative and medical specialties and in the private sector but remained stable in other groups. Our findings underline the importance of continuing to develop technical qualities - including the implementations of national integrations.
Patient Input into the Electronic Health Record : Co-Designing Solutions with Patients and Healthcare Professionals
(2024-08-22) Dudkina, Anna; Kujala, Sari; Hägglund, Maria; Kharko, Anna; Wang, Bo; Soone, Hedvig; Ross, Peeter; Department of Computer Science; Computer Science Lecturers; Lecturer Kujala Sari group; Computer Science - Software and Service Engineering (SSE); Computer Science - Human-Computer Interaction and Design (HCID); Tallinn University of Technology; Uppsala University; University Hospital of North Norway
Patient-generated health data (PGHD) is the person's health-related data collected outside the clinical environment. Integrating this data into the electronic health record (EHR) supports better patient-provider communication and shared decision-making, empowering patients to actively manage their health conditions. In this study, we investigated the essential features needed for patients and healthcare providers to effectively integrate PGHD functionality into the EHR system. Through our collaborative design approach involving healthcare professionals (HCPs) and patients, we developed a prototype and suggestion, using Estonia as a model, which is the ideal approach for collecting and integrating PGHD into the EHR.
Virtual laboratories : Transforming research with AI
(Cambridge University Press, 2024-08-27) Klami, Arto; Damoulas, Theo; Engkvist, Ola; Rinke, Patrick; Kaski, Samuel; Department of Applied Physics; Department of Computer Science; Computational Electronic Structure Theory; Computer Science Professors; Computer Science - Artificial Intelligence and Machine Learning (AIML); Finnish Center for Artificial Intelligence, FCAI; Probabilistic Machine Learning; Helsinki Institute for Information Technology (HIIT); Professorship Kaski Samuel; University of Warwick; AstraZeneca AB; University of Helsinki
New scientific knowledge is needed more urgently than ever, to address global challenges such as climate change, sustainability, health, and societal well-being. Could artificial intelligence (AI) accelerate science to meet these global challenges in time? AI is already revolutionizing individual scientific disciplines, but we argue here that it could be more holistic and encompassing. We introduce the concept of virtual laboratories as a new perspective on scientific knowledge generation and a means to incentivize new AI research and development. Despite the often perceived domain-specific research practices and inherent tacit knowledge, we argue that many elements of the research process recur across scientific domains and that even common software platforms for serving different domains may be possible. We outline how virtual laboratories will make it easier for AI researchers to contribute to a broad range of scientific domains, and highlight the mutual benefits virtual laboratories offer to both AI and domain scientists.
EUROfusion contributions to ITER nuclear operation
(Institute of Physics Publishing, 2024-11) Litaudon, X.; Fantz, U.; Villari, R.; Toigo, V.; Aumeunier, M. H.; Autran, J. L.; Batistoni, P.; Belonohy, E.; Bradnam, S.; Cecchetto, M.; Colangeli, A.; Dacquait, F.; Dal Bello, S.; Dentan, M.; De Pietri, M.; Eriksson, J.; Fabbri, M.; Falchetto, G.; Figini, L.; Figueiredo, J.; Flammini, D.; Fonnesu, N.; Frassinetti, L.; Galdón-Quiroga, J.; Garcia-Alia, R.; Garcia-Munoz, M.; Ghani, Z.; Gonzalez-Martin, J.; Grelier, E.; Di Grazia, L.; Grove, B.; Grove, C. L.; Gusarov, A.; Heinemann, B.; Hjalmarsson, A.; Hyvärinen, O.; Ioannou-Sougleridis, V.; Jones, L.; Kim, H. T.; Kłosowski, M.; Kocan, M.; Kos, B.; Kos, L.; Kotnik, D.; Laszynska, E.; Leichtle, D.; Lengar, I.; Leon-Gutierrez, E.; Sanchis-Sanchez, L.; Snicker, A.; , EUROfusion Tokamak Exploitation Team; , JET Contributors; , NBTF Team; Department of Applied Physics; French Alternative Energies and Atomic Energy Commission; Max-Planck-Institut für Plasmaphysik; Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile; National Research Council of Italy; University of Rennes 1; Culham Science Centre; CERN; National Distance Education University; Uppsala University; Fusion for Energy; CNR-ENEA-EURATOM Association; EUROfusion Programme Management Unit; KTH Royal Institute of Technology; University of Seville; University of Naples Federico II; Oak Ridge National Laboratory; Belgian Nuclear Research Centre; Department of Applied Physics; Demokritos National Centre for Scientific Research; Institute of Nuclear Physics of the Polish Academy of Sciences; ITER; University of Ljubljana; Jožef Stefan Institute; Institute of Plasma Physics and Laser Microfusion; Karlsruhe Institute of Technology; Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas - CIEMAT
ITER is of key importance in the European fusion roadmap as it aims to prove the scientific and technological feasibility of fusion as a future energy source. The EUROfusion consortium of labs within Europe is contributing to the preparation of ITER scientific exploitation and operation and aspires to exploit ITER outcomes in view of DEMO. The paper provides an overview of the major progress obtained recently, carried out in the frame of the new (initiated in 2021) EUROfusion work-package called ‘Preparation of ITER Operation’ (PrIO). The overview paper is directly supported by the eleven EUROfusion PrIO contributions given at the 29th Fusion Energy Conference (16–21 October 2023) London, UK [www.iaea.org/events/ fec2023]. The paper covers the following topics: (i) development and validation of tools in support to ITER operation (plasma breakdown/burn-through with evolving plasma volume, new infra-red synthetic diagnostic for off-line analysis and wall monitoring using Artificial Intelligence techniques, synthetic diagnostics development, development and exploitation of multi-machine databases); (ii) R&D for the radio-frequency ITER neutral beam sources leading to long duration of negative deuterium/hydrogen ions current extraction at ELISE and participation in the neutral beam test facility with progress on the ITER source SPIDER, and, the commissioning of the 1 MV high voltage accelerator (MITICA) with lessons learned for ITER; (iii) validation of neutronic tools for ITER nuclear operation following the second JET deuterium–tritium experimental campaigns carried out in 2021 and in 2023 (neutron streaming and shutdown dose rate calculation, water activation and activated corrosion products with advanced fluid dynamic simulation; irradiation of several materials under 14.1 MeV neutron flux etc).
Potential Power Output from Vehicle Suspension Energy Harvesting Given Bumpy and Random-Surfaced Roads
(MDPI AG, 2024-08) Guo, Hengyu; Zeng, Weijun; Egloff, Dario; Meng, Fei; Dahlsten, Oscar; Department of Applied Physics; Quantum Circuits and Correlations; Centre of Excellence in Quantum Technology, QTF; University of Hong Kong; Universidad de los Andes Colombia; City University of Hong Kong; Southern University of Science and Technology
The energy efficiency of vehicles is a crucial challenge relating to sustainable energy preservation and regeneration methods. Regenerative breaking has proven feasible, and there is interest in whether harvesting energy from a vehicle’s suspension is similarly feasible. We here provide methods for estimating the amount of power that can be regenerated from the suspension for given vehicle and road parameters. We show that a reasonable road model is a generalised Gaussian process known as AR(1). Using this model, we can derive the key equation used in the ISO 8608 standard for measuring road roughness, such that the AR(1) parameters can be related to the measured road roughness data. We find that the road roughness coefficient of ISO 8608 and the diffusion coefficient of the AR(1) road are equal up to a factor. We provide an analytical expression for the maximum amount of power that can be generated for given road and car parameters, derived via Fourier analysis. We further model harvesting from large bumps using Simulink. These results help to estimate the potential power output given the measured road data.
Weighted fractional Poincaré inequalities via isoperimetric inequalities
(Springer, 2024-11) Myyryläinen, Kim; Pérez, Carlos; Weigt, Julian; Department of Mathematics and Systems Analysis; Analysis; University of the Basque Country; University of Warwick
Our main result is a weighted fractional Poincaré–Sobolev inequality improving the celebrated estimate by Bourgain–Brezis–Mironescu. This also yields an improvement of the classical Meyers–Ziemer theorem in several ways. The proof is based on a fractional isoperimetric inequality and is new even in the non-weighted setting. We also extend the celebrated Poincaré–Sobolev estimate with Ap weights of Fabes–Kenig–Serapioni by means of a fractional type result in the spirit of Bourgain–Brezis–Mironescu. Examples are given to show that the corresponding Lp-versions of weighted Poincaré inequalities do not hold for p>1.
Towards Accountable E-Health Policies in the Nordic Countries
(2024-08-22) Faxvaag, Arild; Reponen, Jarmo; Hardardottir, Gudrun Audur; Vehko, Tuulikki; Viitanen, Johanna; Eriksen, Jeppe; Koch, Sabine; Nøhr, Christian; Department of Computer Science; Computer Science Professors; Computer Science - Digital Ethics, Society and Policy (Digital-ESP); Computer Science - Software and Service Engineering (SSE); Computer Science - Human-Computer Interaction and Design (HCID); Professorship Viitanen Johanna; Norwegian University of Science and Technology; University of Oulu; Directorate of Health, Iceland; Finnish Institute for Health and Welfare (THL); Aalborg University; Karolinska Institutet
The Nordic Countries are seen as forerunners in the field of digital health technologies and national implementation has been guided by sector specific strategies for many years. In the context of new European legislation such as the European Health Data Space (EHDS), a review of the existing strategies is indicated. The objective of this policy analysis is to assess and compare the scope, ambitions and extent of accountability in national-level digital health policies in the Nordic countries. The scope of the policies from the five countries were largely centred around a) empowering and activating citizens; b) a shift towards prevention and digital first; c) supporting health operations; d) doing the groundwork; e) making health data more available in research and innovation workflows and f) supporting health personnel. Finland comes out as the most ambitious country with the aim to transform their health system by means of digitalisation. Both Finland and Iceland work towards prevention and the digital first ambition due to large populations in rural areas. These two countries also present the most accountable policies, meaning that their policy documents are the most transparent as to how they arrived at the conclusions and how they are to evaluate the achievements.
Citizen science games on the timeline of quantum games
(Springer, 2024-08) Piispanen, Laura; Department of Computer Science; Department of Applied Physics
This article provides an overview of existing quantum physics-related games, referred to as quantum games, that serve citizen science research in quantum physics. Additionally, we explore the connection between citizen science and quantum computer games, games played on quantum computers. The information presented is derived from academic references and supplemented by diverse sources, including social media publications, conference presentations and blog posts from research groups and developers associated with the presented games. We observe that the current landscape of quantum games is shaped by three distinct driving forces: the serious application of games, the evolution of quantum computers and open game development events such as Quantum Game Jams. Notably, citizen science plays an influential role in all three aspects. The article points to existing design guides for citizen science quantum games and views future prospects of citizen science projects and quantum games through collaborative endeavours, human–machine collaboration and open access quantum computers.
Putting self at stake by telling a story : Storyteller’s narcissistic traits modulate physiological emotional reactions to recipient’s disengagement
(Public Library of Science, 2024-08-01) Koskinen, Emmi; Henttonen, Pentti; Harjunen, Ville; Krusemark, Elizabeth; Piispanen, Matias; Voutilainen, Liisa; Wuolio, Mariel; Peräkylä, Anssi; Department of Neuroscience and Biomedical Engineering; University of Helsinki; Millsaps College; University of Eastern Finland
Telling a story to a disengaged recipient induces stress and threatens positive self-image. In this study, we investigated whether storytellers with overly positive and fragile self-images (e.g., individuals with grandiose and vulnerable narcissism) would show heightened behavioral, emotional, and psychophysiological reactivity to recipient disengagement.Building on Bavelas, Coates, and Johnson [1] we conducted a conversational experiment instructing the participants to tell about a “close call” experience to a previously unknown co-participant. We modified the co-participant’s level of interactional engagement by asking them either to listen to the story carefully or to simultaneously carry out a counting task that distracted them from the content of the story. We found that the distraction condition was unrelated to the storytellers’ narration performance, but a significant positive association was found between the story-recipients’ observed lack of affiliation and the tellers’ narration performance. The distraction of recipients was also associated with increased self-reported arousal in the tellers, indicating disengagement-induced stress in the tellers. Moreover, tellers higher in grandiose narcissism reacted with higher skin conductance response to disengagement, and vulnerable narcissism was associated with higher heart rate during narration in general. Our experiment thus showed that grandiose narcissists are emotionally sensitive to their co-participants’ disengagement.
Sociotechnical Cross-Country Analysis of Contextual Factors That Impact Patients’ Access to Electronic Health Records in 4 European Countries : Framework Evaluation Study
(JMIR Publications, 2024) Moll, Jonas; Scandurra, Isabella; Bärkås, Annika; Blease, Charlotte; Hägglund, Maria; Hörhammer, Iiris; Kane, Bridget; Kristiansen, Eli; Ross, Peeter; Åhlfeldt, Rose Mharie; Klein, Gunnar O.; Department of Computer Science; Lecturer Kujala Sari group; Örebro University; Uppsala University; University Hospital of North Norway; Tallinn University of Technology; University of Skövde
Background: The NORDeHEALTH project studies patient-accessible electronic health records (PAEHRs) in Estonia, Finland, Norway, and Sweden. Such country comparisons require an analysis of the sociotechnical context of these services. Although sociotechnical analyses of PAEHR services have been carried out in the past, a framework specifically tailored to in-depth cross-country analysis has not been developed. Objective: This study aims to develop and evaluate a method for a sociotechnical analysis of PAEHRs that advances a framework for sociotechnical analysis of eHealth solutions first presented by Sittig and Singh. This first article in a series presents the development of the method and a cross-country comparison of the contextual factors that enable PAEHR access and use. Methods: The dimensions of the framework for sociotechnical analysis were thoroughly discussed and extended in a series of workshops with international stakeholders, all being eHealth researchers focusing on PAEHRs. All countries were represented in the working group to make sure that important national perspectives were covered. A spreadsheet with relevant questions related to the studied services and the various dimensions of the sociotechnical framework was constructed and distributed to the 4 participating countries, and the project participants researched various national sources to provide the relevant data for the comparisons in the 10 sociotechnical dimensions. Results: In total, 3 dimensions were added to the methodology of Sittig and Singh to separate clinical content from features and functions of PAEHRs and demonstrate basic characteristics of the different countries regarding national and regional steering of health care and information and communications technology developments. The final framework contained the following dimensions: metadata; hardware and software computing infrastructure; features and functions; clinical content shared with patients; human-computer interface; people; workflow and communication; the health care organization’s internal policies, procedures, and culture; national rules, regulations, and incentives; system measurement and monitoring; and health care system context. The dimensions added during the study mostly concerned background information needed for cross-country comparisons in particular. Several similarities were identified among the compared countries, especially regarding hardware and software computing infrastructure. All countries had, for example, one national access point, and patients are provided a PAEHR automatically. Most of the differences could be identified in the health care system context dimension. One important difference concerned the governing of information and communications technology development, where different levels (state, region, and municipality) were responsible in different countries. Conclusions: This is the first large-scale international sociotechnical analysis of services for patients to access their electronic health records; this study compared services in Estonia, Finland, Norway, and Sweden. A methodology for such an analysis was developed and is presented to enable comparison studies in other national contexts to enable future implementations and evaluations of PAEHRs.
Ground-state cooling of a mechanical oscillator by a noisy environment
(Nature Portfolio, 2024-12) Wang, Cheng; Banniard, Louise; Børkje, Kjetil; Massel, Francesco; Mercier de Lépinay, Laure; Sillanpää, Mika A.; Department of Applied Physics; Quantum Nanomechanics; Centre of Excellence in Quantum Technology, QTF; Quantum NanoOptomechanics and Forces; University of South-Eastern Norway
Dissipation and the accompanying fluctuations are often seen as detrimental for quantum systems since they are associated with fast relaxation and loss of phase coherence. However, it has been proposed that a pure state can be prepared if external noise induces suitable downwards transitions, while exciting transitions are blocked. We demonstrate such a refrigeration mechanism in a cavity optomechanical system, where we prepare a mechanical oscillator in its ground state by injecting strong electromagnetic noise at frequencies around the red mechanical sideband of the cavity. The optimum cooling is reached with a noise bandwidth smaller than but on the order of the cavity decay rate. At higher bandwidths, cooling is less efficient as suitable transitions are not effectively activated. In the opposite regime where the noise bandwidth becomes comparable to the mechanical damping rate, damping follows the noise amplitude adiabatically, and the cooling is also suppressed.
Hyperband Synergistic Metadevices
(Wiley-VCH Verlag, 2024-08-09) Zhang, Jin; Liu, Peng; Xu, Zhenyu; Dai, Yawei; Zhang, Qiang; Zhu, Weiren; Kauppinen, Esko I.; Sun, Zhipei; Department of Electronics and Nanoengineering; Department of Applied Physics; Zhipei Sun Group; Centre of Excellence in Quantum Technology, QTF; NanoMaterials; Shanghai Jiao Tong University
Recent advances in metadevices, featuring complex subwavelength metastructures, have dramatically transformed the control and manipulation of electromagnetic waves. However, the inherently narrow operational bandwidth of these devices, stemming from their wavelength-specific meta-atoms, restricts their application in rapidly advancing fields such as the Internet of Things and advanced intelligent systems. Here, a novel hyperband synergistic metadevice is introduced, realized through a comprehensive multi-scale meta-atom architecture. The complementary metal-oxide-semiconductor (CMOS)-compatible prototype integrates the distinct properties of double-walled carbon nanotubes with advanced interlayer and intralayer coupling mechanisms, coherently combining nanoscale, microscale, and macroscale meta-atoms. This prototype is thus adept at operating across a wide electromagnetic spectrum, spanning from the centimeter-wavelength microwave band to the hundred nanometer-wavelength visible and infrared optical band. Significantly, this singular device synergistically delivers three critical functionalities: selective microwave absorption, efficient terahertz beam steering, and enhanced optical transparency. These result signifies a breakthrough in hyperband electromagnetic device engineering, leading to compact, versatile, intelligent electromagnetic platforms.
Military history on the Semantic Web : Lessons learned from developing three in-use linked open data services and semantic portals for digital humanities
(2024-01) Hyvönen, Eero; Department of Computer Science; Computer Science Professors; Computer Science - Artificial Intelligence and Machine Learning (AIML); Professorship Hyvönen Eero
This chapter reviews three in-use systems for publishing and studying military history on the Semantic Web, namely, WarSampo, WarVictimSampo 1914–1922, and WarMemoirSampo. Targeting Digital Humanities researchers, application developers, and the general public, these systems include a Linked Open Data (LOD) service with a live SPARQL endpoint that can be used with modest programming skills, and a ready-to-use semantic portal on top of it. Lessons learned in developing these systems are discussed based on the so-called Sampo Model, which is a set of principles developed in the process of creating and publishing Knowledge Graphs (KG) as LOD services with semantic portal User Interfaces (UI). The UIs support semantic faceted search, data browsing, and exploration, as well as seamlessly integrated tools for data analyses.
Attention-based approach to predict drug–target interactions across seven target superfamilies
(Oxford University Press, 2024-08-01) Schulman, Aron; Rousu, Juho; Aittokallio, Tero; Tanoli, Ziaurrehman; Department of Computer Science; Computer Science Professors; Computer Science - Large-scale Computing and Data Analysis (LSCA); Computer Science - Artificial Intelligence and Machine Learning (AIML); Computer Science - Computational Life Sciences (CSLife); Helsinki Institute for Information Technology (HIIT); Professorship Rousu Juho; University of Helsinki
Motivation: Drug–target interactions (DTIs) hold a pivotal role in drug repurposing and elucidation of drug mechanisms of action. While single-targeted drugs have demonstrated clinical success, they often exhibit limited efficacy against complex diseases, such as cancers, whose development and treatment is dependent on several biological processes. Therefore, a comprehensive understanding of primary, secondary and even inactive targets becomes essential in the quest for effective and safe treatments for cancer and other indications. The human proteome offers over a thousand druggable targets, yet most FDA-approved drugs bind to only a small fraction of these targets. Results: This study introduces an attention-based method (called as MMAtt-DTA) to predict drug–target bioactivities across human proteins within seven superfamilies. We meticulously examined nine different descriptor sets to identify optimal signature descriptors for predicting novel DTIs. Our testing results demonstrated Spearman correlations exceeding 0.72 (P<0.001) for six out of seven superfamilies. The proposed method outperformed fourteen state-of-the-art machine learning, deep learning and graph-based methods and maintained relatively high performance for most target superfamilies when tested with independent bioactivity data sources. We computationally validated 185 676 drug–target pairs from ChEMBL-V33 that were not available during model training, achieving a reasonable performance with Spearman correlation >0.57 (P<0.001) for most superfamilies. This underscores the robustness of the proposed method for predicting novel DTIs. Finally, we applied our method to predict missing bioactivities among 3492 approved molecules in ChEMBL-V33, offering a valuable tool for advancing drug mechanism discovery and repurposing existing drugs for new indications.
Liouville quantum gravity metrics are not doubling
(Institute of Mathematical Statistics, 2024) Hughes, Liam; Department of Mathematics and Systems Analysis; Mathematical Physics
We observe that non-doubling metric spaces can be characterized as those that contain arbitrarily large sets of approximately equidistant points and use this to show that, for γ ∈ (0, 2], the γ-Liouville quantum gravity metric is almost surely not doubling and thus cannot be quasisymmetrically embedded into any finite-dimensional Euclidean space. This generalizes the corresponding result of Troscheit [34] for the Brownian map (which is equivalent to the case γ =√8/3).
Bayesian learning of feature spaces for multitask regression
(Elsevier Ltd, 2024-11) Sevilla-Salcedo, Carlos; Gallardo-Antolín, Ascensión; Gómez-Verdejo, Vanessa; Parrado-Hernández, Emilio; Department of Computer Science; Universidad Carlos III de Madrid
This paper introduces a novel approach to learn multi-task regression models with constrained architecture complexity. The proposed model, named RFF-BLR, consists of a randomised feedforward neural network with two fundamental characteristics: a single hidden layer whose units implement the random Fourier features that approximate an RBF kernel, and a Bayesian formulation that optimises the weights connecting the hidden and output layers. The RFF-based hidden layer inherits the robustness of kernel methods. The Bayesian formulation enables promoting multioutput sparsity: all tasks interplay during the optimisation to select a compact subset of the hidden layer units that serve as common non-linear mapping for every tasks. The experimental results show that the RFF-BLR framework can lead to significant performance improvements compared to the state-of-the-art methods in multitask nonlinear regression, especially in small-sized training dataset scenarios.
Designing cobalt-free face-centered cubic high-entropy alloys A strategy using d-orbital energy level
(Elsevier, 2024-11) Li, Yulin; Olejarz, Artur; Kurpaska, Łukasz; Lu, Eryang; Alava, Mikko J.; Kim, Hyoung Seop; Huo, Wenyi; Department of Applied Physics; Complex Systems and Materials; National Centre for Nuclear Research; Pohang University of Science and Technology; University of Helsinki
High-entropy alloys (HEAs) are promising materials for high-temperature structural applications such as nuclear reactors due to their outstanding mechanical properties and thermal stability. Instead of the trial-and-error method, it is efficient to design and prepare single-phase face-centered cubic (FCC) structured HEAs using semi-empirical phase formation rules. However, almost all of phase formation rules were proposed without taking into account the cobalt-free situation. The HEAs containing cobalt are unsuitable for nuclear applications because of the long-term activation of cobalt. Here, six parameters, d-orbital energy level, valance electron concentration, entropy of mixing, enthalpy of mixing, atom size differences, and parameter of the entropy of mixing (Ω) were calculated to determine the solid solution phase, especially the FCC phase formation rules in cobalt-free HEAs. HEAs of 4 components were arc melted to verify the newly developed phase formation rules. The nanomechanical properties of produced HEAs were evaluated using nanoindentation. Among the six parameters, the d-orbital energy level and valance electron concentration are the critical factors that determine the FCC phase stability in cobalt-free alloys. Interestingly, the d-orbital energy level can be alone used as a benchmark for developing mechanical properties.
Six types of loves differentially recruit reward and social cognition brain areas
(Oxford University Press, 2024-08) Rinne, Pärttyli; Lahnakoski, Juha; Saarimäki, Heini; Tavast, Mikke; Sams, Mikko; Henriksson, Linda; Department of Computer Science; Department of Neuroscience and Biomedical Engineering; Professorship Hämäläinen Perttu
Feelings of love are among the most significant human phenomena. Love informs the formation and maintenance of pair bonds, parent-offspring attachments, and influences relationships with others and even nature. However, little is known about the neural mechanisms of love beyond romantic and maternal types. Here, we characterize the brain areas involved in love for six different objects: romantic partner, one’s children, friends, strangers, pets, and nature. We used functional magnetic resonance imaging (fMRI) to measure brain activity, while we induced feelings of love using short stories. Our results show that neural activity during a feeling of love depends on its object. Interpersonal love recruited social cognition brain areas in the temporoparietal junction and midline structures significantly more than love for pets or nature. In pet owners, love for pets activated these same regions significantly more than in participants without pets. Love in closer affiliative bonds was associated with significantly stronger and more widespread activation in the brain’s reward system than love for strangers, pets, or nature. We suggest that the experience of love is shaped by both biological and cultural factors, originating from fundamental neurobiological mechanisms of attachment.
Dimensionality and optimal combination of autonomic fear-conditioning measures in humans
(Springer, 2024-09) Mancinelli, Federico; Sporrer, Juliana K.; Myrov, Vladislav; Melinscak, Filip; Zimmermann, Josua; Liu, Huaiyu; Bach, Dominik R.; Department of Neuroscience and Biomedical Engineering; University of Bonn; University College London; University of Zurich
Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.
Self-Stacked 1T-1H Layers in 6R-NbSeTe and the Emergence of Charge and Magnetic Correlations Due to Ligand Disorder
(American Chemical Society, 2024-08-13) Mahatha, Sanjoy K.; Phillips, Jan; Corral-Sertal, Javier; Subires, David; Korshunov, Artem; Kar, Arunava; Buck, Jens; Diekmann, Florian; Garbarino, Gaston; Ivanov, Yurii P.; Chuvilin, Andrey; Mondal, Debashis; Vobornik, Ivana; Bosak, Alexei; Rossnagel, Kai; Pardo, Victor; Fumega, Adolfo O.; Blanco-Canosa, Santiago; Department of Applied Physics; Correlated Quantum Materials (CQM); UGC-DAE Consortium for Scientific Research; University of Santiago de Compostela; Donostia International Physics Center; European Synchrotron Radiation Facility; German Electron Synchrotron; Italian Institute of Technology; CIC nanoGUNE; National Institute for Nuclear Physics
The emergence of correlated phenomena arising from the combination of 1T and 1H van der Waals layers is the focus of intense research. Here, we synthesize a self-stacked 6R phase in NbSeTe, showing perfect alternating 1T and 1H layers that grow coherently along the c-direction, as revealed by scanning transmission electron microscopy. Angle-resolved photoemission spectroscopy shows a mixed contribution of the trigonal and octahedral Nb bands to the Fermi level. Diffuse scattering reveals temperature-independent short-range charge fluctuations with propagation vector qCO = (0.25 0), derived from the condensation of a longitudinal mode in the 1T layer, while the long-range charge density wave is quenched by ligand disorder. Magnetization measurements suggest the presence of an inhomogeneous, short-range magnetic order, further supported by the absence of a clear phase transition in the specific heat. These experimental analyses in combination with ab initio calculations indicate that the ground state of 6R-NbSeTe is described by a statistical distribution of short-range charge-modulated and spin-correlated regions driven by ligand disorder. Our results demonstrate how natural 1T-1H self-stacked bulk heterostructures can be used to engineer emergent phases of matter.

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