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Load sensing technology is a typical hydraulic technology that automatically meets load requirements by adjusting the pressure and flow at the pump outlet. Traditional load sensitive pump control systems rely on variable mechanisms to achieve such flow control characteristics. However, general variable mechanisms have complex structures and poor dynamic performance if frequently adjusted. Therefore, a new variable mechanism, named two-dimensional pulse width modulation rotary valve, is proposed. Different from the pulse width modulation control method of the electronic technology, the two-dimensional pulse width modulation rotary valve conducts secondary distribution of the quantitative pump output in the way of fluid pulse width modulation: the valve core rotates to generate discrete fluid, and the axial sliding of the valve core controls the duty ratio of the discrete fluid. The dynamic balancing of the axial displacement is controlled by feedback pressure to provide a fixed differential pressure for the control valve, achieving that the flow through the control valve is uniquely controlled by the valve opening of the control valve. The principle of the fluid pulse width modulation is first introduced, and then the mathematical model of the proposed variable mechanism and the corresponding system is established. Simulation analysis is implemented. Finally, the effectiveness of the load sensing system controlled by a two-dimensional pulse width modulation rotary valve is verified by the experiment.

Novel glass-ceramics (GCs) containing polymorphic CaTa2O6:Er3+/Yb3+ nanocrystals were prepared in this study using an aerodynamic levitation method followed by heat treatment of the precursor glasses (PGs). The phase transition from cubic to orthorhombic crystal forms depending on the heat-treatment temperature was observed. The appearance of the corresponding GCs changed gradually from transparent to translucent and opaque with increasing temperatures. The evolution of phase composition and microstructure was investigated through X-ray diffraction (XRD), Rietveld refinement and transmission electron microscopy (TEM). Both XRD refinement results and spectroscopic properties, including the decrease in unit cell parameters, significant enhancement in upconversion (UC) luminescence, obvious Stark splitting of the UC and near-infrared (NIR) emission bands and the extension of lifetimes, confirmed the incorporation of the rare-earth (RE) ions into the crystalline phases. Furthermore, the temperature-dependent UC and NIR luminescence variations of the GCs containing polymorphic CaTa2O6:Er3+/Yb3+ nanocrystals were investigated. Based on the fluorescence intensity ratio (FIR) technique, the thermally coupled levels (TCLs) (2H11/2/4S3/2), non-thermally coupled levels (NTCLs) (4S3/2/4F9/2) and Stark sublevels (4I13/2) of Er3+ ions were used for three-mode thermometry. The maximum absolute sensitivities of FIR(H/S) and FIR(S/F) were 3.8 × 10−3 and 3.7 × 10−2 K−1, respectively, which are much higher than those reported in previous reports. Furthermore, FIR(1500/1532) based on the Stark sublevels of orthorhombic phase GC offers a complementary way of temperature sensing. These results suggest the potential application of the GCs in self-referenced optical thermometry. [ABSTRACT FROM AUTHOR]

Intrahepatic cholangiocarcinoma is a rare disease associated with a poor prognosis, primarily due to early recurrence and metastasis. An important feature of this condition is microvascular invasion (MVI). However, current predictive models based on imaging have limited efficacy in this regard. This study employed a random forest model to construct a predictive model for MVI identification and uncover its biological basis. Single-cell transcriptome sequencing, whole exome sequencing, and proteome sequencing were performed. The area under the curve of the prediction model in the validation set was 0.93. Further analysis indicated that MVI-associated tumor cells exhibited functional changes related to epithelial–mesenchymal transition and lipid metabolism due to alterations in the nuclear factor-kappa B and mitogen-activated protein kinase signaling pathways. Tumor cells were also differentially enriched for the interleukin-17 signaling pathway. There was less infiltration of SLC30A1+ CD8+ T cells expressing cytotoxic genes in MVI-associated intrahepatic cholangiocarcinoma, whereas there was more infiltration of myeloid cells with attenuated expression of the major histocompatibility complex II pathway. Additionally, MVI-associated intercellular communication was closely related to the SPP1–CD44 and ANXA1–FPR1 pathways. These findings resulted in a brilliant predictive model and fresh insights into MVI. [ABSTRACT FROM AUTHOR]

Graves' disease is a common condition that is diagnosed clinically by determining the smoothness of the thyroid texture and its morphology in ultrasound images. Currently, the most widely used approach for the automated diagnosis of Graves' disease utilizes Convolutional Neural Networks (CNNs) for both feature extraction and classification. However, these methods demonstrate limited efficacy in capturing texture features. Given the high capacity of wavelets in describing texture features, this research integrates learnable wavelet modules utilizing the Lifting Scheme into CNNs and incorporates a parallel wavelet branch into the ResNet18 model to enhance texture feature extraction. Our model can analyze texture features in spatial and frequency domains simultaneously, leading to optimized classification accuracy. We conducted experiments on collected ultrasound datasets and publicly available natural image texture datasets, our proposed network achieved 97.27% accuracy and 95.60% recall on ultrasound datasets, 60.765% accuracy on natural image texture datasets, surpassing the accuracy of ResNet and confirming the effectiveness of our approach. [ABSTRACT FROM AUTHOR]