Advanced Mass Spectrometry Techniques for Characterizations of Proteome and Lipidome Profiles of Osteosarcoma Cells

Mass Spectrometry has emerged as an analytical core technique in omics sciences, in particularly mass spectrometry has advanced the fields of proteomics, metabolomics and lipidomics in recent years. Mass spectrometric techniques have enabled the characterization and determination of abundance levels of a wide range of biomolecules at molecular and system-wide scales. This dissertation focuses on the development and application of quantitative mass spectrometry-based methods to decipher the molecular changes associated with hypoxic stress in osteosarcoma

Assessing r2SCAN meta-GGA functional for structural parameters, cohesive energy, mechanical modulus and thermophysical properties of 3d, 4d and 5d transition metals

The recent development of the accurate and efficient semilocal density functionals on the third rung of Jacob's ladder of density functional theory such as the revised regularized strongly constrained and appropriately normed (r2SCAN) density functional could enable the rapid and highly reliable prediction of the elasticity and temperature dependence of thermophysical parameters of refractory elements and their intermetallic compounds using quasi-harmonic approximation (QHA). Here, we present a comparative evaluation of the equilibrium cell volumes, cohesive energy, mechanical moduli, and thermophysical properties (Debye temperature and thermal expansion coefficient) for 22 transition metals using semilocal density functionals, including local density approximation (LDA), the Perdew-Burke-Ernzerhof (PBE) and PBEsol generalized gradient approximations (GGA), and the r2SCAN meta-GGA. PBEsol and r2SCAN deliver the same level of accuracies for structural, mechanical and thermophysical properties. Otherwise, PBE and r2SCAN perform better than LDA and PBEsol for calculating cohesive energies of transition metals. Among the tested density functionals, r2SCAN provides an overall well-balanced performance for reliably computing the cell volumes, cohesive energies, mechanical properties, and thermophysical properties of various 3d, 4d, and 5d transition metals using QHA. Therefore, we recommend that r2SCAN could be employed as a workhorse method to evaluate the thermophysical properties of transition metal compounds and alloys in the high throughput workflows

Study on the Service Performance of a Two-Stage Floating-Ring Isolation Seal for a High-Speed Turbopump with a Cryogenic Medium

The reliability and stability of the seal at the fuel-supply end of a rocket-engine turbopump are important factors in determining safety. Conventional single-stage floating rings used for the isolation-sealing of cryogenic media are highly susceptible to operational instability during startup and shutdown, which places demands on the seals’ structure, size, and material properties. In this study, a two-stage floating-ring isolation seal with a non-slotted main sealing surface was designed using a tangential air-intake mode. Based on the full-size three-dimensional finite-volume model, the leakage characteristics of the floating ring during operation were calculated, taking into account the effect of the “inlet effect” on the seal’s performance. Combining the temperature and pressure distributions of the sealing system under cryogenic operating conditions, calculated using a numerical simulation, a reliability analysis of various inlet directions and two kinds of floating-ring schemes was carried out on a self-constructed service-performance test bench. The results indicate that the main wear location of the non-slotted floating ring occurs on the auxiliary sealing surface, with stable working performance. When the inlet direction and spindle-rotation direction are the same, this is more conducive to ensuring the stability of seal performance in practical applications. The results of the current research are instructive for designing floating-ring isolation seals for turbine pumps

Optimization of CMP processing parameters for Si based on response surface method

To improve the polishing efficiency and precision, the optimum processing parameters of Si in the chemical mechanical polishing (CMP) process were analysed by CMP experiments and response surface methodology. The results show that polishing pressure has the largest influence on the material removal rate and surface roughness of Si polishing. The second largest influential factor is polishing rotational speed and the third is polishing fluid flow rate. The prediction models of material removal rate and surface roughness are established. The optimum processing parameters are obtained when the polishing pressure is 48.3 kPa, polishing rotational speed is 70 r/min and polishing fluid flow rate is 65 mL/min with the prediction models and by experiments. With these processing parameters, the material removal rate and surface roughness are 1 058.2 nm/min and 0.771 nm, respectively

Improving RGB-Infrared Object Detection by Reducing Cross-Modality Redundancy

In the field of remote sensing image applications, RGB and infrared image object detection is an important technology. The object detection performance can be improved and the robustness of the algorithm will be enhanced by making full use of their complementary information. Existing RGB-infrared detection methods do not explicitly encourage RGB and infrared images to achieve effective multimodal learning. We find that when fusing RGB and infrared images, cross-modal redundant information weakens the degree of complementary information fusion. Inspired by this observation, we propose a redundant information suppression network (RISNet) which suppresses cross-modal redundant information and facilitates the fusion of RGB-Infrared complementary information. Specifically, we design a novel mutual information minimization module to reduce the redundancy between RGB appearance features and infrared radiation features, which enables the network to take full advantage of the complementary advantages of multimodality and improve the object detection performance. In addition, in view of the drawbacks of the current artificial classification of lighting conditions, such as the subjectivity of artificial classification and the lack of comprehensiveness (divided into day and night only), we propose a method based on histogram statistics to classify lighting conditions in more detail. Experimental results on two public RGB-infrared object detection datasets demonstrate the superiorities of our proposed method over the state-of-the-art approaches, especially under challenging conditions such as poor illumination, complex background, and low contrast

Improving RGB-Infrared Object Detection by Reducing Cross-Modality Redundancy

In the field of remote sensing image applications, RGB and infrared image object detection is an important technology. The object detection performance can be improved and the robustness of the algorithm will be enhanced by making full use of their complementary information. Existing RGB-infrared detection methods do not explicitly encourage RGB and infrared images to achieve effective multimodal learning. We find that when fusing RGB and infrared images, cross-modal redundant information weakens the degree of complementary information fusion. Inspired by this observation, we propose a redundant information suppression network (RISNet) which suppresses cross-modal redundant information and facilitates the fusion of RGB-Infrared complementary information. Specifically, we design a novel mutual information minimization module to reduce the redundancy between RGB appearance features and infrared radiation features, which enables the network to take full advantage of the complementary advantages of multimodality and improve the object detection performance. In addition, in view of the drawbacks of the current artificial classification of lighting conditions, such as the subjectivity of artificial classification and the lack of comprehensiveness (divided into day and night only), we propose a method based on histogram statistics to classify lighting conditions in more detail. Experimental results on two public RGB-infrared object detection datasets demonstrate the superiorities of our proposed method over the state-of-the-art approaches, especially under challenging conditions such as poor illumination, complex background, and low contrast

Assessment of the feasibility of TACE combined with intratumoral injection of cisplatin in hepatocellular carcinoma

The feasibility of transcatheter arterial chemoembolization (TACE) combined with intratumoral injection of cisplatin as treatment for hepatocellular carcinoma. 30 cases receiving TACE were denoted the TACE group, another 30 cases receiving TACE combined with an intratumoral multi-point injection of cisplatin were denoted the TACE/cisplatin group. Cases with partial remission/complete remission (PR/CR) were analyzed using 2 tests; alpha fetoprotein (AFP), aspartate amino transferase (AST), total bilirubin (TBIL), erythrocyte, and platelet levels were detected and the differences between two groups were analyzed using the Student’s t-test; cases with complications, including intrahepatic metastasis (IM), upper gastrointestinal bleeding (UGB), and liver failure were also counted. The correlation of clinical parameters with PR/CR was analyzed using multifactorial correlation analysis. Cases with PR/CR in the TACE/cisplatin group were significantly more than in TACE group, accompanied by significant declination in FAP. There were no significant differences of AST, ALT, TBIL, blood urea nitrogen (BUN), white blood cells (WBC), red blood cells (RBC), and platelets (PLT) between two groups; 3 cases with IM, one case with UGB and one case with LF were found in the TACE group, but only 1 case with IM was found in the TACE/cisplatin group. In addition, tumor stage was correlated with PR/CR. We concluded that TACE combined with intratumoral injection of cisplatin was more effective than TACE, and with fewer complications and side effects

MP-PIC simulation of dilute-phase pneumatic conveying in a horizontal pipe

Dilute gas-solid two-phase flows inside a pneumatic conveying pipe are simulated with the multiphase particle -in-cell (MP-PIC) method. To achieve high simulation accuracy, different particle-wall collision models, drag force models and turbulence modulation models have been tested. Simulation results including pressure drop, gas and solid mean velocities, fluctuating velocities are compared to experimental measurements. It is found that the particle-wall collision restitution coefficient, especially in the tangential direction, significantly influences the total pressure drop. The mean particle velocity and slip velocity are sensitive to the drag force and a much higher drag force can improve the simulation accuracy, whereas the mean gas velocity is not sensitive to the drag force. The fluctuating gas velocity is hard to be predicted with the currently available turbulence modulation modeling choices, implying more efforts are needed in understanding the turbulence in future