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Non-reciprocal (NR) effective interactions violating Newton's third law occur in many biological systems, but can also be engineered in synthetic, colloidal systems. Recent research has shown that such NR interactions can have tremendous effects on the overall collective behavior and pattern formation, but can also influence aggregation processes on the particle scale. Here, we focus on the impact of non-reciprocity on the self-assembly of a colloidal system (originally passive) with anisotropic interactions whose character is tunable by external fields. In the absence of non-reciprocity, that is, under equilibrium conditions, the colloids form square-like and hexagonal aggregates with extremely long lifetimes yet no large-scale phase separation [Kogler et al., Soft Matter 11, 7356 (2015)], indicating kinetic trapping. Here, we study, based on Brownian dynamics simulations in 2D, an NR version of this model consisting of two species with reciprocal isotropic, but NR anisotropic interactions. We find that NR induces an effective propulsion of particle pairs and small aggregates ("active colloidal molecules") forming at the initial stages of self-assembly, an indication of the NR-induced non-equilibrium. The shape and stability of these initial clusters strongly depend on the degree of anisotropy. At longer times, we find, for weak NR interactions, large (even system-spanning) clusters where single particles can escape and enter at the boundaries, in stark contrast to the small rigid aggregates appearing at the same time in the passive case. In this sense, weak NR shortcuts the aggregation. Increasing the degree of NR (and thus, propulsion), we even observe large-scale phase separation if the interactions are weakly anisotropic. In contrast, systems with strong NR and anisotropy remain essentially disordered. Overall, the NR interactions are shown to destabilize the rigid aggregates interrupting self-assembly and phase separation in the passive case, thereby helping the system to overcome kinetic barriers. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have seen a rise in use during the last few years. Such aircrafts are now a convenient way to complete dangerous, dirty, and tedious tasks. Given that their operation involves a control problem which is non-linear and coupled, it is difficult to analyse. This paper presents the modeling and control of a fixed-wing unmanned aircraft as a contribution to this field. The system's flight dynamics is derived using Newton's second law of motion. The system is designed to have a non-linear Proportional Integral Derivative (NPID) controller and a higher-order sliding mode controller (HOSMC). When simulating the system using MATLAB Simulink software, an external disturbance was added to test the robustness of the controllers. Five performance indices which include mean square error (MSE), integral time square error (ITSE), integral absolute error (IAE), integral time absolute error (ITAE), and integral square error (ISE), were used to compare the controllers performance. These indices are used to provide a numerical assessment of the two controllers' performance. The outcomes demonstrate that the roll, pitch, and yaw states performed better than the super-twisting sliding mode controller. On the airspeed control, the non-linear PID performed better than the super-twisting sliding mode controller. [ABSTRACT FROM AUTHOR]

Thermodynamics is a fundamental topic of continuum mechanics and biomechanics, with a wide range of applications to physiological and biological processes. This study addresses two fundamental limitations of current thermodynamic treatments. First, thermodynamics tables distributed online by the U.S. National Institute of Standards and Technology (NIST) report properties of fluids as a function of absolute temperature T and absolute pressure P. These properties include mass density p, specific internal energy u, enthalpy h = u + P/p, and entropy s. However, formulations of jump conditions across phase boundaries derived from Newton's second law of motion and the first law of thermodynamics employ the gauge pressure p = P - Pr, where P, is an arbitrarily selected referential absolute pressure. Interchanging p with P is not innocuous as it alters tabulated NIST values for u while keeping h and s unchanged. Using p for functions of state and governing equations solves the problem with using NIST entries for the specific internal energy u in standard thermodynamics tables and analyses of phase transformation in continuum mechanics. Second, constitutive models for the free energy of fluids, such as water and air, are not typically provided in standard thermodynamics treatments. This study proposes a set of constitutive models and validates them against suitably modified NIST data. [ABSTRACT FROM AUTHOR]

This research proposes an analytical solution of the nano-concrete-epoxy interaction area within nano crack region of the reinforced concrete beam by applying Newton's third law in static equilibrium. For deriving the governing equation, the imaginary beam with free ends (no support) is considered within nano crack region. This imaginary beam is acted along the imaginary line of concrete-epoxy interface. Newton's third law is applicable for deriving the governing equation because of assuming the absence of frictional and other external forces. The parametric study is performed for implementing the proposed formula of nano interactive area considering variable nano crack depths and thicknesses. The nano interactive area is increased gradually with the increment of depths and thicknesses based on the parametric study because of linear functionality of interactive area and geometry of nano crack region. The maximum interactive area is found to be 314 nm2 at 0.6 ratio of depths and thicknesses of the nano crack. The incremental differences in interactive area between the crack depth or thickness ratios of 0.1 and 0.6 are found to be 25.4% and 1.6% for variations of the crack depth and thickness ratios, respectively. So, the crack depth shows higher impact on the interaction area compared to the thickness of the crack. However, there is a scope for enhancing this research in future by deriving closed-formed analytical formulations to consider appropriate boundary conditions. [ABSTRACT FROM AUTHOR]

The given text discusses different approaches to finding equations of motion for physical systems, such as the Newtonian, Lagrangian, and Hamiltonian approaches. It presents a supplementary tool using the total differential of the mechanical energy function to obtain equations of motion for certain systems. The text also explores the relationship between this approach and Hamilton's equations of motion. Additionally, the text provides concise and factual information about different types of motion and their corresponding equations, making it a useful resource for library patrons conducting research on these topics. [Extracted from the article]

This article discusses the use of 3D camera systems and accompanying software in physics instruction. The authors describe a Python program that can track and analyze the momentum of a midair collision between two playground balls. The program is freely available for instructors and can be used in student lab settings or as an instructor-led exercise. The article provides detailed information on the camera system used, the data collection and analysis process, and the results obtained. The authors conclude that the use of 3D cameras and tracking software expands the possibilities for physics experiments and enhances students' understanding of complex systems. [Extracted from the article]

Ojhung is one of the indigenous Indonesian cultures from Sumenep Regency which contains relevant science concepts to be applied in science learning. Therefore, this research aimed to identify and explore the concepts of science contained in the Ojhung tradition while evaluating their relevance to the Merdeka or national curriculum. This research uses a qualitative design with a grounded theory based on scientific concepts in the Ojhung tradition and can be applied in science learning. The concepts of science that have been successfully explored and identified are Newton's Third Law, Sound Waves, Sense of Hearing, Pressure, Flexibility, Body Muscles, Moments of Inertia, and Skin Wounds. All concepts that have been explored can actualise learning outcomes in the Merdeka Curriculum. This research implies applying science concepts to Ojhung to improve public scientific literacy and science learning in schools. [ABSTRACT FROM AUTHOR]

Phenomena-driven instruction is an effective method for addressing science misconceptions. Research has shown that simply teaching correct information does not automatically remove misconceptions, as students often revert back to their prior thinking. To create a permanent change in students' thinking, misconceptions must be directly addressed. Phenomena, which are real-world events or situations, can be used as teaching tools to engage students and help them develop a deeper understanding of concepts. By encountering phenomena that contradict their misconceptions, students can correct their thinking and gain a better understanding of scientific principles. [Extracted from the article]

Newton's third law, action = reaction, is a foundational statement of classical mechanics. However, in natural and living systems, this law appears to be routinely violated for constituents interacting in a nonequilibrium environment. Here, we use computer simulations to explore the macroscopic phase behavior implications of breaking microscopic interaction reciprocity for a simple model system. We consider a binary mixture of attractive particles and introduce a parameter that is a continuous measure of the degree to which interaction reciprocity is broken. In the reciprocal limit, the species are indistinguishable, and the system phase separates into domains with distinct densities and identical compositions. Increasing nonreciprocity is found to drive the system to explore a rich assortment of phases, including phases with strong composition asymmetries and three-phase coexistence. Many of the states induced by these forces, including traveling crystals and liquids, have no equilibrium analogs. By mapping the complete phase diagram for this model system and characterizing these unique phases, our findings offer a concrete path forward toward understanding how nonreciprocity shapes the structures found in living systems and how this might be leveraged in the design of synthetic materials. [ABSTRACT FROM AUTHOR]

Considering the harsh environment of the port, automated straddle carriers, characterized by their large size, tall frame, and high center of gravity, may experience instability during steering and transportation due to inaccurate state estimation. Thus, this paper explores state estimation techniques for automated straddle carriers utilizing smart sensors which are capable of data measurement and processing. First, using the steering principles and lateral characteristics of automated straddle carriers, a dynamic linear model is established based on Newton's second law of motion. Then, in order to enhance the reliability and flexibility of state estimation, a distributed smart sensor network structure is introduced. In addition, considering the challenge of unknown-but-bounded noise and the precision demands of the considered automated straddle carrier, a modified distributed set-membership estimation algorithm is proposed and is derived sufficient conditions for the existence of the estimation set for the considered automated straddle carriers. Finally, the effectiveness and superiority of the proposed method are demonstrated by performance analyses. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This document is a compilation of various scientific papers and preprints covering a wide range of topics, including protein folding, cell migration, machine learning, deep neural networks, neural scaling laws, representations and generalization in artificial and brain neural networks, and the neuron as a direct data-driven controller. The papers discuss different aspects of these subjects, providing a comprehensive overview of the current research in these fields. This document can be a valuable resource for library patrons conducting research on these topics, particularly in the fields of neuroscience and artificial intelligence. [Extracted from the article]

Very recently, a straightforward method was proposed to understand galaxies and galactic clusters without using the very elusive dark matter concept. This method is called the κ -model. The main idea is to maintain the form of the usual physical laws, especially Newton's laws of motion when gravity is weak, but only by applying a local scaling procedure for the related lengths, distances, and velocities. This local scaling appears as a correspondence principle in the κ -model. In this model, the fundamental physical constants remain universal, i.e., they are independent of a point in space and of time. The κ -model is Newtonian in its essence, but there is a relativistic extension that can easily be built. The aim of the present paper is to detail the mathematical formalism supporting it. [ABSTRACT FROM AUTHOR]

This article discusses the technological progress that has been made in the field of wheels and tires. It explains the evolution of wheels from wooden spokes to carbon fiber, and the transition from spoked wheels to solid wheels with hubcaps. The article also explores the development of pneumatic air-filled tires and the dangers of blowouts. It includes a class project idea for students to compare the pressure exerted by a tire on the road with the air pressure inside the tire. The article concludes with a discussion on the rotational motion of wheels and the concept of simulated gravity in rotating habitats. [Extracted from the article]

This article explores the journey of Olympic swimmers and the challenges they face in reaching the top of their sport. It emphasizes the dedication and sacrifices required, as well as the intense competition at the Olympic trials. The article also discusses how mathematics, physics, and technology have revolutionized swimming training, allowing coaches to tailor methods to individual athletes. It further examines the advancements in technology, nutrition, and biomechanics that have contributed to improved performances in Olympic sports over the past century. The article concludes by discussing changes in swimming techniques and the impact of materials science on swimwear. It also highlights the use of physics and mathematical modeling to enhance the training of elite swimmers, including the creation of "digital twins" to analyze and improve performance. The text concludes by reflecting on the impact of technology on the Olympics and the redefinition of human limits. [Extracted from the article]

The article discusses the relevance and importance of teaching physics as the study of nature's rules. The author shares personal experiences and insights into teaching physics, emphasizing the need for critical thinking skills and the appreciation of physics as an awe-inspiring subject. The article also highlights the use of questions and equations in teaching physics, as well as the significance of concepts such as Newton's second law and Einstein's equation. The author encourages educators to make science courses flavorful and awesome to engage students. [Extracted from the article]

The central conclusions of "The Gene: An Appraisal" are that genetic variance does not underpin biological evolution, and, therefore, that genes are not Mendel's units of inheritance. In this response, I will address the criticisms I have received via commentaries on that paper by defending the following statements: 1. Epistasis does not explain the power-law fitness profile of the Long-Term Evolution Experiment (LTEE). The data from the evolution of natural systems displays the power-law form ubiquitously. Epistasis plays no role in evolution. 2. The common characteristics of living things (natural systems) are described by the principle of least action in de Maupertuis's original form, which is synonymous with the 2nd law of thermodynamics and Newton's 2nd law of motion in its complete form, i.e., F = dp/dt. Organisms strive to achieve free energy balance with their environments. 3. Based on an appraisal of the scientific environment between 1880 and 1911, I conclude that Johannsen's genotype conception was perhaps, the only option available to him. 4. The power-law fitness profile of the LTEE falsifies Fisher's Genetical Theory of Natural Selection, Johannsen's genotype conception, and the idea that 'Darwinian evolution' is an exception to the generic thermodynamic process of evolution in natural systems. 5. The use of the technique of genome-wide association to identify the causes and the likelihoods of inherited common diseases and behavioural traits is a 'wild goose chase' because genes are not the units of inheritance. [ABSTRACT FROM AUTHOR]

This article by William H. Bassichis explores two different approaches to teaching introductory physics to engineering students. One approach is the traditional mechanics-based approach, while the other is a newer thermodynamics-based approach. The article discusses the role of free-body diagrams (FBD) in both approaches and highlights the differences in how forces are considered in each. It also compares the use of work and energy in problem-solving and discusses the challenges and benefits of each approach. The author, a highly respected professor, provides valuable insights into the topic. [Extracted from the article]

The rapid advancements in artificial intelligence, particularly in the domains of robotics, prosthetics, and virtual and augmented reality (VR/AR), have driven an escalating demand for intuitive and effective human-machine interactions. Consequently, haptic devices, being electronic displays for the sense of touch, have drawn increasing attention. More efforts are in demand to develop stretchable and lightweight haptic devices that can trigger multiple mechanical cutaneous receptors using a single device. This work presents a new 3-modal 5-DOF stretchable haptic interface that is enabled by electromagnetic actuators and high-fidelity multi-layer metal printing. The haptic device renders rich haptic sensations (i.e., normal force, vibration, angular force, skin dragging) in one device, allowing for the comprehensive delivery of tactile information through the excitation of multiple cutaneous receptors. Additionally, haptic devices are designed to be compact, lightweight, and skin-compatible. The skin-like softness and stretchability enable intimate skin contact, which is crucial for efficient haptic information delivery. This feature prevents the impediment to natural movements of the skin and ensures the functional integrity of the device during daily deformations of the skin. Finally, three proof-of-concept demonstrations illustrate the potential of the reported multimodal haptic devices for advanced haptic interactions across various domains. [ABSTRACT FROM AUTHOR]

This work proposes a three-degrees-of-freedom Human-Vehicle-Road model to study the system's dynamic as a response to road-induced excitations and evaluate the effect of vibrations on ride comfort. The study of the dynamic responses of the system is concerned only with the vertical motion of the passenger, sprung mass, and the tire when subjected to different excitation profiles. The model of the human is developed based on literature and then coupled to a quarter-car model using analytical methods. The mathematical model that describes the motion of the system is derived using Newton's law of motion. The numerical simulations of the mathematical model using MATLAB provide the basis for the ride comfort analysis. The effects of the bump geometry are also studied in terms of the amplitude of each displacement, velocity, acceleration, and transmitted force. The ride comfort analysis is based on the ISO 2631 and BS6841 standards. The new concept of bump rotation is introduced and discussed in comparison with previous results. The investigation of the angle of rotation is presented as a totality of case studies where the bump is rotated with respect to the x -axis from 0 to 75° which is equivalent to a longer bump while maintaining the same height. The dynamic response for all rotation angles is collected to show that longer bumps have better performance because they reduce the forces transmitted to the system while maintaining the required level of discomfort to control the speeds of vehicles on roads. The ride comfort analysis concludes that the cycloidal bump has better performance as a speed control device. [ABSTRACT FROM AUTHOR]

With the wide application of ultra-wideband (UWB) ranging technology in industry, production and aerospace, how to improve the accuracy of UWB ranging has become a research hotspot. If the UWB ranging data is treated as sequence data, it is possible to improve the ranging performance by sequence analysis, which has low computation complexity compared to direct UWB signal processing. However, as the UWB ranging data has its inherent properties, existing sequence analysis methods may not achieve good performance on UWB ranging data. In this paper, a two-path deep-learning framework to process, namely the Multiple Network model with Second order motion (MNS), is proposed the improve UWB ranging performance via ranging sequence analysis. The proposed method fuses the target motion prediction via Newton's laws of motion and error estimation via GRU, LSTM and Bayes. To evaluate our algorithm, we also proposed a method to collect both UWB ranging data and the accurate answer via laser ranging. The collected dataset D A T A _ T S , the proposed MNS algorithm, and the trained model are all open sourced to the community to help researchers for further research,please visit(https://github.com/xiaojiuwotongxue/data-store.git). Experiments on D A T A _ T S shows our proposed method outperforms traditional regresion methods significantly. [ABSTRACT FROM AUTHOR]

The article examines the use of ChatGPT, an AI engine, in physics education. It discusses the potential and limitations of ChatGPT in providing information to students and addresses concerns about its reliability. Previous studies have shown that ChatGPT can be used to enhance critical thinking skills and problem-solving in physics classrooms. The article focuses on the different types of physics education questions and presents the results obtained from using ChatGPT to answer them. The study found that while ChatGPT performed well in answering questions related to net force and acceleration, it struggled with questions involving displacement, trigonometric relationships, and friction. The article emphasizes the importance of educators understanding the limitations of AI tools and designing assignments that promote genuine understanding and critical thinking in physics education. Further research is needed as AI technology continues to advance. [Extracted from the article]

Strategic Intervention Material (SIM) is an instructional learner material developed to enhance the academic performance of low-performing students. This study aimed to develop e-SIM and investigate its effect on the student's academic performance and learning motivation in Newton's Laws of Motion. The participants were 40 students from Grade 12 ABM and HUMSS strands drawn from a private school in Valenzuela City, Philippines. A quasi-experimental design was utilized in this study using a one-group pre-test and post-test design since the study aims to measure the cause-and-effect of using e-SIM in learning physics. The quantitative data of this research was obtained through a motivational scale, concept test (pre-test and post-test), and e-SIM. The data was analyzed by average mean, p-value, and Wilcoxon Signed Ranks Test. According to the analysis result, there is a significant difference between the academic performance and learning motivation of the students using e-SIM. The use of e-SIM in enhancing academic performance and learning motivation in Newton's second law of motion is recommended. [ABSTRACT FROM AUTHOR]

Copyright of Filosofija, Sociologija is the property of Lithuanian Academy of Sciences Publishers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, we propose a novel methodology called Particle Dynamics Method (PDM) for identifying and quantifying influential nodes in complex networks. Inspired by Newton's three laws of motion and the universal gravitation law, PDM is based on a mathematical programming method that leverages node degrees and shortest path lengths. Unlike traditional centrality measures, PDM is easily adaptable to different network sizes and models, making it a versatile tool for network analysis. Our updated version of PDM also considers the direction of each force, resulting in more reliable results. To evaluate PDM's performance, we tested it on a set of benchmark networks with distinct characteristics and models. Our results demonstrate that PDM outperforms other methodologies in the literature, as removing the identified influential nodes results in a significant decrease in network efficiency and robustness. The key feature of PDM is its flexibility in defining distance, which can be adapted to various network types. For instance, in a transportation network, distance can be defined by the flow between nodes, while in an academic publication system, the quartile of the journal could be used. Our research not only demonstrates the effectiveness of PDM but also highlights the influence of universities in the higher education and global university ranking networks, shedding light on the dynamics of these networks. Our interdisciplinary work has significant potential for collaborations between optimization, physics, and network science. This study opens up avenues for future research, including the extension of PDM to multilayer networks and the generalization of the metrics of monolayer networks for this purpose. [ABSTRACT FROM AUTHOR]

This article provides an overview of pseudoscience, which refers to claims presented as scientific but lacking scientific evidence. It acknowledges that scientific knowledge is fallible and subject to change. The article explores the distinction between pseudoscience and other non-scientific areas of knowledge, and whether intentional deception is necessary for pseudoscience. It proposes a definition of pseudoscience based on subject matter, reliability, and presentation. The importance of consulting qualified experts to assess claims is emphasized, as well as the need for specialized scientific expertise in distinguishing between science and pseudoscience. The article also discusses the political implications of labeling doctrines as pseudoscience and the importance of refuting false claims. Additionally, the article provides a list of academic articles covering topics related to lexicon, philosophy of science, and the history and philosophy of scientific studies, which may be useful for library patrons conducting research in these areas. [Extracted from the article]

The article discusses Philip Ewell's book, "On Music Theory," which has generated both positive and negative reactions. The author praises Ewell's ability to engage readers with his storytelling and provocative style. The article focuses on Ewell's claims about the racist views of Heinrich Schenker and their influence on his music theory. The author refrains from commenting on broader cultural and political contexts and instead examines the "infection thesis" proposed by Ewell. The article aims to provide a balanced assessment of Ewell's arguments and their implications for music theory. [Extracted from the article]

In this research, the methodology and solution for combustion performance and emission control of gas turbine engine have been discussed. Because emission control is a big problem in day to day life. Aviation is most powerful and fastest growing field as well as transportation modes in the world. Global aviation contributes about 2.7% of global greenhouse gas emissions and supports 8.9% of the world economic process in terms of GDP. With this phenomenal growth for air trafficking by different national and international airliners, the total carbon space available for flying is being progressively diminished and the consequential emission levels are becoming alarming over passage of time. It is therefore essential to reduce the emission from the aircraft foe a better and greener aviation. A jet engine is a reaction engine, which generates thrust by jet propulsion in accordance with Newton's law of motion. Hence, the power produced by the engine is high and the emissions are greater than the considerable amount. Emissions generally refers to the greenhouse gases such as carbon monoxide, Nitrogen dioxides, hydrocarbons, carbon dioxide etc. various methods are developed to reduce the emission from aircrafts such as use of alternative bio-fuel and reducing fuel consumption. This project deals with emission control by reduction in fuel consumption as it is the most efficient and effective method. In this paper, turbofan engine is modelled and analyzed using ANSYS software. The result after analysis showed that increase in bypass ratio reduces the fuel consumption, thereby reducing the emission. [ABSTRACT FROM AUTHOR]

The article discusses the use of physical equations of motion to train neural networks. It explains that physical principles, such as the principle of least action and Onsager's principle of least power dissipation, can be leveraged for optimization in both physics and computing. The authors present an analog electronic system that uses physical dynamics to optimize the fitting of a nonlinear curve to a set of data points, demonstrating the potential for physical systems to perform machine learning tasks. While the hardware prototype has limitations in terms of scalability and energy efficiency, it serves as an important proof of concept for the use of physical systems in machine learning. [Extracted from the article]