Physical Sciences Research Articles

Paradigm shifts of climate science for climate solutions

Climate science is an indispensable part of climate solutions, and an era of climate actions necessitates certain paradigm shifts of climate science to better support viable climate actions and solutions. Three paradigm shifts are exemplified, namely (1) transcending the boundaries between physical science basis, adaptation, and mitigation; (2) embracing the synergy between climate science and technical innovations for effective climate solutions; and (3) shifting the paradigm from equilibrium climate dynamics toward non-equilibrium dynamics of climate/Earth systems. Beyond the application-driven and solution-oriented studies, curiosity-driven theoretical research is emphasized in the shift toward non-equilibrium climate/Earth systems-tipping elements, abrupt climate changes, and extremes-which may open avenues for new discoveries not only within climate science but also in mathematics, physics, and complex systems science.

In memory of Vladimir Ivanovich Astafyev (30.11.1948 – 08.02.2024)

The article is dedicated to the memory of Doctor of Physical and Mathematical Sciences, Professor Vladimir Ivanovich Astafiev, whose professional activity for more than 35 years has been associated with Samara University. Scientific, teaching and organizational activities of V.I. Astafiev largely determined and will determine the scientific directions developed at the Faculty of Mechanics and Mathematics, and the educational activity at the Faculty of Mechanics and Mathematics. His boundless dedication to the university, his broad and deep education, and high mathematical culture allowed him to educate the whole pleiades of scientists and professors currently working at the university.

Preservice Teachers’ Level of Knowledge on Elements and Rationale for Nature of Science: Towards Advancing Quality Instruction

This study investigates preservice teachers’ knowledge of elements and rationale for Nature of Science (NOS). Skill gap is established in the literature on pedagogical practices of preservice as well as novice teachers of science, reflecting deficiency in their professional training and eventual classroom practice. Examining preservice teachers’ knowledge in these aspects (elements & rationale) of NOS through a quasi-experiment of one-group pretest and post-test design was done. Instructional intervention over two years along with assignments and presentation with researchers as moderators on the science pedagogy module (History of Science and Philosophy of Science) serves as stimuli over the period. Three research questions and two hypotheses were raised to guide this study. One hundred and thirty-six (112 Life Science and 24 Physical Science) preservice teachers were the participants. Element of NOS (ENOS) and Rationale for NOS (RNOS) were the instruments. Reliability of the instruments yielded Cronbach alpha values of .83, .91 and .86 across dimensions of clarity, coherence and relevance by fifteen experienced science educators. Data was analysed using t-test and ANCOVA. The study found the intervention to effectively improve the knowledge of elements and rationale for NOS. Better prepared teachers (More Knowledge Order [MKO] have the potential to improved Zone of Proximal Development [ZPD] in learners) by implication have the competence to guide learners for qualitative and effective learning. The instruments in this study is recommended for foundational training of preservice teachers on NOS for enhanced instruction.

Functional carbon nanoparticles modified poly(3,4-ethylenedioxythiophene) nanocomposites with enhanced dielectric and antibacterial properties

The importance of nanocomposites with tailored properties is growing due to their applications in various fields. In the present study, poly(3,4-ethylenedioxythiophene) (PEDOT) and functionalized carbon nanoparticles (f-CNPs) are synthesized by in-situ chemical oxidative polymerization and pyrolysis methods, respectively. The f-CNPs-PEDOT nanocomposites are prepared by varying the concentration of PEDOT (i.e., 1, 2.5, 5, 10, and 20 wt%), and the thermal stability, dielectric properties and antibacterial activities of f-CNPs-PEDOT nanocomposites were evaluated. The dielectric studies indicated that the addition of PEDOT has enhanced the dielectric properties due to interfacial polarization effect, whereas decreased the thermal stability due to degradation of PEDOT in the nanocomposite, however, it is higher than the pure PEDOT. The antimicrobial potential of synthesized f-CNPs-PEDOT nanocomposites was studied against two different bacterial strains, namely Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli. The findings of this research have potential to open new opportunities for employing f-CNPs-PEDOT nanocomposites in physical sciences and antimicrobial applications.

Integration of Multijunction Absorbers and Catalysts for Efficient Solar‐Driven Artificial Leaf Structures: A Physical and Materials Science Perspective

Artificial leaves could be the breakthrough technology to overcome the limitations of storage and mobility through the synthesis of chemical fuels from sunlight, which will be an essential component of a sustainable future energy system. However, the realization of efficient solar‐driven artificial leaf structures requires integrated specialized materials such as semiconductor absorbers, catalysts, interfacial passivation, and contact layers. To date, no competitive system has emerged due to a lack of scientific understanding, knowledge‐based design rules, and scalable engineering strategies. Herein, competitive artificial leaf devices for water splitting, focusing on multiabsorber structures to achieve solar‐to‐hydrogen conversion efficiencies exceeding 15%, are discussed. A key challenge is integrating photovoltaic and electrochemical functionalities in a single device. Additionally, optimal electrocatalysts for intermittent operation at photocurrent densities of 10–20 mA cm−2 must be immobilized on the absorbers with specifically designed interfacial passivation and contact layers, so‐called buried junctions. This minimizes voltage and current losses and prevents corrosive side reactions. Key challenges include understanding elementary steps, identifying suitable materials, and developing synthesis and processing techniques for all integrated components. This is crucial for efficient, robust, and scalable devices. Herein, corresponding research efforts to produce green hydrogen with unassisted solar‐driven (photo‐)electrochemical devices are discussed and reported.

Analytical Thinking and its Relationship to the Performance of the Simple Response Skill in Foil Weapon for Students

The purpose of this paper is to identifying the level of analytical thinking and its relationship to the skills of response and simple response to the foil weapon for students of the College of Physical Education and Sports Sciences, University of Basra. Achieving the objectives of the research requires the use of a research method, and accordingly, the researchers used the descriptive method using the survey method .The two researchers identified the research community with the students of the third stage - College of Physical Education and Sports Sciences / University of Basra / for the academic year (2021-2022). Their number is (45) students and the two researchers chose the entire research community to represent the research sample. One of the most important results reached by the researcher is that: There is a significant correlation between the student's analytical thinking and the skills of replying and simple replying ,and the research sample individuals have a good level of analytical thinking, which helps them to perform sports skills, including fencing skills. One of the most important recommendations recommended by the researchers is that: Investing in the level of understanding shown by the research sample of the role of analytical thinking in performing skills, fencing lessons and training should include situations that encourage the use of analytical thinking ,and conducting similar studies and research on university students in Iraq.

Teichmüller Theory: Classical, Higher, Super and Quantum

Teichmüller spaces play a major role in many areas of mathematics and physical science. The subject of the conference was recent developments of Teichmüller theory with its different ramifications that include the classical, the higher, the super and the quantum aspects of the theory.

Darcy–Brinkman Model for Ternary Dusty Nanofluid Flow across Stretching/Shrinking Surface with Suction/Injection

Understanding of dusty fluids for different Brinkman numbers in porous media is limited. This study examines the Darcy–Brinkman model for two-dimensional magneto-hydrodynamic fluid flow across permeable stretching/shrinking surfaces with heat transfer. Water was considered as a conventional base fluid in which the copper (Cu), silver (Ag), and titanium dioxide (TiO2) nanoparticles were submerged in a preparation of a ternary dusty nanofluid. The governing nonlinear partial differential equations are converted to ordinary differential equations through suitable similarity conversions. Under radiation and mass transpiration, analytical solutions for stretching sheets/shrinking sheets are obtained. Several parameters are investigated, including the magnetic field, Darcy–Brinkman model, solution domain, and inverse Darcy number. The outcomes of the present article reveal that increasing the Brinkman number and inverse Darcy number decreases the velocity of the fluid and dusty phase. Increasing the magnetic field decreases the momentum of the boundary layer. Ternary dusty nanofluids have significantly improved the heat transmission process for manufacturing with applications in engineering, and biological and physical sciences. The findings of this study demonstrate that the ternary nanofluid phase’s heat and mass transpiration performance is better than the dusty phase’s performance.

Psychological Stress and Its Relationship with Academic Achievement among Students Enrolled in Sports Psychology Courses at the Faculty of Physical Education and Sport Sciences at the Hashemite University

Psychological Stress and Its Relationship with Academic Achievement among Students Enrolled in Sports Psychology Courses at the Faculty of Physical Education and Sport Sciences at the Hashemite University

Optical versus radiographic imaging and tomography: introduction to the ROADS feature issue

Optical imaging is an ancient branch of imaging dating back to thousands of years. Radiographic imaging and tomography (RadIT), including the first use of X-rays by Wilhelm Röntgen, and then, γ-rays, energetic charged particles, neutrons, etc. are about 130 years young. The synergies between optical and radiographic imaging can be cast in the framework of these building blocks: Physics, Sources, Detectors, Methods, and Data Science, as described in Appl. Opt. 61, RDS1 (2022)APOPAI0003-693510.1364/AO.455628. Optical imaging has expanded to include three-dimensional (3D) tomography (including holography), due in to part the invention of optical (including infrared) lasers. RadIT are intrinsically 3D because of the penetrating power of ionizing radiation. Both optical imaging and tomography (OIT) and RadIT are evolving into even higher dimensional regimes, such as time-resolved tomography (4D) and temporarily and spectroscopically resolved tomography (4D+). Further advances in OIT and RadIT will continue to be driven by desires for higher information yield, higher resolutions, and higher probability models with reduced uncertainties. Synergies in quantum physics, laser-driven sources, low-cost detectors, data-driven methods, automated processing of data, and artificially intelligent data acquisition protocols will be beneficial to both branches of imaging in many applications. These topics, along with an overview of the Radiography, Applied Optics, and Data Science virtual feature issue, are discussed here.

Phase transitions of civil unrest across countries and time

Phase transitions, characterized by abrupt shifts between macroscopic patterns of organization, are ubiquitous in complex systems. Despite considerable research in the physical and natural sciences, the empirical study of this phenomenon in societal systems is relatively underdeveloped. The goal of this study is to explore whether the dynamics of collective civil unrest can be plausibly characterized as a sequence of recurrent phase shifts, with each phase having measurable and identifiable latent characteristics. Building on previous efforts to characterize civil unrest as a self-organized critical system, we introduce a macro-level statistical model of civil unrest and evaluate its plausibility using a comprehensive dataset of civil unrest events in 170 countries from 1946 to 2017. Our findings demonstrate that the macro-level phase model effectively captures the characteristics of civil unrest data from diverse countries globally and that universal mechanisms may underlie certain aspects of the dynamics of civil unrest. We also introduce a scale to quantify a country’s long-term unrest per unit of time and show that civil unrest events tend to cluster geographically, with the magnitude of civil unrest concentrated in specific regions. Our approach has the potential to identify and measure phase transitions in various collective human phenomena beyond civil unrest, contributing to a better understanding of complex social systems.

Assessing the attractiveness of chemical and process facilities to terrorism using a situational crime prevention approach

As intentional attacks to industry have been on the rise in the last years, researchers and institutions put effort in addressing risks of industrial assets exposed to acts of interference. One of the key steps of security risk assessment is the evaluation of the attractiveness, i.e. determining which installation or part of it could be of interest to a potential attacker. As security concerns are intrinsically tied to human intention, attractiveness does not only depend on technical characteristics of the facility, but also on the type of threat and its geographic, economic, and socio-political context. Therefore, interdisciplinarity is among the key features of a team tasked with assessing attractiveness. This work is the result of the joint effort of Physical Sciences and Engineering experts and Social Sciences and Humanities experts, and it presents a methodology for the assessment of attractiveness of process facilities to physical terroristic attacks developed using a “terrorist thinking” approach. Technical factors such as plant layout and physical protection systems were combined with modern criminology principles (namely Situational Crime Prevention, i.e. how actors take advantage of situated opportunities to commit a crime) to obtain a comprehensive picture of the possible motives behind a physical terroristic attack to a chemical and process facility (meant as facilities where chemical substances are present and where chemical and/or physical processes occurs). The methodology was applied to a case study featuring facilities located in a critical context; a ranking among facilities was obtained, and the robustness of the results was tested through a Monte Carlo-based uncertainty analysis. The results revealed that it is not possible to obtain a clear ranking of critical facilities accounting only for technical or non-technical factors, but both are necessary. The method developed was demonstrated easy to apply and could be used not only by plant security managers, but also by Institutions and Governments to prioritize critical assets in threatening contexts.

To move or to be promoted: Examining the effect of promotions and academic mobility on professors' productivity and impact

AbstractPromotions and academic mobility are trajectory‐altering events in a researcher's career. This paper compiles a unique large data set and investigates publication and citation differences between two groups of researchers: the ones who are mobile and their counterparts who stay at a university with a promotion. This paper finds that mobile researchers often have a lesser productivity increase than their post‐promotion counterparts. The difference is largely driven by male professors in physical science and clinical health fields moving from more research‐intensive to less research‐intensive institutions. In contrast, the citational impact differences between the two groups are largely minimal.

Impact of activation through bodyweight vs elastic band exercises on jump capacity and dynamic strength

The aim was to analyze the effect of two activation protocols based on exercises with bodyweight and elastic bands on the improvement of muscle power. Ten male university students of Physical Activity and Sports Sciences (age: 23.1±1.5 years) randomly completed with 48 hours of recovery between sessions, a control situation without warm-up (CON) and a warm-up protocol based in bodyweight (ACA) and elastic band (ACE) exercises. After each protocol, power tests were performed in the squat and bench press with submaximal load (i.e., ~1,00m/s and ~0,79m/s, respectively) and vertical jumps without (SJ) and with countermovement (CMJ), together with a horizontal jump (SHB). Compared to CON, no improvements in strength were observed following ACA and ACE. However, significant improvements (p < 0.05) were obtained in SJ, CMJ, and SHB after ACE, while ACA only improved (p < 0.05) SJ and CMJ. Protocols that use exercises with bodyweight or elastic bands can improve performance in actions without load, but do not improve power at submaximal loads.

Computing N-dimensional polytrope via power series

Abstract Polytropic equations (Lane–Emden [LE] equations) are valuable because they offer a simple explanation for a star’s interior structure, interstellar matter, molecular clouds, and even spiral arms that can be calculated and used to estimate various physical parameters. Many analytical and numerical methods are used to solve the polytropic LE equation. The series expansion method played an essential role in many areas of science and has found application in many branches of physical science. This work uses the series expansion method to examine N-dimensional polytropes (i.e., slab, cylinder, and sphere). To solve LE-type equations, a computational method based on accelerated series expansion (ASE) is applied. We calculate several models for the N-dimensional polytropes. The numerical results show good agreement between the ASE and numerical and analytical models of the N-dimensional polytropes.

Public research funding and science-based innovation: An analysis of ERC research grants, publications and patents

Abstract This study aims to advance the discussion around the linkages between public funding for scientific research and new technology development. We develop and test a methodology that matches patents to scientific publications, the latter of which stemming from publicly funded research. We specifically focus on projects that were funded by the European Research Council (ERC) in the Life Sciences and Physical Science and Engineering sectors during the FP7 Programme. We also compare this method’s results with the patents directly reported by the PIs of ERC-funded projects at the end of their grants, finding that the two methods are complementary. In addition to documenting important technological diffusion effects generated by ERC-funded research, our results highlight some factors that shape the relationships between patents, publications, and grants, such as project type, age, duration, scientific domain and number and quality of associated publications. Therefore, our findings present significant policy implications for funding agencies, universities, TTOs, and policymakers who want to monitor the technological outcomes of public research investments.

Bayesian Mechanistic Inference, Statistical Mechanics, and a New Era for Monte Carlo.

On the one hand, much of computational chemistry is concerned with "bottom-up" calculations which elucidate observable behavior starting from exact or approximated physical laws, a paradigm exemplified by typical quantum mechanical calculations and molecular dynamics simulations. On the other hand, "top down" computations aiming to formulate mathematical models consistent with observed data, e.g., parametrizing force fields, binding or kinetic models, have been of interest for decades but recently have grown in sophistication with the use of Bayesian inference (BI). Standard BI provides an estimation of parameter values, uncertainties, and correlations among parameters. Used for "model selection," BI can also distinguish between model structures such as the presence or absence of individual states and transitions. Fortunately for physical scientists, BI can be formulated within a statistical mechanics framework, and indeed, BI has led to a resurgence of interest in Monte Carlo (MC) algorithms, many of which have been directly adapted from or inspired by physical strategies. Certain MC algorithms─notably procedures using an "infinite temperature" reference state─can be successful in a 5-20 parameter BI context which would be unworkable in molecular spaces of 103 coordinates and more. This Review provides a pedagogical introduction to BI and reviews key aspects of BI through a physical lens, setting the computations in terms of energy landscapes and free energy calculations and describing promising sampling algorithms. Statistical mechanics and basic probability theory also provide a reference for understanding intrinsic limitations of Bayesian inference with regard to model selection and the choice of priors.

Cognitive Regulation and Its Influence on the Performance of Volleyball Serve Skill

This study aims to identify the level of cognitive regulation and the level of serve skill performance among female students, and to identify the relationship, contribution and impact of cognitive regulation to the performance of their serve skill. This descriptive correlational study targeted sophomores at the College of Physical Education and Sports Sciences for Girls/University of Baghdad. The study included a purposive sample of (32)،. Participants’ opinions were surveyed using the cognitive regulation scale in volleyball for female students then skillfully testing then using the performance of serve skill considering their accomplishment of learning performing such a skill in their academic courses. Data were analyzed using the statistical package for social science (SPSS) to be the conclusions and recommendations that the level of cognitive regulation among students of the College of Physical Education and Sports Sciences for Girls was acceptable, as well as the performance of their serve skill was acceptable, and that cognitive regulation relates, contributes, and positively affects the performance of serve skill among the study participants. It is necessary to pay attention to mental measurement when teaching the serve skill, especially cognitive regulation owing to its positive role in the performance of this skill. It is also necessary to increase the teachers’ experience with the importance of paying attention to improving the level of cognitive regulation of students, as this awareness is reflected in the positives in achieving the goals of improving performance in the physical education lesson for volleyball

اثر انموذج بيركنز- بلايث في التفكير التحليلي وتعلم مهارة استقبال الارسال لدى طلاب كلية التربية البدنية وعلوم الرياضة جامعة واسط

The Perkins-Blythe model is one of the models that brings great benefit to students by encouraging, exciting, and motivating them to be cooperative in groups. The importance of the research was highlighted in the research based on the Perkins-Blythe model in analytical thinking and learning the skill of receiving the serve among students of the second stage. The aim of the research was to prepare educational units using the Perkins-Blythe model for the skill of receiving the serve in volleyball and to identify the effect of the Perkins-Blythe model on analytical thinking and the skill of receiving. Serving volleyball for second stage students. The research also aimed to prepare a measure of analytical thinking for the students of the second stage of the College of Physical Education and Sports Sciences, University of Wasit. The researchers adopted the experimental method for the two equal groups, the experimental and the control, and the boundaries of the research community were represented by the students of the second stage of the College of Physical Education and Sports Sciences, University of Wasit, for morning study continuing in the academic year (2023-2024). The number of students was (185) and they were divided into the exploratory sample, which numbered (10) students, and (24) students for the main research sample, divided into two groups: the experimental group, which numbered (12) students, and the control group, which numbered (12) students. As for the sample numbers, it was (100) students, and the remaining ones were excluded. The researchers concluded that the Perkins-Blythe model has a positive impact on analytical thinking and learning the skill of receiving a volleyball serve. Also, applying the steps of the Perkins-Blythe model is appropriate for the students’ mental and physical abilities, as well as generating desire and motivation in them. Active participation in analytical thinking and learning the skill of receiving a volleyball serve. The researchers recommended emphasizing raising the level of students with sufficient cognitive information when learning the practical, applied aspect, and urging teachers to diversify teaching methods for everything new by employing modern models, including the Perkins-Blythe model in teaching volleyball to students. Adopting the analytical thinking scale prepared by researchers in educational centers, Ministry of Education schools, and colleges of physical education and sports sciences.

Literature Classification and its Applications in Condensed Matter Physics and Materials Science by Natural Language Process

Abstract The exponential growth of literature is constraining researchers’ access to comprehensive information in related fields. While natural language processing (NLP) may offer an effective solution to literature classification, it remains hindered by the lack of labelled dataset. In this article, we introduce a novel method for generating literature classification models through semi-supervised learning, which can generate labelled dataset iteratively with limited human input. We apply this method to train NLP models for classifying literatures related with several research directions, namely battery, superconductor, topological material, and artificial intelligence (AI) in materials science. The trained NLP ‘battery’ model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738, which indicates the accuracy and reliability of this scheme. Furthermore, our approach demonstrates that even with insufficient data, the not-well-trained model at first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.