Scientific Goals Research Articles

Westernism Genesis in Russian Art as a Reflection of the Fatality of National Policy

The scientific goal of this paper aims to use interdisciplinary analysis to show how reforms of Peter I had a devastating impact on Russia. These reforms had a devastating impact on Russia, which was the last state stronghold of the OrthodoxSlavic world, in favor of Protestant models of Roman-German civilization. The aggressive rejection of Eastern Christianity characterized these models. The political system’s transformations are most clear in its cultural and ideological sphere, where art becomes a means of self-expression for those in power. The author of the article, thus, focuses on architecture as a major type of art and shows the completely pro-Western nature of the country’s reform. And if the power and society were one before Peter I reform, then since the XVII century they became divided into alienated civilizations. Moreover, the Russian authorities subjected the field of art to Western influence, leading to an indirect “foreign yoke.” This fostered antagonistic contradictions within society, culminating in the events of 1917, when the “Alien” power was finally overthrown.

A global neuronal workspace model of functional neurological disorders.

We introduce here a general model of Functional Neurological Disorders based on the following hypothesis: a Functional Neurological Disorder could correspond to a consciously initiated voluntary top-down process causing involuntary lasting consequences that are consciously experienced and subjectively interpreted by the patient as involuntary. We develop this central hypothesis according to Global Neuronal Workspace theory of consciousness, that is particularly suited to describe interactions between conscious and non-conscious cognitive processes. We then present a list of predictions defining a research program aimed at empirically testing their validity. Finally, this general model leads us to reinterpret the long-debated links between hypnotic suggestion and functional neurological disorders. Driven by both scientific and therapeutic goals, this theoretical paper aims at bringing closer the psychiatric and neurological worlds of functional neurological disorders with the latest developments of cognitive neuroscience of consciousness.

Computational reconstruction of mental representations using human behavior

Revealing how the mind represents information is a longstanding goal of cognitive science. However, there is currently no framework for reconstructing the broad range of mental representations that humans possess. Here, we ask participants to indicate what they perceive in images made of random visual features in a deep neural network. We then infer associations between the semantic features of their responses and the visual features of the images. This allows us to reconstruct the mental representations of multiple visual concepts, both those supplied by participants and other concepts extrapolated from the same semantic space. We validate these reconstructions in separate participants and further generalize our approach to predict behavior for new stimuli and in a new task. Finally, we reconstruct the mental representations of individual observers and of a neural network. This framework enables a large-scale investigation of conceptual representations.

Advancing interactive systems with liquid crystal network-based adaptive electronics.

Achieving adaptive behavior in artificial systems, analogous to living organisms, has been a long-standing goal in electronics and materials science. Efforts to integrate adaptive capabilities into synthetic electronics traditionally involved a typical architecture comprising of sensors, an external controller, and actuators constructed from multiple materials. However, challenges arise when attempting to unite these three components into a single entity capable of independently coping with dynamic environments. Here, we unveil an adaptive electronic unit based on a liquid crystal polymer that seamlessly incorporates sensing, signal processing, and actuating functionalities. The polymer forms a film that undergoes anisotropic deformations when exposed to a minor heat pulse generated by human touch. We integrate this property into an electric circuit to facilitate switching. We showcase the concept by creating an interactive system that features distributed information processing including feedback loops and enabling cascading signal transmission across multiple adaptive units. This system responds progressively, in a multi-layered cascade to a dynamic change in its environment. The incorporation of adaptive capabilities into a single piece of responsive material holds immense potential for expediting progress in next-generation flexible electronics, soft robotics, and swarm intelligence.

How much can personality predict prosocial behavior?

Explaining prosocial behavior is a central goal in classic and contemporary behavioral science. Here, for the first time, we apply modern machine learning techniques to uncover the full predictive potential that personality traits have for prosocial behavior. We utilize a large-scale dataset ( N = 2707; 81 personality traits) and state-of-the-art statistical models to predict an incentivized measure of prosocial behavior, Social Value Orientation (SVO). We conclude: (1) traits explain 13.9% of the variance in SVO; (2) linear models are sufficient to obtain good prediction; (3) trait–trait interactions do not improve prediction; (4) narrow traits improve prediction beyond basic personality (i.e., the HEXACO); (5) there is a moderate association between the univariate predictive power of a trait and its multivariate predictive power, suggesting that univariate estimates (e.g., Pearson’s correlation) can serve as a useful proxy for multivariate variable importance. We propose that the limited usefulness of nonlinear models may stem from current measurement practices in personality science, which tend to favor linearly related constructs. Overall, our study provides a benchmark for how well personality predicts SVO and charts a course toward better prediction of prosocial behavior.

Monitoring the impact of forest changes on carbon uptake with solar-induced fluorescence measurements from GOME-2A and TROPOMI for an Australian and Chinese case study

Abstract. Reliable and robust monitoring tools are crucial to assess the effectiveness of land mitigation techniques (LMTs) in enhancing carbon uptake, enabling informed decision making by policymakers. This study, addressing one of the scientific goals of the EU Horizon 2020 Land Use Based Mitigation for Resilient Climate Pathways (LANDMARC) project, examines the feasibility of using satellite solar-induced fluorescence (SIF) in combination with other satellite data as a monitoring proxy to evaluate the effects of LMTs on carbon uptake. Two distinct cases are explored: (1) instantaneous vegetation destruction caused by a 2019 eucalyptus wildfire in southeast Australia and (2) gradual forest gain resulting from reforestation efforts in northern China in 2007–2012. The cases are monitored using SIF from the TROPOspheric Monitoring Instrument (TROPOMI) and Global Ozone Monitoring Experiment-2A (GOME-2A), respectively. Comparing the temporal variability in SIF across the affected areas and nearby reference areas reveals that vegetation dynamics changed as a consequence of the land-use changes in both cases. Specifically, in the Australia case, TROPOMI demonstrated an immediate reduction in the SIF signal of 0.6 mW m−2 sr−1 nm−1 (−72 %) over the eucalypt forest right after the fire. Exploiting the strong correspondence between TROPOMI SIF and gross primary productivity (GPP) at the nearby representative eddy covariance Tumbarumba site and through the FluxSat product, we estimate that the Australian fire led to a loss in GPP of 130–200 GgC in the first 8 months after the fire. Over the northern Chinese provinces of Gansu, Shaanxi, Sichuan, Chongqing, and Shanxi, we report an increase in GOME-2A summertime SIF of 0.1–0.2 mW m−2 sr−1 nm−1, coinciding with reforestation efforts between 2007 and 2012. This increase in the SIF signal is likely driven by a combination of increasingly favourable natural conditions and by the reforestation effort itself. A multivariate model that takes into account growth factors such as water availability and maximum temperature as well as satellite-derived forest-cover data explains the observed variability in GOME-2A SIF in the Chinese case reasonably well (R2=0.72). The model suggests that increases in both forest cover and soil moisture have led, in step, to the observed increase in vegetation activity over northern China. In that region, for every 100 km2 of additional forest cover, SIF increases by 0.1 mW m−2 sr−1 nm−1 between 2007 and 2012. Our study highlights that the use of satellite-based SIF, together with supporting in situ, modelled, and satellite data, allows us to monitor the impact of LMT implementation on regional carbon uptake as long as the scale of the LMT is of sufficient spatial extent.

The Hera Radio Science Experiment at Didymos

Hera represents the European Space Agency's inaugural planetary defense space mission and plays a pivotal role in the Asteroid Impact and Deflection Assessment international collaboration with NASA DART mission that performed the first asteroid deflection experiment using the kinetic impactor techniques. With the primary objective of conducting a detailed post-impact survey of the Didymos binary asteroid following the DART impact on its small moon called Dimorphos, Hera aims to comprehensively assess and characterize the feasibility of the kinetic impactor technique in asteroid deflection while conducting an in-depth investigation of the asteroid binary, including its physical and compositional properties as well as the effect of the impact on the surface and shape of Dimorphos. In this work, we describe the Hera radio science experiment, which will allow us to precisely estimate critical parameters, including the mass, which is required to determine the momentum enhancement resulting from the DART impact, mass distribution, rotational states, relative orbits, and dynamics of the asteroids Didymos and Dimorphos. Through a multi-arc covariance analysis, we present the achievable accuracy for these parameters, which consider the full expected asteroid phase and are based on ground radiometric, Hera optical images, and Hera to CubeSats InterSatellite Link radiometric measurements. The expected formal uncertainties for Didymos and Dimorphos GM are better than 0.01% and 0.1%, respectively, while their J2 formal uncertainties are better than 0.1% and 10%, respectively. Regarding their rotational state, the absolute spin pole orientations of the bodies can be recovered to better than 1°, and Dimorphos' spin rate to better than 10−3%. Dimorphos reconstructed relative orbit can be estimated at the sub-m level. Preliminary results, using a higher-fidelity dynamical model of the coupled motion between rotational and orbital dynamics, show uncertainties in the main parameters of interest that are comparable to those in standard radio science models. A first-order estimate of the expected uncertainty in the momentum transfer efficiency from DART's impact, obtainable with Hera, yields a value of about 0.25. This represents a significant improvement compared to current estimates. Overall, the retrieved values meet the Hera radio science requirements and goals, and remain valid under the condition that the system is determined to be in an excited but non-chaotic (or tumbling) state. The Hera radio science experiment will play an integral role in the exploration of the Didymos binary asteroid system and will provide unique scientific measurements, which, when combined with other observables such as optical images, altimetry measurements, and satellite-to-satellite tracking of the CubeSats, will support the mission's overarching goals in planetary defense and the deep understanding of binary asteroids.

Computational study of diffraction image formation from XFEL irradiated single ribosome molecule

Single particle imaging at atomic resolution is perhaps one of the most desired goals for ultrafast X-ray science with X-ray free-electron lasers. Such a capability would create great opportunity within the biological sciences, as high-resolution structural information of biosamples that may not crystallize is essential for many research areas therein. In this paper, we report on a comprehensive computational study of diffraction image formation during single particle imaging of a macromolecule, containing over one hundred thousand non-hydrogen atoms. For this study, we use a dedicated simulation framework, SIMEX, available at the European XFEL facility. Our results demonstrate the full feasibility of computational single-particle imaging studies for biological samples of realistic size. This finding is important as it shows that the SIMEX platform can be used for simulations to inform relevant single-particle-imaging experiments and help to establish optimal parameters for these experiments. This will enable more focused and more efficient single-particle-imaging experiments at XFEL facilities, making the best use of the resource-intensive XFEL operation.

Characterizing engagement in the science practices: A study of preservice elementary teachers

AbstractPreservice elementary teachers enter their science methods courses with a range of prior experience with science practice. Those prior experiences likely inform much of their science pedagogy and goals. In this study, the authors examine how a cohort of preservice elementary teachers engaged in science practice as they learned content in a physics course. Drawing on course documents, videorecords, and artifacts from in‐class lab work and interviews with nine participants, the authors used an asset‐based, mixed methods approach. The authors developed rubrics to assess the level of sophistication the participants used while engaging in science practice on a scale of 1 (pre‐novice) to 4 (experienced). They used descriptive statistics and ANOVA's to interpret the performance of the participants in addition to grounded theory open coding of interviews to determine the participants' level of prior experience with science practice. The findings suggest that these preservice teachers primarily engaged in science practices at a novice level. In general, their sophistication scores on the rubric aligned with their prior experience. The findings suggest that while one content course steeped in science practice was not enough to significantly change preservice teachers' engagement, it can provide a needed starting place and that it likely takes time to develop these skills. The findings have implications for both teacher educators and researchers who hope to increase the use of science practice as a method of learning science content.

New Generation of Superattenuator for Einstein Telescope: preliminary studies

Seismic noise and local disturbances are dominant noise sources for ground-based gravitational waves detectors in the low frequency region (0.1–10 Hz) limiting their sensitivity and duty cycle. With the introduction of high-performance seismic isolation systems based on mechanical pendula, the 2nd generation laser interferometric detectors have reached the scientific goal of the first direct observation of GW signals thanks to the extension of the detection bandwidth down to 10 Hz. Now, the 3rd generation instrument era is approaching, and the Einstein telescope giant interferometer is becoming a reality with the possibility to install the detector in an underground site where seismic noise is 100 times smaller than on surface. Moreover, new available technologies as well as the experience acquired in operating advanced detectors are key points to further extend the detection bandwidth down to 2 Hz with the possibility to suspend cryogenic payload and then mitigating thermal noise too. Here, we present a preliminary study devoted to improving seismic attenuation performance of the advanced VIRGO superattenuator in the low frequency region of about five orders of magnitude. Particular care has been carried on in analyzing the possibility to improve the vertical attenuation performance with a multi-stage pendulum chain equipped with magnetic anti-springs that is hung to a double inverted pendulum in nested configuration. The feedback control requirements and possible strategies to be adopted for this last element will be presented.

Getting a grip on how we talk about computational practices in science in settings of teacher learning

AbstractBackgroundScience teachers' understanding of the roles of computing practices in science frame how they enact scientific computational practices in their teaching and how their students perceive the relationship between computational practices and scientific endeavours.ObjectivesThis critical, integrative review synthesizes teacher learning literature about the role of computational literacy and computing practices in K‐12 science teaching.MethodsWe examined 54 peer‐reviewed articles and analysed the ways the researchers and teacher participants describe the affordances of integrating computational thinking (CT) and other computational practices in science. We characterize how CT and computational practices are framed in relation to scientific learning goals. We identify six primary affordances for integrating computational practices with science that are conveyed to teachers and by teachers, as represented in these studies of teacher learning.Results and ConclusionsThese six perspectives include (1) learning computer science principles, (2) developing CT dispositions, (3) engagement and inclusion in science, (4) taking ownership of science, (5) supporting learning science content, and (6) participating in computational practice as a form of scientific epistemic practice. Our analysis indicates that computational thinking and computational practices are often integrated in science in order to teach something about computing (e.g., Perspective 1), rather than to support learners' scientific work. Only the 29 articles coded for the sixth perspective—that is, in service of epistemic aims in science—demonstrate commitment to students' uses of computational ideas and practices as epistemic tools to participate in the sensemaking work of science.TakeawaysComparison of Perspectives 5 and 6 illustrates the nuance between computational practices in science that reify something students have already “figured out,” rather than those that serve epistemic goals. Perspective 6 encapsulates the deep synergy among (1) the reflexive nature of computing with scientific ideas and (2) computing as a central practice in science and engineering. We contend that a more focused message of computational practices in service of scientific sensemaking goals is necessary if we expect teachers to enact CT and related computational practices in their classrooms.

The SRG/eROSITA All-Sky Survey

Clusters of galaxies can be used as powerful probes to study astrophysical processes on large scales, test theories of the growth of structure, and constrain cosmological models. The driving science goal of the SRG/eROSITA All-Sky Survey is to assemble a large sample of X-ray clusters with a well-defined selection function to determine the evolution of the mass function and, hence, the cosmological parameters. We present here a catalog of 12 247 optically confirmed galaxy groups and clusters detected in the 0.2–2.3 keV as extended X-ray sources in a 13 116 deg2 region in the western Galactic half of the sky, which eROSITA surveyed in its first six months of operation. The clusters in the sample span the redshift range 0.003 < z < 1.32. The majority (68%) of these clusters, 8361 sources, represent new discoveries without known counterparts in the literature. The mass range of the sample covers three orders of magnitude from 5 × 1012 Msun to 2 × 1015Msun. We construct a sample for cosmology with a higher purity level (~95%) than the primary sample, comprising 5259 securely detected and confirmed clusters in the 12791 deg2 common footprint of eRASS1 and the DESI Legacy Survey DR10. We characterize the X-ray properties of each cluster, including their flux, luminosity and temperature, the total mass, gas mass, gas mass fraction, and mass proxy YX. These are determined within two apertures, 300 kpc, and the overdensity radius R500, and are calculated by applying a forward modeling approach with a rigorous X-ray background treatment, K-factor, and the Galactic absorption corrections. Population studies utilizing log N-log S, the number of clusters detected above a given flux limit, and the luminosity function show overall agreement with the previous X-ray surveys after accounting for the survey completeness and purity through the selection function. The first eROSITA All-Sky Survey provides an unprecedented sample of galaxy groups and clusters selected in the X-ray band. The eRASS1 cluster catalog demonstrates the excellent performance of eROSITA for extended source detection, consistent with the pre-launch expectations for the final all-sky survey, eRASS:8.

Understanding the determinants of sweet taste liking in the African and East Asian ancestry groups in the U.S.-A study protocol.

The liking for sweet taste is a powerful driver for consuming added sugars, and therefore, understanding how sweet liking is formed is a critical step in devising strategies to lower added sugars consumption. However, current research on the influence of genetic and environmental factors on sweet liking is mostly based on research conducted with individuals of European ancestry. Whether these results can be generalized to people of other ancestry groups warrants investigation. We will determine the differences in allele frequencies in sweet-related genetic variants and their effects on sweet liking in 426 adults of either African or East Asian ancestry, who have the highest and lowest average added sugars intake, respectively, among ancestry groups in the U.S. We will collect information on participants' sweet-liking phenotype, added sugars intake (sweetness exposure), anthropometric measures, place-of-birth, and for immigrants, duration of time living in the U.S. and age when immigrated. Ancestry-specific polygenic scores of sweet liking will be computed based on the effect sizes of the sweet-related genetic variants on the sweet-liking phenotype for each ancestry group. The predictive validity of the polygenic scores will be tested using individuals of African and East Asian ancestry from the UK Biobank. We will also compare sweet liking between U.S.-born individuals and immigrants within each ancestry group to test whether differences in environmental sweetness exposure during childhood affect sweet liking in adulthood. Expanding genetic research on taste to individuals from ancestry groups traditionally underrepresented in such research is consistent with equity goals in sensory and nutrition science. Findings from this study will help in the development of a more personalized nutrition approach for diverse populations. This protocol has been preregistered with the Center for Open Science (https://doi.org/10.17605/OSF.IO/WPR9E).

Metrics in biodiversity conservation and the value-free ideal

This paper examines one aspect of the legacy of the Value-Free Ideal in conservation science: the view that measurements and metrics are value-free epistemic tools detached from ideological, ethical, social, and, generally, non-epistemic considerations. Contrary to this view, I will argue that traditional measurement practices entrenched in conservation are in fact permeated with non-epistemic values. I challenge the received view by revealing three non-epistemic assumptions underlying traditional metrics: (1) a human-environment demarcation, (2) the desirability of a people-free landscape, and (3) the exclusion of cultural diversity from biodiversity. I also draw a connection between arguments for retaining traditional metrics to “scientific colonialism,” exemplified by a fortress conservation model. I conclude by advocating for abandoning the myth of the intrinsic value-freedom of measurement practices and embracing metrics aligned with societal and scientific goals.

Towards a Benchmark for Scientific Understanding in Humans and Machines

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be recognized as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines.

What does agricultural science need today?

The article presents some key points of agricultural science existence in the world during the post-pandemic period, the intensive development of digitalization, and the deployment of artificial intelligence. The industry's development is coupled with interdisciplinary sciences, enabling the creation of future scenarios for successful implementation into practice. With tremendous advancement, agricultural science still faces challenges and problems such as outdated agricultural machinery and poor infrastructure in many developing countries. On a global scale, the science addresses sustainable development, soil fertility improvement, and biodiversity conservation in the face of climate change.Many of the solutions to the man-made problems that have been created lead to strong education and reskilling of people on the principle of "life-long learning". Through such approaches, the economic component of agriculture will grow. From the point of view of the research environment, it is necessary to expand research topics in order to close the weak links in the “human-nature” chain. The achievements of agrarian science should find practical application at the local level, involving "farmer-official-scientist" collaboration. There are now many communities, workshops, and platforms promoting educational and practical goals for better agricultural science, combating hunger, nutritious food, and climate change, where one can express personal perspectives and hear from professionals. These events are supported by international organizations such as the United Nations and UNDP, which give a special role to women working in agrarian spheres in order to develop the necessary qualities for practicing agrarian science. Present opportunities have the potential to advance agrarian sciences, drawing from the experiences of advanced countries and adapting them to local conditions, opportunities, and mentalities, with the aim of ensuring high-quality and stable grain production for human food demands.

Critical importance of correctly defining and reporting secondary endpoints when assessing the ethics of research biopsies.

This article reviews the implementation challenges to the American Society of Clinical Oncology's ethical framework for including research biopsies in oncology clinical trials. The primary challenges to implementation relate to the definitions of secondary endpoints, the scientific and regulatory framework, and the incentive structure that encourages inclusion of biopsies. Principles of research stewardship require that the clinical trials community correctly articulate the scientific goals of any research biopsies, especially those that are required for the patient to enroll on a trial and receive an investigational agent. Furthermore, it is important to sufficiently justify the characterization of secondary (as distinguished from exploratory) endpoints, protect the interest of research participants, and report accurate and complete information to ClinicalTrials.gov and the published literature.

Bamboozled by Bonferroni

Abstract When many statistical hypotheses are evaluated simultaneously, statisticians often recommend adjusting (or “correcting”) standard hypothesis tests. In this article, I (1) distinguish two senses of adjustment, (2) investigate the prudential and epistemic goals that adjustment might achieve, and (3) identify conditions under which a researcher should not adjust for multiplicity in the two senses I identify. I tentatively conclude that the goals of scientists and the public may be misaligned with the decision criteria used to evaluate multiple-testing regimes.

Experimental Identification of Potential Martian Biosignatures in Open and Closed Systems.

NASA's Perseverance and ESA's Rosalind Franklin rovers have the scientific goal of searching for evidence of ancient life on Mars. Geochemical biosignatures that form because of microbe-mineral interactions could play a key role in achieving this, as they can be preserved for millions of years on Earth, and the same could be true for Mars. Previous laboratory experiments have explored the formation of biosignatures under closed systems, but these do not represent the open systems that are found in natural martian environments, such as channels and lakes. In this study, we have conducted environmental simulation experiments using a global regolith simulant (OUCM-1), a thermochemically modelled groundwater, and an anaerobic microbial community to explore the formation of geochemical biosignatures within plausible open and closed systems on Mars. This initial investigation showed differences in the diversity of the microbial community developed after 28 days. In an open-system simulation (flow-through experiment), the acetogenic Acetobacterium (49% relative abundance) and the sulfate reducer Desulfosporomusa (43% relative abundance) were the dominant genera. Whereas in the batch experiment, the sulfate reducers Desulfovibrio, Desulfomicrobium, and Desulfuromonas (95% relative abundance in total) were dominant. We also found evidence of enhanced mineral dissolution within the flow-through experiment, but there was little evidence of secondary deposits in the presence of biota. In contrast, SiO2 and Fe deposits formed within the batch experiment with biota but not under abiotic conditions. The results from these initial experiments indicate that different geochemical biosignatures can be generated between open and closed systems, and therefore, biosignature formation in open systems warrants further investigation.

The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing

Abstract In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues, and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.