Adaptive Weighted Nuclear Norm Minimization for Removing Speckle Noise from Optical Coherence Tomography Images

Low-rank matrix approximation is widely used in various fields of computer science, and weighted nuclear norm minimization (WNNM) has demonstrated improved results by shrinking the different weights of singular values. In this paper, an adaptive WNNM is proposed, considering the relative significance of image information by modifying the WNNM. As a result, singular values that contain more important information are relatively saved, whereas those that contain less crucial information are drastically reduced. When applying this method to noised image with black and white dot- noised images, the algorithm showed improved performance in both instances. Especially, when applied to images with white dot noise, the denoised results were outstanding. In addition, the proposed algorithm was successfully applied onto the optical coherence tomography images, numerically and visually.N

Model Predictive Control Technique for Ducted Fan Aerial Vehicles Using Physics-Informed Machine Learning

This paper proposes a model predictive control (MPC) approach for ducted fan aerial robots using physics-informed machine learning (ML), where the task is to fully exploit the capabilities of the predictive control design with an accurate dynamic model by means of a hybrid modeling technique. For this purpose, an indigenously developed ducted fan miniature aerial vehicle with adequate flying capabilities is used. The physics-informed dynamical model is derived offline by considering the forces and moments acting on the platform. On the basis of the physics-informed model, a data-driven ML approach called adaptive sparse identification of nonlinear dynamics is utilized for model identification, estimation, and correction online. Thereafter, an MPC-based optimization problem is computed by updating the physics-informed states with the physics-informed ML model at each step, yielding an effective control performance. Closed-loop stability and recursive feasibility are ensured under sufficient conditions. Finally, a simulation study is conducted to concisely corroborate the efficacy of the presented framework

Preventative effect of TSPO ligands on mixed antibody-mediated rejection through a Mitochondria-mediated metabolic disorder

Abstract Background Immune-mediated rejection was the major cause of graft dysfunction. Although the advances in immunosuppressive agents have markedly reduced the incidence of T-cell-mediated rejection after transplantation. However, the incidence of antibody-mediated rejection (AMR) remains high. Donor-specific antibodies (DSAs) were considered the major mediators of allograft loss. Previously, we showed that treatment with 18-kDa translocator protein (TSPO) ligands inhibited the differentiation and effector functions of T cells and reduced the rejection observed after allogeneic skin transplantation in mice. This study we further investigate the effect of TSPO ligands on B cells and DSAs production in the recipients of mixed-AMR model. Methods In vitro, we explored the effect of treatment with TSPO ligands on the activation, proliferation, and antibody production of B cells. Further, we established a heart-transplantation mixed-AMR model in rats. This model was treated with the TSPO ligands, FGIN1-27 or Ro5-4864, to investigate the role of ligands in preventing transplant rejection and DSAs production in vivo. As TSPO was the mitochondrial membrane transporters, we then investigated the TSPO ligands effect on mitochondrial-related metabolic ability of B cells as well as expression of downstream proteins. Results In vitro studies, treatment with TSPO ligands inhibited the differentiation of B cells into CD138+CD27+ plasma cells; reduced antibodies, IgG and IgM, secretion of B cells; and suppressed the B cell activation and proliferation. In the mixed-AMR rat model, treatment with FGIN1-27 or Ro5-4864 attenuated DSA-mediated cardiac-allograft injury, prolonged graft survival, and reduced the numbers of B cells, including IgG+ secreting B cells, T cells and macrophages infiltrating in grafts. For the further mechanism exploration, treatment with TSPO ligands inhibited the metabolic ability of B cells by downregulating expression of pyruvate dehydrogenase kinase 1 and proteins in complexes I, II, and IV of the electron transport chain. Conclusions We clarified the mechanism of action of TSPO ligands on B-cell functions and provided new ideas and drug targets for the clinical treatment of postoperative AMR

A Physically Interpretable Rice Field Extraction Model for PolSAR Imagery

Reliable and timely rice distribution information is of great value for real-time, quantitative, and localized control of rice production information. Synthetic aperture radar (SAR) has all-weather and all-day observation capability to monitor rice distribution in tropical and subtropical areas. To improve the physical interpretability and spatial interpretability of the deep learning model for SAR rice field extraction, a new SHapley Additive exPlanation (SHAP) value-guided explanation model (SGEM) for polarimetric SAR (PolSAR) data was proposed. First, a rice sample set was produced based on field survey and optical data, and the physical characteristics were extracted using decomposition of polarimetric scattering. Then a SHAP-based Physical Feature Interpretable Module (SPFIM) combing the long short-term memory (LSTM) model and SHAP values was designed to analyze the importance of physical characteristics, a credible physical interpretation associated with rice phenology was provided, and the weight of physical interpretation was combined with the weight of original PolSAR data. Moreover, a SHAP-guided spatial interpretation network (SSEN) was constructed to internalize the spatial interpretation values into the network layer to optimize the spatial refinement of the extraction results. Shanwei City, Guangdong Province, China, was chosen as the study area. The experimental results showed that the physical explanation provided by the proposed method had a high correlation with the rice phenology, and spatial self-interpretation for finer extraction results. The overall accuracy of the rice mapping results was 95.73%, and the kappa coefficient reached 0.9143. The proposed method has a high interpretability and practical value compared with other methods

Response of deep soil drought to precipitation, land use and topography across a semiarid watershed

Soil drought caused by climatic change and/or poor land management in arid and semi-arid regions are seldom recognised due to a lack of comparative data on soil moisture (SM) in soil profiles. This lack of information endangers the sustainability of these fragile ecosystems. The current study assessed spatial-temporal variations of soil drought, as indicated by dried soil layers (DSL), at a watershed scale, and tested the hypothesis that soil drought in deep profiles is controlled by the combined effects of meteorological processes, land use, and topography. We measured SM to a depth of 500 cm on 20 occasions at 73 locations from 2013 to 2016 at a small watershed on the Chinese Loess Plateau (CLP). We also collected data on possible environmental factors including meteorological variables, land use, topographical elements, and soil properties. The DSLs occurred at > 90% of the sampling sites within the watershed, and the spatially and temporally averaged DSL formation depth (DSLFD), DSL thickness (DSLT) and soil water content within the DSL (DSL-SWC) were 125 cm, 257 cm, and 10.4%, respectively. This suggests that 51.4% of the 500-cm-profile is drying out below 125 cm. The DSLFD, DSLT and DSL-SWC demonstrated a moderate degree of variability (20% < CV < 84%) in space, and showed a moderate, moderate and weak temporal variability, in time, respectively. The temporal series of the mean spatial DSLT and DSLFD were significantly correlated with climatic variables. The spatial variation of the mean temporal DSL-SWC differed significantly among the land uses and between shaded and sunlit aspects. We found that plan curvature, slope gradient, clay and silt content regulated DSLs in both space and time. This result verified our hypothesis that meteorological processes, land use, and topography play an essential role in shaping DSL variation and distribution pattern. Taking DSL reclamation into account in the study area, grassland would be the optimum land use type. Understanding this information is helpful for watershed soil and water conservation, and soil drought meditation via the best management practices in the CLP and other water-limited regions with deep soils

MSCs overexpressing GDNF restores brain structure and neurological function in rats with intracerebral hemorrhage

Abstract Mesenchymal stem cells (MSCs) have been applied in transplantation to treat intracerebral hemorrhage (ICH) but with limited efficacy. Accumulated evidence has shown that glial cell-derived neurotrophic factor (GDNF) plays a crucial part in neuronal protection and functional recovery of the brain after ICH; however, GDNF has difficulty crossing the blood–brain barrier, which limits its application. In this study, we investigated the influences of MSCs overexpressing GDNF (MSCs/GDNF) on the brain structure as well as gait of rats after ICH and explored the possible mechanisms. We found that cell transplantation could reverse the neurological dysfunction and brain damage caused by ICH to a certain extent, and MSCs/GDNF transplantation was superior to MSCs transplantation. Moreover, Transplantation of MSCs overexpressing GDNF effectively reduced the volume of bleeding foci and increased the level of glucose uptake in rats with ICH, which could be related to improving mitochondrial quality. Furthermore, GDNF produced by transplanted MSCs/GDNF further inhibited neuroinflammation, improved mitochondrial quality and function, promoted angiogenesis and the survival of neurons and oligodendrocytes, and enhanced synaptic plasticity in ICH rats when compared with simple MSC transplantation. Overall, our data indicate that GDNF overexpression heightens the curative effect of MSC implantation in treating rats following ICH

HTRA1 from OVX rat osteoclasts causes detrimental effects on endplate chondrocytes through NF-κB

Endplate osteochondritis is considered one of the major causes of intervertebral disc degeneration (IVDD) and low back pain. Menopausal women have a higher rate of endplate cartilage degeneration than similarly aged men, but the related mechanisms are still unclear. Subchondral bone changes, mainly mediated by osteoblasts and osteoclasts, are considered an important reason for the degeneration of cartilage. This work explored the role of osteoclasts in endplate cartilage degeneration, as well as its underlying mechanisms. A rat ovariectomy (OVX) model was used to induce estrogen deficiency. Our experiments indicated that OVX significantly promoted osteoclastogenesis and anabolism and catabolism changes in endplate chondrocytes. OVX osteoclasts cause an imbalance between anabolism and catabolism in endplate chondrocytes, as shown by a decrease in anabolic markers such as Aggrecan and Collagen II, and an increase in catabolic markers such as a disintegrin and metalloproteinase with thrombospondin motifs 5 (ADAMTS5) and matrix metalloproteinases (MMP13). Osteoclasts were also confirmed in this study to be able to secrete HtrA serine peptidase 1 (HTRA1), which resulted in increased catabolism in endplate chondrocytes through the NF-κB pathway under estrogen deficiency. This study demonstrated the involvement and mechanism of osteoclasts in the anabolism and catabolism changes of endplate cartilage under estrogen deficiency, and proposed a new strategy for the treatment of endplate osteochondritis and IVDD by targeting HTRA1

Hierarchical Nanoassembly of MoS2/Co9S8/Ni3S2/Ni as a Highly Efficient Electrocatalyst for Overall Water Splitting in a Wide pH Range

The design of low-cost yet high-efficiency electrocatalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) over a wide pH range is highly challenging. We now report a hierarchical co-assembly of interacting MoS2 and Co9S8 nanosheets attached on Ni3S2 nanorod arrays which are supported on nickel foam (NF). This tiered structure endows high performance toward HER and OER over a very broad pH range. By adjusting the molar ratio of the Co:Mo precursors, we have created CoMoNiS-NF-xy composites (x:y means Co:Mo molar ratios ranging from 5:1 to 1:3) with controllable morphology and composition. The three-dimensional composites have an abundance of active sites capable of universal pH catalytic HER and OER activity. The CoMoNiS-NF-31 demonstrates the best electrocatalytic activity, giving ultralow overpotentials (113, 103, and 117 mV for HER and 166, 228, and 405 mV for OER) to achieve a current density of 10 mA cm–2 in alkaline, acidic, and neutral electrolytes, respectively. It also shows a remarkable balance between electrocatalytic activity and stability. Based on the distinguished catalytic performance of CoMoNiS-NF-31 toward HER and OER, we demonstrate a two-electrode electrolyzer performing water electrolysis over a wide pH range, with low cell voltages of 1.54, 1.45, and 1.80 V at 10 mA cm–2 in alkaline, acidic, and neutral media, respectively. First-principles calculations suggest that the high OER activity arises from electron transfer from Co9S8 to MoS2 at the interface, which alters the binding energies of adsorbed species and decreases overpotentials. Our results demonstrate that hierarchical metal sulfides can serve as highly efficient all-pH (pH = 0–14) electrocatalysts for overall water splitting