Maximum Cross Section Research Articles

Analytical method for predicting interference in ion mobility spectrometric detection of drug compounds with phthalates

In ion mobility spectrometry (IMS), ions are distinguished by their mobility through a gas, which depends on their size, shape, and charge. Ions with very similar reduced ion mobility (Ko) values are not separated. This technique is widely used for the onsite detection of drug compounds. However, the presence of phthalates can interfere with IMS-based detection of drug compounds because some of them may have Ko values similar to those of drug compounds. In this study, the interference of phthalates in the IMS detection of drug compounds was investigated using drug compounds and phthalates in the molecular weight range of 134–335 g mol−1. The relationships between Ko and the m/z value, collision cross section (CCS), maximum cross section (CSmax), and minimum cross section (CSmin) of the product ions were examined. The CSmax and CSmin values were calculated from the energy-minimized structures of the ions. It was found that the m/z, CCS, and CSmax values were not closely related to the Ko value. However, the CSmin values showed a strong correlation with the Ko values, exhibiting excellent linear relationships with R2 values of 0.997 for the drug compounds and 0.990 for the phthalates. By comparing the CSmin values of drug compounds and phthalates, the probability of their peaks overlapping in the IMS spectra can be determined. For chemicals that are difficult to identify, the overlap of the peaks with the target chemicals can be determined using their CSmin values.

Neutrino roof: Single-scatter cross section ceilings in dark matter direct detection experiments

We identify the maximum cross sections probed by single-scatter weakly interacting massive particle (WIMP) searches in dark matter direct detection. Owing to Poisson fluctuations in scatter multiplicity, these ceilings scale logarithmically with mass for heavy dark matter and often lie in regions probed by multiscatter searches. Using a generalized formula for single-scatter event rates we recast WIMP searches by the quintal-to-tonne scale detectors XENON1T, XENONnT, LZ, PANDAX-II, PANDAX-4T, DarkSide-50, and DEAP-3600 to obtain ceilings and floors up to a few 1017 GeV mass and 10−22 cm2 per nucleus cross section. We do this for coherent, geometric, isospin-violating xenophobic and argophobic spin-independent scattering, and neutron-only and proton-only spin-dependent scattering. Future large-exposure detectors would register an almost irreducible background of atmospheric neutrinos that would determine a dark matter sensitivity ceiling that we call the “neutrino roof,” in analogy with the well-studied “neutrino floor.” Accounting for this background, we estimate the reaches of the 10–100 tonne scale DarkSide-20k, DARWIN/XLZD, PANDAX-xT, and Argo, which would probe many decades of unconstrained parameter space up to the Planck mass, as well as of 103–104 tonne scale noble liquid detectors that have been proposed in synergy with neutrino experiments. Published by the American Physical Society 2024

Construction of a 2.5D Deep Learning Model for Predicting Early Postoperative Recurrence of Hepatocellular Carcinoma Using Multi-View and Multi-Phase CT Images.

To construct a 2.5-dimensional (2.5D) CT radiomics-based deep learning (DL) model to predict early postoperative recurrence of hepatocellular carcinoma (HCC). We retrospectively analyzed the data of patients who underwent HCC resection at 2 centers. The 232 patients from center 1 were randomly divided into the training (162 patients) and internal validation cohorts (70 patients); 91 patients from center 2 formed the external validation cohort. We developed a 2.5D DL model based on a central 2D image with the maximum tumor cross-section and adjacent slices. Multiple views (transverse, sagittal, and coronal) and phases (arterial, plain, and portal) were incorporated. Multi-instance learning techniques were applied to the extracted data; the resulting comprehensive feature set was modeled using Logistic Regression, RandomForest, ExtraTrees, XGBoost, and LightGBM, with 5-fold cross validation and hyperparameter optimization with Grid-search. Receiver operating characteristic curves, calibration curves, DeLong test, and decision curve analysis were used to evaluate model performance. The 2.5D DL model performed well in the training (AUC: 0.920), internal validation (AUC: 0.825), and external validation cohorts (AUC: 0.795). The 3D DL model performed well in the training cohort and poorly in the internal and external validation cohorts (AUCs: 0.751, 0.666, and 0.567, respectively), indicating overfitting. The combined model (2.5D DL+clinical) performed well in all cohorts (AUCs: 0.921, 0.835, 0.804). The Hosmer-Lemeshow test, DeLong test, and decision curve analysis confirmed the superiority of the combined model over the other signatures. The combined model integrating 2.5D DL and clinical features accurately predicts early postoperative HCC recurrence.

Application of machine learning for the differentiation of thymomas and thymic cysts using deep transfer learning: A multi-center comparison of diagnostic performance based on different dimensional models.

This study aimed to evaluate the feasibility and performance of deep transfer learning (DTL) networks with different types and dimensions in differentiating thymomas from thymic cysts in a retrospective cohort. Based on chest-enhanced computed tomography (CT), the region of interest was delineated, and the maximum cross section of the lesion was selected as the input image. Five convolutional neural networks (CNNs) and Vision Transformer (ViT) were used to construct a 2D DTL model. The 2D model constructed by the maximum section (n) and the upper and lower layers (n - 1, n + 1) of the lesion was used for feature extraction, and the features were selected. The remaining features were pre-fused to construct a 2.5D model. The whole lesion image was selected for input and constructing a 3D model. In the 2D model, the area under curve (AUC) of Resnet50 was 0.950 in the training cohort and 0.907 in the internal validation cohort. In the 2.5D model, the AUCs of Vgg11 in the internal validation cohort and external validation cohort 1 were 0.937 and 0.965, respectively. The AUCs of Inception_v3 in the training cohort and external validation cohort 2 were 0.981 and 0.950, respectively. The AUC values of 3D_Resnet50 in the four cohorts were 0.987, 0.937, 0.938, and 0.905. The DTL model based on multiple different dimensions can be used as a highly sensitive and specific tool for the non-invasive differential diagnosis of thymomas and thymic cysts to assist clinicians in decision-making.

Enhanced 3 μm emission in Ho3+/Yb3+ co-doped bismuth-fluoride glasses by Gd2O3

In this work, (100-b)(45Bi2O3-40GeO2-15BaF2)-bGd2O3-2Yb2O3-0.5Ho2O3 glass was prepared to use a high-temperature melting method(where b= 0, 2.5, 5, 7.5, 10). The absorption and fluorescence spectra indicate that the optimal Gd2O3 content is 7.5 mol% (BGBG7.5HY), with an Ω2 value of 6.20×10−20 cm2 for the main glass, which is superior to that of BGBG0HY glass. This suggests that the incorporation of Gd2O3 enhances the mid-infrared emission capacity. Raman spectroscopy studies demonstrate that the introduction of Gd₂O₃ results in a substantial influx of oxygen atoms into the glass network, accompanied by a transition of [BiO₆] to [BiO₃] within the glass mesh. This is evidenced by a notable redshift of the characteristic peaks at 509 cm−1 and 677 cm−1 in comparison to BGB glass. The introduction of Gd2O3 also expands the distance between Ho3+/Yb3+ ions, inhibits rare earth ion clusters, improves the Ho3+ luminescence center environment, and thus enhances the 3 μm emission performance of bismuth fluoride glass. The maximum emission cross section is 1.82 × 10−20 cm2 and the maximum gain coefficient is 3.71 cm−1. The results show that the bismuth fluoride glass prepared in this paper is an excellent gain material for mid-infrared fiber lasers.

Synthesis of a novel water-soluble pyridine dicarboxylate and its application in fluorescence cell imaging

Abstract A novel water-soluble substituted pyridine dicarboxylate containing a quaternary ammonium ion with potential applications in fluorescence cell imaging was synthesized and characterized. Remarkably, this compound exhibited water solubility in the absence of additional solubilizers, enabling direct dissolution in phosphate-buffered saline for cell studies. No obvious cytotoxicity was observed in 4T1 cells (mouse breast cancer cells) within the concentration range of 0.2–25 μmol L−1, with a cell survival rate above 89%. Furthermore, the compound exhibited a maximum two-photon absorption cross-section of 86 GM at an excitation wavelength of 780 nm, demonstrating high cell permeability, effective distribution in the cytoplasm, and preferential targeting of organelles. Single- and two-photon fluorescence imaging of cells revealed a distinctive blue emission and strong bright green emission, respectively. The newly synthesized substituted pyridine dicarboxylate exhibited low cytotoxicity and strong fluorescence imaging properties, demonstrating its potential in cell imaging applications.

Biomimetic Multi-Interface Design of Raspberry-like Absorbent: Gd-doped FeNi3@Covalent Organic Framework Derivatives for Efficient Electromagnetic Attenuation.

Structural design and interface regulation are useful strategies for achieving strong electromagnetic wave absorption (EMWA) and broad effective absorption bandwidth (EAB). Herein, a monomer-mediated strategy is employed to control the growth of covalent organic framework (COF) wrapping flower-shaped Gd-doped FeNi3 (GFN), and a novel raspberry-like absorbent based on biomimetic design is fabricated by thermal catalysis. Further, a unique dielectric-magnetic synergistic system is constructed by utilizing the COF-derived nitrogen-doped porous carbon (NPC) as the shell and anisotropic GFN as the core. The electromagnetic parameters of the GFN@NPC composites can be tuned by adjusting the proportions of GFN and NPC. Off-axis electron holography results further clarify the interface polarization and microscale magnetic interactions affecting the EMW loss mechanism. As a result, the GFN@NPC samples exhibit broad EMWA performance. The EAB values of all GFN@NPC composites reach up to 6.0 GHz, with the GFN@NPC-2 sample showing a minimum reflection loss (RLmin) of -69.6 dB at 1.68 mm. In addition, GFN@NPC-2 achieves a maximum radar cross-section (RCS) reduction of 29.75 dB·m2. A multi-layer gradient structure is also constructed using metamaterial simulation to achieve an ultra-wide EAB of 12.24 GHz. Overall, this work provides a novel bio-inspired design strategy to develop high-performance EMWA materials.

Designing Electronic Structures of Multiscale Helical Converters for Tailored Ultrabroad Electromagnetic Absorption

HighlightsThe energy conversion mechanism is thoroughly analyzed, with a detailed quantitative characterization of the dissipation capacities of polarization, conduction, and magnetic loss.Inspired by DNA transcription, atom and geometry configurations co-modulating multi-scale helical converters achieve the RLmin of −63.13 dB at 1.29 mm, and the maximum RCS reduction value reach 36.4 dB m2.Orbital coupling, spin and cross polarization synergize to realize a 6.08 GHz EAB, further expanding to ultrabroad electromagnetic wave absorption of 12.16 GHz through metamaterial design.

Four cyclometalated Ir(iii) complexes and insights into their luminescence, cytotoxicity and DNA/BSA binding performance.

Four cyclometalated Ir(iii) complexes based on 4'-p-N,N-bis(2-hydroxyethyl)benzyl-2,2':6',2''-terpyridine (TPYOH) and 4'-p-N,N-bis(2-hydroxyethyl)benzyl-6'-benzyl-2,2'-bipyridine (PhbpyOH) were synthesized and characterized. All the Ir(iii) complexes exhibited strong MLCT absorption peaks at about 450 nm, broad emission bands in the range of 500-700 nm. Z-scan results revealed that only complex Ir1A could exhibit certain two-photon absorption with maximal cross section values of 215 GM at 890 nm. When excited by 700-850 nm femtosecond laser, complex Ir1A gave a TPEF peak around 567 nm. All four complexes exhibited enhanced cell growth inhibitory activity against MCF-7 tumour cells under light irradiation comparing to their dark toxicity, with Ir1B showing the highest PI value (>50). The pathways and efficiencies of ROS generation by Ir(iii) complexes varied, with Ir2A being more effective in producing 1O2 while Ir1A mainly generating O2˙-. The Ir(iii) complexes undergo hydrogen bonding with DNA bases/phosphodiester through two O-H bonds on the bis(hydroxyethyl)amino group. The free pyridine-N atom in Ir1A forms additional hydrogen bond with DNA base, while the ligand TPYOH in Ir2A has better molecular planarity due to adopting {N, N, N} coordination mode, thus these two complexes show better DNA affinity. The complexes demonstrated weak interactions with BSA, through hydrogen bonding with amino acid residues at different regions of BSA molecule.

Magnetic bimetallic nanoparticles confined growth for enhancement of electromagnetic loss in void@Fe@SiO2/Co/C particles

The dispersion of diverse magnetic metallic in a single particle plays an important role in microwave absorption; however, its contribution is not clear due to the challenge of controllable synthesis of magnetic bimetallic nanoparticles in one micro/nanostructure. Herein, a series of magnetic bimetallic nanoparticles separately confined growth in a hollow multi-shell microsphere with proper impedance matching characteristic were prepared, which can be used as theoretical models to elucidate magnetic coupling effect between diverse magnetic metallic nanoparticles in a single particle on electromagnetic attenuation. The coupling effect of magnetic Co and Fe nanoparticles dispersed in different shell effectively enhance the microwave absorption performance of void@Fe@SiO2/Co/C particles with minimum reflection loss (RLmin) of −62.3 dB (RL=-20 dB, 99 % absorption) at a thickness of 2.05 mm, provoking the maximum radar cross-section (RCS) reduction value of perfect electric conductor (PEC) 37.37 dBm2. Meanwhile, broad effective bandwidth (EBW, RL≤-10 dB, ≥90 % absorption) response of 7.04 GHz at a thickness of 2.44 mm was achieved. These findings can provide guidance for the designation of novel magnetic broadband microwave absorbing materials (MAMs).

Multi-heterogeneous interfaces boost dielectric polarization in PBA-derived Co/MnO@NC ternary composites for electromagnetic wave absorption

The elaborate construction of multi-component composites has been deemed as a promising strategy to enhance dielectric polarization response capability in the preparation of highly efficient microwave absorbers. However, the rational design and integration of homogeneous composites with diverse components continues to pose a great challenge. Herein, we propose a straightforward self-assembly-carbonization strategy for fabricating Co/MnO@NC ternary composites derived from CoMn-Prussian Blue Analogous precursors, featuring enriched heterogeneous interfaces and balanced magneto-electric coupling synergy. The ternary composites effectively introduce diverse dissipation mechanisms, including interfacial polarization behavior originated from the constructed heterogeneous interfaces, dipole polarization relaxation triggered by atomic defects, and optimized magnetic loss ability from well-dispersed metallic Co species. Benefiting from these advantages, the Co/MnO@NC composites demonstrate superior electromagnetic wave absorption performances, with a minimum reflection loss value of −61.37 dB at the thickness of 3.5 mm and effective frequency absorption bandwidth of 6.32 GHz, covering the full Ku-band. Furthermore, power loss density and radar cross-section simulations validate that the Co/MnO@NC ternary composites possess exceptional microwave signal attenuation abilities, with a maximum radar cross-section reduction value of up to 27.98 dBm2 at 0°. Such outstanding absorption properties exceed those of most currently reported ternary composites and exhibit significant potential to replace conventional ferromagnetic-based absorbers. This work offers a straightforward strategy to fabricate ternary composites with excellent electromagnetic wave attenuation properties and sheds novel insights into the dissipation mechanisms.

Study on the delamination damage prediction of wind turbine blade spar cap based on morphology feature recognition

In order to study the degradation of local mechanical properties caused by delamination defects of wind turbine blades, a progressive damage prediction method of blade spar cap based on quantitative identification of delamination morphology features by infrared thermal image was proposed in this paper. Firstly, based on the thermal conduction theory of laminate plates, infrared thermal imaging technology was used to realize quantitatively identify delamination morphology features. Then, based on the cohesive zone model (CZM) and the classical laminate theory (CLT), a numerical analysis model of unidirectional laminate with delamination defects was established, and the accuracy of the numerical model was verified by comparison with the experimental results of axial tensile and compressive displacement loads. Finally, a 2 MW-45.3 blade spar cap with maximum chord cross-section was used as a prediction model, and the effect of different delamination sizes and depths on the failure mode, failure strength and damage evolution of the blade spar cap was successfully predicted by using the equivalent fatigue load. The research shows that the delamination depth has a more profound influence on the damage of spar cap compared with the delamination size. With the increase of delamination depth, the delamination failure modes undergo the evolution process of non-buckling, local buckling, delamination expansion and strength failure. Shallow delamination causes local buckling and strength failure of blade spar cap. When the delamination depth reaches half of the spar cap thickness, the delamination extends to intralaminar and interlaminar, the local failure changes to global failure.

Enhanced electromagnetic wave absorption of bacterial cellulose/ reduced graphene oxide aerogel by eco-friendly in-situ construction

Electromagnetic wave absorption materials (EWAMs) have become an effective means to address electromagnetic (EM) radiation and enhance stealth technology, among which aerogels are valued for their lightweight nature and excellent designability. This study utilized environmentally friendly preparation and in-situ reduction techniques to fabricate bacterial cellulose (BC) / reduced graphene oxide (RGO) aerogels, achieving tailored EM wave loss capabilities by controlling the reduction time of ascorbic acid. Benefitting from the effects of freeze-casting, BC winding, hydrogen bond, and RGO layers coupling, the aerogel maintains their original structure after reduction and exhibits satisfactory EM wave absorption. The minimum reflection loss (RLmin) is −38.52 dB, with an effective absorption bandwidth (EAB) of 6.68 GHz and a maximum radar cross section (RCS) reduction of 44.69 dBsm. Additionally, the aerogel’s lightweight (a low density of 9.03 mg/cm3) and outstanding thermal insulation properties enable it to adapt to complex conditions. Thus, the study provides a novel approach for the construction of industrialized and sustainable RGO-based EWAMs.

Lightweight and hierarchical carboxyl chitosan-derived carbon aerogel for electromagnetic wave absorber and heat insulation

In recent years, carbon aerogels derived from biomass have shown promising potential in electromagnetic wave (EMW) absorption field owing to their lightweight nature, controllable structure, environmental friendliness, and abundant pore structure. This study reports a novel type of carbon aerogels based on carboxyl chitosan (CCS) and graphene oxide (GO) with rich pores and a unique three-dimensional interconnected structure through solution mixing, freeze-drying, and pyrolysis process. The EMW absorption performances of the carboxyl chitosan/GO xerogel derived carbon aerogels (CGCAs) are adjusted by varying the content of graphene oxide (GO). The nitrogen elements inherent in chitosan can provide a large number of defects to the carbonized material, effectively capturing and attenuating EMW. Synthesized CGCAs show excellent EMW absorption performance with increasing GO content and the CGCA-6 exhibits the best performance. At a thickness of 1.7 mm, it has RLmin of −61.67 dB, and at a thickness of 1.5 mm, it has the widest effective absorption bandwidth (EAB) of 4.24 GHz (12.96–17.12 GHz). Additionally, under far-field conditions, at a thickness of 1.7 mm, the maximum radar cross-section (RCS) reduction relative to a PEC plate for the prepared CGCA-6 is 22.28 dB m2. Furthermore, the good thermal insulation capability exhibited by CGCA-6 makes it suitable for complex application scenarios. Therefore, this biomass-derived multi-functional carbon aerogel with excellent EMW absorption performance, radar stealth, infrared stealth, and thermal insulation capabilities has broad prospects for applications in EMW protection and aerospace fields.

Multifunctional bacterial cellulose‑derived carbon hybrid aerogel for ultrabroad microwave absorption and thermal insulation

Carbon aerogel has gained intense attention as one of the most promising microwave absorption materials. It can overcome severe electromagnetic pollution, thanks to its 3D macroscopic structure and superb conductive loss capacity. However, there is still a big challenge to endow multifunctionality to carbon aerogel while maintaining its good electromagnetic wave absorption (EWA) so as to adapt wide practical application. Herein, a novel carbon-based aerogel consisting of Cu and TiO2 nanoparticles dispersed on carbon nanofiber framework was derived from carbonized bacterial cellulose (CBC) decorated with its mother bacteria via freeze-drying, in situ growth and carbonization strategies. The synthesized carbon-based CBC/Cu/TiO2 aerogel achieved an excellent EWA performance with a broad effective absorption bandwidth (EAB) of 8.32 GHz. It is attributed to the synergistic loss mechanism from multiple scattering, conductive network loss, interfacial polarization loss and dipolar polarization relaxation. Meanwhile, the obtained aerogel also shows an excellent thermal insulation with a 3-mm-thick sample generating a temperature gradient of over 42 °C at 85 °C and a maximum radar cross-section (RCS) reduction of 23.88 dB m2 owing to the cellular structure and synergistic effects of multi-components. Therefore, this study proposes a feasible design approach for creating lightweight, effective, and multifunctional CBC-based EWA materials, which offer a new platform to develop ultrabroad electromagnetic wave absorber under the guidance of RCS simulation.

Hemodynamics in the treatment of pseudoaneurysm caused by extreme constriction of aortic arch with coated stent.

To evaluate the changes in distal vascular morphology and hemodynamics in patients with extremely severe aortic coarctation (CoA) after covered palliative (CP) stent dilation with different surgical strategies. Perioperative computed tomography angiography and digital subtraction angiography were utilized to construct three aortic models with varying stenosis rates and one follow-up model in a patient with extremely severe CoA. The models included: an idealized non-stenosed model (A: 0%), a model post initial stent deployment (B: 28%), a model post balloon expansion (C: 39%), and a model 18 months after post-balloon expansion (D: 39%). Consistent boundary conditions were applied to all models, and hemodynamic simulation was conducted using the pure fluid method. The narrowest and distal diameter of the stent increased by 34.71% and 59.29%, respectively, from model B to C. Additionally, the distal diameter of the stent increased by -13.80% and +43.68% compared to the descending aorta diameter, respectively. Furthermore, the ellipticity of the maximum cross-section of the aneurysm region in model A to D continued to increase. The oscillatory shear index at the stenosis to the region of the aneurysm were found to be higher in Models A and B, and lower in Models C and D. At the moment of maximum flow velocity, the blood flow distribution in models A and B was more uniform in the widest section of the blood vessels at the distal end of the stenosis, whereas models C and D exhibited disturbed blood flow with more than 2 eddy currents. The time-averaged wall shear stress (TAWSS) decreased in the distal and basal aneurysms, while it significantly increased at the step position. The aneurysmal region exhibited an endothelial cell activation potential value lower than 0.4 Pa-1. In patients with extremely severe CoA, it is crucial to ensure that the expanded diameter at both ends of the CP stent does not exceed the native vascular diameter during deployment. Our simulation results demonstrate that overdilation leads to a decrease in the TAWSS above the injured vessel, creating an abnormal hemodynamic environment that may contribute to the development and enlargement of false aneurysms in the early postoperative period. ClinicalTrials.gov, (NCT02917980).

Dark sink enhances the direct detection of freeze-in dark matter

We describe a simple dark sector structure which, if present, has implications for the direct detection of dark matter (DM); . A dark sink transports energy density from the DM into light dark-sector states that do not appreciably contribute to the DM density. As an example, we consider a light, neutral fermion ψ which interacts solely with DM χ via the exchange of a heavy scalar Φ. We illustrate the impact of a dark sink by adding one to a DM freeze-in model in which χ couples to a light dark photon γ′ which kinetically mixes with the Standard Model (SM) photon. This freeze-in model (absent the sink) is itself a benchmark for ongoing experiments. In some cases, the literature for this benchmark has contained errors; we correct the predictions and provide them as a public code. We then analyze how the dark sink modifies this benchmark, solving coupled Boltzmann equations for the dark-sector energy density and DM yield. We check the contribution of the dark sink ψ’s to dark radiation; consistency with existing data limits the maximum attainable cross section. For DM with a mass between MeV−O(10 GeV), adding the dark sink can increase predictions for the direct detection cross section all the way up to the current limits. Published by the American Physical Society 2024

Novel cable‐like tin@carbon whiskers derived from the Ti2SnC MAX phase for ultra‐wideband electromagnetic wave absorption

AbstractOne‐dimensional (1D) metals are well known for their exceptional conductivity and their ease of formation of interconnected networks that facilitate electron migration, making them promising candidates for electromagnetic (EM) attenuation. However, the impedance mismatch from high conductivity and their singular mode of energy loss hinder effective EM wave dissipation. Construction of cable structures not only optimizes impedance matching but also introduces a multitude of heterojunctions, increasing attenuation modes and potentially enhancing EM wave absorption (EMA) performance. Herein, we showcase the scalable synthesis of tin (Sn) whiskers from a Ti2SnC MAX phase precursor, followed by creation of a 1D tin@carbon (Sn@C) cable structure through polymerization of PDA on their surface and annealing in argon. The EMA capabilities of Sn@C significantly surpass those of uncoated Sn whiskers, with an effective absorption bandwidth reaching 7.4 GHz. Remarkably, its maximum radar cross section reduction value of 27.85 dB m2 indicates its exceptional stealth capabilities. The enhanced EMA performance is first attributed to optimized impedance matching, and furthermore, the Sn@C cable structures have rich SnO2/C and Sn/SnO2 heterointerfaces and the associated defects, which increase interfacial and defect‐induced polarization losses, as visually demonstrated by off‐axis electron holography. The development of the Sn@C cable structure represents a notable advancement in broadening the scope of materials with potential applications in stealth technology, and this study also contributes to the understanding of how heterojunctions can improve EMA performance.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region

ObjectivesTo explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI).MethodsA total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC).ResultsThe XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80.ConclusionCompared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted.Clinical relevance statementThe 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region.Key PointsWe investigated tumor and different peritumoral regions, as well as their fusion.MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region.The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.Graphical

Investigation of Thermal and Spectroscopic Properties of Tellurite-Based Glasses Doped with Rare-Earth Oxides for Infrared Solid-State Lasers.

The thermal and optical properties of 60TeO2-20K2TeO3-10WO3-10Nb2O5 (in mol%) glasses doped with Ho2O3, Er2O3, and Tm2O3 were explored in the present work. The thermal stability, refractive index n, extinction coefficient k, absorption coefficient α, and optical band gap of the glasses were evaluated. The UV-Vis-NIR absorption spectra, the Judd-Ofelt intensity parameter, the spectroscopic quality factor, and the emission and absorption cross-sections were calculated to investigate the effects of Er3+ and Tm3+, respectively, on the band spectroscopic properties of Ho3+ ions. The results showed that the maximum emission cross-section was approximately 8×10-21 cm2, and the values of the full width at half maximum (FWHM), quality factor (σe×FWHM), and gain coefficient of Ho3+: 5I7→5I8 were also reported. The value of the FWHM×σe was 1200×10-28 cm3, which showed greater gain characteristics than earlier study results. For 2 μm mid-infrared solid-state lasers, the glasses that were examined might be a good host material.