Filtering for discrete-time nonhomogeneous Markov jump systems with uncertainties

This paper studies the problem of robust H1 filtering for a class of uncertain discrete-time nonhomogeneous Markov jump systems. The time-varying jump transition probability matrix is described by a polytope. By Lyapunov function approach, mode-dependent and variation-dependent H1 filter is designed such that the resulting error dynamic system is stochastically stable and has a prescribed H1 performance index. A numerical example is given to illustrate the effectiveness of the developed techniques

An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI

Magnetic Resonance Imaging (MRI) plays an important role in diagnosing the parotid tumor, where accurate segmentation of tumors is highly desired for determining appropriate treatment plans and avoiding unnecessary surgery. However, the task remains nontrivial and challenging due to ambiguous boundaries and various sizes of the tumor, as well as the presence of a large number of anatomical structures around the parotid gland that are similar to the tumor. To overcome these problems, we propose a novel anatomy-aware framework for automatic segmentation of parotid tumors from multimodal MRI. First, a Transformer-based multimodal fusion network PT-Net is proposed in this paper. The encoder of PT-Net extracts and fuses contextual information from three modalities of MRI from coarse to fine, to obtain cross-modality and multi-scale tumor information. The decoder stacks the feature maps of different modalities and calibrates the multimodal information using the channel attention mechanism. Second, considering that the segmentation model is prone to be disturbed by similar anatomical structures and make wrong predictions, we design anatomy-aware loss. By calculating the distance between the activation regions of the prediction segmentation and the ground truth, our loss function forces the model to distinguish similar anatomical structures with the tumor and make correct predictions. Extensive experiments with MRI scans of the parotid tumor showed that our PT-Net achieved higher segmentation accuracy than existing networks. The anatomy-aware loss outperformed state-of-the-art loss functions for parotid tumor segmentation. Our framework can potentially improve the quality of preoperative diagnosis and surgery planning of parotid tumors.Comment: under revie

Spatial Distribution of Glomalin-related Soil Proteins in Coniferous and Broadleaf mixed Temperate Forest

Glomalin-related soil protein (GRSP), as an important component of soil organic carbon (SOC) pool, is a glycoprotein produced by the hyphae of arbuscular mycorrhizal fungi (AMF), which play a vital role in carbon and nutrient cycling in forest ecosystem. Here we investigated the spatial distribution of GRSP in plant community of the dominated species not associated with AMF based on a typical coniferous and broad-leaved temperate forest in Mt. Changbai, Northeastern China. Spatial distribution of GRSP including easily extractable GRSP (EEG) and total GRSP (TG) is represented by Moran’s I on different soil depth among seven soil layers of 0-5 cm, 5-10 cm, 10-20 cm, 20-30 cm, 30-50 cm, 50-70 cm and 70-100 cm. The concentrations of EEG and TG decreased with the increase of soil depth according to a logarithmic function. The Moran’s I coefficient of GRSP was negative in all soil layers except TG in 20-30 cm and 50-70 cm soil layers. When EEG and TG were considered, the Moran’s I coefficient was positive in majority of soil layers within the separation distance of less than 4 m but in soil layers of 10-20 cm and 20-30 cm for EEG and in 30-50 cm for TG. The largest Moran’s I coefficient including EEG and TG was observed in the soil layer of 5-10 cm. The spatial distribution of GRSP was discrete in typical coniferous and broad-leaved temperate forest, and was affected by mycorrhizal colonization rate, soil organic carbon and total nitrogen

The ROS/NF-κB/NR4A2 Pathway is Involved in H\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e2\u3c/sub\u3e Induced Apoptosis of Resident Cardiac Stem Cells via Autophagy

Cardiac stem cells (CSCs)-based therapy provides a promising avenue for the management of ischemic heart diseases. However, engrafted CSCs are subjected to acute cell apoptosis in the ischemic microenvironment. Here, stem cell antigen 1 positive (Sca-1+) CSCs proved to own therapy potential were cultured and treated with H2O2 to mimic the ischemia situation. As autophagy inhibitor, 3-methyladenine (3MA), inhibited H2O2-induced CSCs apoptosis, thus we demonstrated that H2O2 induced autophagy-dependent apoptosis in CSCs, and continued to find key proteins responsible for the crosstalk between autophagy and apoptosis. Nuclear Receptor Subfamily 4 Group A Member 2 (NR4A2), increased upon cardiomyocyte injury with unknown functions in CSCs, was increased by H2O2. NR4A2 siRNA attenuated H2O2 induced autophagy and apoptosis in CSCs, which suggested an important role of NR4A2 in CSCs survival in ischemia conditions. Reactive oxygen species (ROS) and NF- κB (P65) subunit were both increased by H2O2. Either the ROS scavenger, N-acetyl-lcysteine (NAC) or NF-κB signaling inhibitor, bay11-7082 could attenuate H2O2-induced autophagy and apoptosis in CSCs, which suggested they were involved in this process. Furthermore, NAC inhibited NF-κB activities, while bay11-7082 inhibited NR4A2 expression, which revealed a ROS/NF-κB/NR4A2 pathway responsible for H2O2- induced autophagy and apoptosis in CSCs. Our study supports a new clue enhancing the survival rate of CSCs in the infarcted myocardium for cell therapy in ischemic cardiomyopathy