Field Strength Research Articles

Electrocombustion Characteristics of Iron Particle-Laden Methanol and Ethanol Droplets in a Direct Current Field

ABSTRACT This study investigates the electrocombustion and atomization behavior of single droplets (2.5 wt.% Fe) of ethanol (EtOH) and methanol (MeOH) fuels at the droplet scale. The experiments utilize a system with two opposing plate electrodes of varying distances (200, 150, and 100 mm) and both negative (↓) and positive (↑) polarizations within a vertical direct current (DC) electric field. The results show that for EtOH and EtOH/Fe droplets, the flame envelope changes to a spherical form at (↓) and (↑) polarizations at 100 mm plate spacing, while for MeOH and MeOH/Fe droplets, the flame envelope changes to a spherical form at (↓) and (↑) polarizations at 200, 150 and 100 mm plate spacing. Increasing electric field strength reduced the micro-explosion tendency of Fe particles in the flame region and the micro-explosion intensity of Fe particles was found to be higher in ethanol droplets than in methanol. No systematic relationship could be established between the electric field effect and the presence of Fe particles. The MeOH/Fe/150(↑) droplet exhibited the lowest extinction time of 1050 ms. The electric field fundamentally alters the secondary atomization process of the fuel droplets. Notably, the diameter regression of all MeOH-based fuel droplets deviates significantly from a linear relationship. The investigation into the combustion behavior of pure EtOH, MeOH, and their Fe-blended counterparts within an electric field environment suggests that MeOH and MeOH/Fe fuels exhibit superior combustion characteristics. However, further research is necessary to fully elucidate these findings.

Recovering MRI magnetic field strength properties using machine learning based on image compression quality scores

AbstractOver the years, significant hardware advancements have led to higher magnetic field MRI (Magnetic Resonance Imaging) acquisitions, providing improved diagnostic image quality at a higher cost. While higher image quality is desired, the investment required for high-field MRI imaging systems remains a significant consideration. Furthermore, historical patient records may still contain low-field magnetic strength MRI data. In this work, we present how image compression quality scores of MRI images could be used to recover their magnetic field strength properties. This work presents an interesting inverse problem scenario where output properties are used to recover an input property of an image. We implemented supervised machine learning models that utilize compressed image quality scores - based on Mean Squared Error (MSE), Structural Similarity Index (SSIM), Visual Information Fidelity (VIF), and Earth Movers Distance (EM) metrics - as inputs. These models classify images into specific classes of magnetic field strength at which they were acquired (Low, Medium, and High) based solely on the quality scores of their compressed copies. The trained machine learning models (Support Vector Machine (SVM), Logistic Regression, K-nearest Neighbours (KNN), Decision Tree and Random Forest) achieved nearly 100% performance efficiency based on accuracy and F-1 score for all considered quality measures. This comprehensive evaluation offers insights into how compression techniques and quality factors impact image fidelity across various MRI magnetic field strengths. The findings of this study may prove valuable in recovering missing meta-tag information in historical image DICOM records and Context-Based Retrieval Systems (CBRS). The approach of using quality scores as features in training machine learning models, as demonstrated in this work, can be extended to other image groups where input parameters create statistically significant distinctions or are challenging to extract from images.

Nanostructured Polymer-Dispersed Liquid Crystals Using a Ferroelectric Smectic A Liquid Crystal.

Nanostructured polymer-dispersed liquid crystals (nano-PDLCs) are transparent and optically isotropic materials in which submicron-sized liquid crystal (LC) domains are dispersed within a polymer matrix. Nano-PDLCs can induce birefringence by applying an electric field (E-field) based on the reorientation of the LC molecules. If nano-PDLCs are utilized as light-scattering-less birefringence memory materials, it is necessary to suppress the relaxation of the LC molecule orientation after the removal of the E-field. We focused on the ferroelectric smectic A (SmA) phase to suppress the relaxation of LC molecules, owing to its layered structure and high viscosity. Although nano-PDLCs require a strong E-field to reorient their LC molecules because of the anchoring effect at the LC/polymer interface, the required field strength can be reduced using a ferroelectric smectic A (SmAF) LC with a large dielectric constant. In this study, we fabricated a nano-PDLC by shining an ultraviolet light on a mixture comprised an SmAF LC, photocurable monomers, and a photo-initiator. The electro-birefringence effect was evaluated using polarizing optical microscopy. After the removal of the E-field, an enhanced memory effect was observed in the sample using SmAF LC compared with nematic LC-based nano-PDLCs.

Prediction of MRI relaxometry in the presence of hepatic steatosis by Monte Carlo simulations.

To develop Monte Carlo simulations to predict the relationship of with liver fat content at 1.5T and 3.0T. For various fat fractions (FFs) from 1% to 25%, four types of virtual liver models were developed by incorporating the size and spatial distribution of fat droplets. Magnetic fields were then generated under different fat susceptibilities at 1.5T and 3.0T, and proton movement was simulated for phase accrual and MRI signal synthesis. The synthesized signal was fit to single-peak and multi-peak fat signal models for and proton density fat fraction (PDFF) predictions. In addition, the relationships between and PDFF predictions were compared with in vivo calibrations and Bland-Altman analysis was performed to quantitatively evaluate the effects of these components (type of virtual liver model, fat susceptibility, and fat signal model) on predictions. A virtual liver model with realistic morphology of fat droplets was demonstrated, and and PDFF values were predicted by Monte Carlo simulations at 1.5T and 3.0T. predictions were linearly correlated with PDFF, while the slope was unaffected by the type of virtual liver model and increased as fat susceptibility increased. Compared with in vivo calibrations, the multi-peak fat signal model showed superior performance to the single-peak fat signal model, which yielded an underestimation of liver fat. The -PDFF relationships by simulations with fat susceptibility of 0.6ppm and the multi-peak fat signal model were ( , ) at 1.5T and ( , ) at 3.0T. Monte Carlo simulations provide a new means for -PDFF prediction, which is primarily determined by fat susceptibility, fat signal model, and magnetic field strength. Accurate -PDFF calibration has the potential to correct the effect of fat on quantification, and may be helpful for accurate measurements in liver iron overload. In this study, a Monte Carlo simulation of hepatic steatosis was developed to predict the relationship between and PDFF. Furthermore, the effects of fat droplet morphology, fat susceptibility, fat signal model, and magnetic field strength were evaluated for the -PDFF calibration. Our results suggest that Monte Carlo simulations provide a new means for -PDFF prediction and this means can be easily generated for various regimes, such as simulations with higher fields and different echo times, as well as correction of magnetic susceptibility measurements for liver iron quantification.

Nanosized Eu3+-Doped NaY9Si6O26 Oxyapatite Phosphor: A Comprehensive Insight into Its Hydrothermal Synthesis and Structural, Morphological, Electronic, and Optical Properties.

Detailed analysis covered the optical and structural properties of Eu3+-doped NaY9Si6O26 oxyapatite phosphors, which were obtained via hydrothermal synthesis. X-ray diffraction patterns of NaY9Si6O26:xEu3+ (x = 0, 1, 5, 7, 10 mol% Eu3+) samples proved a single-phase hexagonal structure (P63/m (176) space group). Differential thermal analysis showed an exothermic peak at 995 °C attributed to the amorphous to crystalline transformation of NaY9Si6O26. Electron microscopy showed agglomerates composed of round-shaped nanoparticles ~53 nm in size. Room temperature photoluminescent emission spectra consisted of emission bands in the visible spectral region corresponding to 5D0 → 7FJ (J = 0, 1, 2, 3, 4) f-f transitions of Eu3+. Lifetime measurements showed that the Eu3+ concentration had no substantial effect on the rather long 5D0-level lifetime. The Eu3+ energy levels in the structure were determined using room-temperature excitation/emission spectra. Using the 7F1 manifold, the Nv-crystal field strength parameter was calculated to be 1442.65 cm-1. Structural, electronic, and optical properties were calculated to determine the band gap value, density of states, and index of refraction. The calculated direct band gap value was 4.665 eV (local density approximation) and 3.765 eV (general gradient approximation). Finally, the complete Judd-Ofelt analysis performed on all samples confirmed the experimental findings.

Effect of the Dispersion Medium on NMR Relaxation Properties of Superparamagnetic Iron Oxide Nanoparticles between 0.24 mT and 14.1 T.

Due to weak exchange interactions, magnetite particles at a critical diameter of about 20 nm are considered monodomain. At this size, they exhibit a phenomenological magnetic property called superparamagnetism, making them useful as magnetic resonance imaging contrast agents, or MRI CAs. However, questions persist regarding the impact of using different physiological solvents and varying the environment in which these particles are dispersed on their performance, determined by their relaxivity. A colloidal suspension of superparamagnetic iron oxide nanoparticles (SPIONs) electrostatically stabilized by citrate ligand was synthesized using a fast, reliable, and reproducible developed microwave approach, ensuring high stability over time at pH 7. We studied the effects of three physiological media on these MRI CAs. Ultrapure water was used for the synthesis, while phosphate-buffered saline and physiological liquid were used to disperse the nanoparticles, as these media contain essential electrolytes for the functioning of the human body. The SPIONs underwent systematic characterizations to determine their physicochemical and magnetic properties. This study reports the longitudinal relaxivities of SPIONs at medically relevant magnetic field strengths. Field dependence of their relaxivity (efficacy) was evaluated using a nuclear magnetic resonance dispersion (NMRD) profile measured over a wide range of proton resonance frequencies between 5 kHz and 600 MHz. The Roch et al. model (Roch, A.; et al. J. Chem. Phys., 1999, 110, 5403-5411) was used to analyze the NMRD profile and evaluate the impact of SPIONs on water proton relaxation in the different redispersion media. It was observed in this study that the dynamics of water protons are not influenced by the redispersion media of these citrate-coated SPIONs. However, the presence of salt ions notably reduces their relaxivities by lowering the saturation magnetization of SPIONs.

A regularisation technique to precisely infer limb darkening using transit measurements: Can we estimate stellar surface magnetic fields?

Abstract The high-precision measurements of exoplanet transit light curves that are now available contain information about the planet properties, their orbital parameters, and stellar limb darkening (LD). Recent 3D magneto-hydrodynamical (MHD) simulations of stellar atmospheres have shown that LD depends on the photospheric magnetic field, and hence its precise determination can be used to estimate the field strength. Among existing LD laws, the uses of the simplest ones may lead to biased inferences, whereas the uses of complex laws typically lead to a large degeneracy among the LD parameters. We have developed a novel approach in which we use a complex LD model but with second derivative regularisation during the fitting process. Regularisation controls the complexity of the model appropriately and reduces the degeneracy among LD parameters, thus resulting in precise inferences. The tests on simulated data suggest that our inferences are not only precise but also accurate. This technique is used to re-analyse 43 transit light curves measured by the NASA Kepler and TESS missions. Comparisons of our LD inferences with the corresponding literature values show good agreement, while the precisions of our measurements are better by up to a factor of 2. We find that 1D non-magnetic model atmospheres fail to reproduce the observations while 3D MHD simulations are qualitatively consistent. The LD measurements, together with MHD simulations, confirm that Kepler-17, WASP-18, and KELT-24 have relatively high magnetic fields (>200 G). This study paves the way for estimating the stellar surface magnetic field using the LD measurements.

Delamination and thrust force mitigation during drilling of unidirectional carbon fibre-reinforced plastic laminate using magnetorheological elastomer

Abstract In new improvements to the aviation industry, carbon fibre-reinforced plastic (CFRP) is a buoyant material due to its noteworthy and application-friendly properties. The behaviour of transversely isotropic CFRP, which prompts drilling-induced delamination, causes critical damage that leads to the rejection of the final product. The cause of the delamination damage is the thrust force generated by the drilling tool during the machining operation. The present work proposes an indigenous approach to suppress delamination significantly using magnetorheological elastomer (MRE). The thrust force generated by the drilling tool is recorded for varying magnetic field strengths. Delamination damage was computed using the MATLAB script. Meanwhile, specific focus was given to studying the interlaminar mechanics of a drilled hole through scanning electron microscopy. The results show that nearly 45% of the thrust force is reduced using this MRE at a maximum field strength of 0.4T compared to a conventional one. The results are further supported by a 22% and 30% smoothening of the delamination at the hole’s entry and exit, respectively. Thus, this approach helps to reduce delamination during drilling.

Transient induced response on cables by lightning electromagnetic pulse with different experimental conditions

The coupling of lightning electromagnetic pulse (LEMP) on cables can generate disruptive surge current and voltage, which may cause damage to devices or systems connected with cables. In this paper, a double toroidal magnetic field, through injection of an 8/20 μs lightning current into a double toroidal coil, is generated to induce indirect effects on nine communication/electrical cables. The impacts of different types and shielding methods of communication cables on induced surge current are evaluated, and the results show that twisted-pair cables with shielding layer have the best shielding effectiveness, with the ability to absorb more energy on the communication cables from LEMP. In addition, the study's findings demonstrate that the induction properties of cables are independent of the number of cores, but related to the shielding layer of cables. Meanwhile, simulation analysis in CST Studio Suite is carried out here, and results are basically similar to experimental results, with the difference attributed to the ignorance of some losses in the simulation environment. Finally, the magnetic field strength at each point of the LEMP is simulated, with some engineering proposals for the actual and simulated experiments.

Effects of gravity rainbow on scalar bosonic and oscillator fields in Bonnor–Melvin space-time with a cosmological constant

In this paper, we explore the relativistic quantum motion of spin-zero scalar charge-free particles influenced by rainbow gravity’s (RG’s) in Bonnor–Melvin magnetic space-time, a four-dimensional solution featuring a positive cosmological constant. We solve the Klein–Gordon equation in this scenario by using two sets of rainbow function: (i) f(χ)=1(1-βχ)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$f(\\chi )=\\frac{1}{(1-\\beta \\,\\chi )}$$\\end{document}, h(χ)=1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$h(\\chi )=1$$\\end{document} and (ii) f(χ)=1(1-βχ)=h(χ)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$f(\\chi )=\\frac{1}{(1-\\beta \\,\\chi )}=h(\\chi )$$\\end{document}, where 0<χ=|E|Ep≤1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0 < \\chi \\left( =\\frac{|E|}{E_p}\\right) \\le 1$$\\end{document} with Ep\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E_p$$\\end{document} being the Planck’s energy, E is the particle’s energy, and β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document} is the rainbow parameter. Furthermore, we study the relativistic quantum oscillator through the Klein–Gordon oscillator equation in the same Bonnor–Melvin magnetic space-time under RG effects. Employing the first pair of rainbow function, we obtain an approximate eigenvalue solution of the quantum oscillator fields. Notably, we demonstrate that the relativistic energy profile of scalar and oscillator particles are influenced by the topology of the geometry and the cosmological constant which is related with the magnetic field strength lies along the symmetry axis. Additionally, we see the impact of rainbow parameter on these approximate relativistic energy profiles in both quantum systems.

Signatures of substorm onset in thermodynamic model of geomagnetic tail

Earlier, an entropy switch model (ESM) for substorm onset as a result of the development of localized inner magnetospheric interchange-ballooning instability, was suggested. Shown observations testify that the substorm onset is accompanied by the reversal and strong fluctuations in key magnetospheric parameters such as total magnetic field strength, plasma pressure, entropy, and some others. Independently, similar behavior was attributed to a thermodynamic theory, where the onset of a substorm is regarded as a consequence of global energy development in the geomagnetic tail. In the latter, the geomagnetic tail is taken as an open thermodynamic system with an infinite number of conserved energy links (CEL) to the external space environment, and the shaping of the substorm profile is ultimately controlled by the system properties of the tail. A comparison between the signatures of substorm onset in the ESM and CEL models is conducted, and correspondence between experimental data and theoretical results is discussed.

Identification and classification of clusters of dipolar colloids in an external field.

Colloids can acquire a dipolar interaction in the presence of an external AC electric field. At high field strength, the particles form strings in the field direction. However, at weaker field strength, competition with isotropic interactions is expected. One means to investigate this interplay between dipolar and isotropic interactions is to consider clusters of such particles. Therefore, we have identified, using the GMIN basin-hopping tool, a rich library of lowest energy clusters of a dipolar colloidal system, where the dipole orientation is fixed to lie along the z axis and the dipole strength is varied for m-membered clusters of 7 ≤ m ≤ 13. In the regime where the isotropic and dipolar interactions are comparable, we find elongated polytetrahedral, octahedral, and spiral clusters as well as a set of non-rigid clusters, which emerge close to the transition to strings. We further implement a search algorithm that identifies these minimum energy clusters in bulk systems using the topological cluster classification [J. Chem. Phys. 139 234506 (2013)]. We demonstrate this methodology with computer simulations, which show instances of these clusters as a function of dipole strength.

Conceptual model of electrostatic non-ionizing air filter

Abstract Many infectious diseases such as SARS-CoV-2, rhinovirus, adenovirus, and influenza are transmitted through small respiratory droplets and various filtration systems are used to reduce the risk of airborne infection. Here, we develop a conceptual model of a filter, which is based on the electrostatic deposition of air droplets potentially containing pathogens. Within the model, we explore the effect of polarization of neutral spherical droplets moving in an air flow past cylindrical electrodes. The strength of electric field they produce is low enough to eliminate corona discharge and minimize air ionization, but high enough to capture the droplets. Based on the proposed model, we calculate the filtration efficiency in a quasi-continuous approximation. Also, we conduct numerical simulations of the deposition of respiratory droplets on a compact periodic array of cylindrical electrodes located at the nodes of a square lattice. The droplets with a radius of 10-20 μm pose the greatest threat in spreading the respiratory infections, and as we demonstrate, the proposed system is very effective in capturing droplets of this size, specifically, for a filter element with a width of about 5 mm, the filtration efficiency exceeds 90%.

Atmospheric escape in hot Jupiters under sub-Alfvénic interactions

ABSTRACT Hot Jupiters might reside inside the Alfvén surface of their host star wind, where the stellar wind is dominated by magnetic energy. The implications of such a sub-Alfvénic environment for atmospheric escape are not fully understood. Here, we employ 3D radiation-magnetohydrodynamic simulations and Ly-$\alpha$ transit calculations to investigate atmospheric escape properties of magnetized hot Jupiters. By varying the planetary magnetic field strength ($B_\mathrm{p}$) and obliquity, we find that the structure of the outflowing atmosphere transitions from a magnetically unconfined regime, where a tail of material streams from the nightside of the planet, to a magnetically confined regime, where material escapes through the polar regions. Notably, we find an increase in the planet escape rate with $B_\mathrm{p}$ in both regimes, with a local decrease when the planet transitions from the unconfined to the confined regime. Contrary to super-Alfvénic interactions, which predicted two polar outflows from the planet, our sub-Alfvénic models show only one significant polar outflow. In the opposing pole, the planetary field lines connect to the star. Finally, our synthetic Ly-$\alpha$ transits show that both the red-wing and blue-wing absorptions increase with $B_\mathrm{p}$. Furthermore, there is a degeneracy between $B_\mathrm{p}$ and the stellar wind mass-loss rate when considering absorption of individual Ly-$\alpha$ wings. This degeneracy can be broken by considering the ratio between the blue-wing and the red-wing absorptions, as stronger stellar winds result in higher blue-to-red absorption ratios. We show that, by using the absorption ratios, Ly-$\alpha$ transits can probe stellar wind properties and exoplanetary magnetic fields.

Ultrafast T1-T1ρ NMR for Correlating Different Motional Regimes of Molecules.

Nuclear magnetic resonance (NMR) relaxation times provide detailed information about molecular motions and local chemical environments. Longitudinal T1 relaxation time is most often sensitive to relatively fast, nano- to picosecond ranges of molecular motion. Rotating frame T1ρ relaxation time reflects a much slower, micro- to millisecond range of motion, and the motional regime can be tuned by changing spin-lock field strength. Conventional methods for measuring T1 and T1ρ relaxation times are time-consuming, since experiments must be repeated many times with incremented magnetization recovery or decay delay. In this work, we introduce two novel and efficient NMR methods to correlate the T1 and T1ρ relaxation times. The first method, IR-SPICY, combines the conventional T1 inversion recovery (IR) with the single-scan T1ρ detection-based spin-lock cycle (SPICY). The second method, ultrafast (UF) IR-SPICY, allows measurement of whole two-dimensional T1-T1ρ correlation data in a single scan, in a couple of seconds, based on spatial encoding of the T1 dimension. We demonstrate the performance of the methods by studying relaxation of water in porous silica and hydrogel samples, latter acting as a model of the articular cartilage extracellular matrix. The methods allow correlating different molecular motional regimes, potentially providing unprecedented information about various chemical and biochemical systems, such as structures and fluid dynamics in porous materials, macromolecular changes in tissues, and protein dynamics. One to three orders of magnitude shortened experiment time enable the studies of changing or degrading samples. Furthermore, the single-scan approach may significantly facilitate the use of modern nuclear-spin hyperpolarization techniques to enhance the sensitivity of T1-T1ρ measurements by several orders of magnitude.

Formation of a magnetized hybrid star with a purely toroidal field from phase-transition-induced collapse

ABSTRACT Strongly magnetized neutron stars are popular candidates for producing detectable electromagnetic and gravitational-wave signals. Gravitational collapses of neutron stars triggered by a phase transition from hadrons to deconfined quarks in the cores could also release a considerable amount of energy in the form of gravitational waves and neutrinos. Hence, the formation of a magnetized hybrid star from such a phase-transition-induced collapse is an interesting scenario for detecting all these signals. These detections may provide essential probes for the magnetic field and composition of such stars. Thus far, a dynamical study of the formation of a magnetized hybrid star from a phase-transition-induced collapse has yet to be realized. Here, we investigate the formation of a magnetized hybrid star with a purely toroidal field and its properties through dynamical simulations. We find that the maximum values of rest-mass density and magnetic field strength increase slightly and these two quantities are coupled in phase during the formation. We then demonstrate that all microscopic and macroscopic quantities of the resulting hybrid star vary drastically when the maximum magnetic field strength goes beyond a threshold of $\sim 5 \times 10^{17}$ G, but they are insensitive to the magnetic field below this threshold. Specifically, the magnetic deformation makes the rest-mass density drop significantly, suppressing the matter fraction in the mixed phase. These behaviours agree with those in the equilibrium models of previous studies. Therefore, this work provides a solid support for the magnetic effects on a hybrid star.

Characterizing brain mechanics through 7 tesla magnetic resonance elastography

Magnetic resonance elastography (MRE) is a non-invasive method for determining the mechanical response of tissues using applied harmonic deformation and motion-sensitive MRI. MRE studies of the human brain are typically performed at conventional field strengths, with a few attempts at the ultra-high field strength, 7T, reporting increased spatial resolution with partial brain coverage. Achieving high-resolution human brain scans using 7T MRE presents unique challenges of decreased octahedral shear strain-based signal-to-noise ratio (OSS-SNR) and lower shear wave motion sensitivity. In this study, we establish high resolution MRE at 7T with a custom 2D multi-slice single-shot spin-echo echo-planar imaging sequence, using the Gadgetron advanced image reconstruction framework, applying Marchenko-Pastur Principal component analysis denoising, and using nonlinear viscoelastic inversion. These techniques allowed us to calculate the viscoelastic properties of the whole human brain at 1.1 mm isotropic imaging resolution with high OSS-SNR and repeatability. Using phantom models and 7T MRE data of eighteen healthy volunteers, we demonstrate the robustness and accuracy of our method at high-resolution while quantifying the feasible tradeoff between resolution, OSS-SNR, and scan time. Using these post-processing techniques, we significantly increased OSS-SNR at 1.1 mm resolution with whole-brain coverage by approximately 4-fold and generated elastograms with high anatomical detail. Performing high-resolution MRE at 7T on the human brain can provide information on different substructures within brain tissue based on their mechanical properties, which can then be used to diagnose pathologies (e.g. Alzheimer's disease), indicate disease progression, or better investigate neurodegeneration effects or other relevant brain disorders,in vivo.

Research on Collision Warning Method for Ship-Bridge Based on Safety Potential Field

In order to ensure the safety of navigation in a bridge area, and based on the theory of the safety potential field, a method of ship safety assessment and early warning in an inland river bridge area is proposed. Firstly, the risk elements associated with ship collisions in a bridge area are classified. Secondly, these risks are quantified using the potential energy field, the boundary potential field and the behavioural field, and then the ship state under the influence of wind flow, predicted by the Kalman filter, is quantified using the kinetic energy field. Then, the above four potential energy fields are merged to obtain a superposition field, and the magnitude of the instantaneous risk in the bridge area is obtained based on its magnitude. Finally, the change of field strength values under different moments is used for early warning. The results of the simulation of a ship passing through the piers of the Baijusi Bridge show that the model can effectively quantify the risk of a ship–bridge collision in the inland bridge area and provide real-time warning of the risk of a ship–bridge collision in the bridge area, which is of great significance for improving the safety of the inland bridge area.

Characterization of AI-enhanced magnetophoretic transistors operating in a tri-axial magnetic field for on-chip bioparticle sorting.

We demonstrate two general classes of magnetophoretic transistors, called the "trap" and the "repel-and-collect" transistors, capable of switching single magnetically labeled cells and magnetic particles between different paths in a microfluidic chamber. Compared with prior work on magnetophoretic transistors operating in a two-dimensional in-plane rotating field, the use of a tri-axial magnetic field has the fundamental advantages of preventing particle cluster formation and better syncing of single particles with the general operating clock. We use finite element methods to investigate the energy distribution on the chip surface and to predict the particle behavior at various device geometries. We then fabricate the proposed transistors and compare the experimental results with the simulation predictions. We found that with gate electrical currents of ~ 40mA for a transistor with proper geometry, complete switching of magnetic particles with diameters in the range of 8-15μm is achieved. We show that the device is reliable and works well at different magnetic field strengths (50-100 Oe) and frequencies (0.05-0.5Hz). We also employed an image processing code with a trained convolutional neural network to automate the proposed transistors for identifying and sorting particles with various sizes and magnetic susceptibilities with accuracies higher than 98%. The proposed transistors can be used in designing novel magnetophoretic circuits for important applications in biomedical microdevices and single-cell biology.

Second harmonic generation based on graphene hyperstructure for higher resolution and performance on top of achieving fundamental wave detection in theory

In this paper, an innovative one-dimensional graphene hyperstructure (GHS) is proposed, allowing for the concurrent detection of multiple physical parameters in both the fundamental and second harmonic generation. The sensing characteristics of GHS pertaining to magnetic field strength (B), incident electromagnetic wave angle (θ), and graphene thickness (dgt) are systematically investigated. Moreover, through the incorporation of second harmonic generation alongside fundamental detection, higher resolution and performance are achieved. The findings indicate an expansion of the measurement range for B, θ, and dgt, from 0.3∼0.5 T, 35∼55°, and 1∼6 layers to 0.3∼1 T, 35∼65°, and 1∼10 layers, providing increased flexibility and adjustability. Additionally, by leveraging nonlinear effects and widening the Fabry-Perot cavity width, this structure effectively enhances the quality factor (Q) from 2.94 × 102 to 1.95 × 105, resulting in a substantial improvement in sensing performance. This development holds tremendous promise in surpassing the diffraction limit and addressing high-Q value sensing requirements. In comparison to conventional detectors, the GHS not only enhances detection efficiency but also harbors the potential for multiple physical quantities detection. This forward-looking research is pivotal in its successful resolution of detector performance limitations, ushering in novel possibilities across diverse domains.