Scientific Experiments Research Articles

Scientific Knowledge in Bacon Philosophy: Insights from Dialectical Materialism

Francis Bacon occupies a central position in the history of the philosophy of science, representing a pivotal shift from medieval to early modern scientific thought. Therefore, in the contemporary context, understanding Bacon's philosophy is crucial for appreciating the foundations of modern science and its ongoing evolution. The purpose of the article is to examine the enduring relevance of Francis Bacon's philosophy of science, particularly in the context of his emphasis on empirical methodology, experimentation, and the socio-cultural dimensions of scientific knowledge. By analyzing Bacon's contributions, the study aims to elucidate his methodological innovations and their implications for contemporary scientific practice and theory. The work uses thematic and comparative analysis to determine the role of F. Bacon's philosophy in the analysis of the concept of knowledge.The research highlights Bacon's seminal contributions to the philosophy of science, emphasizing his advocacy for empirical methodology, systematic experimentation, and the socio-cultural context of scientific inquiry. By critiquing the methodological limitations of scholastic philosophy and advocating for a methodological overhaul grounded in experience and observation, Bacon laid the groundwork for modern experimental science. In the conclusion, his integration of dialectical materialism and interdisciplinary perspectives underscores the significance of collective scientific endeavor and the foundational role of natural history in establishing the ontological basis of scientific knowledge. By elucidating Bacon's vision for a science that serves the general welfare of society, the study underscores the continued importance of his insights for addressing contemporary challenges and advancing scientific knowledge for the betterment of humanity.

Effects of first vs. third-person perspective and self- versus other-avatars on user movements in virtual reality

Social science experiments in virtual reality (VR) frequently manipulate the perspective from which a user views an avatar and the identity of an avatar to change participant perceptions and attitudes. However, avatar embodiment may also influence physical behaviors—i.e., the way participants move—during the VR experience. For example, users may shift their position to align with avatars they see from a first-person perspective, a phenomenon known as the self-follower effect. We conducted a between-subjects, pre-registered study to understand how common techniques such as manipulating perspective and appearance might affect participant movements while in VR. We demonstrate that even when participants do not have agency over their avatars' movements, viewing avatar movements influences their own actions, whether these are viewed from the first or the third-person perspective. These phenomena hold potential as interventions to prompt participant movements in other contexts.

Integration of Digital Twins Technologies in Education for Experiential learning: Benefits and Challenges

In order to provide an immersive and engaging learning environment, digital twins in education are virtual representations of real-world items, settings, or people. From elementary to secondary school to higher education establishments, digital twins can be employed in a variety of educational contexts. For instance, students can imitate scientific experiments that would be hard to execute in the classroom owing to safety issues or a lack of resources, by using digital twins to create virtual versions of the investigations. With the help of digital twins, educators may even plan virtual field trips that let learners travel the globe without ever leaving the classroom. For instance, students might be able to study history, tour of Taj Mahal in Agra in-depth, and even engage with historical personalities through a digital duplicate of the wall. Students can communicate with lecturers or subject matter experts virtually by using digital duplicates to build virtual versions of them. In remote learning environments, where students do not have access to actual classrooms or in-person instructors, this can be especially helpful. This research study discusses the advantages of using digital twin technologies extensively in the educational system, as well as the technological, social, and ethical constraints.

Optimal 3D angular sampling with applications to cryo-EM problems

The goal of cryo-EM experiments in the biological sciences is to determine the atomic structure of a molecule and deduce insights into its functions and mechanisms. Despite improvements in instrumentation for data collection and new software algorithms, in most cases, individual atoms are not resolved. Model building of proteins, nucleic acids, or molecules in general, is feasible from the experimentally determined density maps at resolutions up to the range of 3–4 Angstroms. For lower-resolution maps or parts of maps, fitting smaller structures obtained by modelling or experimental techniques with higher resolution is a way to resolve the issue. In practice, we have an atomic structure, generate its density map at a given resolution, and translate/rotate the map within a region of interest in the experimental map, computing a measure-of-fit score with the corresponding areas of the experimental map. This procedure is computationally intensive since we work in 6D space. An optimal ordered list of rotations will reduce the angular error and help to find the best-fitting positions faster for a coarse global search or a local refinement. It can be used for adaptive approaches to stop fitting algorithms earlier once the desired accuracy has been achieved. We demonstrate how the performance of some fitting algorithms can be improved by grouping sets of rotations. We present an approach to generate more efficient 3D angular sampling, and provide the computer code to generate lists of optimal orientations for single and grouped rotations and the lists themselves.

Final physical design of engineering materials diffractometer at the China spallation neutron source

Neutron diffraction is a widely utilized technique in detecting microstructures and residual strains in large-scale engineering components. In this study, we present the final physical design of an upcoming neutron diffractometer for engineering materials at the China Spallation Neutron Source. Our primary objective is to minimize the experimental time required for precise diffraction peak determination. To achieve this, the design includes a neutron transport system, a neutron wavelength selection system, a diffracted neutron optical system, and a resolution and intensity regulation system. Notably, we optimized the wavelength bandwidth specifically for scientific experiments, while the neutron flux or integrated peak intensity were optimized through careful considerations of neutron transport. Additionally, we placed great emphasis on ensuring the uniformity of the neutron phase space to enhance measurement accuracy. Moreover, we optimized the combinations of resolution and integrated peak intensity based on the best figure of merit. Consequently, we successfully developed an advanced diffractometer that is poised to offer new capabilities for engineering material studies.

Inferred wind speed and direction during the descent and landing of Perseverance on Mars

Perseverance successfully parachuted into Jezero crater close to its western rim on a Martian spring afternoon. In situ observations of the wind conditions during the parachute and powered descent are unavailable. These observations are important for characterising the Planetary Boundary Layer (PBL) and to better constrain atmospheric conditions in Jezero crater.We infer the winds during Perseverance's parachute descent from an altitude of 12 km down to 2 km by fitting a trajectory model to the reconstructed trajectory data published by the M2020 Entry, Descent and Landing team. Below 2 km altitude we infer the winds by analysing a High Resolution Imaging Science Experiment (HiRISE) image of the landing site that was obtained about one sol after the landing.Our inferred wind speed and direction profile indicate high speed winds at an altitude of 7 km blowing from the east and at 3 km blowing from the southwest. Below an altitude of 2 km, the winds are inferred to be easterlies. The heat shield impact on the surface was observed by Perseverance's Lander Vision System Camera (LCAM). Afterwards, ejecta clouds were observed moving towards the north of the impact site. These observations, together with the orientation of the parachute canopy on the surface, suggest near-surface winds at the time were southerlies.We have inferred the wind speed and direction during Perseverance's descent that are consistent with its horizontal motion as revealed by trajectory data and HiRISE image. Comparisons with atmospheric models suggest the high speed winds could be related to topographic forcing. This study provides constraints for atmospheric modelling and advances the characterisation of winds in Jezero crater, focusing on the vertical structure of the complex wind field present in the crater.

Research on Tracking and Positioning Technology for Structural Components of Assembled Buildings

This article critically examines Charles Bonnet’s seminal contributions to experimental science, particularly through his influential work, ‘Research on the Use of Leaves.’ The primary objective is to delineate the functions and forms of natural experimentation as they were understood and practiced in the mid-18th century. During this period, scientists esteemed experimentation as the zenith of scientific proof, acutely cognizant of its multifaceted functional and typological aspects. Their methodology was characterized by a detailed narration of research methodologies, fostering a ‘rhetoric of transparency’ in scientific discourse. Nevertheless, the advent of new norms in scientific discourse during the 19th century, coupled with a paradigmatic philosophical shift in the 20th century, resulted in the marginalization of empirical practices of the Enlightenment era. Contemporary historians are now endeavoring to reconcile significant terminological discrepancies and to recontextualize the divergent methodologies among natural historians of that epoch. This involves a critical distinction between exploratory and demonstrative (or discriminant) forms of experimentation. Bonnet’s systematic preference for discriminant experimentation serves as a quintessential example of the logical approach in natural history. However, this perspective does not wholly represent the 18th-century ‘art of observation,’ which embraced a plethora of methodologies including taxonomy, anatomical dissection, chemical analysis, and physical measurements.

Regression Analysis of the Relationship Between ESG Performance and Firms’ Technological Innovation Capability

This article critically examines Charles Bonnet’s seminal contributions to experimental science, particularly through his influential work, ‘Research on the Use of Leaves.’ The primary objective is to delineate the functions and forms of natural experimentation as they were understood and practiced in the mid-18th century. During this period, scientists esteemed experimentation as the zenith of scientific proof, acutely cognizant of its multifaceted functional and typological aspects. Their methodology was characterized by a detailed narration of research methodologies, fostering a ‘rhetoric of transparency’ in scientific discourse. Nevertheless, the advent of new norms in scientific discourse during the 19th century, coupled with a paradigmatic philosophical shift in the 20th century, resulted in the marginalization of empirical practices of the Enlightenment era. Contemporary historians are now endeavoring to reconcile significant terminological discrepancies and to recontextualize the divergent methodologies among natural historians of that epoch. This involves a critical distinction between exploratory and demonstrative (or discriminant) forms of experimentation. Bonnet’s systematic preference for discriminant experimentation serves as a quintessential example of the logical approach in natural history. However, this perspective does not wholly represent the 18th-century ‘art of observation,’ which embraced a plethora of methodologies including taxonomy, anatomical dissection, chemical analysis, and physical measurements.

The Relationship Between a Green, Low-carbon and Recycling Economy, Economic Policy and Industrial Structure Development

This article critically examines Charles Bonnet’s seminal contributions to experimental science, particularly through his influential work, ‘Research on the Use of Leaves.’ The primary objective is to delineate the functions and forms of natural experimentation as they were understood and practiced in the mid-18th century. During this period, scientists esteemed experimentation as the zenith of scientific proof, acutely cognizant of its multifaceted functional and typological aspects. Their methodology was characterized by a detailed narration of research methodologies, fostering a ‘rhetoric of transparency’ in scientific discourse. Nevertheless, the advent of new norms in scientific discourse during the 19th century, coupled with a paradigmatic philosophical shift in the 20th century, resulted in the marginalization of empirical practices of the Enlightenment era. Contemporary historians are now endeavoring to reconcile significant terminological discrepancies and to recontextualize the divergent methodologies among natural historians of that epoch. This involves a critical distinction between exploratory and demonstrative (or discriminant) forms of experimentation. Bonnet’s systematic preference for discriminant experimentation serves as a quintessential example of the logical approach in natural history. However, this perspective does not wholly represent the 18th-century ‘art of observation,’ which embraced a plethora of methodologies including taxonomy, anatomical dissection, chemical analysis, and physical measurements.

Искусственный интеллект против ученого в вопросе о сохранении баланса между правом на информацию и необходимостью защиты персональных данных от незаконного использования

This article reflects the results of a scientific experiment caused by a discussion about the possibility of replacing scientists with neural networks. The development of digital technologies today raises many controversial issues in science and legal practice. One of the most popular is the question of how to ensure human protection in the context of the transformation of inviolable rights and freedoms: information, privacy and inviolability. The large-scale spread of new technologies poses many questions to the regulator, one of which is the question of finding a balance between the right to information and the need to ensure the protection of personal data in a dynamic and constantly evolving Internet environment. Such a choice is faced by the legislator due to the fact that the spread of innovations involves constant work with personal data, accelerating their exchange, storage and protection. The introduction of digital technologies is beneficial for the development of public services, interaction and control, which ultimately leads to increased efficiency and accelerated information exchange for citizens and legal entities. Taking into account the progressive development of artificial intelligence technologies, it was quite interesting to conduct an experiment comparing the answers to the question of maintaining a balance between the right to information and the need to protect personal data given by scientists and artificial intelligence, in particular, the YandexGPT2 neural network. The responses of the neural network are analyzed for compliance with the main criteria of scientific work: reliability, objectivity and novelty, and are evaluated in comparison with the response of the authors of the scientific article.

Optimization and Performance Analysis of CAT Method for DNA Sequence Similarity Searching and Alignment.

Bioinformatics is a rapidly developing field enabling scientific experiments via computer models and simulations. In recent years, there has been an extraordinary growth in biological databases. Therefore, it is extremely important to propose effective methods and algorithms for the fast and accurate processing of biological data. Sequence comparisons are the best way to investigate and understand the biological functions and evolutionary relationships between genes on the basis of the alignment of two or more DNA sequences in order to maximize the identity level and degree of similarity. This paper presents a new version of the pairwise DNA sequences alignment algorithm, based on a new method called CAT, where a dependency with a previous match and the closest neighbor are taken into consideration to increase the uniqueness of the CAT profile and to reduce possible collisions, i.e., two or more sequence with the same CAT profiles. This makes the proposed algorithm suitable for finding the exact match of a concrete DNA sequence in a large set of DNA data faster. In order to enable the usage of the profiles as sequence metadata, CAT profiles are generated once prior to data uploading to the database. The proposed algorithm consists of two main stages: CAT profile calculation depending on the chosen benchmark sequences and sequence comparison by using the calculated CAT profiles. Improvements in the generation of the CAT profiles are detailed and described in this paper. Block schemes, pseudo code tables, and figures were updated according to the proposed new version and experimental results. Experiments were carried out using the new version of the CAT method for DNA sequence alignment and different datasets. New experimental results regarding collisions, speed, and efficiency of the suggested new implementation are presented. Experiments related to the performance comparison with Needleman-Wunsch were re-executed with the new version of the algorithm to confirm that we have the same performance. A performance analysis of the proposed algorithm based on the CAT method against the Knuth-Morris-Pratt algorithm, which has a complexity of O(n) and is widely used for biological data searching, was performed. The impact of prior matching dependencies on uniqueness for generated CAT profiles is investigated. The experimental results from sequence alignment demonstrate that the proposed CAT method-based algorithm exhibits minimal deviation, which can be deemed negligible if such deviation is considered permissible in favor of enhanced performance. It should be noted that the performance of the CAT algorithm in terms of execution time remains stable, unaffected by the length of the analyzed sequences. Hence, the primary benefit of the suggested approach lies in its rapid processing capabilities in large-scale sequence alignment, a task that traditional exact algorithms would require significantly more time to perform.

Interrogating site dependent kinetics over SiO2-supported Pt nanoparticles

A detailed knowledge of reaction kinetics is key to the development of new more efficient heterogeneous catalytic processes. However, the ability to resolve site dependent kinetics has been largely limited to surface science experiments on model systems. Herein, we can bypass the pressure, materials, and temperature gaps, resolving and quantifying two distinct pathways for CO oxidation over SiO2-supported 2 nm Pt nanoparticles using transient pressure pulse experiments. We find that the pathway distribution directly correlates with the distribution of well-coordinated (e.g., terrace) and under-coordinated (e.g., edge, vertex) CO adsorption sites on the 2 nm Pt nanoparticles as measured by in situ DRIFTS. We conclude that well-coordinated sites follow classic Langmuir-Hinshelwood kinetics, but under-coordinated sites follow non-standard kinetics with CO oxidation being barrierless but conversely also slow. This fundamental method of kinetic site deconvolution is broadly applicable to other catalytic systems, affording bridging of the complexity gap in heterogeneous catalysis.

Workflow-Induced Uncertainty in Data-Driven Mineral Prospectivity Mapping

The primary goal of mineral prospectivity mapping (MPM) is to narrow the search for mineral resources by producing spatially selective maps. However, in the data-driven domain, MPM products vary depending on the workflow implemented. Although the data science framework is popular to guide the implementation of data-driven MPM tasks, and is intended to create objective and replicable workflows, this does not necessarily mean that maps derived from data science workflows are optimal in a spatial sense. In this study, we explore interactions between key components of a geodata science-based MPM workflow on the geospatial outcome, within the modeling stage by modulating: (1) feature space dimensionality, (2) the choice of machine learning algorithms, and (3) performance metrics that guide hyperparameter tuning. We specifically relate these variations in the data science workflow to the spatial selectivity of resulting maps using uncertainty propagation. Results demonstrate that typical geodata science-based MPM workflows contain substantial local minima, as it is highly probable for an arbitrary combination of workflow choices to produce highly discriminating models. In addition, variable domain metrics, which are key to guide the iterative implementation of the data science framework, exhibit inconsistent relationships with spatial selectivity. We refer to this class of uncertainty as workflow-induced uncertainty. Consequently, we propose that the canonical concept of scientific consensus from the greater experimental science framework should be adhered to, in order to quantify and mitigate against workflow-induced uncertainty as part of data-driven experimentation. Scientific consensus stipulates that the degree of consensus of experimental outcomes is the determinant in the reliability of findings. Indeed, we demonstrate that consensus through purposeful modulations of components of a data-driven MPM workflow is an effective method to understand and quantify workflow-induced uncertainty on MPM products. In other words, enlarging the search space for workflow design and experimenting with workflow components can result in more meaningful reductions in the physical search space for mineral resources.

THE SCIENCE OF SPEECH IN THE ISLAMIC EAST: NISHAPUR AS A MODEL OF THEOLOGICAL AND LINGUISTIC INNOVATION IN THE FOURTH CENTURY AH

This research provides a concise exploration of “Islamic theology” in Nishapur. The city’s profound impact on Islamic civilization has led it to be recognized as one of the three most influential cities of its time. That is why this study, aims to encompass all the cities, districts, and villages of Nishapur that contributed to the development and prominence of theology through the efforts of its scholars, educational institutions, and cultural centers. Following the Islamic conquest of Nishapur in the 31st year after Hijra (AH), during the time of Caliph Uthman bin Affan, the people of Nishapur embraced Islam peacefully. Subsequently, they actively engaged in scientific pursuits across various fields, including both Experimental and Religious Sciences. However, the share of Experimental sciences, particularly the science of theology, did not attain the same prominence as Religious sciences, i.e. those sciences that focused solely on Islamic jurisprudence. This disparity may be attributed to Nishapur’s, in deed all other Islamic countries at that time, intense emphasis on religious sciences, which often overshadowed other areas of inquiry. Notably, religious sciences, especially those related to the Qur’an and Sunnah, were regarded as the most sublime and beneficial among all disciplines. Nishapur, however, played a pivotal role in the development of Theology as a science. The city established specialized schools, like that of Abi Ishaq Al-Esfrayini (418 AH), which nurtured a community of scholars. These institutions became a sought-after destination for those seeking this unique form of knowledge. In this research, we delve into this aspect of Nishapur, employing a descriptive methodology and relying on analysis and deduction.Our investigation draws upon several key references and research works, including: • “Tabaqat Al-Fuqaha” by Abi Eshaq Al-Sirazi (476 AH) • “Ta’rifat” by Ali bin Muhammad Al-Jirjani (816 AH) • “Al-Ghuniah fi Usul Al-Din” by Abi Saeed Al-Nishapoury (478 AH) • “An Introduction to the Arabic Scientific Movements in the Islamic East” by Dr. Tariq Fathi Sultan and others

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. We discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

Perspectives on predicting and controlling turbulent flows through deep learning

The current revolution in the field of machine learning is leading to many interesting developments in a wide range of areas, including fluid mechanics. Fluid mechanics, and more concretely turbulence, is an ubiquitous problem in science and engineering. Being able to understand and predict the evolution of turbulent flows can have a critical impact on our possibilities to tackle a wide range of sustainability problems (including the current climate emergency) and industrial applications. Here, we review recent and emerging possibilities in the context of predictions, simulations, and control of fluid flows, focusing on wall-bounded turbulence. When it comes to flow control, we refer to the active manipulation of the fluid flow to improve the efficiency of processes such as reduced drag in vehicles, increased mixing in industrial processes, enhanced heat transfer in heat exchangers, and pollution reduction in urban environments. A number of important areas are benefiting from ML, and it is important to identify the synergies with the existing pillars of scientific discovery, i.e., theory, experiments, and simulations. Finally, I would like to encourage a balanced approach as a community in order to harness all the positive potential of these novel methods.

Evidence from the future.

The outcome of any scientific experiment or intervention will naturally unfold over time. How then should individuals make causal inferences from measurements over time? Across three experiments, we had participants observe experimental and control groups over several days posttreatment in a fictional biological research setting. We identify competing perspectives in the literature: contingency-driven accounts predict no effect of the outcome timing while the contiguity principle suggests people will view a treatment as more harmful to the extent that bad treatment outcomes occur earlier rather than later. In contrast, inference of the functional form of a treatment effect can license extrapolation beyond the measurements and lead to different causal inferences. We find participants' causal strength and direction judgments in temporal settings vary with minimal manipulations of instruction framing. When it is implied that the observations are made over a preplanned number of days, causal judgments depend strongly on contiguity. When it is implied that the observation may be ongoing, participants extrapolate current trends into the future and adapt their causal judgments accordingly. When data are revealed sequentially, participants rely on extrapolation regardless of instruction framing. Our results demonstrate human flexibility in interpreting temporal evidence for causal reasoning and emphasize human tendency to generalize from evidence in ways that are acutely sensitive to task framing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Acute effects of negative heel shoes on perceived pain and knee biomechanical characteristics of runners with patellofemoral pain.

To determine the effects of negative heel shoes on perceived pain and knee biomechanical characteristics of runners with patellofemoral pain (PFP) during running. Sixteen runners with PFP ran in negative (-11mm drops) and positive (5mm drops) heel shoes while visual analog scale (VAS) scores, retroreflective markers, and ground reaction force were acquired by applying a 10-cm VAS, infrared motion capture system, and a three-dimensional force plate. Knee moment, patellofemoral joint stress (PFJS), and other biomechanical parameters during the stance phase were calculated based on inverse dynamics and a biomechanical model of the patellofemoral joint. The foot inclination angle, peak PFJS during the stance phase, patellofemoral joint reaction force, knee extension moment, and quadriceps force at the time of peak PFJS of runners with PFP in negative heel shoes were lower than that in positive heel shoes, no significant difference was found in VAS scores, knee flexion angle, patellofemoral contact area, and quadriceps moment arm at the time of peak PFJS. Compared to positive heel shoes, running in negative heel shoes decreases peak PFJS in runners with PFP, which may decrease patellofemoral joint loading, thus reducing the possibility of further development of PFP. Sports Science Experiment Ethics Committee of Beijing Sport University. 2023095H, April 18, 2023 (prospectively registered).

Development of the Continuous Readout Digitising Imager Array detector

The CoRDIA project aims to develop an X-ray imager capable of continuous operation in excess of 100 kframe/s. The goal is to provide a suitable instrument for Photon Science experiments at diffraction-limited Synchrotron Rings and Free Electron Lasers considering Continuous Wave operation. Several chip prototypes were designed in a 65 nm process: in this paper we will present an overview of the challenges and solutions adopted in the ASIC design.

Research on the Teaching Design of Primary School Science Experiment Based on Project Learning

This study discusses the application and effect of project-based learning in primary science education. Through the case study method, the influence of project learning on improving pupils' scientific knowledge, experimental skills and innovative thinking is analyzed. The project activity takes "Ecosystem and Environmental Protection" as the theme, emphasizing the active participation of students and the application of interdisciplinary knowledge. The research results show that project-based learning effectively enhances students' subject understanding and problem-solving ability, and promotes the cultivation of team spirit. Ultimately, it is suggested that future research should explore the cross-application of project-based learning among different disciplines and evaluate its impact on students' long-term development in order to promote the wide application of this teaching model.