An acoustic metamaterial lens for acoustic point-to-point communication in air

Acoustic metamaterials have become a novel and effective way to control sound waves and design acoustic devices. In this study, we design a 3D acoustic metamaterial lens (AML) to achieve point-to-point acoustic communication in air: any acoustic source (i.e. a speaker) in air enclosed by such an AML can produce an acoustic image where the acoustic wave is focused (i.e. the field intensity is at a maximum, and the listener can receive the information), while the acoustic field at other spatial positions is low enough that listeners can hear almost nothing. Unlike a conventional elliptical reflective mirror, the acoustic source can be moved around inside our proposed AML. Numerical simulations are given to verify the performance of the proposed AML

MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model

Over the past few years, self-supervised monocular depth estimation that does not depend on ground-truth during the training phase has received widespread attention. Most efforts focus on designing different types of network architectures and loss functions or handling edge cases, e.g., occlusion and dynamic objects. In this work, we introduce a novel self-supervised depth estimation framework, dubbed MonoDiffusion, by formulating it as an iterative denoising process. Because the depth ground-truth is unavailable in the training phase, we develop a pseudo ground-truth diffusion process to assist the diffusion in MonoDiffusion. The pseudo ground-truth diffusion gradually adds noise to the depth map generated by a pre-trained teacher model. Moreover,the teacher model allows applying a distillation loss to guide the denoised depth. Further, we develop a masked visual condition mechanism to enhance the denoising ability of model. Extensive experiments are conducted on the KITTI and Make3D datasets and the proposed MonoDiffusion outperforms prior state-of-the-art competitors. The source code will be available at https://github.com/ShuweiShao/MonoDiffusion.Comment: 10 pages, 8 figure

Research on a highway truck anti-defl ection load system

In order to improve the safety of road trucks, an anti-bias load system for road trucks is proposed. The system integrates real-time monitoring and safety alarm functions, and is composed of sensor components and on-board control units. The system is installed on the truck axle, through the single-chip computer calculation and monitoring technology, real-time monitoring of the truck load, especially the detection of the off -load state. Once the off -load situation occurs, the device immediately issues a safety alarm to remind the driver to take necessary measures to reduce the risk of truck rollover and other accidents and improve road traffi c safety. The research results are expected to enhance the stability and safety of trucks and promote road traffi c technology innovation

Hyperoxalemia Leads to Oxidative Stress in Endothelial Cells and Mice with Chronic Kidney Disease

Introduction: Cardiovascular disease is the most common cause of morbidity and mortality in patients with ESRD. In addition to phosphate overload, oxalate, a common uremic toxin, is also involved in vascular calcification in patients with ESRD. The present study investigated the role and mechanism of hyperoxalemia in vascular calcification in mice with uremia. Methods: A uremic atherosclerosis (UA) model was established by left renal excision and right renal electrocoagulation in apoE−/− mice to investigate the relationship between oxalate loading and vascular calcification. After 12 weeks, serum and vascular levels of oxalate, vascular calcification, inflammatory factors (TNF-α and IL-6), oxidative stress markers (malondialdehyde [MDA], and advanced oxidation protein products [AOPP]) were assessed in UA mice. The oral oxalate-degrading microbe Oxalobacter formigenes (O. formigenes) was used to evaluate the effect of a reduction in oxalate levels on vascular calcification. The mechanism underlying the effect of oxalate loading on vascular calcification was assessed in cultured human aortic endothelial cells (HAECs) and human aortic smooth muscle cells (HASMCs). Results: Serum oxalate levels were significantly increased in UA mice. Compared to the control mice, UA mice developed more areas of aortic calcification and showed significant increases in aortic oxalate levels and serum levels of oxidative stress markers and inflammatory factors. The correlation analysis showed that serum oxalate levels were positively correlated with the vascular oxalate levels and serum MDA, AOPP, and TNF-α levels, and negatively correlated with superoxide dismutase activity. The O. formigenes intervention decreased serum and vascular oxalate levels, while did not improve vascular calcification significantly. In addition, systemic inflammation and oxidative stress were also improved in the O. formigenes group. In vitro, high concentrations of oxalate dose-dependently increased oxidative stress and inflammatory factor expression in HAECs, but not in HASMCs. Conclusions: Our results indicated that hyperoxalemia led to the systemic inflammation and the activation of oxidative stress. The reduction in oxalate levels by O. formigenes might be a promising treatment for the prevention of oxalate deposition in calcified areas of patients with ESRD

In Silico Identification of Structure Requirement for Novel Thiazole and Oxazole Derivatives as Potent Fructose 1,6-Bisphosphatase Inhibitors

Fructose 1,6-bisphosphatase (FBPase) has been identified as a drug discovery target for lowering glucose in type 2 diabetes mellitus. In this study, a large series of 105 FBPase inhibitors were studied using a combinational method by 3D-QSAR, molecular docking and molecular dynamics simulations for a further improvement in potency. The optimal 3D models exhibit high statistical significance of the results, especially for the CoMFA results with rncv2, q2 values of 0.986, 0.514 for internal validation, and rpred2, rm2 statistics of 0.902, 0.828 statistics for external validation. Graphic representation of the results, as contoured 3D coefficient plots, also provides a clue to the reasonable modification of molecules. (1) Substituents with a proper length and size at the C5 position of the thiazole core are required to enhance the potency; (2) A small and electron-withdrawing group at the C2 position linked to the thiazole core is likely to help increase the FBPase inhibition; (3) Substituent groups as hydrogen bond acceptors at the C2 position of the furan ring are favored. In addition, the agreement between 3D-QSAR, molecular docking and molecular dynamics simulation proves the rationality of the developed models. These results, we hope, may be helpful in designing novel and potential FBPase inhibitors

A Classification Study of Respiratory Syncytial Virus (RSV) Inhibitors by Variable Selection with Random Forest

Experimental pEC50s for 216 selective respiratory syncytial virus (RSV) inhibitors are used to develop classification models as a potential screening tool for a large library of target compounds. Variable selection algorithm coupled with random forests (VS-RF) is used to extract the physicochemical features most relevant to the RSV inhibition. Based on the selected small set of descriptors, four other widely used approaches, i.e., support vector machine (SVM), Gaussian process (GP), linear discriminant analysis (LDA) and k nearest neighbors (kNN) routines are also employed and compared with the VS-RF method in terms of several of rigorous evaluation criteria. The obtained results indicate that the VS-RF model is a powerful tool for classification of RSV inhibitors, producing the highest overall accuracy of 94.34% for the external prediction set, which significantly outperforms the other four methods with the average accuracy of 80.66%. The proposed model with excellent prediction capacity from internal to external quality should be important for screening and optimization of potential RSV inhibitors prior to chemical synthesis in drug development