Effects of structural characteristics on microwave dielectric properties of low-loss (Zn1-xNix)ZrNbTaO8 ceramics

Low-loss (Zn_1-xNi_x)ZrNbTaO₈ (0.02?≤?x?≤?0.10) ceramics possessing single wolframite structure are initiatively synthesized by solid-state route. Based on the results of Rietveld refinement, complex chemical bond theory is used to establish the correlation between structural characteristics and microwave performance in this ceramic system. A small amount of Ni²⁺ (x?=?0.06) in A-site with the fixed substitution of Ta⁵⁺ in B-site can effectually raise the Q?×?f value of ZnZrNb₂O₈ ceramic, embodying a dense microstructure and high lattice energy. The dielectric constant and τ_f are mainly affected by bond ionicity and the average octahedral distortion. The (Zn_0.94Ni_0.06)ZrNbTaO₈ ceramic sample sintered at 1150?°C for 3?h exhibits an outstanding combination of microwave dielectric properties: ε_r =?27.88, Q?×?f?=?128,951?GHz, τ_f =?–39.9?ppm/°C. Thus, it is considered to be a candidate material for the communication device applications at high frequency.     

Mixed-Metal MOF-74 Templated Catalysts for Efficient Carbon Dioxide Capture and Methanation

The vast chemical and structural tunability of metal–organic frameworks (MOFs) are beginning to be harnessed as functional supports for catalytic nanoparticles spanning a range of applications. However, a lack of straightforward methods for producing nanoparticle-encapsulated MOFs as efficient heterogeneous catalysts limits their usage. Herein, a mixed-metal MOF, NiMg-MOF-74, is utilized as a template to disperse small Ni nanoclusters throughout the parent MOF. By exploiting the difference in Ni O and Mg O coordination bond strength, Ni²⁺ is selectively reduced to form highly dispersed Ni nanoclusters constrained by the parent MOF pore diameter, while Mg²⁺ remains coordinated in the framework. By varying the ratio of Ni to Mg in the parent MOF, accessible surface area and crystallinity can be tuned upon thermal treatment, influencing CO₂ adsorption capacity and hydrogenation selectivity. The resulting Ni nanoclusters prove to be an active catalyst for CO₂ methanation and are examined using extended X-ray absorption fine structure and X-ray photoelectron spectroscopy. By preserving a segment of the Mg²⁺-containing MOF framework, the composite system retains a portion of its CO₂ adsorption capacity while continuing to deliver catalytic activity. The approach is thus critical for designing materials that can bridge the gap between carbon capture and CO₂ utilization.     

Quantifying the limits of CAR T-cell delivery in mice and men

CAR (Chimeric Antigen Receptor) T cells have demonstrated clinical success for the treatment of multiple lymphomas and leukaemias, but not for various solid tumours, despite promising data from murine models. Lower effective CAR T-cell delivery rates to human solid tumours compared to haematological malignancies in humans and solid tumours in mice might partially explain these divergent outcomes. We used anatomical and physiological data for human and rodent circulatory systems to calculate the typical perfusion of healthy and tumour tissues, and estimated the upper limits of immune cell delivery rates across different organs, tumour types and species. Estimated maximum delivery rates were up to 10 000-fold greater in mice than humans yet reported CAR T-cell doses are typically only 10–100-fold lower in mice, suggesting that the effective delivery rates of CAR T cells into tumours in clinical trials are far lower than in corresponding mouse models. Estimated delivery rates were found to be consistent with published positron emission tomography data. Results suggest that higher effective human doses may be needed to drive efficacy comparable to mouse solid tumour models, and that lower doses should be tested in mice. We posit that quantitation of species and organ-specific delivery and homing of engineered T cells will be key to unlocking their potential for solid tumours.     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

Effect of Al2O3 Addition on Mineralogical Modification and Crystallization Kinetics of a High Basicity BOF Steel Slag

Metallurgical and Materials Transactions B - Basic oxygen furnace (BOF) steel slag is a main byproduct that is produced during the converter steelmaking process. The volume instability and fast...     

Global Exponential Stability of Hybrid Non-autonomous Neural Networks with Markovian Switching

Neural Processing Letters - This paper discusses the global exponential stability for a class of hybrid non-autonomous neural networks (HNNNs) with Markovian switching, which includes the factors...     

Anchoring single Pt atoms on hollow Ag3VO4 spheres for improved activity towards photocatalytic H2 evolution reaction

The high cost of noble metal catalysts has been a great bottleneck for the catalyst industry. Using the noble metal at a single-atom level for catalytic applications could dramatically decrease the cost. The impacts of single Pt atoms on the photocatalytic performance of Ag₃VO₄ have been investigated and reported. In this report, single Pt atoms were anchored on the surface of Ag₃VO₄ (AVO) as a cocatalyst, and the resultant composite photocatalyst has been studied for photocatalytic H₂ production from water driven by visible light. The as-prepared AVO particles are hollow nanospheres in the monoclinic phase with a bandgap of 2.20 eV. The light absorption edge of AVO/Pt is slightly red-shifted compared to that of the pristine AVO, indicating more visible light absorption of AVO/Pt. The XPS peaks of Ag, V, and Pt exhibit a significant shift after AVO and Pt get into contact, suggesting the strong interaction between the surface Ag and V atoms, and single Pt atoms. After 3-h illumination, the photocatalytic H₂ evolution amount from AVO/Pt is improved up to 1400 μmol, which is 2.8 times that on the bare AVO. Such efficient photocatalytic H₂ evolution on AVO/Pt is still maintained after five reaction cycles. The better photocatalytic performance of AVO/Pt has been attributed to the more efficient visible light utilization and the lower interfacial charge transfer resistance, as demonstrated in the DRS and EIS spectra. The presence of the surface Pt atoms also leads to a higher amount of reactive radicals, which could efficiently promote the surface redox reactions.     

A dynamic SVR–ARMA model with improved fruit fly algorithm for the nonlinear fiber stretching process

Natural Computing - The fiber stretching process plays the key role in the process of fiber production and its effects is measured by the stretching ratio. The stretching ratio is determined by the...