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The generation of abrasive particles is an unavoidable consequence of sliding electrical contact wear in conductive slip rings (SRs). The adhesion of abrasive particles to the insulators may lead to a decrease in flashover voltage, posing a risk to satellite power transmission. In this paper, the effect of abrasive particles on flashover is first studied. Surface abrasive particles can distort the surface electric field of the dielectric, absorb scattered electrons, and then re-emit them, thereby accelerating the development and formation of secondary electron avalanches. Flashover test results indicate that surface abrasive particles lead to a significant reduction in flashover voltage. To mitigate the impact of particle adhesion on flashover, a method of constructing particle traps on the surface of insulators is proposed. The location and structural parameters of the particle trap are further optimized and determined. The flashover test results using planar dielectric samples and SR insulator samples both demonstrate that the optimized particle trap can significantly improve the flashover voltage. The dielectric maintains high electrical strength even when particles are trapped in particle traps. The physical details of the impact of particles on flashover and the effect of particle traps are analyzed utilizing an electron movement simulation, corroborating the experiment from a microscopic aspect. [ABSTRACT FROM AUTHOR]

Concentration plays an essential role in generating hydroxyl radicals in irradiated nanoenhancer suspensions. In this paper, we used coumarin-3-carboxylic acid as a hydroxyl radical-specific probe to investigate the hydroxyl radical production of different concentration nanodiamonds (NDs) and CeO2 NPs in phosphate-buffered saline under x-ray irradiation. NDs significantly enhanced hydroxyl radical production, and the maximum enhancement of hydroxyl radical production was observed at a concentration of 10 µg/ml, with an enhanced factor of 1.398 ± 0.262. CeO2 NPs can increase and scavenge hydroxyl radicals at different concentration ranges, with the lowest and highest enhanced factors of 0.623 ± 0.069 and 1.738 ± 0.264, respectively. We tested the hydrodynamic diameter at various concentrations to explore the concentration effect further. We found that with increasing concentration, there might be factors, such as hydroxyl radical recombination and nanoparticle agglomeration, that lead to changes in the enhancement factor. Based on the data from previous and present studies, the experimental results indicate that the concentration factor is essential for hydroxyl radical generation in nanoenhancer suspensions under ionizing radiation. We also provide possible mechanisms for enhancing hydroxyl radical production by nanoenhancers in water under ionizing radiation and the decrease in enhancement factor at high concentrations of nanoenhancers. [ABSTRACT FROM AUTHOR]

Renewable energy sources such as wind and solar power exhibit strong stochasticity and volatility, resulting in decreased power supply security and sustainability. A strategically optimized hybrid renewable energy system (HRES) is crucial for maintaining stable load operations and achieving sustainable energy development. This paper introduces an energy optimization management model for an independent HRES consisting of wind turbines, photovoltaic systems, diesel generators, and energy storage units. Operational strategies focus on energy storage-led loads following diesel generator-led load prioritizations. The model aims to optimize objectives to include economic, environmental, and power supply reliability indices. A dynamic adaptive parameter approach balances the parameters of the objective function at various instances. The optimal capacity allocation of the model is solved using the improved gray wolf optimization (IGWO) algorithm. This approach incorporates the golden sine strategy, the levy flight strategy, and the dynamic inverse learning strategy into the traditional GWO algorithm. Analyzing different test functions, evaluation metrics, and actual load data indicates that the proposed algorithm excels in global optimization capabilities and search speeds. The model significantly reduces the economic and environmental costs of the HRES microgrids and improves the sustainable development of renewable energy in various scenarios. [ABSTRACT FROM AUTHOR]

To separate the complexities in plasma physics and geometric effects, compact formulas for local geometric properties of a tokamak equilibrium are presented in this paper. They are written in a form similar to the Frenet formulas. All of the geometric quantities are expressed in terms of curvature and torsion of the three spatial curves for the moving local frame of reference, i.e., local orthogonal vector basis. In this representation, the local magnetic shear and the normalized parallel current are just the differences between two torsions of the vector basis. All of the geometric properties are coordinate invariants and form a prime set of quantities for describing tokamak plasma equilibrium. This prime set can be evaluated in both flux coordinates with closed flux surfaces and cylindrical coordinates including areas with open field lines, which may allow the extension of some analysis on the open field lines outside the last closed surface. Fundamental differential operators for stability and transport studies can be expressed explicitly in terms of these geometric properties. It can also be used to simplify analytic studies. [ABSTRACT FROM AUTHOR]

This paper thoroughly investigates the analysis of a modified generalized mean-field Ising model. The thermodynamic limit of free energy is investigated, and both the upper and lower bounds are derived. The lower bound is derived using a standard entropic variational principle, whereas a decoupling method is employed to derive the upper bound. Although the two bounds differ in form, they exhibit the same local maxima. Finally, the impact of a slight external field on the magnetic order is analyzed. [ABSTRACT FROM AUTHOR]

Geophysical domains typically exhibit intricate, irregular boundaries characterized by fractal-like geometries, while underlying physical processes operate across a broad spectrum of spatial scales. The challenge lies in generating spatial discretization of these domains that conform to their geographical constraints, utilizing anisotropic, fully adaptive meshes. This problem is compounded by the vast range of scales and a notably heterogeneous parameter space. Current methodologies often rely on ad hoc, model-specific, or application-dependent approaches, which lack comprehensive descriptions. Consequently, the development of new spatial domains is labor-intensive, prone to errors, challenging to replicate, and difficult to maintain consistency due to substantial human involvement. This predicament poses obstacles to the reproducibility of simulations and the establishment of provenance in data handling and model initialization, and it hinders rigorous model intercomparisons. Furthermore, the likelihood of discrepancies in model initialization and forcing parameters increases when employing flexible adaptive meshes. This paper introduces a systematic approach to the automated generation of adaptive meshes for geophysical models. This method is efficient in its generation process and readily reproducible, offering robust and consistent adherence to the source data. The proposed approach facilitates research in complex multi-scale geophysical domains, which would be challenging using existing methods. A simulation of monthly mean currents was carried out as a case study in the Gulf of Thailand. Results revealed that the simulated current circulations agreed with the observation. Examples of its application in various ongoing geophysical modeling endeavors illustrate its effectiveness. [ABSTRACT FROM AUTHOR]

In order to improve the immunity and speed tracking performance of active inverters in resonant overvoltage flexible suppression under load variation, parameter perturbation, and other uncertainties, a current control strategy of a resonant overvoltage flexible grounding device based on a cascading linear-nonlinear active disturbance rejection controller is proposed in this paper. First, the mathematical model of the flexible device considering load disturbance and parameter mismatch is established. Second, a cascade of linear and nonlinear extended state observers is designed to estimate and compensate the uncertain disturbance of the system in real time. The former linear extended state observer ensures the stability of the system under large disturbance, and the latter nonlinear extended state observer further improves the estimation accuracy of the disturbance by using the nonlinear mechanism. Finally, the flexible grounding system based on PI control and cascaded linear-nonlinear active disturbance rejection control (CL-NLADRC) is simulated and compared. Compared with PI control, NLADRC, and CLADRC, the current drop of the proposed CL-NLADRC during loading is 0.03 kA, which is 81.1%, 85.7%, and 73% of the three, respectively, and the regulation time is 13 ms, which is 82%, 75%, and 18.7% shorter than the three, respectively. The speed increase during load shedding is 93.5%, 80.5%, and 74.3% of the three, and the adjustment time is shortened by 80%, 73%, and 28%, respectively. The superiority of the proposed method is verified. [ABSTRACT FROM AUTHOR]

Support Vector Machines (SVMs) have achieved significant success in the field of power transformer fault diagnosis. However, challenges such as determining SVM hyperparameters and their suitability for binary classification still exist. This paper proposes a novel method for power transformer fault diagnosis, called ECOC-WSO-SVM, which utilizes a White Shark Optimizer (WSO) and error correcting output codes to optimize SVMs. First, t-distributed Stochastic Neighbor Embedding (t-SNE) is employed to reduce the dimensionality of Dissolved Gas Analysis (DGA) features constructed using the correlation ratio method, from 26 dimensions. In addition, to effectively solve the hyperparameters of SVMs, a multi-strategy fusion method is proposed to improve the WSO, incorporating tent chaos initialization, elite opposite learning, and selection strategies, forming TEWSO, and its superior optimization performance is validated using IEEE CEC2021 test functions. Furthermore, to address the limitations of SVMs as a binary classifier, an error correcting output code fusion SVM is introduced, thus constructing a multi-class SVM model. Finally, the diagnostic performance of the ECOC-TEWSO-SVM model is validated using real-world data. Results demonstrate that the proposed model exhibits the best diagnostic performance compared to traditional models and those in the literature, thereby proving the significance and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Pipeline transportation is an important engineering component, which is widely used in transporting gas and liquid resources. The safety of the pipeline became the central point of this study. Pipeline deformation caused by liquid storage pressure is of great significance to the safety of pipeline engineering. Previous studies mainly focused on pipe deformation under ring force and less on deformation caused by internal liquid. In this paper, the theoretical results of strain distribution are derived based on elastic mechanics, and the strain distribution equation is established. The effects of the liquid storage pressure, pipe diameter, and pipe length on pipe strain are investigated experimentally. The experimental results are in agreement with the equation. It is found that the strain increases linearly with the increase in reservoir pressure. Under the same length, the larger the pipe diameter is, the larger the pipe strain is when the pipe diameter is 5–10 mm. In the range of 10–15 mm, the average strain is basically unchanged. Under the same pipe diameter, the pipe length has little effect on the average strain. The strain is greatest in the middle of the pipeline and decreases gradually to both sides. The results have important guiding significance for pipeline protection and stress corrosion prevention. [ABSTRACT FROM AUTHOR]

Laser blindness can reduce or disable the information acquisition ability of photoelectric imaging systems. In this paper, numerical simulation and experimental verification are both performed to systematically study the laser protection performance of the vortex phase mask. First, the imaging model and laser transmission model of the vortex wavefront coding imaging system are introduced in detail. Then, the experimental setup of the imaging system is built, and the imaging result of the imaging system is obtained. Finally, the influence of propagation distance on the maximum single-pixel receiving power and suppression ratio of the imaging system is measured experimentally. The simulation and experimental results both show that the energy suppression ratio of this method can reach more than two orders of magnitude compared with the conventional imaging system, and the probability of laser blindness can be effectively reduced. [ABSTRACT FROM AUTHOR]

Cryogenic refrigeration technology based on magnetocaloric effects plays a critical role in a variety of technological applications. In this paper, we report the cryogenic magnetocaloric effects of a series of sodium-rare earth fluoride samples (Ln = Gd, Tb, Dy, Ho, Er, Tm, Yb) synthesized by the solid-state reaction method. These compounds all crystallize in a hexagonal crystal structure. Down to 2 K, no magnetic ordering was detected, while all compounds show negative Curie–Weiss temperatures indicative of strong antiferromagnetic coupling. Magnetic fields effectively suppress the magnetic fluctuations, leading to a maximum magnetic entropy change of −56 J kg−1 K−1 in NaGdF4 at the magnetic field change from 0 to 50 kOe. These series of compounds are potentially excellent magnetic refrigerants at low temperatures. [ABSTRACT FROM AUTHOR]

Previous experimental results show that the poloidal mode spacing of the filamentary structures increases and the dominant toroidal mode number decreases in the edgelocalized mode (ELM) rising phase with increasing plasma current. In addition, the experimental results in this paper show that the energy loss ratio of the pedestal (ΔW/Wped) decreases as the edge safety factor (q95) increases. The BOUT++ three-field two-fluid model can reproduce the experimental results and provide a possible explanation mechanism. The pedestal density plays an important role in the characteristics of filamentary structures as the current ramps up. On the one hand, the resistivity related to the pedestal density drives the instability of the peeling–ballooning mode, and the resistive effect is stronger in the high current case, making the dominant toroidal mode number lower and the corresponding poloidal mode spacing wider in the high current case. A low q95 corresponds to a high pedestal collision rate and a high pedestal energy loss ratio. On the other hand, the ELM crash process is dominated by resistivity, so the ratio of pedestal energy loss caused by ELM is not inversely proportional to the pedestal collision rate. [ABSTRACT FROM AUTHOR]

State-of-health (SOH) estimation of lithium-ion batteries stands as a fundamental metric within the battery management system. It reflects the current level of battery aging and is important for early warning of battery failure to avoid unsafe battery behavior. Therefore, accurate SOH estimation can ensure safe and reliable battery operation. In this paper, the capacity data of the discharge phase are used as the input of the SOH estimation model, and a gray wolf optimization (GWO)–variable mode decomposition (VMD)-transformer-based SOH estimation method for lithium-ion batteries is proposed in a data-driven framework. First, the GWO algorithm is adopted to optimize VMD to decompose the original battery capacity degradation sequence into a series of intrinsic mode functions (IMFs). Then, the transformer is used to separately predict each of these IMFs. Finally, the predicted values of each IMF are integrated to obtain the final prediction of the battery capacity degradation sequence. The model undergoes testing across various datasets, and comparative evaluations are conducted against other data-driven prediction models. The experimental findings underscore the superior SOH estimation performance of the proposed method, along with its robustness when confronted with diverse types of lithium-ion batteries, spanning distinct operational conditions and different aging degrees. [ABSTRACT FROM AUTHOR]

The SF6/N2 gas mixture as a preliminary alternative to SF6 is used in the power industry gas insulation medium. At present, the application of the 30% SF6/70% N2 gas mixture has made some progress, but the influence law of microwater content on its discharge decomposition characteristics is still unclear. In this paper, we simulate the defects of metal protrusions in the equipment through needle-plate electrodes, carry out SF6/N2 96hPD and its decomposition characteristic test under different microwater contents, and find that the increase of the microwater content in the SF6/N2 gas mixture will exacerbate the phenomenon of PD, resulting in the enhancement of the average discharge, and under the action of prolonged PD, more characteristic decomposition products will be generated, of which the SOF2 content is the highest, which can be as one of the characteristic components for fault severity judgment. This study provides a certain reference for the specific requirements of the microwater content of the SF6/N2 gas mixture in power equipment. [ABSTRACT FROM AUTHOR]

The undulator is a key luminous component of the Shanghai high repetition rate x-ray free electron laser and extreme light facility, and the motion control system is an important part of the undulator. The main task of the motion control system is to complete the high precision adjustment of the gap and taper between the upper magnetic pole girder and lower magnetic pole girder, so as to adjust the wavelength of the radiation light. According to the development requirements of the motion control system for the U26 undulator, which is a conventional permanent magnet, this paper proposes a new motion control system with double position feedback closed-loop control, including programmable logic controller (PLC) closed-loop control based on position feedback by a linear absolute encoder (LAE) and driver closed-loop control based on position feedback by a rotary absolute encoder (RAE) of a servo motor. Multiple motion tests of the U26 undulator have shown that the repeatability accuracy of the gap is ±50 nm and the gap drive can reach 0.1 µm step size, the error of which is about ±20 nm according to the feedback of the LAE. The conclusion can be drawn that the motion step size and repeatability accuracy of the motion control system for the U26 undulator are improved by one order of magnitude on the basis of meeting all technical requirements. At the same time, motor torque protection, motor temperature protection, and redundant position protection with RAE can further improve the reliability and safety of the motion control system for the U26 undulator. [ABSTRACT FROM AUTHOR]

In this paper, we consider two nonlinear models arising in mathematical physics, namely, the Landau–Ginzburg–Higgs (LGH) equation and the nonlinear dispersive modified Benjamin–Bona (DMBBM) equation. The LGH model describes the exchange between mid-latitude Rossby and equatorial waves, as well as nonlinear waves with long-range and weak scattering interactions between tropical tropospheres and mid-latitude. The DMBBM model explains surface wave propagation estimates in a nonlinear dispersive medium. We employed He's semi-inverse approach in order to solve these models. Specifically, we present hyperbolic wave solutions. The proposed method is straightforward, reliable, and effective, and its potential for use in solving additional partial differential equations in applied research is encouraging. Appropriate values for the parameters are taken into consideration when simulating certain 2D and 3D graphs that correspond to select solutions using Matlab software. [ABSTRACT FROM AUTHOR]

The classical wave theory can trace its historical origins to the seminal works of Christian Huygens, Thomas Young, and Augustin Fresnel. To explain some of light's observed properties, such as rectilinear propagation, reflection, and refraction, Huygens proposed a simple geometrical construction of secondary spherical wavelets with centers of disturbance located on a primary wavefront. More than a century later, Young formulated the law of interference to both predict the formation of fringes in his now famous double slit experiment and also to estimate the wavelengths associated with different colors. A decade after that, Fresnel combined Huygens' construction with Young's interference law to qualitatively and quantitatively describe diffraction, which is the bending of light upon encountering an obstacle or an aperture. This grand synthesis, called the Huygens–Fresnel principle, acts as a powerful pictorial aid and conceptual tool that can describe a wide variety of complicated optical phenomena. However, the applications of the principle and its later developments, such as the Kirchhoff–Fresnel integral, are strewn with several simplifying assumptions and approximations that are aimed at minimizing the mathematical challenges involved. Consequently, two distinct formalisms are necessary to account for diffraction effects when the source of light or observation screen is placed nearby and far away from the aperture or obstacle. Recently, a hyperbola framework for analyzing wave interference at a multi-slit barrier was shown to successfully circumvent all conventionally imposed ad hoc conditions. The method commences directly from the Huygens–Fresnel principle and the ensuing predictions pertaining to the distribution of fringe characteristics, namely, positions, widths, and intensities on a detection screen can, therefore, justifiably claim accuracy in both the near field (Fresnel regime) and the far field (Fraunhofer regime). In this paper, the analysis that was previously carried out for the special case of slits of negligible widths is further extended to encompass slits of finite widths as well. [ABSTRACT FROM AUTHOR]

In recent years, composite structures have been used in a large number of applications in aerospace, machinery, marine, and civil engineering. However, there are inevitably many uncertainties in the whole life cycle of composite structures, which can easily lead to structural damage and failure. Therefore, it is important to analyze the reliability and sensitivity of composite structures. At present, most of the contributions use the first-order reliability method (FORM) and the second-order reliability method (SORM) to study the reliability of composite structures and compare them with the results of the Monte Carlo simulation. However, both methods have their limitations. FORM cannot guarantee the calculation accuracy for the highly nonlinear limit state equation, and the calculation efficiency of SORM is too low. Therefore, this paper proposes to use importance sampling (IS) and backpropagation neural network-based Monte Carlo (MC-BPNN) to study the reliability, sensitivity, and dispersion of delamination growth of composite laminates. The results show that compared with FORM and SORM, IS and MC-BPNN have higher calculation accuracy and efficiency and can more accurately evaluate the failure degree of composite structures and ensure their safe operation in the field of aerospace equipment. The universality of this method can make it being widely used in the reliability and sensitivity analysis of different composite materials as well as dispersion analysis. [ABSTRACT FROM AUTHOR]

The interaction between an atmospheric pressure plasma jet (APPJ) and an aqueous solution has great application prospects in biomedicine and many other fields. Reactive species adjacent to a water surface is critical to the activation of APPJ-treated water, which is affected by both the water evaporation and the admixture of ambient air. In this paper, taking He APPJ as an example, a two-dimensional (2D) cylindrically symmetric fluid model is developed to obtain the spatial distributions of gas components before discharging, and a series of global models are developed for the discharge in the boundary gas layer adjacent to the water surface. The interfacial distributions of reactive species and their fluxes onto the water surface are quantified. It is found that the electron density is 1016–1017 m−3 and it shows an annular distribution in the boundary gas layer. The density distributions of most reactive species there reveal ring-like shapes as well. The dominant cation and anion in such a boundary layer are H3O+ and OH−, respectively. The most abundant metastable is O2(a1Δ), the most abundant reactive oxygen species are H2O2 and OH, and the most abundant reactive nitrogen species are NO and HNO2. The species of H2O2, OH, HO2, and HNO2 are reportedly to have significant biological effects, and in our simulation, their fluxes onto the water surface are remarkable, higher than 1017 m−2 s−1. In addition, the effects of radial gas velocity and water evaporation on the particle flux distributions are also revealed. [ABSTRACT FROM AUTHOR]

Artificial neural network is considered to be one of the effective ways to enable soft robots to achieve high-performance control due to their significant advantages, such as massively parallel processing and distributed storage of information, adaptivity, and fault tolerance. Artificial neural networks are composed of microelectronic components connected together, of which the most basic units are artificial neural synaptic units, such as atomic switches, memristors, and synaptic transistors. This paper first introduces the research status of soft robots and artificial neural synapses, predicts the demand of soft robots for artificial neural synapses, summarizes the difficulties and problems that may be encountered in the application of artificial neural synapses to soft robots, and finally points out the importance and feasibility of artificial neural synapses in the research and development of soft robots. [ABSTRACT FROM AUTHOR]

Granular matter like sand is composed of a large number of interacting grains and is, thus, expected to be amenable to a statistical physics treatment. Yet, the frictional properties of grains make the statistical physics of granular matter significantly different from the equilibrium statistical physics of atomic or molecular systems. We use three simple models to illustrate some of the key concepts of the statistical physics introduced by Edwards and co-workers more than 30 years ago to describe shaken granular piles: non-interacting frictional grains attached to a wall by a spring, a chain of frictional grains connected by springs, and a simplified mean-field model of a granular packing. We observe that a chain of frictional grains connected by springs exhibits a critical point at an infinite effective temperature (i.e., infinitely strong shaking) at odds with the zero-temperature critical point generically found in one-dimensional systems at thermal equilibrium in the presence of local interactions. Since the late 20th century, granular materials have been recognized as forming a distinct state of matter, neither solid nor liquid, but amenable to a statistical description. It turns out that dissipation, through inter-grain friction, governs the large-scale properties of these systems, so that the usual Boltzmann–Gibbs statistics is replaced by the Edwards statistics. These statistics are full of surprises. For instance, model granular systems can exhibit a critical point at infinite-temperature. To know more, you can delve into this paper, which can be used in advanced statistical physics courses, or as a graduate-level introduction to soft matter. [ABSTRACT FROM AUTHOR]

Multimode interference of light is an optical interference phenomenon based on waveguides, which has broad applications in optical communication, lasers, and optical fiber sensing. Since optical fiber has become the most widely used optical waveguide in modern society, multimode interference in optical fibers is an ideal candidate for projects in university teaching laboratories. Here, we implement an in-fiber Mach–Zehnder strain sensor-based experiment to study multimode interference in optical fibers. The sensor is fabricated by fusion splicing a piece of thin core fiber between two single mode fibers. One end of the thin core fiber is spliced without a core offset, while the other end is spliced with a core offset. Due to the mode field diameter mismatch and core offset, cladding modes are excited and interfere with the core mode in thin core fiber. Students can observe the sensor fabrication demonstration and perform a strain test with an optical spectrum analyzer. The wavelength spectra captured by the optical spectrum analyzer under different strains are analyzed with the signal processing tools of fast Fourier transform and fast Fourier transform filter. Students then find characteristics of the multimode interference in the sensor from the analysis. The experiment extends undergraduates' knowledge of light interference and is an instructive exercise for them in modern coherence theory. This paper reports the development of an advanced instructional laboratory experiment aimed at teaching undergraduates about the physics and applications of multimode interference effects in optical fibers. The experiment is based on an in-fiber Mach-Zehnder strain sensor, which is fabricated by fusion-splicing a thin core fiber between two single-mode fiber leads. The experiment introduces students to optical fiber sensing in a cost-effective way and applies theoretical concepts they have learned in courses in the areas of wave guides, optical interference, and spectral analysis. Experimental results are presented for the sensor's output optical interference spectrum as well as the spectral response to strain. This experiment will be of interest to advanced laboratory and upper-level optics course instructors. [ABSTRACT FROM AUTHOR]

In this paper, we use differential forms to prove a number of theorems of integral vector calculus that are rarely found in textbooks. Two of them, as far as the author knows, have not been published before. Some possible applications to problems in physics are shared including a general approach for computing net forces and torques on current-carrying loops that yields insights that are not evident from the standard approach. Readers who are familiar with differential forms will enjoy seeing how they can be employed to prove several new vector calculus identities. But even readers who do not follow those derivations will benefit from seeing how these identities can be employed to find forces and torques on current-carrying loops. [ABSTRACT FROM AUTHOR]

Newton's Theorem of Revolving Orbits derives the force that is necessary to explain a particular precession that leaves the shape of an orbit unchanged. Newton showed that for an orbiting body that is already subject to any central force, the inclusion of an additional inverse-cube central force will change that body's angular speed without affecting its radial motion; this leads to the orbit's precession. After reviewing the relevant concepts of Kepler orbits, we present a full description and explanation of Newton's theorem using modern physical and mathematical approaches aimed at a general audience. We specifically highlight the use of the transformation between a rotating reference frame and an inertial reference frame, making this a suitable topic for an upper-level undergraduate mechanics course. It is commonly known that Newton derived the Kepler orbits that result from an inverse square central force in his famous work Principia. But fewer people know that Newton also considered precessing orbits in Principia, showing that they are produced by an inverse cubed central force. Subsequent texts on precessing orbits explored the problem with such technical detail that the simplicity of the original problem was often lost. This paper presents the derivation using modern techniques, while also frequently referring back to Newton's original derivation to provide context, providing a nice introduction to the topic appropriate for undergraduate mechanics students. [ABSTRACT FROM AUTHOR]

Textbooks often present the phenomenon of screening within the Thomas–Fermi model for three-dimensional free electron gases, but obtaining the dielectric response function and screening potential for dielectric systems of reduced dimensionality is also of pedagogical interest. In this work, we introduce a simple approach to investigate static screening in dielectric systems in the presence of an impurity charge for different dimensionalities. This approach is applicable to semiconductors and insulators alike. We demonstrate that, in 3D systems, the macroscopic dielectric function in reciprocal space is a constant, while in 2D and 1D systems, it strongly depends on the momentum transferred to the electrons in the dielectric. Through the proposed dielectric screening model, one can also determine binding energies in a hydrogenic model that can be used to describe excitations in real semiconductor systems. Screening in dielectrics is a measure of the strength of Coulomb interactions. Because of the reduced dimensionality, screening is hampered in 2D or quasi-1D materials, with important consequences in nanometer-scale systems that are currently important to the condensed matter community. This paper explains why reduced dimensionality reduces the screening. The topic is appropriate for undergraduate electromagnetism classes or advanced condensed matter courses. [ABSTRACT FROM AUTHOR]

We demonstrate a method for constructing spacetime diagrams for special relativity on graph paper that has been rotated by 45o. The diagonal grid lines represent light-flash worldlines in Minkowski spacetime, and the boxes in the grid (called "clock diamonds") represent units of measurement corresponding to the ticks of an inertial observer's light clock. We show that many quantitative results can be read off a spacetime diagram simply by counting boxes, with very little algebra. In particular, we show that the squared interval between two events is equal to the signed area of the parallelogram on the grid (called the "causal diamond") with opposite vertices corresponding to those events. We use the Doppler effect-without explicit use of the Doppler formula-to motivate the method. [ABSTRACT FROM AUTHOR]

An experiment studying the physical principles of electrophoresis in liquids was developed for an undergraduate laboratory. We have improved upon the standard agarose gel electrophoresis experimental regime with a straightforward and cost-effective procedure, in which drops of widely available black food coloring were separated by electric field into their dye components on strips of chromatography paper soaked in a baking soda/water solution. Terminal velocities of seven student-safe dyes were measured as a function of the electric potential applied along the strips. The molecular mobility was introduced and calculated by analyzing data for a single dye. Sources of systematic and random errors were investigated. [ABSTRACT FROM AUTHOR]

Sonoluminescence is the production of electromagnetic radiation, much of it in the form of visible light, that is emitted from a gas-filled cavity that has grown and collapsed under the influence of a varying pressure field. This resource paper provides a guide to the literature of sonoluminescence, from its early history to the present. [ABSTRACT FROM AUTHOR]

Paper-based microfluidics are an increasingly popular alternative to devices with conventional open channel geometries. The low cost of fabrication and the absence of external instrumentation needed to drive paper microchannels make them especially well suited for medical diagnostics in resource-limited settings. Despite the advantages of paper microfluidics, many assays performed using conventional open channel microfluidics are challenging to translate onto paper, such as bead, emulsion, and cell-based assays. To overcome this challenge, we have developed a hybrid open-channel/paper channel microfluidic device. In this design, wick-driven paper channels control the flow rates within conventional microfluidics. We fabricate these hybrid chips using laser-micromachined polymer sheets and filter paper. In contrast to previous efforts that utilized external, macroscopic paper-based pumps, we integrated micro-scale paper and open channels onto a single chip to control multiple open channels and control complex laminar flow-pattern within individual channels. We demonstrated that flow patterns within the open channels can be quantitatively controlled by modulating the geometry of the paper channels, and that these flow rates agree with Darcy's law. The utility of these hybrid chips, for applications such as bead-, cell-, or emulsion-based assays, was demonstrated by constructing a hybrid chip that hydrodynamically focused micrometer-sized polystyrene beads stably for >10 min, as well as cells, without external instrumentation to drive fluid flow. [ABSTRACT FROM AUTHOR]

The cylindrical piezoelectric transducer has the advantages of large radiation area, high electromechanical coupled coefficient, and omni-direction radiation along the radius. In this paper, a piezoelectric transducer consisting of a radially polarized piezoelectric cylinder and an outer metal cylinder of varying height is presented. The metal cylinder of varying height is approximated as the radial superposition of multiple uniform height metal cylinders, and the equivalent impedance of the transducer's coupled vibration is obtained by using the impedance matrix method, and then the resonance frequency, anti-resonance frequency, effective electromechanical coupled coefficient, and displacement amplification coefficient are obtained. In this paper, the relationship between the vibration characteristics of the cylindrical piezoelectric transducer and its geometric dimensions is studied. An experimental sample of the transducer is fabricated and assembled, and its electrical impedance curve is measured. The measured results are in good agreement with the simulation results and the theoretical calculation results. The displacement distribution of the radiation surface of the transducer at resonance frequency is measured, which verifies that the two coupled vibration modes of the transducer can be effectively excited. [ABSTRACT FROM AUTHOR]

The application of acoustic liners near/directly over a sound source has gained significant interest for the excess noise reduction achieved with Over-the-Rotor (OTR) liners compared to the conventional liner installations at the intake of an aero-engine. However, the mechanism of noise reduction achieved in the OTR liners is not clearly understood. This paper aims to explain this mechanism by considering a static monopole source placed over a finite liner insert with a zero background mean flow. This has been investigated numerically using COMSOL Multiphysics in a half-space domain and compared with reference analytical solutions for infinite lined walls. One of the key findings of the paper is the underlying physics of the source modification mechanism, which has been found to be the interference between the primary noise source and a secondary noise source forming on the liner surface. It is identified through an optimal impedance study that this back-reaction mechanism is dominant when the source is located for a normalised tip gap, e / λ < 0.25 , where e is the distance between the source and the liner surface and λ is the acoustic wavelength. Within this region, there exists an optimum normalised liner length, L / e providing a maximum insertion loss. [ABSTRACT FROM AUTHOR]

This paper presents an alternative energy function for global optimization (GO) beamforming, tailored to acoustic broadband sources. Given that properties, such as the source location, multipole rotation, or flow conditions, are parameterized over the frequency, a cross spectral matrix-fitting can be performed for all frequencies at once. A numerical analysis shows that the nonlinear energy function for the standard GO problem is equivalent to the source's point spread function (PSF) and contains local minima at the locations of the grating lobes and side lobes. The energy function is improved with the proposed broadband energy, as it averages the PSF. Further, it simplifies the process of identifying sources and reconstructing their spectra from the results. The paper shows that the method is superior on synthetic monopoles compared to standard GO and CLEAN based on source coherence (CLEAN-SC). For real-world data, the results of the proposed method and CLEAN-SC are similar, and outperform standard GO. The main difference is that source assumption violations cause noisy maps for CLEAN-SC and cause wrong spectral estimations of the proposed method. By using reasonable initial values, the GO problem reduces to a local optimization problem with similar results. Further, the proposed method is able to identify synthetic multipoles with different pole amplitudes and unknown pole rotations. [ABSTRACT FROM AUTHOR]

In the Bayesian estimation method for the parameters of random distributions, the process of selecting hyperparameters for the prior distributions is one of the important and complex matters that determine the efficiency of the estimation. Therefore, researchers have recently been interested in the expected Bayesian (E-Bayes) estimation as a solution to hyperparameter problems. In this paper, we discuss the Bayes and E-Bayes estimation process based on generalized type-I hybrid censored data from Burr-XII distribution. We used symmetric and asymmetric loss functions, such as squared error, Degroot, quadratic, and linear exponential loss functions. All of these methods were compared using Monte Carlo simulations, using which mean square errors and average of estimators were calculated. Moreover, real data were used as an applied and illustrative example. Finally, some conclusions were drawn in the concluding comments of this paper. [ABSTRACT FROM AUTHOR]

Magneto-mechano-electric (MME) generators consisting of piezoelectric and magnetostrictive materials can convert the stray magnetic noise to useful electric energy for the wireless sensor networks utilizing the magnetoelectric coupling effect and magnetic interactions. In this paper, a scalable engineering approach was proposed to fabricate the laminate MME generator composed of a PZT/Fe–Ga/PZT sandwich structure. The Goss-oriented Fe81Ga19 thin sheet with a large magnetostriction of 244 ppm was produced by a simple and low-cost approach, and the commercial polycrystalline piezoelectric ceramic products (PZT-5H) were used as the PZT layers. The effect of grain orientation, device structure, magnetic field amplitude, and resonance frequency on the electrical output of the PZT/Fe–Ga/PZT MME generator was investigated. The electrical output of the MME generator containing the Goss-oriented Fe81Ga19 thin sheet reached an AC voltage of 4.58 V and the ME coefficient of 76.33 V/cm·Oe under a low excitation magnetic field of 26 Oe at a low resonance frequency of 26 Hz. The MME generator with a Goss-oriented Fe–Ga layer shows 4.7 times higher output voltage and ME coupling coefficient than that with the no-oriented polycrystalline Fe–Ga layer, but only 81% of the latter's resonance frequency. This is related to the significant increase in magnetostriction due to the texture transition after secondary recrystallization annealing at the temperature of 950 °C. This paper provides a very promising solution to meet the self-power supply needs of the Internet of Things utilizing low-value and low-frequency magnetic fields. [ABSTRACT FROM AUTHOR]

This paper reports a study on the production of plasma jets that are out of equilibrium through numerical solutions of electron energy distribution function using a self-consistent methodology. The approach includes the integration of the continuity, momentum, and Poisson equations, which allows the use of the mean electron energy to fit the transport and source coefficients. The paper concurrently presents an analysis of cold plasma generation in a tube. This investigation utilizes COMSOL Multiphysics software to simulate the electric field, potential, and electron density in space. Moreover, the study examines how the dielectric's permittivity impacts plasma propagation. The simulated outcomes are compared with experimental and numerical results. As electron density, ionization rate and electric potential vary during plasma propagation on a dielectric surface, and the permittivity of dielectric materials increases, it promotes an increase in electron density around it. This, in turn, accelerates the ionization front, indicating efficient polarization and accumulation of electric charges, specifically electrons, near the dielectric surface. [ABSTRACT FROM AUTHOR]

Permanent magnet vernier motor (PMVM) is extremely attractive in low-speed large-torque, whereas it always suffers from poor power factor. In order to realize the cooperative improvement of torque and power factor, this paper applies dual-three phase winding in PMVM, and investigates the influence of phase shift on torque and power factor improvement from the perspective of working harmonics and non-working harmonics. The key of this paper is to decompose the armature field harmonics. Through appropriated phase shift, increasing the armature working harmonics to improve the torque, and eliminating the armature non-working harmonics to enhance the power factor. Then the 24/38 DTP-PMVM is designed. Through theoretical derivation and simulation, it is verified that the DTP-PMVM torque is optimal and power factor is improved by phase shift 30°, compared with phase shift 0°. [ABSTRACT FROM AUTHOR]

Currently, China is using the SF6/N2 gas mixture to gradually replace SF6 in GIS and other equipment. However, gas-insulated equipment will inevitably have local overheating faults. The SF6/N2 gas mixture will decompose to some extent at high temperatures. Impurities such as moisture in the equipment can affect this decomposition process. At present, there are fewer studies on the moisture content of the superheated decomposition of the SF6/N2 gas mixture. Therefore, this paper carries out the SF6/N2 mixed gas superheat decomposition experiment on the constructed superheat decomposition simulation experiment platform. By changing the content of trace water, the influence of trace water on the decomposition of the SF6/N2 mixed gas insulation medium with superheat failure was initially investigated. It is found that trace H2O will promote the generation of SF6 characteristic decomposition products, especially for the generation of SO2F2. The generation of SO2 in the product is the largest, and its generation process needs the full participation of H2O. In addition, the addition of trace water will also improve the yield of nitrogen-containing products NO and NO2, and under the experimental conditions of this paper, by adding the microwater, the yield reaches 100–300 µl/l. The reaction mechanism of H2O decomposition and combining with N atoms to generate NO and NO2 at high temperatures was analyzed in this paper. The thermodynamic properties of the main reaction paths and the equilibrium constants were calculated based on the density functional theory, which provided theoretical references for the further study of the mechanism of SF6/N2 superheated decomposition. [ABSTRACT FROM AUTHOR]

The use of fractal–fractional derivatives has attracted considerable interest in the analysis of chaotic and nonlinear systems as they provide a unique capability to represent complex dynamics that cannot be fully described by integer-order derivatives. The fractal–fractional derivative with a power law kernel is used in this paper as an analytical tool to analyze the dynamics of a chaotic integrated circuit. Using coupled ordinary differential equations of classical order, the complexity of an integrated circuit is modeled. The classical order model is generalized via fractal–fractional derivatives of the power law kernel. Moreover, this paper is concerned with investigating the Ulam stability of the model and conducting theoretical studies in order to analyze equilibrium points, identify unique solutions, and verify the existence of such solutions. By examining the complex dynamics that result in chaotic behavior, these investigations shed light on the fundamental properties of integrated circuits. For the purpose of exploring the non-linear fractal–fractional order system, a numerical algorithm has been developed to facilitate our analysis. MATLAB software has been used to implement this algorithm, making it possible to carry out detailed simulations. Simulating solutions are accomplished using 2D and 3D portraits, which provide visual and graphical representations of the results. Throughout the simulation phase, particular attention is given to the impact of fractional order parameter and fractal dimension. As a result of this study, we have gained a comprehensive understanding of the behavior of the system and its response to variations in values. [ABSTRACT FROM AUTHOR]

The value for core hysteresis loss (CHL) resistance in Buntenbach's analogy hysteresis model does not consider the impact of frequency variations. In order to address this issue, this paper proposes a calculation expression for CHL resistance that takes into account the influence of frequency variation through a variable coefficient. The paper analyzes changes in CHL resistance values at different frequencies using hysteresis loss characteristics and circuit theory. To validate the proposed calculation method for CHL resistance, Buntenbach's analogy hysteresis model is applied to model the Epstein frame and magnetically saturated controllable reactor. The comparative results reveal that the proposed calculation expression for CHL resistance is effective. [ABSTRACT FROM AUTHOR]

It provides a challenge for remaining useful life prediction due to the complexity of the engine degradation process. Therefore, this paper proposes an improved method for engine remaining useful life prediction with long and short memory neural networks (LSTM) and extraction of health indicators for measured parameters. In order to overcome the limitation of measured parameters, a second-order polynomial approach is implemented to construct novel virtual parameters based on the existing parameters and improve the representativeness of the data to the engine degradation process. Then, random forests are used to score the importance of these parameters on the basis of which the higher rated parameters are filtered to reduce the computational burden. For the hyperparameter optimization problem of LSTM, an improved golden jackal optimization method is proposed in this paper, in which chaotic mapping is used to initialize the population to increase the uniformity of the initial population distribution in space. An adaptive method is introduced to improve the exploration and exploration capabilities of the golden jackal algorithm. Finally, the effectiveness of the proposed method is verified by NASA's public dataset. The experimental results show that the R2 of the proposed method is greater than 0.99, the error of mean absolute percentage error is within 3%, and the root mean square error is smaller than 4. The proposed method can provide better predicted performance compared with the traditional methods. [ABSTRACT FROM AUTHOR]

Influenced by multiple factors such as low light intensity, dispersed light, excessive dust, and excessive ambient noise inside cable tunnels, the images captured by cable tunnel inspection robots have shortcomings such as low contrast, low pixel values, and high noise. To improve the image quality, this paper proposes an image enhancement method suitable for cable tunnel inspection robot. First, in this paper, a bivariate hybrid optimization module using the alternating direction multiplier method and the adaptive learning rate acceleration SVRG algorithm is constructed to achieve image pre-processing. Second, a feature extraction module combining a U-Net network and a coordinate attention mechanism is constructed to extract features from the original image and the pre-processed image. Third, the progressive feature fusion module and the image recovery module are constructed to fuse the above features and are combined with the original image to obtain the enhanced image. Finally, the pixel compensation module is constructed to compensate for the features of the enhanced image and recover the lost texture details. [ABSTRACT FROM AUTHOR]

More evidence indicates that central nervous system diseases are related to abnormal regulation of the reciprocal expression of nerve cells and astrocytes. In this paper, we investigated the dynamics of a model incorporating both a neuron and an astrocyte to elucidate the effective interaction between the two components. In this coupled system, external stimulation is applied to the neuron and the astrocyte, respectively. The results showed that after successive stimuli separated by 20 s, both neurons and astrocytes can exhibit the so-called hyperexcitability and nonlinear wave characterized by a decrease in the threshold for activation and an increase in spontaneous firing rate. Furthermore, this paper reveals the potential dynamic changes in the formation and disappearance of hyperexcitability and its transition mechanisms. It can be helpful for further understanding the bifurcation behavior during the progression of central nervous system dysfunction. [ABSTRACT FROM AUTHOR]

Manipulation of untethered millimeter-sized devices (bots) inside the human body has many medical applications. Most of the prior work focused on movement of such bots inside fluids, usually at low Reynolds numbers. Yet, many medical procedures are performed within soft tissues. Bot translation in soft materials differs dramatically from their motion in fluid. This paper focuses on trajectory control of small, untethered spheres driven magnetically in soft media commonly used to simulate tissues. While spherical bot shapes offer the advantage of potentially rapid change in the direction of motion, the main challenge in controlling trajectories through soft materials is their nonlinear and history dependent response forces associated with irreversible medium modification. This paper introduces control modules for manipulating spherical bots in soft media along elementary trajectories of circular and straight segments, from which more general trajectories may be assembled. The proposed control is based on a phenomenological model of soft media response forces. Numerical implementation of the proposed trajectory control along circular trajectories is shown to compare well with the results of experimental tests indicating that the accuracy on the order of the bot radius is readily achievable for trajectories whose radii of curvature is on the order of 10 bot radii. [ABSTRACT FROM AUTHOR]

Minimizing the offloading latency of agricultural drip irrigation and fertilization tasks has long been a pressing issue in agricultural drip irrigation and fertilization wireless sensor networks (AIFWSNs). The introduction of edge computing as a robust and practical aid to cloud computing in AIFWSNs can significantly improve the execution speed of agricultural drip irrigation and fertilization tasks and effectively reduce the task offloading latency. Therefore, this paper investigates the optimization method of drip irrigation and fertilization task offloading delay in AIFWSNs based on edge computing and proposes a new edge task offloading method for AIFWSNs, namely, Quantum Chaotic Genetic Optimization Algorithm (QCGA). This paper introduces a novel quantum operator in QCGA, comprising a quantum non-gate and a quantum rotation gate, to improve the algorithm's global search capability. The quantum operator accomplishes the updating of quantum rotating gates without querying the quantum rotation angle table, which reduces the computational complexity of introducing quantum optimization into the task offloading problem of AIFWSNs. This paper proposes a new chaotic operator to make the initial solution more uniformly distributed in the search space by chaotic mapping. This paper's simulation experiments compared QCGA and snake optimizer (SO), genetic algorithm (GA), particle swarm optimization (PSO), sequential offloading, and random offloading methods. Simulation results showed that, compared with SO, GA, PSO, sequential offloading, and random offloading methods, the average delay of QCGA was reduced by 9.96%, 26.78%, 29.31%, 44.67%, and 61.24%. [ABSTRACT FROM AUTHOR]

In this paper, aiming at the current distribution network with power operation in the presence of outdoor bright light, the operating scene is complex and not fixed, the transmission lines and lead samples are small and uneven, leading to poor accuracy of machine learning and other methods of distribution network with power operation robot identification and localization, this paper selects three-dimensional LIDAR to design a set of support vector machine (SVM) classifier and correlation analysis based on the target recognition method. This paper selects three-dimensional LIDAR to design a set of support vector machine (SVM) classifier and correlation analysis based on the target recognition method. First, in the context of power distribution network operations, we have explored various filtering methods suitable for preprocessing transmission line data. These methods aim to remove outliers and clutter from point clouds, thus enhancing both point cloud quality and processing speed. This, in turn, improves the efficiency of real-time on-site detection. We conducted experimental comparisons of various clustering algorithms and opted for a region-based point cloud clustering algorithm to achieve the segmentation of individual point clouds. Secondly, we proposed a multi-feature composite approach based on the Viewpoint Feature Histogram (VFH) features, which helps maintain the scale-invariant characteristics of the features. We then introduced a multi-feature composite criterion based on VFH features to extract features from segmented point clouds. Subsequently, an SVM classifier based on this composite feature criterion was developed to achieve target identification and classification. Experimental results have demonstrated improved accuracy in target identification. Finally, we integrated this system with a bucket-arm vehicle for coordinate conversion and precise navigation of the robot to the target station. This method significantly improves the overall operational efficiency of power distribution tasks. [ABSTRACT FROM AUTHOR]

TEAM Problem 35, a benchmark problem in the optimization of electrical equipment, is a multi-objective, multi-variable optimization problem involving uniform field optimization. This paper proposes a novel guided optimization algorithm to address this problem and achieve optimal magnetic field regulation. First, the deep learning method is used to predict the magnetic field of the solenoid; second, the generated magnetic field cloud map is screened to extract the magnetic field information of the more optimal solution with uniform magnetic field distribution by calculating the variance of the generated magnetic field map; finally, the magnetic field features are combined with the particle swarm optimization algorithm; specifically, the variance of the calculated magnetic field map is added to the objective function of the optimization algorithm to strengthen the optimization process. This integration improves the convergence speed of the optimization process and ensures the continuity and stability of the obtained Pareto solutions. To optimize the solenoid, this paper considers the uniformity of magnetic field distribution and power loss as the primary optimization objectives. The radius of the coil is chosen as the design variable. The optimization results are compared with those obtained by conventional optimization algorithms, demonstrating superior optimization performance. [ABSTRACT FROM AUTHOR]

Sound source localization has a wide range of application prospects in many fields, such as smart home and audio monitoring. Traditional methods are difficult to achieve accurate location in the face of multi-path reflection, reverberation, and ambient noise. In this paper, a complex mapping conversion method for sound source location is proposed. By using complex-valued convolutional neural networks to fuse the amplitude and phase information of the data, a more accurate and comprehensive analysis can be carried out to improve its robustness and realize the accurate location of the sound source. The sound source location method based on complex-valued convolutional neural networks is studied, and the complex mapping principle is analyzed. Simulation and experimental studies were carried out, and the results of simulation and experiment are basically consistent. In the experiment, the positioning accuracy of the complex mapping method is 9.49% higher than that of the absolute value method and 15.81% higher than that of the phase angle method. In addition, its localization success rate, respectively, increased by 4.9% and 8.6% compared to two other methods. This paper opens up a new way for the application of complex-valued convolutional neural networks in sound source localization. [ABSTRACT FROM AUTHOR]

This paper describes the energy resolution of microwave kinetic inductance detectors and models some limiting factors to it. Energy resolution is a measure of the smallest possible difference in energy of the impinging photons, ΔE, that the detector can identify and, as such, is of critical importance for many applications. Limits to the energy resolution caused by the Fano effect, amplifier noise, current inhomogeneities, and readout sampling frequency are taken into consideration for this model. This paper describes an approach to combine all of these limitations and predict a wavelength dependency of the upper limit to the resolving power. [ABSTRACT FROM AUTHOR]

This paper presents a method to generative design bionic bone structures wing ribs by simulating the formation process of soap bubble boundary. In this method, the position of the central control point is optimized by the genetic algorithm to simulate the moving process of the bubble, and the control point is simplified by the K-means classification method to improve the computational efficiency. The boundary formed by the extrusion of bubbles is filled with a bone-like grid structure to realize the optimal design of a bone-like rib structure. Compared with the traditional honeycomb sandwich structure, the bone-like rib structure can distribute the stress evenly throughout the structure, thus reducing the stress concentration and improving the bearing capacity of the structure. The method proposed in this paper provides a new idea for a multilevel structure design. [ABSTRACT FROM AUTHOR]

This paper explores the synergy between early diabetes detection and artificial intelligence (AI)-based diabetic retinopathy screening. It emphasizes the crucial role of integration for enhancing patient care. Diabetes and its complications, such as diabetic retinopathy, can be better managed with early intervention. AI techniques are revolutionizing medical diagnostics, offering potential for accurate prediction of diabetes risk and automated analysis of retinal images for retinopathy detection. By combining these aspects, we uncover a comprehensive strategy that not only identifies diabetes in its early stages but also ensures timely management of its ocular complications. This integrated approach shows promise for personalized care, improved outcomes, and efficient resource utilization. This paper underscores the need for collaboration between medical and AI experts to maximize the potential of this dual-focused approach for transforming diabetes management. [ABSTRACT FROM AUTHOR]