Small Scattering Research Articles

The Linear Sampling Method for Data Generated by Small Random Scatterers

The Linear Sampling Method for Data Generated by Small Random Scatterers

Free-electron coupling to surface polaritons mediated by small scatterers.

The ability of surface polaritons (SPs) to enhance and manipulate light fields down to deep-subwavelength length scales enables applications in optical sensing and nonlinear optics at the nanoscale. However, the wavelength mismatch between light and SPs prevents direct optical excitation of surface-bound modes, thereby limiting the widespread development of SP-based photonics. Free electrons are a natural choice to directly excite strongly confined SPs because they can supply field components of high momentum at designated positions with subnanometer precision. Here, we theoretically explore free-electron-SP coupling mediated by small scatterers and show that low-energy electrons can efficiently excite surface modes with a maximum probability reached at an optimum surface-scatterer distance. By aligning the electron beam with a periodic array of scatterers placed near a polariton-supporting interface, in-plane Smith-Purcell emission results in the excitation of surface modes along well-defined directions. Our results support using scattering elements to excite SPs with low-energy electrons.

Metagratings for underwater acoustic wavefront manipulation

Metagratings are flat periodic assemblies of small scatterers, engineered to achieve effects such as steering, beamforming, or absorption. They have recently received attention in both electromagnetism and acoustic fields. In this work, we report the design, modeling, and experimental characterization of metagratings to steer underwater acoustic wavefronts towards anomalous directions (i.e. not classically allowed by Snell-Decartes relationships) with high efficiency (close to 100%). They are build from simple assemblies of small brass cylinders, hold by 3D-printed plastic supports, and can redirect ultrasonic wavefronts either in reflection mode (when placed in front of a reflective surface like e.g. the water / air interface) or in transmission mode. Furthermore, we demonstrate how metagratings build from an asymmetrical pattern of multiple basic elements can achieve near perfect asymmetrical transmission: a wavefront incident from side of the structure is fully transmitted, while a similar wavefront incoming from the other side is fully reflected, achieving an acoustic one-way mirror effect. This work combine theoretical analysis, finite element modeling, and experimentation in water tanks to explore and demonstrate the potential of such metagratings for various applications in underwater acoustics, like communication, noise mitigation, and stealth.

Spatially Separate Center-to-Surround Radiation Structure Induced Tandem Electron Transfer Effect for Stable and Enhanced Photocatalysis.

Spatially separate anchoring redox cocatalysts on the photocatalyst to shunt the charge migration paths is an effective route to regulate the charge flow. Differently, we herein introduce an artificially synthesized Sun-planet-like spatially separated center-to-surround radiation photosensitizer-cocatalyst structure to regulate electron flow in a tandem manner. A single Au sphere acts as the Sun/photosensitizer in the center, and small Pt particles scatter around as the planets/cocatalyst, both of which are fixed inside the MOF crystal. Such a structure can not only simultaneously increase the light harvesting capacity and electron migration kinetics but also optimize the electron transfer pathway to minimize the electron migration distance, so that the hot electrons generated by Au can be quickly transferred to Pt through MOF before annihilation, leading to a significant photoactivity promotion.

Intercomparison of sensible and latent heat flux measurements from combined eddy covariance, energy balance, and Bowen ratio methods above a grassland prairie

We present a comparison of four different methods of measuring sensible (H) and latent (LE) heat fluxes for a year over a mixed grass prairie ecosystem in the Nebraska SandHills [eddy covariance (EC), energy balance/Bowen ratio (EBBR), residual energy (RES), modified Bowen ratio (MBR) methods]. Additionally, we developed a set of quality control criteria for each method and present a simplification to the traditional EBBR setup. Using EC as reference, all methods yielded similar estimates of yearly H (regression slopes (m) ~ 2% from unity; HEC > HEBBR, HRES, and HMBR). For yearly LE, EBBR and RES yielded similar estimates with EC (m ~ 2% from unity; LEEC < LEEBBR and LERES), while a larger bias was found from MBR (m ~ 8% from unity; LEEC > LEMBR). At shorter time scales (~ hourly), moderate scatter was found about linear regression fits for H between EBBR and EC (R2 = 0.81), with smaller scatter between RES and MBR, and EC (R2 = 0.91). For LE, smaller scatter was also measured between EC, and EBBR and RES (R2 = 0.89 and 0.87, respectively), with the larger scatter between EC and MBR (R2 = 0.65). This suggests methods other than EC may be well suited to longer-term applications (≥ yearly), but have larger uncertainty on individual measurements.

Effect of concrete cover on the pure torsional behavior of reinforced concrete beams: Analytical model

Experimental data on RC members subjected to pure torsion is compiled from published studies so far. Interestingly, the past studies have concentrated largely on members with small to moderate concrete covers, with handful data on members with thick concrete cover. Widely accepted torsion models including the diagonal compression field theory (CFT), softened truss model (STM) and softened membrane model for torsion (SMMT) are verified on the domains of experimental data missing-in specimens with thick concrete cover. With increasing demand for durability design of RC structures use of thick concrete cover, say up to 75 mm, is being introduced in practice. Recent experimental investigation by the authors demonstrated that spalling of concrete cover, particularly in cases of thick covers, significantly impacts the torsional behavior of RC members. The present study uses these set of experiments to look at the response prediction capability of the existing advanced models and assess the reliability of existing concrete cover spalling theories. For cases with thick cover, the existing models either did not adequately capture the ultimate capacity or erroneously predicted the torsional behavior of the members due to the different mechanics between RC beams with thin and thick covers. Similarly, the spalling theories failed to fully explain the physically observed spalling behavior. Guided by the recent experimental observations and the apparent gaps, the study provides a rational theory for the spalling of concrete cover. The initiation and gradual evolution of concrete cover spalling is traced by observing the acting spalling moment and spalling resistance formulated in the proposed spalling model. The proposed spalling model inherently assumes members susceptibility to spalling of cover concrete and is governed by, the thickness of the concrete cover, tensile strength of concrete, presence of rebar cage and their location, and size of the member. The theory is unified and can explain the spalling of cover due to torsion as well as shear. Its capability is examined by integrating the approach into existing truss model. When compared with state-of-the-art models, the proposed method provides consistent prediction with a relatively smaller scatter, for cases with thick concrete cover as well.

The impact of environment on size: Galaxies are 50% smaller in the Fornax Cluster compared to the field

Size is a fundamental parameter for measuring the growth of galaxies and the role of the environment on their evolution. However, the conventional size definitions used for this purpose are often biased and miss the diffuse, outermost signatures of galaxy growth, including star formation and gas accretion. We address this issue by examining low surface brightness truncations or galaxy `edges' as a physically motivated tracer of size based on star formation thresholds. Our total sample consists of $ galaxies with stellar masses ranging from $10^5 odot &lt; M_ star M_ odot $. This sample of nearby cluster, group satellite, and nearly isolated field galaxies was compiled using multi-band imaging from the Fornax Deep Survey, deep IAC Stripe 82, and Dark Energy Camera Legacy Surveys. We find that the edge radii scale as $R_ edge star $, with a very small intrinsic scatter ($ 0.07$\,dex). The scatter is driven by the morphology and environment of galaxies. In both the cluster and field, early-type dwarfs are systematically smaller by approximately $20&lt;!PCT!&gt;$ compared to late-type dwarfs. However, galaxies in the Fornax cluster are the most impacted. At a fixed stellar mass, edges in the cluster can be found at about 50&lt;!PCT!&gt; smaller radii, and the average stellar surface density at the edges is a factor of two higher, $ odot $/pc$^2$. Our findings support the rapid removal of loosely bound neutral hydrogen ( ) in hot, crowded environments, which truncates galaxies outside-in earlier, preventing the formation of more extended sizes and lower density edges. Our results highlight the importance of deep imaging surveys to the study of low surface brightness imprints of the large-scale structure and environment on galaxy evolution.

Cyclic damage quantification in composite materials using discrete damage mechanics

A method for fatigue damage quantification in composite materials, based on experimental stiffness degradation data for composite laminates subjected to cyclic load is proposed. Discrete damage mechanics theory is used to calculate crack density vs. number of cycles from elastic moduli-reduction data obtained during fatigue experiments. The calculated crack density simplifies fatigue testing by diminishing the need for counting cracks during testing. Accurate results are achieved and reported. The defect-nucleation rate, which controls the fatigue damage rate, is also obtained from processing the modulus-reduction data. It is observed that the defect-nucleation rate has a small scatter and is independent of applied load magnitude. Furthermore, the onset of delamination observed in the experiments correlates very well with the onset of deviation between the predicted and experimental curves of elastic moduli-reduction versus accumulated crack density. An additional parameter, the defect-nucleation threshold, is here proposed to further characterize the fatigue performance of the composite material under stress-controlled fatigue loading, in contrast to thermal fatigue results from the literature. Furthermore, the difference in damage nucleation rate between strain-controlled and stress-controlled was observed and discussed.

Molecular beam scattering from flat jets of liquid dodecane and water

AbstractMolecular beam experiments in which gas molecules are scattered from liquids provide detailed, microscopic perspectives on the gas–liquid interface. Extending these methods to volatile liquids while maintaining the ability to measure product energy and angular distributions presents a significant challenge. The incorporation of flat liquid jets into molecular beam scattering experiments in our laboratory has allowed us to demonstrate their utility in uncovering dynamics in this complex chemical environment. Here, we summarize recent work on the evaporation and scattering of Ne, CD4, ND3, and D2O from a dodecane flat liquid jet and present first results on the evaporation and scattering of Ar from a cold salty water jet. In the evaporation experiments, Maxwell–Boltzmann flux distributions with a cosθ angular distribution are observed. Scattering experiments reveal both impulsive scattering (IS) and trapping followed by thermal desorption (TD). Super‐specular scattering is observed for all four species scattered from dodecane and is attributed to anisotropic momentum transfer to the liquid surface. In the IS channel, rotational excitation of the polyatomic scatterers is a significant energy sink, and these species accommodate more readily on the dodecane surface compared to Ne. Our preliminary results on cold salty water jets suggest that Ar atoms undergo some vapor‐phase collisions when evaporating from the liquid surface. Initial scattering experiments characterize the mechanisms of Ar interacting with an aqueous jet, allowing for comparison to dodecane systems.Key Points Molecular beam scattering from flat liquid jets is a powerful technique to elucidate mechanistic detail at the gas–liquid interface. Previous dodecane scattering experiments have uncovered angularly‐resolved thermal desorption fractions and energy transfer at the interface for several small molecule scatterers. Preliminary results on scattering from cold salty water reveal mechanisms of interaction between argon and an aqueous jet.

Robust design of turbine blades with friction contacts in the presence of multiple response levels

Dry friction damping is a widely used solution to mitigate vibrations of turbine blades. At design stage, the computation of the forced response of assemblies of bodies in contact (whose relative motion could result in dry friction damping) could give non-unique solutions due to the possibility of having different static equilibria. Infinite possible vibratory levels in a range are hence possible. A desirable condition for designers is to deal with systems whose response boundaries are not far from each other, i.e. with a low scatter in the response. For systems with multiple vibration levels, the notion of robustness (a robust system has a small response scatter, and viceversa), is particularly important.A robust design is hence needed for such assemblies. Once a design parameter is identified, two possible approaches are possible to accomplish this task.The so-called manual approach explores a certain number of values of the design parameter belonging to a certain interval, and chooses the most robust configuration among those calculated. This computation could result in a huge effort if the number of considered values of the design parameter is high.To overcome this issue, a second approach is here proposed. It is based on a Nested Optimization Algorithm (NOA), which consists in two levels of optimization in order to directly find the most robust configuration in the considered range for the design parameter.In this paper, NOA is applied to a particular test case consisting in a lumped-parameter system simulating three blades with two UPDs interposed among them. Such a system provides the necessary coupling between different contact interfaces necessary to obtain multiple response levels. In addition, it is useful to investigate the mutual interaction among different UPDs.Results of NOA are presented together with the results of the manual approach in order to give a validation of the double optimization. Dependence of the response scatter from the contact states of the interfaces is also investigated.

Improving metallicity estimates for very metal-poor stars in the Gaia DR3 GSP-Spec catalog

Context. In the latest Gaia Data Release (DR3), the GSP-Spec module has provided stellar parameters and chemical abundances measured from the RVS spectra alone. However, the GSP-Spec parameters – including metallicity – for very metal-poor (VMP; [Fe/H] &lt; −2) stars suffer from parameter degeneracy due to a lack of information in their spectra, and are therefore affected by a large measurement uncertainty and systematic offset. Furthermore, the recommended quality cuts filter out the majority (~80%) of the VMP stars because some of them are confused with hot stars or with cool K- and M-type giants, for which the current pipeline is known to have problems. Aims. We aim to provide more precise metallicity estimates for VMP stars analyzed by the GSP-Spec module by taking photometric information into account in the analysis and breaking the degeneracy. Methods. We reanalyzed FGK-type stars in the GSP-Spec catalog by computing the Ca triplet equivalent widths from the published set of GSP-Spec stellar parameters. We compared these recovered equivalent widths with the values directly measured from public Gaia RVS spectra and investigated the precision of the recovered values and the parameter range within which the recovered values are reliable. We then converted the recovered equivalent widths to metallicities by adopting photometric temperatures and surface gravities that we derive based on Gaia and 2MASS catalogs. Results. The recovered equivalent widths agree with the directly measured values with a scatter of 0.05 dex for the stars that pass the GSP-Spec quality cuts. Among the stars recommended for filtering out, we observe a similar scatter for FGK-type stars initially misidentified as hot stars. Contrarily, we find a poorer agreement, in general, for stars that the GSP-Spec identifies as cool K- and M-type giants, although we can still define subsets that show reasonable agreement. At the low-metallicity end ([Fe/H] &lt; −1.5), our metallicity estimates have a typical uncertainty of 0.18 dex, which is about half of the quoted GSP-Spec metallicity uncertainty at the same metallicity. Our metallicities also show better agreement with the high-resolution literature values than the original GSP-Spec metallicities at low metallicity; the scatter in the comparison decreases from 0.36–0.46 dex to 0.17−0.29 dex for stars that satisfy the GSP-Spec quality cuts. While the GSP-Spec metallicities show increasing scatter when misidentified “hot” stars and the subsets of the “cool K- and M-type giants” are included (up to 1.06 dex), we can now identify them as FGK-type stars and provide metallicities that show a small scatter in the comparisons (up to 0.34 dex), which helps us to increase the number of VMP stars with reliable and precise metallicity. Conclusions. The inclusion of photometric information greatly contributes to breaking parameter degeneracy, enabling precise metallicity estimates for VMP stars from Gaia RVS spectra. We produce a publicly available catalog of bright metal-poor stars suitable for high-resolution follow-up. The sample contains about 2345 VMP stars with an estimated contamination rate of 5%.

Stellar Variability and Distance Indicators in the Near-infrared in Nearby Galaxies. I. RR Lyrae and Anomalous Cepheids in Draco Dwarf Spheroidal

The Draco Dwarf spheroidal (dSph) galaxy is one of the nearest and the most dark-matter-dominated satellites of the Milky Way. We obtained multiepoch near-infrared (NIR, JHK s ) observations of the central region of Draco dSph covering a sky area of ∼21′ × 21′ using the WIRCam instrument at the 3.6 m Canada–France–Hawaii Telescope. Homogeneous JHK s time-series photometry for 212 RR Lyrae (173 fundamental-mode, 24 first-overtone, and 15 mixed-mode variables) and five Anomalous Cepheids in Draco dSph are presented and used to derive their period–luminosity relations at NIR wavelengths for the first-time. The small scatter of ∼0.05 mag in these empirical relations for RR Lyrae stars is consistent with those in globular clusters and suggests a very small metallicity spread, up to ∼0.2 dex, among these centrally located variables. Based on empirically calibrated NIR period–luminosity–metallicity relations for RR Lyrae in globular clusters, we determined a distance modulus to Draco dSph of μ RRL = 19.557 ± 0.026 mag. The calibrated K s -band period–luminosity relations for Anomalous Cepheids in the Draco dSph and the Large Magellanic Cloud exhibit statistically consistent slopes but systematically different zero points, hinting at possible metallicity dependence of ∼ − 0.3 mag dex−1. Finally, the apparent magnitudes of the tip of the red-giant branch in I and J bands also agree well with their absolute calibrations with the adopted RR Lyrae distance to Draco. Our recommended ∼1.5% precise RR Lyrae distance, D Draco = 81.55 ± 0.98(statistical) ± 1.17(systematic) kpc, is the most accurate and precise distance to Draco dSph galaxy.

Deep Neighborhood-aware Proxy Hashing with Uniform Distribution Constraint for Cross-modal Retrieval

Cross-modal retrieval methods based on hashing have gained significant attention in both academic and industrial research. Deep learning techniques have played a crucial role in advancing supervised cross-modal hashing methods, leading to significant practical improvements. Despite these achievements, current deep cross-modal hashing still encounters some underexplored limitations. Specifically, most of the available deep hashing usually utilizes pair-wise or triplet-wise strategies to promote the separation of the inter-classes by calculating the relative similarities between samples, weakening the compactness of intra-class data from different modalities, which could generate ambiguous neighborhoods. In this article, the Deep Neighborhood-aware Proxy Hashing (DNPH) framework is proposed to learn a discriminative embedding space with the original neighborhood relation preserved. By introducing learnable shared category proxies, the neighborhood-aware proxy loss is proposed to project the heterogeneous data into a unified common embedding, in which the sample is pulled closer to the corresponding category proxy and is pushed away from other proxies, capturing small within-class scatter and big between-class scatter. To enhance the quality of the obtained binary codes, the uniform distribution constraint is developed to make each hash bit independently obey the discrete uniform distribution. In addition, the discrimination loss is designed to preserve modality-specific semantic information of samples. Extensive experiments are performed on three benchmark datasets to prove that our proposed DNPH framework achieves comparable or even better performance compared with the state-of-the-art cross-modal retrieval applications. The corresponding code implementation of our DNPH framework is as follows: https://github.com/QinLab-WFU/OUR-DNPH .

Metal enrichment: the apex accretor perspective

The goal of this work is to devise a description of the enrichment process in large-scale structure that explains the available observations and makes predictions for future measurements. We took a spartan approach to this study, employing observational results and algebra to connect stellar assembly in star-forming halos with metal enrichment of the intra-cluster and group medium. On one hand, our construct is the first to provide an explanation for much of the phenomenology of metal enrichment in clusters and groups. It sheds light on the lack of redshift evolution in metal abundance, as well as the small scatter of metal abundance profiles, the entropy versus abundance anti-correlation found in cool core clusters, and the so-called Fe conundrum, along with several other aspects of cluster enrichment. On the other hand, it also allows us to infer the properties of other constituents of large-scale structure. We find that gas that is not bound to halos must have a metal abundance similar to that of the ICM and only about one-seventh to one-third of the Fe in the Universe is locked in stars. A comparable amount is found in gas in groups and clusters and, lastly and most importantly, about three-fifths of the total Fe is contained in a tenuous warm or hot gaseous medium in or between galaxies. We point out that several of our results follow from two critical but well motivated assumptions: 1) the stellar mass in massive halos is currently underestimated and 2) the adopted Fe yield is only marginally consistent with predictions from synthesis models and SN rates. One of the most appealing features of the work presented here is that it provides an observationally grounded construct where vital questions on chemical enrichment in the large-scale structure can be addressed. We hope that it may serve as a useful baseline for future works.

Detecting the edges of galaxies with deep learning

Galaxy edges or truncations are low-surface-brightness (LSB) features located in the galaxy outskirts that delimit the distance up to where the gas density enables efficient star formation. As such, they could be interpreted as a non-arbitrary means to determine the galaxy size and this is also reinforced by the smaller scatter in the galaxy mass-size relation when comparing them with other size proxies. However, there are several problems attached to this novel metric, namely, the access to deep imaging and the need to contrast the surface brightness, color, and mass profiles to derive the edge position. While the first hurdle is already overcome by new ultra-deep galaxy observations, we hereby propose the use of machine learning (ML) algorithms to determine the position of these features for very large datasets. We compare the semantic segmentation by our deep learning (DL) models with the results obtained by humans for HST observations of a sample of 1052 massive (Mstellar &gt; 1010 M⊙) galaxies at z &lt; 1. In addition, the concept of astronomic augmentations is introduced to endow the inputs of the networks with a physical meaning. Our findings suggest that similar performances than humans could be routinely achieved, although in the majority of cases, the best results are obtained by combining (with a pixel-by-pixel democratic vote) the output of several neural networks using ensemble learning. Additionally, we find that using edge-aware loss functions allows for the networks to focus their optimization on the galaxy boundaries and, therefore, to provide estimates that are much more sensitive to the presence of neighboring bodies that may affect the shape of the truncation. The experiments reveal a great similarity between the semantic segmentation performed by the AI compared to the human model. For the best model, an average dice of 0.8969 is achieved, while an average dice of 0.9104 is reached by the best ensemble, where the dice coefficient represents the harmonic mean between the precision and the recall. This methodology will be profusely used in future datasets, such as that of Euclid, to derive scaling relations that are expected to closely follow the galaxy mass assembly. We also offer to the community our DL algorithms in the author's github repository.

Numerical extraction of three-dimensional acoustic polarizabilities for acoustically small scatterers

Polarizability is a convenient descriptor for scattering from low-ka inhomogeneities in both electromagnetism, where it originated, and in acoustics, where it is increasingly used in the design of metamaterial elements. In two or three dimensions, the polarizability is represented by a block matrix that couples the local pressure and particle velocity fields to the lowest-order components of the multipole expansion, usually truncated to dipole order. A fully dense acoustic polarizability matrix has components that couple spatially uniform pressure and velocity oscillations to dipole and monopole scattering, respectively. This unique coupling leads to acoustic bianisotropy, also known as Willis coupling, for a collection of scatterers. The design of Willis materials necessitates computationally efficient methods to extract all components of the polarizability matrix and, at present, only two-dimensional analytical extraction methods are found in the literature. In this work, we present an algorithm to extract all components of the three-dimensional polarizability matrix from a scatterer with arbitrary geometry and composition. The method presented here is numerically efficient and yields results that are in agreement with an analytically obtained benchmark polarizability, providing a useful tool for acoustic metamaterial design.

A Comparative Study between M30 and M92: M92 is a Merger Remnant with a Large Helium Enhancement

We perform a comparative study of the ex situ second-parameter pair globular clusters (GCs) M30 and M92, having similar metallicities but different horizontal branch morphologies. We obtain similar mean primordial carbon abundances for both clusters. However, M92 shows a large dispersion in carbon due to a more extended C–N anticorrelation, while M30 exhibits a higher primordial nitrogen abundance, suggesting that they have different chemical enrichment histories. Our new results confirm our previous result that M92 is a metal-complex GC showing a bimodal metallicity distribution. We also find that the metal-rich group of stars in M92 shows a helium enhancement as large as ΔY ∼ 0.05 from the red giant branch bump V magnitudes, which can also be supported by (i) a lack of bright red giant branch stars, (ii) synthetic evolutionary horizontal branch population models and (iii) the more extended spatial distribution due to different degree of the diffusion process from their lower masses. We reinterpret the [Eu/Fe] measurements by others, finding that the two metallicity groups of stars in M92 have significantly different [Eu/Fe] abundances with small scatters. This strongly suggests that they formed independently out of well-mixed interstellar media in different environments. We suggest that M92 is a more complex system than a normal GC, most likely a merger remnant of two GCs or an even more complex system. In the Appendix, we address the problems with the recently developed color–temperature relations and the usage of broadband photometry in the populational taggings.

MAGNETOTHERMAL PROPERTIES OF COPPER FERRITE

In this work, we carried out the directed synthesis of copper ferrite (CuFe2O4) by co-precipitation from solutions with an excess of alkali at a temperature of 373 К. The methods of scanning electron microscopy and X-ray phase analysis were used to study the crystal structure and surface morphology of copper ferrite. The ratio of the characteristic peaks of the diffractogram was carried out in accordance with the JCPDS database. It is shown that copper (II) ferrite crystallizes in the structure of the cubic spinel. Microphotographs of the synthesized copper ferrite samples at different magnifications are given. It is established that ferrite particles consist of conglomerates of crystals with different sizes of individual grains. Their small scatter in size is observed. The average particle size is in the range of 100-200 nm. Using a dynamic heat flux differential scanning calorimeter, the temperature dependence of the heat capacity of copper ferrite samples was obtained in the temperature range of 273–373 K. Using an original microcalorimetric setup in the temperature range of 288–346 K and with a change in the magnetic field induction from 0 to 1.0 T, thermodynamic characteristics were obtained - the magnetocaloric effect (MCE) and the change in entropy (ΔS) during the magnetization of copper (II) ferrite. It was found that with an increase in the magnitude of the magnetic field, the magnitude of the MCE increases and decreases with increasing temperature. It was found that the temperature dependences of the magnetocaloric effect and specific heat have an extreme character. In the region of room temperatures (308–315 K), a maximum of the magnetocaloric effect and a minimum of the specific heat are observed. This previously unknown anomalous behavior of the magneto-thermal properties of copper II ferrite was discovered for the first time.

Hermite-scan imaging for differentiating glioblastoma from normal brain: Simulations and ex vivo studies for applications in intra-operative tumor identificationa).

Hermite-scan (H-scan) imaging is a tissue characterization technique based on the analysis of raw ultrasound radio frequency (RF) echoes. It matches the RF echoes to Gaussian-weighted Hermite polynomials of various orders to extract information related to scatterer diameter. It provides a color map of large and small scatterers in the red and blue H-scan image channels, respectively. H-scan has been previously reported for characterizing breast, pancreatic, and thyroid tumors. The present work evaluated H-scan imaging to differentiate glioblastoma tumors from normal brain tissue ex vivo. First, we conducted 2-D numerical simulations using the k-wave toolbox to assess the performance of parameters derived from H-scan images of acoustic scatterers (15-150 μm diameters) and concentrations (0.2%-1% w/v). We found that the parameter intensity-weighted percentage of red (IWPR) was sensitive to changes in scatterer diameters independent of concentration. Next, we assessed the feasibility of using the IWPR parameter for differentiating glioblastoma and normal brain tissues (n = 11 samples per group). The IWPR parameter estimates for normal tissue (44.1% ± 1.4%) were significantly different (p < 0.0001) from those for glioblastoma (36.2% ± 0.65%). These findings advance the development of H-scan imaging for potential use in differentiating glioblastoma tumors from normal brain tissue during resection surgery.

The characteristic shape of damping wings during reionization

ABSTRACT Spectroscopic analysis of Ly α damping wings of bright sources at z &amp;gt; 6 is a promising way to measure the reionization history of the universe. However, the theoretical interpretation of the damping wings is challenging due to the inhomogeneous nature of the reionization process and the proximity effect of bright sources. In this Letter, we analyse the damping wings arising from the neutral patches in the radiative transfer cosmological simulation suite cosmic reionization on computers. We find that the damping wing profile remains a tight function of volume-weighted neutral fraction &amp;lt;xH i&amp;gt;v, especially when &amp;lt;xH i&amp;gt;v &amp;gt; 0.5, despite the patchy nature of reionization and the proximity effect. This small scatter indicates that with a well-measured damping wing profile, we could constrain the volume-weighted neutral fraction as precise as Δ &amp;lt;xH i&amp;gt;v ≲ 0.1 in the first half of reionization. Due to resonant Ly α absorption from the residual neutral hydrogen inside the ionized bubble, it may be challenging to find the starting point of the damping wing for faint sources like normal galaxies or gamma-ray bursts. However, for bright sources like quasars, it is hopeful to measure the entire damping wing and use them to measure the neutral fraction accurately.