Characteristics of Moisture Transfer and Surface Crack Development of a Single Lignite Particle Driven by Humidity Difference

The research on moisture transfer characteristics and surface crack development of a single lignite particle (SLP) driven by humidity difference is helpful to achieve a better understanding of the fragmentation characteristics of lignite during the moisture transfer process. This is of great significance to the safe operation of a drying system. The characteristics of moisture transfer within SLP driven by humidity difference were studied in different stages. Six drying equations commonly used in the literature were selected to describe the moisture transfer behavior. The apparent diffusion coefficient (Deff) of moisture in each stage was calculated to compare the driving forces of moisture transfer in different stages. The surface crack rate (CR) was used to quantitatively analyze the fragmentation characteristics of SLP caused by moisture transfer. The results showed that the moisture transfer process of SLP driven by humidity difference can be divided into three stages, and stage I is the main moisture removal stage. The larger the particle size, the longer the stage I, while less moisture is removed in this stage. A logarithmic drying equation best simulates the moisture transfer process of SLP. The larger the particle size, the larger the Deff value in each stage. The driving force of moisture transfer in stage I is the largest, which is the opposite of a thermal drying process. CR for SLP has experienced a rapid increase-stable at the highest value-rapid decrease-stable during the moisture transfer process driven by the humidity difference.</p

Vortex-induced Shear Polaritons

Hyperbolic shear polaritons (HShPs) emerge with widespread attention as a new class of polariton modes with broken symmetry due to shear lattices. In this letter, we find a new mechanism of generating HShPs. When utilizing vortex waves as excitation sources of hyperbolic materials without off-diagonal elements, HShPs will appear. In addition, this asymmetric HShPs can be recovered as symmetric modes away from the source, with a critical transition mode between the left-skewed and right-skewed HShPs, via tuning the magnitude of the off-diagonal imaginary component and controlling the topological charge of vortex source. It is worth mentioning that we explore the influence of parity of topological charges on the field distribution and demonstrate these exotic phenomena from numerical and analytical perspectives. Our results will promote new opportunities for both HShPs and vortex waves, widening the horizon for various hyperbolic materials based on vortex sources and offering a new degree of freedom to control various kinds of polaritons

A Novel Method for Sea-Land Clutter Separation Using Regularized Randomized and Kernel Ridge Neural Networks

Classification of clutter, especially in the context of shore based radars, plays a crucial role in several applications. However, the task of distinguishing and classifying the sea clutter from land clutter has been historically performed using clutter models and/or coastal maps. In this paper, we propose two machine learning, particularly neural network, based approaches for sea-land clutter separation, namely the regularized randomized neural network (RRNN) and the kernel ridge regression neural network (KRR). We use a number of features, such as energy variation, discrete signal amplitude change frequency, autocorrelation performance, and other statistical characteristics of the respective clutter distributions, to improve the performance of the classification. Our evaluation based on a unique mixed dataset, which is comprised of partially synthetic clutter data for land and real clutter data from sea, offers improved classification accuracy. More specifically, the RRNN and KRR methods offer 98.50% and 98.75% accuracy, outperforming the conventional support vector machine and extreme learning based solutions

Identification of differentially expressed microRNAs and the potential of microRNA-455-3p as a novel prognostic biomarker in glioma.

Glioma is an aggressive central nervous system malignancy. MicroRNAs (miRNAs/miRs) have been reported to be involved in the tumorigenesis of numerous types of cancer, including glioma. The present study aimed to identify the differentially expressed miRNAs in glioma, and further explore the clinical value of miR-455-3p in patients with glioma. GEO2R was used for the identification of the differentially expressed miRNAs according to the miRNA expression profiles obtained from the Gene Expression Omnibus database. OncomiR was used to analyze the relationship of miRNAs with the survival outcomes of the patients with glioma. A total of 108 patients with glioma were recruited to examine the expression levels of miR-455-3p and further explore its clinical value. The bioinformatics analysis results suggested that a total of 64 and 48 differentially expressed miRNAs were identified in the GSE90603 and GSE103229 datasets, respectively. There were 12 miRNAs in the overlap of the two datasets, of which three were able to accurately predict overall cancer survival, namely hsa-miR-7-5p, hsa-miR-21-3p and hsa-miR-455-3p. In patients with glioma, miR-455-3p was determined to be significantly upregulated (P<0.001). Additionally, patients with high miR-455-3p expression had significantly lower 5-year overall survival than those with low miR-455-3p expression (log-rank test, P=0.001). Cox regression analysis further determined that miR-455-3p was an independent prognostic indicator for overall survival in patients with glioma (hazard ratio=2.136; 95% CI=1.177-3.877; P=0.013). In conclusion, the present study revealed a series of miRNAs with potential functional roles in the pathogenesis of glioma, and provides findings that indicate miR-455-3p as a promising biomarker for the prognosis of glioma

Wide-area measurement-based supervision of the cerebral venous hemodynamic in a novel rat model

Abstract(#br)Background(#br)Traumatic brain injury (TBI) includes primary and secondary injuries, while monitoring intracranial pressure (ICP) and cerebral blood flow (CBF) is conducive to improve the prognosis of patients. However, the function of cerebral venous in this process is still unclear.(#br)New Method(#br)An acute epidural hematoma (AEDH) model was developed by placing a controllable microballoon in the right epidural space of a rat. The laser speckle contrast imaging (LSCI) system was used to observe CBF in real time, while ICP was monitored simultaneously. And the stability of this model was examined by magnetic resonance imaging (MRI).(#br)Results(#br)The blood perfusion rate (BPR) of venous was significantly negatively correlated with ICP. In the 100 μL group, the ipsilateral cerebral venous and microcirculation blood flow significantly decreased. According to the gross observations and pathological results, ischemic brain injury was the most serious on this condition.(#br)Comparison with Existing Method(s)(#br)Modeling method is relatively simple, which effectively reduces the cost. The volume of the microballoon is adjusted to simulate the volume of different size of hematomas. In addition, LSCI, as an advanced blood flow monitoring technology, has high sensitivity to detect subtle changes in CBF.(#br)Conclusion(#br)This study successfully developed a stable and reproducible AEDH rat model. Based on this model, it is preliminarily demonstrated that local intracranial hypertension can cause cerebral venous return restriction, which is an indispensable factor leading to the aggravation of secondary brain injury