In this work commercial 18650 lithium-ion cells with LiMn₂O₄, LiFePO₄ and Li(Ni_0.33Mn_0.33Co_0.33)O₂ cathodes were exposed to external heating in an Accelerating Rate Calorimeter (es-ARC, THT Company) to investigate the thermal behavior under abuse conditions. New procedures for measuring external and internal pressure change of cells were developed. The external pressure was measured utilizing a gas-tight cylinder inside the calorimeter chamber in order to detect venting of the cells. For internal pressure measurements, a pressure line connected to a pressure transducer was directly inserted into the cell. During the thermal runaway experiments, three stages (low rate, medium rate and high rate reaction) have been observed. Both pressure and temperature change indicated different stages of exothermic reactions, which produced gases or/and heat. The onset temperature of thermal runaway was estimated according to temperature and pressure changes. Moreover, the different activation energies for the exothermic reactions could be derived from Arrhenius plots.

We all have in mind Einstein's famous thought experiment in the elevator where we observe the free fall of a body, and then the trajectory of a light ray. Simply here, in addition to the qualitative aspect, we carry out the exact calculation, and for the first time the worldlines equations are given. We consider a uniformly accelerated reference frame in rectilinear translation, and we show that the trajectories of the particles are semi-ellipses with the center on the event horizon. The frame of reference is non-inertial, the space-time is flat, and the computations are performed within the framework of special relativity. Some experimental consequences are discussed, especially the experiment with the accelerated Michelson-Morley interferometer is solved, and we described an experiment where a new relativistic paradox appears --- a particle of matter seems to go faster than light. The differences, compared to the classical case, are important at large scale and close to the horizon, but they are small in the lift where the interest is above all theoretical. The concepts of metric, coordinated velocity and horizon are discussed, and the analogy with the black hole is made.

The task of conveying scientific research to individuals with varying levels of knowledge and understanding can prove to be quite challenging for a research scientist. The difficulty is further compounded when the exchange of information must be conducted within a limited timeframe. Notwithstanding, the 'elevator pitch' is a valuable tool that enables researchers to navigate these potential obstacles. An effective elevator pitch not only facilitates the communication of a researcher's scientific findings but also highlights the individual's skills and the significance of their research. Moreover, a well-crafted elevator pitch is a critical career development tool, serving as a means of networking and paving the way for future communications, scientific collaborations, and funding opportunities. This article examines the value of a scientific elevator pitch and provides step-by-step guidelines for developing and constructing an impactful pitch. Furthermore, we provide resources and an example of a successful elevator pitch delivered by a Fellow from the NIH-funded Accelerating Career Transitions (ACT) program, a professional development program established and managed by the American Society for Cell Biology (ASCB).

Electric and/or magnetic fields are generated by stationary charges, uniformly moving charges and accelerating charges. These field components are described in the literature as static fields, velocity fields (or generalized Coulomb field) and radiation fields (or acceleration fields), respectively. In the literature, the electromagnetic fields generated by lightning return strokes are presented using the field components associated with short dipoles and in this description the one to one association of the electromagnetic field terms with the physical process that gives rise to them is lost. In this paper, we will derive expressions for the electromagnetic fields using field equations associated with accelerating (and moving) charges and separate the resulting fields into static, velocity and radiation fields. The results illustrates how the radiation fields emanating from the lightning channel give rise to field terms varying as inverse of distance and distance squired, the velocity fields generating field terms varying as inverse of distance squired and the static fields generating fields components varying as inverse of distance squired and distance cube. These field components depend explicitly on the speed of propagation of the current pulse. However, the total field does not depend explicitly on the speed of propagation of the current pulse. It is shown that these field components can be combined to generate the field components pertinent to the dipole technique. However, in this conversion process the connection of the field components to the physical process taking place at the source that generate these fields (i.e. static charges, uniformly moving charges and accelerating charges) is lost.

This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with attributes/features allowing ARGs to encode rich structural information widely observed in real applications. Existing graph neural networks offer limited ability to capture complex interactions within local structural contexts, which hinders them from taking advantage of the expression power of ARGs. We propose Motif Convolution Module (MCM), a new motif-based graph representation learning technique to better utilize local structural information. The ability to handle continuous edge and node features is one of MCM’s advantages over existing motif-based models. MCM builds a motif vocabulary in an unsupervised way and deploys a novel motif convolution operation to extract the local structural context of individual nodes, which is then used to learn higher-level node representations via multilayer perceptron and/or message passing in graph neural networks. When compared with other graph learning approaches to classifying synthetic graphs, our approach is substantially better in capturing structural context. We also demonstrate the performance and explainability advantages of our approach by applying it to several molecular benchmarks.

Abstract Unlike accelerated motion or curvalinear motion,a nonlinear motion state(non-inertial system) can be described by differential equations or the other algebric equations in axiom 2, the accelerated motion in axiom 3 can be considered to be described by using the equation of the linear and curvilinear process of the continuum extending to infinitely distance.Further, this linear and curvilinear process of the continuum is a quantitative continuum in essence as a unity of infinitely quantities and infinitely dimensions at infinite distance (infinity) relative to all orientations in which we exist. These indicates that an accelerated motion accumulates continuously started from a finite quantities, leaping to transit from finite to infinite quantities by an infinitely great accelerating force.

With the development of satellite load technology and very-large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. Limited by severe size, weight, and power consumption constraints, a key challenge of on-board SAR imaging system design is to achieve high real-time processing performance. In addition, with the rise of multi-mode SAR applications, the reconfiguration of the on-board processing system is beginning to receive widespread attention. This paper presents a multi-mode SAR imaging chip with SoC architecture based on the reconfigurable double-operation engines and multilayer switching network. We decompose the commonly used extend chirp scaling (CS) SAR imaging algorithm into 8 types of double-operation engines according to the computing orders, and design a three-level switching network to connect these engines for data transition. The CPU is responsible for engine scheduling based on data flow driven with instructions to implement each part of the CS algorithm. Thus, multi-mode floating-point SAR imaging processing can be integrated into a single Application-Specific Integrated Circuit (ASIC) chip instead of relying on distributed technologies. As a proof of concept, a prototype measurement system with chip-included board is implemented, and the performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. A chip requires 9.2 s, 50.6 s and 7.4 s for a stripmap with 16,384×16,384 granularity, multi-channel stripmap with 65.536×8192 granularity and multi-channel scan mode with 32,768×4096 granularity and 6.9 W for the system hardware to process the SAR raw data.