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Social robots, owing to their embodied physical presence in human spaces and the ability to directly interact with the users and their environment, have a great potential to support children in various activities in education, healthcare and daily life. Child-Robot Interaction (CRI), as any domain involving children, inevitably faces the major challenge of designing generalized strategies to work with unique, turbulent and very diverse individuals. Addressing this challenging endeavor requires to combine the standpoint of the robot-centered perspective, i.e. what robots technically can and are best positioned to do, with that of the child-centered perspective, i.e. what children may gain from the robot and how the robot should act to best support them in reaching the goals of the interaction. This article aims to help researchers bridge the two perspectives and proposes to address the development of CRI scenarios with insights from child psychology and child development theories. To that end, we review the outcomes of the CRI studies, outline common trends and challenges, and identify two key factors from child psychology that impact child-robot interactions, especially in a long-term perspective: developmental stage and individual characteristics. For both of them we discuss prospective experiment designs which support building naturally engaging and sustainable interactions., Open Access funding enabled and organized by Projekt DEAL.

The relevance of the topic is due to the need to research the scientific aspects of reconciling the contradictions between the growing importance of the development of digital technologies and the formation of an information society, between the level of development of the information security of society and the readiness of state authorities to respond to strategic and tactical threats. The purpose of the article is to develop conceptual provisions for the formation of the mechanism of state management of the development of digital technologies in the country's national security system. To achieve the goal, general scientific methods of learning phenomena and processes were used: induction and deduction, system analysis and generalization, structuring, abstraction, formalization and graphic. It has been proven that the implementation of digital technologies in the process of state administration is an important element of the national security system. It is substantiated that the mechanism of state management of the development of digital technologies is a set of organizational, economic and legal measures, the interaction of which ensures the implementation of digital technologies in the national security system and the functioning of the structures that provide it, as well as the vital activities of society., La relevancia del tema se debe a la necesidad de investigar los aspectos científicos de conciliar las contradicciones entre la creciente importancia del desarrollo de las tecnologías digitales y la formación de una sociedad de la información, entre el nivel de desarrollo de la seguridad de la información de la sociedad y la disposición de las autoridades estatales para responder a amenazas estratégicas y tácticas. El propósito del artículo es desarrollar disposiciones conceptuales para la formación del mecanismo de gestión estatal del desarrollo de las tecnologías digitales en el sistema de seguridad nacional del país. Para lograr el objetivo se utilizaron métodos científicos generales de aprendizaje de fenómenos y procesos: inducción y deducción, análisis y generalización de sistemas, estructuración, abstracción, formalización y gráfico. Está demostrado que la implementación de tecnologías digitales en el proceso de administración estatal es un elemento importante del sistema de seguridad nacional. Se fundamenta que el mecanismo de gestión estatal del desarrollo de las tecnologías digitales es un conjunto de medidas organizativas, económicas y legales, cuya interacción asegura la implementación de las tecnologías digitales en el sistema de seguridad nacional y el funcionamiento de las estructuras que la proporcionan, así como las actividades vitales de la sociedad.

Reconstructing interglacial marine environments helps us understand the climate change mechanisms of the past. To contribute to this body of knowledge, we studied a high-resolution 455 cm-thick sediment sequence of the Boreal (Eemian) marine beds directly overlying Moscovian (Saalian) moraine in the Bychye-2 section on the Pyoza River. We analyzed lithological and microfossil (foraminifers, ostracods, pollen, aquatic palynomorphs) variations at the studied site. Stratigraphical zonation is based on the local and well-established regional pollen zones, correlated with the western European pollen zones. The studied marine beds accumulated from the end of the Moscovian glacial (>131 ka) until ca. 119.5 ka. We distinguished three successive phases: a seasonally sea-ice-covered, relatively deep, freshened basin in the initial rapid flooding stage (>131–130.5 ka); a deep basin in the maximum flooding phase with less extensive sea ice cover (130.5–130.25 ka); and a shallow basin with reduced sea ice cover (130.25–119.5 ka). According to a pollen zone comparison with other sites, the regional glacioisostatic rebound started ca. 130 ka. The diverse warm-water assemblages of benthic foraminifers and ostracods containing typical Baltic Sea species occurred during the regression, mainly 128–124 ka, thus giving evidence for a relatively long-lasting connection between the White and Baltic Seas.

Contactin 2 (CNTN2) is a cell adhesion molecule involved in axon guidance, neuronal migration, and fasciculation. The ectodomains of CNTN1-CNTN6 are composed of six Ig domains (Ig1-Ig6) and four FN domains. Here, we show that CNTN2 forms transient homophilic interactions (KD ∼200 nM). Cryo-EM structures of full-length CNTN2 and CNTN2_Ig1-Ig6 reveal a T-shaped homodimer formed by intertwined, parallel monomers. Unexpectedly, the horseshoe-shaped Ig1-Ig4 headpieces extend their Ig2-Ig3 tips outwards on either side of the homodimer, while Ig4, Ig5, Ig6, and the FN domains form a central stalk. Cross-linking mass spectrometry and cell-based binding assays confirm the 3D assembly of the CNTN2 homodimer. The interface mediating homodimer formation differs between CNTNs, as do the homophilic versus heterophilic interaction mechanisms. The CNTN family thus encodes a versatile molecular platform that supports a very diverse portfolio of protein interactions and that can be leveraged to strategically guide neural circuit development.

Robots and other intelligent systems navigating in complex dynamic environments should predict future actions and intentions of surrounding agents to reach their goals efficiently and avoid collisions. The dynamics of those agents strongly depends on their tasks, roles, or observable labels. Class-conditioned motion prediction is thus an appealing way to reduce forecast uncertainty and get more accurate predictions for heterogeneous agents. However, this is hardly explored in the prior art, especially for mobile robots and in limited data applications. In this paper, we analyse different class-conditioned trajectory prediction methods on two datasets. We propose a set of conditional pattern-based and efficient deep learning-based baselines, and evaluate their performance on robotics and outdoors datasets (TH & Ouml;R-MAGNI and Stanford Drone Dataset). Our experiments show that all methods improve accuracy in most of the settings when considering class labels. More importantly, we observe that there are significant differences when learning from imbalanced datasets, or in new environments where sufficient data is not available. In particular, we find that deep learning methods perform better on balanced datasets, but in applications with limited data, e.g., cold start of a robot in a new environment, or imbalanced classes, pattern-based methods may be preferable.

Carbon nitrides featuring three-dimensional frameworks of CN4 tetrahedra are one of the great aspirations of materials science, expected to have a hardness greater than or comparable to diamond. After more than three decades of efforts to synthesize them, no unambiguous evidence of their existence has been delivered. Here, the high-pressure high-temperature synthesis of three carbon-nitrogen compounds, tI14-C3N4, hP126-C3N4, and tI24-CN2, in laser-heated diamond anvil cells, is reported. Their structures are solved and refined using synchrotron single-crystal X-ray diffraction. Physical properties investigations show that these strongly covalently bonded materials, ultra-incompressible and superhard, also possess high energy density, piezoelectric, and photoluminescence properties. The novel carbon nitrides are unique among high-pressure materials, as being produced above 100 GPa they are recoverable in air at ambient conditions., Funding: National Science Foundation - Earth Sciences; DOE Office of Science; Deutsche Forschungsgemeinschaft (DFG) [EAR - 1634415]; UKRI Future Leaders Fellowship [DE-AC02-06CH11357]; DFG [LA-4916/1-1, DU 945/15-1, DU 393-9/2, DU 393-13/1, MR/V025724/1]; DFG [DU 954-11/1]; BIOVIA [INST 91/315-1 FUGG, INST 91/251-1 FUGG]; Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoping University; Swedish Research Council (VR); Knut and Alice Wallenberg Foundation [2009 00971]; Swedish Research Council [2019-05600]; RSF [KAW-2018.0194]; [2022-06725]; [2018-05973]; [22-12-00193]

The light-induced ultrafast switching between molecular isomers norbornadiene and quadricyclane can reversibly store and release a substantial amount of chemical energy. Prior work observed signatures of ultrafast molecular dynamics in both isomers upon ultraviolet excitation but could not follow the electronic relaxation all the way back to the ground state experimentally. Here we study the electronic relaxation of quadricyclane after exciting in the ultraviolet (201 nanometres) using time-resolved gas-phase extreme ultraviolet photoelectron spectroscopy combined with non-adiabatic molecular dynamics simulations. We identify two competing pathways by which electronically excited quadricyclane molecules relax to the electronic ground state. The fast pathway (<100 femtoseconds) is distinguished by effective coupling to valence electronic states, while the slow pathway involves initial motions across Rydberg states and takes several hundred femtoseconds. Both pathways facilitate interconversion between the two isomers, albeit on different timescales, and we predict that the branching ratio of norbornadiene/quadricyclane products immediately after returning to the electronic ground state is approximately 3:2.

C3N4 is a recently discovered phase of carbon nitrides with the tetragonal crystal structure [D. Laniel et al., Adv. Mater. (2023), doi:10.1002/adma.202308030] that is stable at ambient conditions. C3N4 is a semiconductor exhibiting flat-band anomalies in the valence band, suggesting the emergence of many-body instabilities upon hole doping. Here, using state-of-the-art first-principles calculations we show that hole-doped C3N4 reveals strong electron-phonon coupling, leading to the formation of a gapped superconducting state. The phase transition temperatures turn out to be strongly dependent on the hole concentration. We propose that holes could be injected into C3N4 via boron doping which induces, according to our results, a rigid shift of the Fermi energy without significant modification of the electronic structure. Based on the electron-phonon coupling and Coulomb pseudopotential calculated from first principles, we conclude that the boron concentration of 6 atoms per nm3 would be required to reach the critical temperature of ∼36 K at ambient pressure., Funding Agencies|FASTCORR, (KAW-2018.0194); European Research Council, ERC, (854843); Linköpings Universitet, LiU, (2009 00971); Vetenskapsrådet, VR, (2019-05600)

Pump–probe experiments with subfemtosecond resolution are the key to understanding electronic dynamics in quantum systems. Here we demonstrate the generation and control of subfemtosecond pulse pairs from a two-colour X-ray free-electron laser. By measuring the delay between the two pulses with an angular streaking diagnostic, we characterize the group velocity of the X-ray free-electron laser and show control of the pulse delay down to 270 as. We confirm the application of this technique to a pump–probe measurement in core-ionized para-aminophenol. These results reveal the ability to perform pump–probe experiments with subfemtosecond resolution and atomic site specificity.

Long-term human motion prediction (LHMP) is essential for safely operating autonomous robots and vehicles in populated environments. It is fundamental for various applications, including motion planning, tracking, human-robot interaction and safety monitoring. However, accurate prediction of human trajectories is challenging due to complex factors, including, for example, social norms and environmental conditions. The influence of such factors can be captured through Maps of Dynamics (MoDs), which encode spatial motion patterns learned from (possibly scattered and partial) past observations of motion in the environment and which can be used for data-efficient, interpretable motion prediction (MoD-LHMP). To address the limitations of prior work, especially regarding accuracy and sensitivity to anomalies in long-term prediction, we propose the Laminar Component Enhanced LHMP approach (LaCE-LHMP). Our approach is inspired by data-driven airflow modelling, which estimates laminar and turbulent flow components and uses predominantly the laminar components to make flow predictions. Based on the hypothesis that human trajectory patterns also manifest laminar flow (that represents predictable motion) and turbulent flow components (that reflect more unpredictable and arbitrary motion), LaCE-LHMP extracts the laminar patterns in human dynamics and uses them for human motion prediction. We demonstrate the superior prediction performance of LaCE-LHMP through benchmark comparisons with state-of-the-art LHMP methods, offering an unconventional perspective and a more intuitive understanding of human movement patterns., Comment: Accepted to the 2024 IEEE International Conference on Robotics and Automation (ICRA)

We present a new large dataset of indoor human and robot navigation and interaction, called TH\"OR-MAGNI, that is designed to facilitate research on social navigation: e.g., modelling and predicting human motion, analyzing goal-oriented interactions between humans and robots, and investigating visual attention in a social interaction context. TH\"OR-MAGNI was created to fill a gap in available datasets for human motion analysis and HRI. This gap is characterized by a lack of comprehensive inclusion of exogenous factors and essential target agent cues, which hinders the development of robust models capable of capturing the relationship between contextual cues and human behavior in different scenarios. Unlike existing datasets, TH\"OR-MAGNI includes a broader set of contextual features and offers multiple scenario variations to facilitate factor isolation. The dataset includes many social human-human and human-robot interaction scenarios, rich context annotations, and multi-modal data, such as walking trajectories, gaze tracking data, and lidar and camera streams recorded from a mobile robot. We also provide a set of tools for visualization and processing of the recorded data. TH\"OR-MAGNI is, to the best of our knowledge, unique in the amount and diversity of sensor data collected in a contextualized and socially dynamic environment, capturing natural human-robot interactions., Comment: Submitted to The International Journal of Robotics Research (IJRR) on 28 of February 2024

[eng] Aim: to investigate the novel medical advancement in surgery. We also aim to investigate the various modern challenges of implementing artificial intelligence in medicine. Methods: In our review, we involved English studies from common databases such as Web of Science, Scopus, Google Scholar, Pubmed, and the Cochrane Library using the following keywords “advancement”, “artificial intelligence”, “innovations in surgery”, and “operative surgery” till November 2023. Scientific novelty: There are published studies that have tried to determine the role of new technologies in the field of surgery; however, there is a lack of studies that have attempted to identify a comprehensive analysis of these innovations and their integration into healthcare services. In our article, we tried to evaluate the role of new technologies in modern medicine and dentistry, especially in the surgical field. Conclusion: Newly advanced technologies have greatly benefited in developing overall healthcare services, especially in the surgical field. AI has several applications in the field of surgery, which has significantly impacted the current healthcare systems., [spa] Objetivo: investigar los novedosos avances médicos en cirugía. También se pretende investigar los diversos retos modernos de la aplicación de la inteligencia artificial en medicina. Métodos: En nuestra revisión, involucramos estudios en inglés de bases de datos comunes como Web of Science, Scopus, Google Scholar, Pubmed y Cochrane Library utilizando las siguientes palabras clave “avance”, “inteligencia artificial”, “innovaciones en cirugía” y “cirugía operatoria” hasta noviembre de 2023. Novedad científica: Existen estudios publicados que han intentado determinar el papel de las nuevas tecnologías en el campo de la cirugía; sin embargo, faltan estudios que hayan intentado identificar un análisis exhaustivo de estas innovaciones y su integración en los servicios sanitarios. En nuestro artículo, intentamos evaluar el papel de las nuevas tecnologías en la medicina y la odontología modernas, especialmente en el ámbito quirúrgico. Conclusiones: Las nuevas tecnologías avanzadas han contribuido en gran medida al desarrollo de los servicios sanitarios en general, especialmente en el ámbito quirúrgico. La IA tiene varias aplicaciones en el campo de la cirugía, lo que ha repercutido significativamente en los sistemas sanitarios actuales.

Background: Resistant hypertension is associated with increased cardiovascular risk. The endothelin pathway has been implicated in the pathogenesis of hypertension, but it is currently not targeted therapeutically, thereby leaving this relevant pathophysiological pathway unopposed with currently available drugs. The aim of the study was to assess the blood pressure lowering efficacy of the dual endothelin antagonist aprocitentan in patients with resistant hypertension. Methods: PRECISION was a multicentre, blinded, randomised, parallel-group, phase 3 study, which was done in hospitals or research centres in Europe, North America, Asia, and Australia. Patients were eligible for randomisation if their sitting systolic blood pressure was 140 mm Hg or higher despite taking standardised background therapy consisting of three antihypertensive drugs, including a diuretic. The study consisted of three sequential parts: part 1 was the 4-week double-blind, randomised, and placebo-controlled part, in which patients received aprocitentan 12·5 mg, aprocitentan 25 mg, or placebo in a 1:1:1 ratio; part 2 was a 32-week single (patient)-blind part, in which all patients received aprocitentan 25 mg; and part 3 was a 12-week double-blind, randomised, and placebo-controlled withdrawal part, in which patients were re-randomised to aprocitentan 25 mg or placebo in a 1:1 ratio. The primary and key secondary endpoints were changes in unattended office systolic blood pressure from baseline to week 4 and from withdrawal baseline to week 40, respectively. Secondary endpoints included 24-h ambulatory blood pressure changes. The study is registered on ClinicalTrials.gov, NCT03541174. Findings: The PRECISION study was done from June 18, 2018, to April 25, 2022. 1965 individuals were screened and 730 were randomly assigned. Of these 730 patients, 704 (96%) completed part 1 of the study; of these, 613 (87%) completed part 2 and, of these, 577 (94%) completed part 3 of the study. The least square m

Human motion prediction is important for mobile service robots and intelligent vehicles to operate safely and smoothly around people. The more accurate predictions are, particularly over extended periods of time, the better a system can, e.g., assess collision risks and plan ahead. In this paper, we propose to exploit maps of dynamics (MoDs, a class of general representations of place-dependent spatial motion patterns, learned from prior observations) for long-term human motion prediction (LHMP). We present a new MoD-informed human motion prediction approach, named CLiFF-LHMP, which is data efficient, explainable, and insensitive to errors from an upstream tracking system. Our approach uses CLiFF -map, a specific MoD trained with human motion data recorded in the same environment. We bias a constant velocity prediction with samples from the CLiFF-map to generate multi-modal trajectory predictions. In two public datasets we show that this algorithm outperforms the state of the art for predictions over very extended periods of time, achieving 45 % more accurate prediction performance at 50s compared to the baseline., DARKO

The research studied the pressing problem of the fuel and energy strategy of the XXI century. For the first time, there was shown the diversity of the authors' approach to theoretical and applied problems of hydrogen energy. General issues of fundamental and applied aspects of hydrogen origin were covered. The study provides the results of scientific developments on hydrogen mapping performed within the framework of scientific and practical exploratory and geo-ecological research on more than 200 hydrocarbon objects both on land (including mining fields) and in marine water areas. Prognostic and search system criteria were substantiated, with hydrogen being used for the first time as a component of the complex of methodical solutions in the search practice. The research showed the importance of solving the problem of geo-ecological processes and accidents in mine workings and wells, connected to numerous disasters. According to numerous studies of mine massives, a set of preventive measures and criteria that prevent explosive processes was provided. The presence of a unique complex of natural components of hydrogen technology, solar and wind energy resources and fresh waters of the Danube lakes and the Danube was stated. The study emphasises the decisive role of Ukraine in the competition for primacy in scientific developments. For the first time in world practice, the implementation of global projects for the extraction and production of green and white hydrogen was substantiated. The technology was tested on numerous hydrocarbon deposits, water resources and mine workings and therefore has all the prospects for the effective application in the search and extraction of hydrogen. This monograph can be useful and informative for specialists in the fields of oil and gas geology, general and regional geology, hydrology, environmental protection, as well as for the students and postgraduate students of fuel and energy, oil and gas geological and hydrological areas, as w

The purpose of the paper is to determine the characteristics of Ukrainian environmental ethics development in the XX-XXI centuries as of a product of international relations and situate Ukrainian environmental ethics within a global and future-oriented context from a postcolonial perspective.

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Since the Covid19 pandemic there has been a rise in the use of digital platforms such as online-game based learning platforms (OGBLPs) to diversify the learning experiences of students. This paper investigates the implementation, challenges, and benefits of online game-based learning platforms for English learning of students with English as a second language (ESL) in Sweden’s upper secondary schools. We aimed to explore teachers’ experiences of students’ vocabulary acquisition and whether it is facilitated by employing OGBLPs. We also examined the benefits and challenges of using OGBLPs for vocabulary acquisition. For this purpose we employed a qualitative approach where five upper secondary school English teachers were interviewed. All data was later transcribed, where responses from the interviews were used to highlight how teachers used OGBLPs, and what they considered challenges and benefits. Overall, teachers reported positive attitudes towards the use of OGBLPs as it influences elements such as student engagement and leads to increased motivation. However, all participants of this study also claim that OGBLPs ought to be used in combination with a theme or presentation connected to curriculum content as they doubt the effectiveness of OGBLPs in vocabulary acquisition when used in isolation, as a single learning activity.

The conversion of protons to positrons at the horizon of a black hole (BH) is considered. It is shown that the process may efficiently proceed for BHs with masses in the range $\sim 10^{18}$ -- $10^{21}$ g. It is argued that the electric charge of BH acquired by the proton accretion to BH could create electric field near BH horizon close to the critical Schwinger one. It leads to efficient electron-positron pair production, when electron is back capture by the BH while positron is emitted into outer space. The electron-positron annihilation in the interstellar medium may explain the origin of the observed 511 keV line., Comment: 12 pages, 3 figures

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Purpose: The aim of this study is analyze the importance of educational change for the effectiveness of organizational development and the role of organizational development in the processes of human development today, in the context of the information society and extreme social networking. Theoretical framework: Russia’s war against Ukraine has pushed up demand for (new) administrative processes. But this did not negate the need for institutions to develop their potential using various, for example digital tools, and to constantly improve the quality of educational services in the context of extreme conditions and extraordinary circumstances. Design/methodology/approach: Development of education creates new opportunities for the development of human potential for extreme social networking. Findings: The approaches of joint creative activity of the participants of the educational process (in the context of security challenges) as effective means that create an unfavorable context for educational changes are determined. It is emphasized that the development of human potential depends on the ability of education to be flexible to the needs of the information society. It is determined that the transformation of the social institute of education requires radical changes in the training of a new generation of managers with a high level of professionalism, culture, innovative creative thinking. Research, Practical & Social implications: It is found out that a set of theories of organizational development is submitted methodologically capacious for creation of conceptual models of management of educational changes. Originality/value: Reasonably scientific bases of educational changes as objects of public management are characterized by tendentiousness of public management of educational changes on the basis of collective nature.

For robots navigating in dynamic environments, exploiting and understanding uncertain human motion prediction is key to generate efficient, safe and legible actions. The robot may perform poorly and cause hindrances if it does not reason over possible, multi-modal future social interactions. With the goal of enhancing autonomous navigation in cluttered environments, we propose a novel formulation for nonlinear model predictive control including multi-modal predictions of human motion. As a result, our approach leads to less conservative, smooth and intuitive human-aware navigation with reduced risk of collisions, and shows a good balance between task efficiency, collision avoidance and human comfort. To show its effectiveness, we compare our approach against the state of the art in crowded simulated environments, and with real-world human motion data from the THOR dataset. This comparison shows that we are able to improve task efficiency, keep a larger distance to humans and significantly reduce the collision time, when navigating in cluttered dynamic environ-ments. Furthermore, the method is shown to work robustly with different state-of-the-art human motion predictors.

Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial component: active communication of robot intent. Here, we present an anthropomorphic solution where a humanoid robot communicates the intent of its host robot acting as an "Anthropomorphic Robotic Mock Driver" (ARMoD). We evaluate this approach in two experiments in which participants work alongside a mobile robot on various tasks, while the ARMoD communicates a need for human attention, when required, or gives instructions to collaborate on a joint task. The experiments feature two interaction styles of the ARMoD: a verbal-only mode using only speech and a multimodal mode, additionally including robotic gaze and pointing gestures to support communication and register intent in space. Our results show that the multimodal interaction style, including head movements and eye gaze as well as pointing gestures, leads to more natural fixation behavior. Participants naturally identified and fixated longer on the areas relevant for intent communication, and reacted faster to instructions in collaborative tasks. Our research further indicates that the ARMoD intent communication improves engagement and social interaction with mobile robots in workplace settings.

Autonomous systems, that need to operate in human environments and interact with the users, rely on understanding and anticipating human activity and motion. Among the many factors which influence human motion, semantic attributes, such as the roles and ongoing activities of the detected people, provide a powerful cue on their future motion, actions, and intentions. In this work we adapt several popular deep learning models for trajectory prediction with labels corresponding to the roles of the people. To this end we use the novel THOR-Magni dataset, which captures human activity in industrial settings and includes the relevant semantic labels for people who navigate complex environments, interact with objects and robots, work alone and in groups. In qualitative and quantitative experiments we show that the role-conditioned LSTM, Transformer, GAN and VAE methods can effectively incorporate the semantic categories, better capture the underlying input distribution and therefore produce more accurate motion predictions in terms of Top-K ADE/FDE and log-likelihood metrics.

The Einstein Equivalence Principle (EEP) is a cornerstone of general relativity and predicts the existence of gravitational redshift. We report on new results of measuring this shift with RadioAstron (RA), a space VLBI spacecraft launched into an evolving high eccentricity orbit around Earth with geocentric distances reaching 353,000 km. The spacecraft and ground tracking stations at Pushchino, Russia, and Green Bank, USA, were each equipped with a hydrogen maser frequency standard allowing a possible violation of the predicted gravitational redshift, in the form of a violation parameter $\varepsilon$, to be measured. By alternating between RadioAstron's frequency referencing modes during dedicated sessions between 2015 and 2017, the recorded downlink frequencies can essentially be corrected for the non-relativistic Doppler shift. We report on an analysis using the Doppler-tracking frequency measurements made during these sessions and find $\varepsilon = (2.1 \pm 3.3)\times10^{-4}$. We also discuss prospects for measuring $\varepsilon$ with a significantly smaller uncertainty using instead the time-domain recordings of the spacecraft signals and envision how $10^{-7}$ might be possible for a future space VLBI mission., Comment: Nelson V Nunes et al 2023 Class. Quantum Grav. in press https://doi.org/10.1088/1361-6382/ace609

Wiley, The authors wish to thank the patients for their participation in this study. In addition, Leonard Lionnet, PhD providedmedical writing assistance which was funded by UCARE (www.ga2len--ucare.com). Open Access funding enabled and organized by Projekt DEAL.

Human motion prediction is essential for the safe and smooth operation of mobile service robots and intelligent vehicles around people. Commonly used neural network-based approaches often require large amounts of complete trajectories to represent motion dynamics in complex semantically-rich spaces. This requirement may complicate deployment of physical systems in new environments, especially when the data is being collected online from onboard sensors. In this paper we explore a data-efficient alternative using maps of dynamics (MoD) to represent place-dependent multi-modal spatial motion patterns, learned from prior observations. Our approach can perform efficient human motion prediction in the long-term perspective of up to 60 seconds. We quantitatively evaluate its accuracy with limited amount of training data in comparison to an LSTM-based baseline, and qualitatively show that the predicted trajectories reflect the natural semantic properties of the environment, e.g. the locations of short- and long-term goals, navigation in narrow passages, around obstacles, etc., Comment: in 5th LHMP Workshop held in conjunction with 40th IEEE International Conference on Robotics and Automation (ICRA), 29/05 - 02/06 2023, London

The paradigmatic approach in the study of vocal phenomena art offers new approaches and produces non-traditional standards of scientific thinking, making significant corrections to the general scientific picture of the world. This is precisely what is connected with the growth of scientific interest in the multidimensional personality phenomenon of music theorist, composer, pianist-concertmaster Boleslav Yavorsky (1877–1942) and his influence on the formation of the vocal paradigm of music education in Ukraine. Historical musicology, exploring different areas of artistic life, has lost track of an important topic such as the concertmaster activity of pianistscomposers who traditionally accompanied the performance of not only their but also other’s compositions, resulting in the unique creative act when one author was becoming the interpreter of other master’s compositions – his predecessor or contemporary. In the cognition of music history, such artistic events are of notable significance, as they reflect not just the performing evolution but also the process of creative reframing of the musical material. The main benefits of Yavorsky’s theory consist in analyzing the structure of mode formation and the internal modal organization of musical composition and musical-historical processes as well as drawing analogies in the development of various kinds of arts.

This chapter presents existing legal and regulatory structures and some of the overarching governance practices that apply to “genetically modified” animals in what are considered “research” settings in selected countries or geopolitical units around the world. It incorporates the ethics of animal use by reference and concentrates on the statutory regulation and softer governance systems in situations in which animals that are clones (or their offspring) or that have intentional genomic alterations that fit within the rubric of “techniques of modern biotechnology” as defined by the WHO and FAO are used for research purposes. The chapter defines ‘What is an animal?’, the meaning of “modified” or “altered” and of “research”, then delves into the nuances around terms such as “regulation” and “governance”. It looks at the special case of non-human primates before providing a detailed compendium of the laws, regulations, and standards pertaining to research involving genetically modified animals in all major regions of the world.

Background: Concern about disease exacerbations and fear of reactions after coronavirus disease 2019 (COVID-19) vaccinations are common in chronic urticaria (CU) patients and may lead to vaccine hesitancy. Objective: We assessed the frequency and risk factors of CU exacerbation and adverse reactions in CU patients after COVID-19 vaccination. Methods: COVAC-CU is an international multicenter study of Urticaria Centers of Reference and Excellence (UCAREs) that retrospectively evaluated the effects of COVID-19 vaccination in CU patients aged ≥18 years and vaccinated with ≥1 dose of any COVID-19 vaccine. We evaluated CU exacerbations and severe allergic reactions as well as other adverse events associated with COVID-19 vaccinations and their association with various CU parameters. Results: Across 2769 COVID-19–vaccinated CU patients, most (90%) received at least 2 COVID-19 vaccine doses, and most patients received CU treatment and had well-controlled disease. The rate of COVID-19 vaccination–induced CU exacerbation was 9%. Of 223 patients with CU exacerbation after the first dose, 53.4% experienced recurrence of CU exacerbation after the second dose. CU exacerbation most often started <48 hours after vaccination (59.2%), lasted for a few weeks or less (70%), and was treated mainly with antihistamines (70.3%). Factors that increased the risk for COVID-19 vaccination–induced CU exacerbation included female sex, disease duration shorter than 24 months, having chronic spontaneous versus inducible urticaria, receipt of adenovirus viral vector vaccine, having nonsteroidal anti-inflammatory drug/aspirin intolerance, and having concerns about getting vaccinated; receiving omalizumab treatment and Latino/Hispanic ethnicity lowered the risk. First-dose vaccine–related adverse effects, most commonly local reactions, fever, fatigue, and muscle pain, were reported by 43.5% of CU patients. Seven patients reported severe allergic reactions. Conclusions: COVID-19 vaccination lead

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The purpose of the study is to summarize the current state of the art in the economic and legal aspects of ensuring the functioning of critical infrastructure in the housing sector of the national economy and to substantiate proposals for its improvement. The study used general and special research methods: synergistic approach, trend statistical analysis method, economic-mathematical modelling using Statgraphics XV&I Centurion program, logical method and generalization method. The main results of the study include. It has been concluded that housing and public utilities infrastructure is the largest consumer of resources in the world economy, so its operation and development require further research. The authors have defined the tendencies for increasing the volumes of construction works on the territory of Ukraine for the period of 2016-2020 and slow rate for increasing the construction of housing stock. With the help of economic and mathematical modeling, the authors have obtained results of the forecast of the volume of commissioning of the total area of residential buildings in Ukraine. Based on the analysis of the dynamics of emergencies in residential buildings or constructions in Ukraine for the period of 2015-2020, the authors have made a conclusion on the need to implement measures on preventing emergencies. Critical infrastructure facilities within the residential sector of the national economy include both enterprises in the field of water supply, sewerage, production, transportation and marketing of heat and electricity, gas distribution and transportation and water heating and gas supply networks in residential buildings, as well as elevators and networks that provide communication.

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Contains fulltext : 250590.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 248606.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 250794.pdf (Publisher’s version ) (Open Access)

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Chromium triiodide is an intrinsically magnetic van der Waals material down to the single-layer limit. Here, we provide a first-principles description of finite-temperature magnetic and spectral properties of monolayer (ML) CrI3 based on fully charge self-consistent density functional theory (DFT) combined with dynamical mean-field theory, revealing a formation of local moments on Cr from strong local Coulomb interactions. We show that the presence of local dynamical correlations leads to a modification of the electronic structure of ferromagnetically ordered CrI3. In contrast to conventional DFT+U calculations, we find that the top of the valence band in ML CrI3 demonstrates essentially different orbital character for minority and majority spin states, which is closer to the standard DFT results. This leads to a strong spin polarization of the optical conductivity upon hole doping, which could be verified experimentally.

Robots are increasingly deployed in spaces shared with humans, including home settings and industrial environments. In these environments, the interaction between humans and robots (HRI) is crucial for safety, legibility, andefficiency. A key factor in HRI is trust, which modulates the acceptance of the system. Anthropomorphism has been shown to modulate trust development in a robot, but robotsin industrial environments are usually not anthropomorphic. We designed a simple interaction in an industrial environment in which an anthropomorphic mock driver (ARMoD) robot simulates driving an autonomous guided vehicle (AGV). The task consisted of a human crossing paths with the AGV, with or without the ARMoD mounted on the top, in a narrow corridor. The human and the system needed to negotiate trajectories when crossing paths, meaning that the human had to attend to the trajectory of the robot to avoid a collision with it. There was a significant increment in the reported trust scores in the condition where the ARMoD was present, showing that the presence of an anthropomorphic robot is enough to modulate the trust, even in limited interactions as the one we present here., CC BY-SA 4.0This work was supported by the European Union’s Horizon 2020 researchand innovation program under grant agreement No. 101017274 (DARKO) and grant agreement No. 754285

Crystalline black nitrogen (BN) is an allotrope of nitrogen with the black phosphorus (BP) structure recently synthesized at high pressure by two independent research groups [Ji et al., Sci. Adv. 6, eaba9206 (2020); Laniel et al., Phys. Rev. Lett. 124, 216001 (2020)]. Here, we present a systematic study of the electronic and optical properties of BN focusing on its comparison with BP. To this end, we use the state-of-the-art quasiparticle self-consistent GW approach with vertex corrections in both the electronic and optical channels. Despite many similarities, the properties of BN are found to be considerably different. Unlike BP, BN exhibits a larger optical gap (2.5 vs 0.26 eV), making BN transparent in the visible spectral region with a highly anisotropic optical response. This difference can be primarily attributed to a considerably reduced dielectric screening in BN, leading to enhancement of the effective Coulomb interaction. Despite relatively strong Coulomb interaction, exciton formation is largely suppressed in both materials. Our analysis of the elastic properties shows exceptionally high stiffness of BN, comparable to that of diamond., Funding Agencies|ERC Synergy Grant [854843 FASTCORR]; Knut and Alice Wallenberg Foundation (Wallenberg Scholar Grant) [KAW-2018.0194]; Swedish Government Strategic Research Areas in Materials Science on Functional Materials at Linkoping University [2009 00971]; Swedish e-Science Research Center (SeRC); Swedish Research Council (VR) [201905600]; VINN Excellence Center Functional Nanoscale Materials (FunMat-2) [201605156]; RFBR [20-02-00178]; U.S. Department of Energy, Office of Science, Basic Energy Sciences, Division of Chemical Sciences [DE-AC36-08GO28308]; Swedish Research Council [2016-07213]; PRACE; SURF Cooperative

The ultraviolet (UV)-induced dissociation and photofragmentation of gas-phase CH2BrI molecules induced by intense femtosecond extreme ultraviolet (XUV) pulses at three different photon energies are studied by multi-mass ion imaging. Using a UV-pump-XUV-probe scheme, charge transfer between highly charged iodine ions and neutral CH2Br radicals produced by C-I bond cleavage is investigated. In earlier charge-transfer studies, the center of mass of the molecules was located along the axis of the bond cleaved by the pump pulse. In the present case of CH2BrI, this is not the case, thus inducing a rotation of the fragment. We discuss the influence of the rotation on the charge transfer process using a classical over-the-barrier model. Our modeling suggests that, despite the fact that the dissociation is slower due to the rotational excitation, the critical interatomic distance for charge transfer is reached faster. Furthermore, we suggest that charge transfer during molecular fragmentation may be modulated in a complex way.

Reliability assessment and prediction of the number of faults/defects is an important part of the software engineering process. Many software reliability models assume that all detected are removed with certainty and no new faults are introduced. However, the introduction of secondary faults during software updates has become quite common in software development practice, which can be explained by the enormous complexity of modern computer applications. In the paper we consider different scenarios of introducing secondary faults and how to predict number of such faults. Finally, we discuss how different SRGMs like Jelinski-Moranda, Exponential, Schick-Wolverton, Musa and Lipov models can be modified to account secondary faults in order to improve accuracy of software reliability prediction. We use an industrial case study to demonstrate applicability of the proposed approach. Our results show that considering secondary faults helped to considerably improve accuracy of software failure rate prediction.

During the last decade, X-ray free-electron lasers (XFELs) have enabled the study of light-matter interaction under extreme conditions. Atoms which are subject to XFEL radiation are charged by a complex interplay of (several subsequent) photoionization events and electronic decay processes within a few femtoseconds. The interaction with molecules is even more intriguing, since intricate nuclear dynamics occur as the molecules start to dissociate during the charge-up process. Here, we demonstrate that by analyzing photoelectron angular emission distributions and kinetic energy release of charge states of ionic molecular fragments, we can obtain a detailed understanding of the charge-up and fragmentation dynamics. Our novel approach allows for gathering such information without the need of complex ab initio modeling. As an example, we provide a detailed view on the processes happening on a femtosecond time scale in oxygen molecules exposed to intense XFEL pulses.

Contains fulltext : 287774.pdf (Publisher’s version ) (Open Access)