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Machine-learning (ML)-based interatomic potentials are increasingly popular in material modeling, enabling highly accurate simulations with thousands and millions of atoms. However, the performance of machine-learned potentials depends strongly on the choice of hyperparameters—that is, of those parameters that are set before the model encounters data. This problem is particularly acute where hyperparameters have no intuitive physical interpretation and where the corresponding optimization space is large. Here, we describe an openly available Python package that facilitates hyperparameter optimization across different ML potential fitting frameworks. We discuss methodological aspects relating to the optimization itself and to the selection of validation data, and we show example applications. We expect this package to become part of a wider computational framework to speed up the mainstream adaptation of ML potentials in the physical sciences. [ABSTRACT FROM AUTHOR]

The article focuses on the impact of climate change on rising global temperatures and the consequent increase in heat waves, attributing these changes to human activity. It discusses the alarming rise in heat-related deaths and the need for policies to mitigate risks and enhance community resilience to extreme heat, emphasizing the importance of understanding the health effects of heat exposure for informing patient care and broader strategies for adaptation.

The primary objective of this article is to construct novel solitary wave solutions for the nonlinear (3+1)-dimensional modified Korteweg-de Vries-Zakharov-Kuznetsov equation with a conformable derivative by employing the subsidiary ordinary differential equation method and 1 φ (ς) , φ ′ (ς) φ (ς) method. The solutions obtained encompass diverse bright, dark, singular, and periodic solitary waves. Additionally, the article thoroughly discusses the sufficient conditions for the existence of these solutions. To visually represent the obtained solutions, we include 2D and 3D graphical images using the computational software Maple 18. We also included a comparison of fractional derivatives at different values of fractional order and conducted an analysis to understand the influence of nonlinear parameters on wave behaviors. The significance of these solutions lies in their wide-ranging applications in applied sciences and mathematical physics. Furthermore, the proposed methods are invaluable in efficiently solving nonlinear partial differential equations prevalent in engineering and physical science. [ABSTRACT FROM AUTHOR]

This document discusses a new method for preparing thin sections of bones for histomorphological study. The method addresses issues with the conventional method, such as post-mortem stains and birefringence of the epoxy resin. It provides detailed protocols for sample preparation, removal of pigment and epoxy resin, and evaluation of section quality. The authors recommend using (poly-) methyl methacrylate instead of epoxy resin for embedding fragile bones. The document also includes a list of references that cover various topics in bone histology and paleontology, which may be useful for researchers in these fields. [Extracted from the article]

The present article examines the micropolar fluid flow with nanofluid suspension across porous stretching/shrinking surfaces with added heat transfer through heat source/sink and radiation. The situation arises in the electrolytic fluid flow across fuel-cell membranes in advanced batteries or fuel cells. To understand the flows and the efficacy of the fuel cell, we study the fluid dynamics of the flow across such shrinking/stretching membranes by converting the non-dimensional governing partial differential equations to ordinary differential equations by using suitable similarity transforms. The energy equation is then analytically solved using hypergeometric series. It is noted that there is a lack of study on nanofluids in the circumstances of micropolar and radiation with porous media. The novelty of the present problem is to examine the influence of micropolar nanofluid flow with heat transfer over permeable surfaces. Analyses show that increasing the rate of shrinking/stretching boundary and increasing the Darcy number decreases the velocity of the fluid while increasing the Eringen number decreases the skin friction decreases dramatically, and increasing the thermal radiation and heat source/sink parameters enhances the thermal boundary layer. Other variations of parameters are also studied and explained graphically. The current work has many useful implications in efficient fuel-cell developments, developing nanofluid has significantly improved the heat transmission process for manufacturing with applications in engineering, biological, and physical sciences. • The present article studies the micropolar nanofluid flow across porous surfaces. • Heat transfer was studied by adding radiation to the energy equation. • Temperature increases due to rising the values of volume fraction. • Momentum and energy equations contain velocity slip and temperature jump boundary conditions. • Both momentum and energy equations are solved analytically. [ABSTRACT FROM AUTHOR]

This article presents a study on the synthesis of pyrido[1,2-a:4,3-b']diindoles through a ruthenium-catalyzed coupling/cyclization reaction. The researchers investigated the reaction conditions and found that electron-donating groups and certain substitutions on the indole ring were well tolerated, resulting in good yields of the desired products. The proposed reaction pathway involves the formation of a ruthenacycle intermediate, followed by the insertion of a sulfur ylide and subsequent cyclization. The authors suggest that these pyrido[1,2-a:4,3-b']diindole derivatives may have potential pharmaceutical applications. [Extracted from the article]

Background: Internal and external fixation are common surgical procedures for treating fractures. However, the impact of different surgical approaches (including internal and external fixations) on patients' psychological status and Quality of Life (QoL) is rarely examined. Herein, we aimed to investigate the effects of internal and external fixation on anxiety, depression, insomnia, and overall mental and physical health in Distal Radius Fractures (DRF) patients. Methods: We performed a retrospective study on 96 fracture patients who underwent internal fixation (57 patients) or external fixation (39 patients). The Visual Analog Scale (VAS), the Hospital Anxiety and Depression Scale (HADS), the Athens Insomnia Scale (AIS), and the Medical Outcomes Study Short Form 36 (SF-36) questionnaire were used to assess the patients' pain, anxiety, depression, sleep, and QoL before surgery and at seven days, one month, and three months post-surgery. Results: The VAS scores were significantly lower in the Internal Fixation Group (IFG) than in the External Fixation Group (EFG) on the seventh day and one month postoperatively (P < 0.05). Although both groups showed no significant anxiety, depression, or insomnia before surgery (P > 0.05), the EFG showed significantly higher HADS-A, HADS-D, and AIS scores than the IFG at seven days and one and three months postoperatively (P < 0.05). Additionally, changes in HADS-A, HADS-D, and AIS scores were most significant at day seven post-surgery in the EFG (P < 0.05). Furthermore, no significant difference was found between the two groups in the average Physical Component Summary (PCS) and Mental Component Summary (MCS) scores before surgery (P > 0.05). However, both groups showed positive changes in PCS and MCS scores at postoperative day seven and one and three months postoperatively, with the IFG having significantly higher average PCS and MCS scores compared to the EFG (P < 0.05). Conclusion: Compared to external fixation, internal fixation did not significantly impact patients' emotions regarding anxiety and depression in the early postoperative period, and physical and mental health recovery was better during the postoperative rehabilitation period. Furthermore, when there are no absolute indications, the impact on patients' psychological well-being should be considered as one of the key factors in the treatment plan during surgical approach selection. [ABSTRACT FROM AUTHOR]

The article focuses on supported atomically dispersed palladium (Pd) catalysis for direct alkoxylation and allylic alkylation, emphasizing the catalyst's efficiency and unique mechanism. It discusses the utilization of atomically dispersed Pd on titanium dioxide (TiO2) nanosheets for direct allylic alkylation from allylic alcohols, highlighting the role of hydrogen bonding at the organic-inorganic interface in facilitating the reaction.

This study presents and explains the phenomenon of indexjacking, which involves the systematic infiltration of hijacked journals into international indexing databases, with Scopus being one of the most infiltrated among these databases. Through an analysis of known lists of hijacked journals, the study identified at least 67 hijacked journals that have penetrated Scopus since 2013. Of these, 33 journals indexed unauthorized content in Scopus and 23 compromised the homepage link in the journal's profile, while 11 did both. As of September 2023, 41 hijacked journals are still compromising the data of legitimate journals in Scopus. The presence of hijacked journals in Scopus is a challenge for scientific integrity due to the legitimization of unreliable papers that have not undergone peer review and compromises the quality of the Scopus database. The presence of hijacked journals in Scopus has far‐reaching effects. Papers published in these journals may be cited, and unauthorized content from these journals in Scopus is thus imported into other databases, including ORCID and the WHO COVID‐19 Research Database. This poses a particular challenge for research evaluation in those countries, where cloned versions of approved journals may be used to acquire publications and verifying their authenticity can be difficult. [ABSTRACT FROM AUTHOR]

This article explores the development of new nucleoside analogues for treating viral infections and cancer. Specifically, it focuses on fluorinated carbocyclic systems, which have shown promise in medicinal and biological chemistry. The authors discuss the synthesis of various analogues with unsaturation and stereoinversion, as well as different reaction methods. The article also highlights the relevance of nucleoside analogues in the context of the COVID-19 pandemic and the development of mRNA vaccines and antiviral medications. The researchers successfully synthesized a small library of fluorinated carbocyclic nucleoside analogues, achieving C2'-C3' unsaturation using Corey-Winter or Eastwood olefination. They also discovered an unusual C1'-C2' alkene scaffold as a side-product, enabling the synthesis of a 1',2'-didehydro 6'-fluorinated carbauridine and carbacytidine. NMR data was used to investigate the conformations of the analogues in solution, revealing that C2'-C3' unsaturation favored a 6'-endo envelope conformation. Biological evaluation of these nucleoside motifs is currently ongoing. [Extracted from the article]

This research analyzed the state of metacognition in South African Physical Science classrooms, the extent to which South African Physical Science teachers possess metacognitive awareness, and how effective the teachers are in fostering metacognition. Assessment of the current state of metacognition in a sample of Physical Science classes at two KwaZulu-Natal districts, inferring the observed and analyzed level of metacognition of the participants, was based on the assumption that low levels of metacognitive awareness was the reason for achieved poor results. The major findings of this research found; there is a poor state of metacognitive awareness within the studied Physical Science classrooms. [ABSTRACT FROM AUTHOR]

Physical fitness self-concept (PFSC) is an important predictor of motivation and physical activity in children. Recent studies revealed that not only PFSC but also its interplay with perceptions of one's ideal and ought physical fitness self are related to motivation and physical activity. As the meaning of ideal and ought selves in children is yet unclear, this study aimed to investigate how PFSC, ideal physical fitness self, and ought physical fitness self are related to children's motivation and physical activity. Six hundred forty-five children (Mage = 8.87 years) filled out questionnaires twice with an interval of approximately 8 months. Polynomial regression with response surface analyses and mediation analyses was conducted. Results showed that PFSC, rather than ideal and ought self-perceptions, is associated with autonomous motivation, self-efficacy, and physical activity. The relationship between PFSC and physical activity was mediated by self-efficacy. Findings indicate that physical activity promotion programs should include PFSC and self-efficacy enhancement in childhood. [ABSTRACT FROM AUTHOR]

Marine cloud brightening (MCB) is the deliberate injection of aerosol particles into shallow marine clouds to increase their reflection of solar radiation and reduce the amount of energy absorbed by the climate system. From the physical science perspective, the consensus of a broad international group of scientists is that the viability of MCB will ultimately depend on whether observations and models can robustly assess the scale-up of local-to-global brightening in today's climate and identify strategies that will ensure an equitable geographical distribution of the benefits and risks associated with projected regional changes in temperature and precipitation. To address the physical science knowledge gaps required to assess the societal implications of MCB, we propose a substantial and targeted program of research--field and laboratory experiments, monitoring, and numerical modeling across a range of scales. [ABSTRACT FROM AUTHOR]

The Journal of Materials Science is a reputable journal that publishes articles on various topics in materials science. It receives numerous submissions each year, which are reviewed by editors who are active researchers themselves. The journal has a strong emphasis on bio and medical materials science, as well as chemical routes to materials. The document provides summaries of the research interests and achievements of several scientists in the field, including Catalin Croitoru, Yi (David) Ju, Steven E. Naleway, Ghanshyam Pilania, Subha Narayan Rath, and Annela M. Seddon. The summaries highlight their contributions to the field, including their research focus, affiliations, publications, and awards. This resource is designed to assist library patrons in determining whether they would like to explore these scientists' work further. [Extracted from the article]

This document features essays from five women in the field of microscopy, each sharing their unique experiences and perspectives. The essays cover topics such as the challenges faced in academia, the importance of diversity and inclusion in STEM fields, the role of mentorship in career development, and the advancements made by women in leadership positions. The document provides valuable insights into the experiences of women in microscopy and emphasizes the significance of representation and support in the field. Additionally, it highlights the achievements and contributions of three individuals who have made significant impacts in the field of microscopy. [Extracted from the article]

This scientific commentary discusses the importance of understanding carbon source-sink dynamics in masting tree species, particularly in the context of climate change and drought stress. The authors examine the responses of carbon allocation to environmental constraints in stone pine stands, focusing on reproductive effort, radial growth, and tree-ring isotope composition. They find evidence of a shift from sink-limited to source- and sink-co-limited reproduction, suggesting diminishing carbon resources due to drought stress. However, caution is needed in interpreting the data, and further research is necessary to fully understand carbon allocation in trees. [Extracted from the article]

In this essay, I argue that modern science can function as a source of "sacred reminders" for aspects of Christian theology, like the doctrine of the Trinity, that are not normally engaged with in the empirical world. This approach is an alternative to the usual ways of relating scientific and theological endeavors in terms of conflict, separation, or consonance. I demonstrate this by beginning with the thoughts of two representative physicists (John Archibald Wheeler and Steven Hawking), particularly focusing on a fundamental distinction they make about the underlying ideal of the physical sciences. Noting a striking similarity of this distinction with some of the biblical imagery of God's Word and Spirit, I review biblical texts along these lines to show partial continuity with the groundbreaking ideas of our physicists, and to show how they can be generalized to include (a) levels of organization beyond those of physics; (b) intensive, localized agencies of Word and Spirit as well as the more extensive agencies suggested their ideas; and (c) the commissioning agency of God the Father. A review of the theology of Irenaeus shows that these distinctions in biblical imagery were developed in the early Church and played an important role in early Trinitarian theology. [ABSTRACT FROM AUTHOR]

We consider a stochastic, dynamic runway scheduling problem involving aircraft landings on a single runway. Sequencing decisions are made with knowledge of the estimated arrival times (ETAs) of all aircraft due to arrive at the airport, and these ETAs vary according to continuous-time stochastic processes. Time separations between consecutive runway landings are modeled via sequence-dependent Erlang distributions and are affected by weather conditions, which also evolve continuously over time. The resulting multistage optimization problem is intractable using exact methods, and we propose a novel simheuristic approach based on the application of methods analogous to variable neighborhood search in a high-dimensional stochastic environment. Our model is calibrated using flight tracking data for over 98,000 arrivals at Heathrow Airport. Results from numerical experiments indicate that our proposed simheuristic algorithm outperforms an alternative based on deterministic forecasts under a wide range of parameter values, with the largest benefits seen when the underlying stochastic processes become more volatile and also when the on-time requirements of individual flights are given greater weight in the objective function. Funding: This work was supported by the Engineering and Physical Sciences Research Council [Grant EP/M020258/1]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/trsc.2022.0400. [ABSTRACT FROM AUTHOR]

Physical laws manifest themselves through the amalgamation of mathematical symbols, numbers, functions, geometries, and relationships. These intricate combinations unfold within a mathematical model devised to capture and represent the "objective reality" of the system under examination. In this symbiotic relationship between physics and mathematics, the language of mathematics becomes a powerful tool for describing and predicting the behavior of the physical world. The language used and the associated concepts are in a perpetual state of evolution, mirroring the ongoing expansion of the phenomena accessible to our scientific understanding. In this contribution, written in honor of Richard Kerner, we delve into fundamental, at times seemingly elementary, elements of the mathematical language inherent to the physical sciences, guided by the overarching principles of symmetry and group theory. Our focus turns to the captivating realm of spheres, those strikingly symmetric entities that manifest prominently within our geometric landscape. By exploring the interplay between mathematical abstraction and the tangible beauty of symmetry, we seek to deepen our understanding of the underlying structures that govern our interpretation of the physical world. [ABSTRACT FROM AUTHOR]

The article discusses the role of physics in logical empiricism, a philosophical movement that was primarily concerned with the philosophy of science. The editors of the volume argue that there has been relatively little research on the logical empiricists' philosophy of the natural sciences, particularly physics. The volume aims to explore the traditions, methods, concepts, and ideas that influenced the logical empiricists' philosophy of physics, as well as their various and sometimes contradictory ideas about the physical sciences. While the volume contains some interesting insights, it also has some flaws, such as a lack of unity and contextualization in certain chapters. Overall, the volume may be valuable for experts in the field, but may not be the best starting point for those unfamiliar with logical empiricism. [Extracted from the article]

This document is a correction to the supporting information for an article on the preservation of cellulose in ancient textiles. The authors note an error in Table S2, which has been corrected online. The article discusses the analysis of fibers from archaeological sites in Turkmenistan, Pakistan, and Iraq using synchrotron X-ray microtomography and μ-FTIR spectroscopy. The document provides technical information about the methods and equipment used in the study, including second-harmonic generation microscopy and energy-dispersive X-ray spectroscopy. It also includes tables and figures related to the analysis of compounds found in archaeological contexts, specifically copper artifacts from Nausharo and Tello. The information can be helpful for researchers studying similar topics. [Extracted from the article]

Teaching physical sciences presents a significant challenge in various countries, including Morocco, where student performance remains a subject of concern. This study aims to investigate the impact of introducing educational robotics as compared to computer-assisted experiments (EXAO) on students' motivation and learning in physical sciences. We divided a group of 120 middle-school students into two cohorts: one used the cost-effective educational robot, EducThermoBot, as an experimental group, while the other employed traditional EXAO as a control group. The findings demonstrate that the integration of educational robotics has a noteworthy and positive impact on students' motivation, whereas the overall academic performance exhibited no significant disparities between the two cohorts. Notwithstanding some limitations, this research offers valuable insights to enhance pedagogical practices by promoting the integration of educational robotics into the teaching of physical sciences in Morocco. [ABSTRACT FROM AUTHOR]

Recent work in science education has emphasized the importance of the conceptual, social, and epistemic dimensions in science learning. But what about the material dimension—the actual physical materials that students use? The way their characteristics and affordances limit or determine instruction has thus far not been as thoroughly explored. Despite the vast body of work that exists on science and engineering practices, there are relatively few examples of how physical science materials are linked to and can support engagement with such practices for sensemaking. In this paper, we propose a framework for analyzing the design of these physical materials and the activities associated with them that can serve as lenses for educators and researchers to consider when planning and reflecting on classroom instruction. To validate our framework, we apply it to analyze activities developed and implemented by teachers during a four-year research-practice partnership project conducted in a city in Brazil, and investigate potential connections between the design of physical materials and students' epistemic agency. We conclude with recommendations for the development of physical resources in labs and makerspaces for science learning. [ABSTRACT FROM AUTHOR]

The problem of computing the rate of diffusion-aided activated barrier crossings between metastable states is one of broad relevance in physical sciences. The transition path formalism aims to compute the rate of these events by analysing the statistical properties of the transition path between the two metastable regions concerned. In this paper, we show that the transition path process is a unique solution to an associated stochastic differential equation, with a discontinuous and singular drift term. The singularity arises from a local time contribution, which accounts for the fluctuations at the boundaries of the metastable regions. The presence of fluctuations at the local time scale calls for an excursion theoretic consideration of barrier crossing events. We show that the rate of such events, as computed from excursion theory, factorizes into a local time term and an excursion measure term, which bears empirical similarity to the transition state theory rate expression. Since excursion theory makes no assumption about the presence of a transition state in the potential energy landscape, the mathematical structure underlying this factorization ought to be general. We hence expect excursion theory (and local times) to provide some physical and mathematical insights in generic barrier crossing problems. [ABSTRACT FROM AUTHOR]

"Joel D. Hamkins.Lectures on the Philosophy of Mathematics" is an introductory textbook written by a prominent set theorist. The book covers both mathematical and philosophical material, combining interesting mathematical material with discussions of philosophical issues. While the book may cover too much mathematical material for some readers, it could be of great interest to students studying a combination of math and philosophy. The book is divided into chapters on Number, Rigor, Infinity, Geometry, Proof, Computability, Incompleteness, and Set theory, with the chapters on Number and Set theory being the longest. The author often adopts a lecturing attitude, introducing key ideas but leaving the issues open for further exploration. The book also discusses the ontological controversy between the universe and multiverse views in set theory, with the author presenting arguments for the multiverse view. Overall, the book provides a wide and ambitious coverage of the philosophy of mathematics, although some readers may find certain topics could have been presented in a different light or more carefully. [Extracted from the article]

Rietveld refinements are widely used for many purposes in the physical sciences. Conducting a Rietveld refinement typically requires expert input because correct results may require that parameters be added to the fit in the proper order. This order will depend on the nature of the data and the initial parameter values. A mechanism for computing the next parameter to add to the refinement is shown. The fitting function is evaluated with the current parameter value set and each parameter incremented and decremented by a small offset. This provides the partial derivatives with respect to each parameter, along with information to discriminate meaningful values from numerical computational errors. The implementation of this mechanism in the open‐source GSAS‐II program is discussed. This new method is discussed as an important step towards the development of automated Rietveld refinement technology. [ABSTRACT FROM AUTHOR]

Unlike in controlled settings, social scientists' performance when predicting real-world societal trends is indistinguishable from that of laypeople or naive statistical methods. There is no conclusive evidence that domain-specific expertise improves predictive accuracy of societal change. Causal models in social sciences are oversimplified, confusing levels of analysis, and generally lack specificity about the magnitude or distribution of effects, limiting prediction accuracy. Engaging in counterfactual thought experiments to go beyond the most obvious factors specified in a theory, predictive accuracy in social sciences can be improved. Integrating broad foundational models with context-specific time series data, as in meteorology, can enhance the accuracy of social science predictions. Enhancing analytical training and understanding of temporal dynamics can yield more precise, riskier predictions, the practical application of which requires the fostering of intellectual humility in scientists. We examine the opportunities and challenges of expert judgment in the social sciences, scrutinizing the way social scientists make predictions. While social scientists show above-chance accuracy in predicting laboratory-based phenomena, they often struggle to predict real-world societal changes. We argue that most causal models used in social sciences are oversimplified, confuse levels of analysis to which a model applies, misalign the nature of the model with the nature of the phenomena, and fail to consider factors beyond the scientist's pet theory. Taking cues from physical sciences and meteorology, we advocate an approach that integrates broad foundational models with context-specific time series data. We call for a shift in the social sciences towards more precise, daring predictions and greater intellectual humility. [ABSTRACT FROM AUTHOR]

The simplified modified Camassa Holm (SMCH) equation is an essential nonlinear model for classifying several wave phenomena in physical science. In this study, the new m + 1 / G ′ -expansion method has been applied to the SMCH equation. Based on the given method, we have obtained some typical analytical solutions, such as exponential and rational function and complex function solutions of the SMCH equation. The three-dimensional and contour graphs of the obtained results are drawn for appropriate values of parameters. Getting the results and graphic drawings have been made using the Wolfram Mathematica. All the obtained solutions are crucial for understanding the nonlinear phenomena of dispersive waves. The solutions have shown that the presented method is powerful, practical, and suitable for investigating nonlinear models. [ABSTRACT FROM AUTHOR]

Numerous variations of cognitive challenges, such as those in fluid mechanics, plasma physics and nonlinear optics as well as in engineering and mathematics, involve nonlinear partial differential equations. In this study, we explore the (3+1)-dimensional generalized Yu–Toda–Sasa–Fukuyama (YTSF) equation with application in engineering and physical science. Three (1+1)-dimensional nonlinear partial differential equations can be acquired from the YTSF equation. Using a N-fold Darboux transformation technique of Lax pair to obtain the multi-soliton, resonant and complex soliton solutions of the equation. Also, by showing the solutions graphically, the completeness of the outcome was confirmed. The conclusions in this study might be useful for understanding the soliton solutions in mathematics and physics. [ABSTRACT FROM AUTHOR]

Manifold visualisation techniques are commonly used to visualise high-dimensional datasets in physical sciences. In this paper, we apply a recently introduced manifold visualisation method, slisemap, on datasets from physics and chemistry. slisemap combines manifold visualisation with explainable artificial intelligence. Explainable artificial intelligence investigates the decision processes of black box machine learning models and complex simulators. With slisemap, we find an embedding such that data items with similar local explanations are grouped together. Hence, slisemap gives us an overview of the different behaviours of a black box model, where the patterns in the embedding reflect a target property. In this paper, we show how slisemap can be used and evaluated on physical data and that it is helpful in finding meaningful information on classification and regression models trained on these datasets. [ABSTRACT FROM AUTHOR]

This document provides a summary of a special issue on smart sensors for structural health monitoring (SHM) and nondestructive evaluation (NDE). It discusses the importance of developing defect detection and monitoring techniques for structures to ensure their integrity and prevent failure. The document highlights the challenges faced in implementing SHM and NDE, as well as the various techniques and smart sensors used in these fields. It also provides an overview of 33 papers published in the special issue, covering topics such as sensor technology, signal processing, and field applications. The authors hope that these papers will inspire future research in these rapidly developing areas. [Extracted from the article]

Understanding symmetry-breaking states of materials is a major challenge in the modern physical sciences. Quantum atmosphere proposed recently sheds light on the hidden world of these symmetry broken patterns. Yet, no experiment has been performed to demonstrate its potential. In our experiment, we prepare time-reversal-symmetry conserved and broken quantum atmosphere of a single nuclear spin and successfully observe their symmetry properties. Our work proves in principle that finding symmetry patterns from quantum atmosphere is conceptually viable. It also opens up entirely new possibilities in the potential application of quantum sensing in material diagnosis. [ABSTRACT FROM AUTHOR]

The book "Dual-Aspect Monism and the Deep Structure of Meaning" by Atmanspacher and Rickles delves into the connection between the mind and the material world, specifically focusing on Jung's concept of the Unus Mundus, archetypes, and synchronicity. The authors argue that this concept extends beyond the collaboration between Jung and Pauli and applies to other influential figures in quantum theory. Divided into three parts, the book covers the philosophical background, theories of meaning, and three approaches to quantum theory. While it requires a solid understanding of quantum theory, the book offers profound insights into the nature of the psyche and the implications of quantum theory. The text also explores the Pauli/Jung Conjecture, which examines the relationship between psychology and quantum physics. The authors propose a dual-aspect monism framework, where the psycho-physically neutral base separates into mental and physical states that are structurally correlated, with archetypal patterns forming the foundation of this correlation. The text further delves into the implications of this conjecture for analytical psychology, synchronicity, and the nature of meaning in the world. [Extracted from the article]

The current manuscript investigates a model of the spread of polio under the condition of vaccination by using the novel modified Atangana-Baleanu-Caputo (mABC) fractional derivative. This problem has been studied for non-zero solutions under the modified operator. The series-type solution has been obtained through the application of a Laplace transformation, along with the decomposition technique and Adomian polynomial for the nonlinear terms. The qualitative analysis for the solution of the model has been tested by using fixed point theory. The stability of the solution is also crucial for a dynamical system; therefore, it was checked by using the T-Picard method. With the help of the approximate scheme, numerical simulations were conducted for the proposed model by using different fractional orders and transmission parameters. Based on the obtained positivity of the solutions and numerical stability, we have established the analysis of the mABC operator in the field of fractional calculus and other physical sciences. [ABSTRACT FROM AUTHOR]

The Bowei Research Conference (BRC) series, established by Mr. Bowei Lee in Taiwan, provides a platform for young scientists, postdoctoral fellows, and graduate students to network and exchange ideas. The article highlights past conferences, such as BRC-2 and BRC-3, and the upcoming BRC-4 conference with the theme "The Magic of Synthesis - New Frontiers of Molecular Architecture." The LCY Group and the LCY Education Foundation organize and sponsor the BRC series. The opening ceremony of BRC-4 featured distinguished guests, a buffet dinner, and traditional Chinese music, emphasizing the importance of chemistry in solving global challenges and promoting innovation. Keynote lectures covered topics like sustainable chemistry, natural product synthesis, and molecular machines, providing valuable insights into advancements in the field. The conference also included a poster session and retreat activities, and the next conference, BRC-5, will focus on "The Magic of Chemical Biology." [Extracted from the article]

Looking towards the future, what STEM skills will be most important for students? Going beyond memorization and recitation of scientific facts, how do we get students to fully engage in science and engineering design practices (as defined in the Next Generation Science Standards) and to improve their science literacy? The answers to these questions are at the heart of the "Learning by Making" (LbyM) experience. LbyM is an innovative, integrated year-long curriculum that includes skill building units that teach coding and how to build simple electronic circuits. Using a simple browser-based interface, LbyM students are able to easily write code, control LED lights and acquire and analyze sensor data within the overarching theme of energy and matter. Rather than being siloed in pre-engineering courses, these important STEM skills are developed within the context of a physical science class. By engaging in phenomena-based explorations, LbyM develops students' self-efficacy, and ability to work in teams to gather environmental data relevant to their communities and critical to the future of our planet. [ABSTRACT FROM AUTHOR]

Physics-based and first-principles models pervade the engineering and physical sciences, allowing for the ability to model the dynamics of complex systems with a prescribed accuracy. The approximations used in deriving governing equations often result in discrepancies between the model and sensor-based measurements of the system, revealing the approximate nature of the equations and/or the signal-to-noise ratio of the sensor itself. In modern dynamical systems, such discrepancies between model and measurement can lead to poor quantification, often undermining the ability to produce accurate and precise control algorithms. We introduce a discrepancy modeling framework to identify the missing physics and resolve the model-measurement mismatch with two distinct approaches: (i) by learning a model for the evolution of systematic state-space residual, and (ii) by discovering a model for the deterministic dynamical error. Regardless of approach, a common suite of data-driven model discovery methods can be used. Specifically, we use four fundamentally different methods to demonstrate the mathematical implementations of discrepancy modeling: (i) the sparse identification of nonlinear dynamics, (ii) dynamic mode decomposition, (iii) Gaussian process regression, and (iv) neural networks. The choice of method depends on one's intent (e.g., mechanistic interpretability) for discrepancy modeling, sensor measurement characteristics (e.g., quantity, quality, resolution), and constraints imposed by practical applications (e.g., state- or dynamical-space operability). We demonstrate the utility and suitability for discrepancy modeling using the suite of data-driven modeling methods on four dynamical systems under varying signal-to-noise ratios. Finally, we emphasize structural shortcomings of each discrepancy modeling approach depending on error type. In summary, if the true dynamics are unknown (i.e., an imperfect model), one should learn a discrepancy model of the missing physics in the dynamical space. Yet, if the true dynamics are known yet model-measurement mismatch still exists, one should learn a discrepancy model in the state space. [ABSTRACT FROM AUTHOR]

This article explores the concept of the Anthropocene, a term used to describe the period in which human activities have significantly impacted the Earth's environment. It discusses the "Great Acceleration," which encompasses processes like climate change, urbanization, and species extinction. The recognition of the Anthropocene as a geological unit is a topic of ongoing debate, and geographers play a crucial role in understanding and defining this concept. The article also highlights the challenges in determining the beginning of the Anthropocene and the importance of using various datasets to study the Great Acceleration. Geographers are encouraged to contribute papers that offer conceptual frameworks and solutions for addressing the challenges of the Anthropocene, with the Covid-19 pandemic serving as a template for studying this phenomenon. [Extracted from the article]

Modern trends in the development of experimental research methods imply not only an increase in the accuracy of a specific technique but also the possibility of combining diverse measurements in the course of one experiment. While optical spectroscopy remains one of the most powerful tools used in the chemical and physical sciences to study the structure of a wide range of materials, it is impossible to imagine a single study of local mechanical properties without instrumental indentation. A powerful investigation technique is the in situ combination of these two methods within one experiment. This can be made by focusing the laser either through the transparent sample or through the transparent indenter tip of the special geometry preventing the total internal reflection in diamond. This Tutorial discusses the preparation and characterization of such a transparent diamond indenter. The obtained experimental results and promising application areas of simultaneous measurement of optical spectra during indentation are considered. [ABSTRACT FROM AUTHOR]

In this manuscript, an analysis is carried out on the dynamic behavior of the ill-posed Boussinesq equation, which arises in nonlinear lattices and shallow water waves. The simplified Hirota method is employed to obtain multi-wave structures, such as one-soliton, two-soliton and three-soliton solutions. Some solutions are visually demonstrated through 3D, 2D and density plots. Furthermore, a comprehensive discussion on the stability analysis of the equation under study is presented. These results are innovative and have not been previously investigated in the context of this equation. These results show that the methodology used is concise, straightforward, and efficient, and as a result, it makes a significant contribution to comprehending the complexity of multi-wave profiles in nonlinear physical science models. [ABSTRACT FROM AUTHOR]

Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur and to make testable models that explain the phenomena. Discovering equations, laws, and principles that are invariant, robust, and causal has been fundamental in physical sciences throughout the centuries. Discoveries emerge from observing the world and, when possible, performing interventions on the system under study. With the advent of big data and data-driven methods, the fields of causal and equation discovery have developed and accelerated progress in computer science, physics, statistics, philosophy, and many applied fields. This paper reviews the concepts, methods, and relevant works on causal and equation discovery in the broad field of physics and outlines the most important challenges and promising future lines of research. We also provide a taxonomy for data-driven causal and equation discovery, point out connections, and showcase comprehensive case studies in Earth and climate sciences, fluid dynamics and mechanics, and the neurosciences. This review demonstrates that discovering fundamental laws and causal relations by observing natural phenomena is revolutionised with the efficient exploitation of observational data and simulations, modern machine learning algorithms and the combination with domain knowledge. Exciting times are ahead with many challenges and opportunities to improve our understanding of complex systems. [ABSTRACT FROM AUTHOR]

The Louisiana State University College of the Coast & Environment (LSU CC&E) developed a multi-faceted strategic initiative to increase its diversity, equity, and inclusion. Elements of this initiative began one-by-one over the last decade and were aggregated into a comprehensive implementation plan--the 2020 CC&E Diversity, Equity, and Inclusion Action Plan. Based on best practices in the "physical sciences" (i.e., geosciences, including oceanography), the plan aims to augment recruitment and retention using limited resources and personnel. The long-range goal is to increase the number of PhD graduates from underrepresented groups by employing strategies that start at the 6-12th grade level. The plan involves a change in culture, clear communications about needs and goals, and active participation and engagement of CC&E faculty, students, staff, supporters, and partners. This plan is increasing the diversity of enrollment in our academic programs and will ultimately lead to more students with both undergraduate and graduate degrees. [ABSTRACT FROM AUTHOR]

Surfaces and their descriptions are significant in design, physical science, geology, and other natural phenomena. This study introduces a neutrosophic Bézier surface approximation with a four-by-four control net for the bicubic situation. The neutrosophic notion defines the neutrosophic control net relation. The control net is mixed with the Bernstein basis function to generate a surface blending function and a neutrosophic bicubic Bézier surface. Finally, the neutrosophic bicubic Bézier surface is shown using an approximation approach and data points having neutrosophic properties. [ABSTRACT FROM AUTHOR]

Lévy processes are useful tools for analysis and modeling of jump‐diffusion processes. Such processes are commonly used in the financial and physical sciences. One approach to building new Lévy processes is through subordination, or a random time change. In this work, we discuss and examine a type of multiply subordinated Lévy process model that we term a deep variance gamma (DVG) process, including estimation and inspection methods for selecting the appropriate level of subordination given data. We perform an extensive simulation study to identify situations in which different subordination depths are identifiable and provide a rigorous theoretical result detailing the behavior of a DVG process as the levels of subordination tend to infinity. We test the model and estimation approach on a data set of intraday 1‐min cryptocurrency returns and show that our approach outperforms other state‐of‐the‐art subordinated Lévy process models. [ABSTRACT FROM AUTHOR]