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Remote sensing data and techniques are reliable tools for monitoring land cover and land-use change. For time-series change detection algorithms, detecting the breakpoints accurately is the key ele...

Background: Lipopolysaccharide (LPS) is a potent trigger of macrophage-mediated inflammation and its repeated stimulation results in immune tolerance. This study is to explore the cellular mechanisms of LPS-mediated tumor immune tolerance and to investigate whether melatonin can reverse this tolerance. Methods: The effect of melatonin and LPS on macrophages was assessed by cell proliferation, morphological changes, phagocytosis and autophagy in vitro. The tumor-preventing effect of melatonin and LPS were evaluated in the urethane-induced lung carcinoma model and in the H22 liver cancer allograft model. Immunofluorescence, immunohistochemistry and ELISA were used to examine protein expression. The related targets and pathways of melatonin were predicted by comprehensive bioinformatics, and the clinical association of bacterial infections and survival was evaluated in cancer patients by meta-analysis.Results: In vitro，Raw264.7 macrophages were polarized toward the M1 phenotype by single LPS administration but toward the M2 phenotype by repeated LPS administration. Interestingly, combination treatment with repeated LPS and 10 µM melatonin prevented macrophage polarization toward the M2-like phenotype and exerted lasting antitumor efficacy. In the urethane-induced lung carcinoma model, repeated LPS administration stimulated macrophage polarization toward the M2 phenotype and promoted lung carcinogenesis, which was abrogated by macrophage depletion, while melatonin alone or in combination with repeated LPS challenge restored M1-like macrophages and prevented carcinogenesis. In the H22 liver cancer allograft model, melatonin maintained the macrophage phenotype and promoted the tumor-suppressing effect of repeated LPS challenge. Furthermore, we found that macrophages repeatedly stimulated with LPS had a high level of surface lipid rafts that mediated PI3K/AKT and JAK2/STAT3 signaling and prevented both LPS sensitivity and immune response by self-expression of PD-L1 and surface expression of PD-1 receptor on NK cells, whereas melatonin decreased surface lipid rafts and PI3K/AKT and JAK2/STAT3 signaling. Finally, we conducted a comprehensive bioinformatics analysis of melatonin-relevant targets and pathways involved in M2 macrophage polarization and evaluated the clinical associations of bacterial infections and survival in cancer patients. Conclusions: This study suggests a function of melatonin in regulating macrophage polarization to maintain LPS-stimulated tumor immune surveillance.

In this paper, we propose a significance test-based change detection method that can automatically discriminate between changed and unchanged pixels in the difference image. The method adaptively considers the local contextual information, which is contained in the neighborhoods of each pixel, to derive the decision threshold. In our method, a significance test algorithm based on maximuming a posteriori estimate is constructed; then, a weight to each pixel in the block is imposed to increase the change detection accuracy. In our proposed method, the distribution of the difference image satisfying Laplace model also leads to good precision. For the experimental component, two types of images were tested. And experimental results proved the effectiveness of the significance test method when compared with four state-of-the-art change detection methods.

Currently, individual animal movement data can be obtained using a variety of methods, but each methodology is limited in either temporal or spatial resolution. A new method of active tracking was developed which utilizes autonomous underwater vehicles (AUV) equipped with stereo-hydrophones that can accurately estimate the position of a moving acoustic tag, while remaining at a distance. This technology was tested and compared to standard human-based active tracking technology to understand the benefits and limitations of this new technique. An AUV and a researcher independently tracked stationary and moving targets of known location in order to compare their spatial and temporal accuracy. Both methods were then used to track a leopard shark, Triakis semifasciata, in the field. The autonomous vehicle accurately positioned both stationary and moving tags with a positional error of

Time series change detection is an effective way of analyzing land use and land cover change (LULCC). However, producing accurate LULCC map is still challenging because of amplified false detections and high omission errors. Here, we proposed a new change detection method to reduce false detections while maintaining low omission errors. First, the time series is decomposed into three components in the temporal scale which is seasonal, linear trend and noise. The potential LULCC are detected in the seasonal component to keep a low omission rate. Second, the false alarm rate is reduced by combining the breakpoint information of all the spectral bands and the post-classification result. Finally, the information of neighboring pixels is utilized to reduce false alarm further. With Kansas City as the study sites, the results demonstrated the effectiveness and stability of the proposed approach. Our results will show the timing and location of LULCC for qualitative analysis. The results will also show that false detections are reduced significantly without compromising omission rate for quantitative analysis.

Hyperspectral anomaly change detection aims at finding rare and anomalous changes in multi-temporal hyperspectral images. There are existing many works about anomaly change detection algorithms, whereas they are all proposed and evaluated on their own datasets. With the publication of “Viareggio 2013 Trial”, it is necessary to compare the state-of-the-art methods on this dataset with fully ground-truth references. In this paper, we compare 8 anomaly change detection methods on the two multi-temporal pairs of “Viareggio 2013 Trial”. The experimental results indicate that slow feature analysis with LCRA obtains the best performance.

With the development of 5G and the Internet of Things (IoT), mobile terminals are widely used in various applications under multicast scenarios. However, due to the limited computation resources of mobile terminals, reducing the computation cost of members in group key distribution processes of dynamic groups has become an important issue. In this paper, we propose a computation-efficient group key distribution (CEGKD) protocol. First, an improved secret sharing scheme is proposed to construct faster encryption and decryption algorithms. Second, the tree structure of logical key hierarchy (LKH) is employed to implement a simple and effective key-numbering method. Theoretical analysis is given to prove that the proposed protocol meets forward security and backward security. In addition, the experiment results show that the computation cost of CEGKD on the member side is reduced by more than 85% compared with that of the LKH scheme.

Background Hypercoagulation and neutrophilia are described in several cancers, however, whether they are involved in lung carcinogenesis is currently unknown. Emodin is the main bioactive component from Rheum palmatum and has many medicinal values, such as anti-inflammation and anticancer. This study is to investigate the contributions of neutrophils to the effects of emodin on hypercoagulation and carcinogenesis. Methods The effects of emodin on neutrophil phenotypes were assessed by cell proliferation, morphological changes, phagocytosis and autophagy in vitro. The anti-coagulation and cancer-preventing actions of emodin were evaluated in the urethane-induced lung carcinogenic model. The expressions of Cit-H3 and PAD4 in lung sections were assessed by immunohistochemistry, CD66b+ neutrophils were distinguished by immunofluorescence, and cytokines and ROS were examined with ELISA. The neutrophils-regulating and hypercoagulation-improving efficacies of emodin were confirmed in a Lewis lung cancer allograft model. The related targets and pathways of emodin were predicted by network pharmacology. Results In vitro, emodin at the dose of 20 µM had no effect on cell viability in HL-60N1 but increased ROS and decreased autophagy and thus induced apoptosis in HL-60N2 with the morphological changes. In the urethane-induced lung carcinogenic model, before lung carcinogenesis, urethane induced obvious hypercoagulation which was positively correlated with lung N2 neutrophils. There were the aggravated hypercoagulation and lung N2 neutrophils after lung carcinoma lesions. Emodin treatment resulted in the ameliorated hypercoagulation and lung carcinogenesis accompanied by the decreased N2 neutrophils (CD66b+) in the alveolar cavity. ELISA showed that there were more IFN-γ, IL-12 and ROS and less IL-6, TNF-α and TGF-β1 in the alveolar cavity in the emodin group than those in the control group. Immunohistochemical analysis showed that emodin treatment decreased Cit-H3 and PAD4 in lung sections. In the Lewis lung cancer allograft model, emodin inhibits tumor growth accompanied by the attenuated coagulation and intratumor N2 neutrophils. Network pharmacology indicated the multi-target roles of emodin in N2 neutrophil activation. Conclusions This study suggests a novel function of emodin, whereby it selectively suppresses N2 neutrophils to prevent hypercoagulation and lung carcinogenesis.

Recently, the United States Geological Survey (USGS) has released a new dataset, called Landsat Analysis Ready Data (ARD), which is designed specifically for facilitating time series analysis. In this study, we evaluated the temporal consistency of this new dataset and recommended several processing streamlines for improving data consistency. Specifically, we examined the impacts of data resampling, cloud/cloud shadow detection, Bidirectional Reflectance Distribution Function (BRDF) correction, and topographic correction on the temporal consistency of the Landsat Time Series (LTS). We have four major observations. First, single-resampled data (ARD) are generally more consistent than double-resampled data (re-projected Collection 1 data), but the difference is very minor. Second, the improved cloud and cloud shadow detection approach (e.g., Fmask 4.0 vs. 3.3) moderately increased data consistency. Third, BRDF correction contributed the most in making LTS consistent. Finally, we corrected the topographic effects by using several widely used algorithms, including Sun-Canopy-Sensor (SCS), a semiempirical SCS (SCS+C), and Illumination Correction (IC) algorithms, however they were found to have very limited or even negative impacts on the consistency of LTS. Therefore, we recommend using Landsat ARD with the improved cloud and cloud shadow detection approach (Fmask 4.0), and with BRDF correction for routine time series analysis.

Momordicoside G is a bioactive component from Momordica charantia, this study explores the contributions of macrophages to the effects of momordicoside G on lung injury and carcinoma lesion. In vitro, when administered at the dose that has no effect on cell viability in M2-like macrophages, momordicoside G decreased ROS and promoted autophagy and thus induced apoptosis in M1-like macrophages with the morphological changes. In the urethane-induced lung carcinogenic model, prior to lung carcinoma lesions, urethane induced obvious lung injury accompanied by the increased macrophage infiltration. The lung carcinoma lesions were positively correlated with lung tissue injury and macrophage infiltration in alveolar cavities in the control group, these macrophages showed mainly a M1-like (iNOS+/CD68+) phenotype. ELISA showed that the levels of IL-6 and IL-12 were increased and the levels of IL-10 and TGF-β1 were reduced in the control group. After momordicoside G treatment, lung tissue injury and carcinoma lesions were ameliorated with the decreased M1-like macrophages and the increased M2-like (arginase+/CD68+) macrophages, whereas macrophage depletion by liposome-encapsulated clodronate (LEC) decreased significantly lung tissue injury and carcinoma lesions and also attenuated the protective efficacy of momordicoside G. The M2 macrophage dependent efficacy of momordicoside G was confirmed in a LPS-induced lung injury model in which epithelial closure was promoted by the transfer of M2-like macrophages and delayed by the transfer of M1-like macrophages. To acquire further insight into the underlying molecular mechanisms by which momordicoside G regulates M1 macrophages, we conduct a comprehensive bioinformatics analysis of momordicoside G relevant targets and pathways involved in M1 macrophage phenotype. This study suggests a function of momordicoside G, whereby it selectively suppresses M1 macrophages to stimulate M2-associated lung injury repair and prevent inflammation-associated lung carcinoma lesions.

This paper presents a multi-autonomous underwater vehicle system capable of cooperatively and autonomously tracking and following marine targets (i.e., fish) tagged with an acoustic transmitter. The AUVs have been equipped with stereo-hydrophones that receive signals broadcasted by the acoustic transmitter tags to enable real-time calculation of bearing-to-tag and distance-to-tag measurements. These measurements are shared between AUVs via acoustic modem and fused within each AUV's particle filter for estimating the target's position. The AUVs use a leader/follower multi-AUV control system to enable the AUVs to drive toward the estimated target state by following collision-free paths. Once within the local area of the target, the AUVs circumnavigate the target state until it moves to another area. The system builds on previous work by incorporating a new SmartTag package that can be attached to an individual's dorsal fin. The SmartTag houses a full inertial measurement unit (INU), video logger, acoustic transmitter, and timed release mechanism. After real-time AUV tracking experiments, the SmartTag is recovered. Logged IMU data are fused with logged AUV-obtained acoustic tag measurements within a particle filter to improve state estimation accuracy. This improvement is validated through a series of multi-AUV shark and boat tracking experiments conducted at Santa Catalina Island, California. When compared with previous work that did not use the SmartTag package, results demonstrated a decrease in mean position estimation error of 25–75%, tag orientation estimation errors dropped from 80° to 30° , the sensitivity of mean position error with respect to distance to the tag was less by a factor of 50, and the sensitivity of mean position error with respect to acoustic signal reception frequency to the tag was 25 times less. These statistics demonstrate a large improvement in the system's robustness when the SmartTag package is used.

The aim of the present study was to investigate the potential neuroprotective effects of electroacupuncture (EA) in the treatment of cerebral ischemia/reperfusion (I/R) injury, and to elucidate the association between this neuroprotective effect and brain ultrastructure and expression of matrix metalloproteinase (MMP)‑2 and 9. Rats underwent focal cerebral I/R injury by arterial ligation and received in vivo therapeutic EA at the Baihui (DU20) and Shenting (DU24) acupoints. The therapeutic efficacy was then evaluated following the surgery. The results of the current study demonstrated that EA treatment significantly ameliorated neurological deficits and reduced cerebral infarct volume compared with I/R injured rats. Furthermore, EA improved the learning and memory ability of rats following I/R injury, inhibited blood brain barrier breakdown and reduced neuronal damage in the ischemic penumbra. Furthermore, EA attenuated ultrastructural changes in the brain tissue following ischemia and inhibited MMP‑2/MMP‑9 expression in cerebral I/R injured rats. The results suggest that EA ameliorates anatomical deterioration, and learning and memory deficits in rats with cerebral I/R injury.

Monitoring cotton status during the growing season is critical in increasing production efficiency. The water status in cotton is a key factor for yield and cotton quality. Stem water potential (SWP) is a precise indicator for assessing cotton water status. Satellite remote sensing is an effective approach for monitoring cotton growth at a large scale. The aim of this study is to estimate cotton water stress at a high temporal frequency and at a large scale. In this study, we measured midday SWP samples according to the acquisition dates of Sentinel-2 images and used them to build linear-regression-based and machine-learning-based models to estimate cotton water stress during the growing season (June to August, 2018). For the linear-regression-based method, we estimated SWP based on different Sentinel-2 spectral bands and vegetation indices, where the normalized difference index 45 (NDI45) achieved the best performance (R2 = 0.6269; RMSE = 3.6802 (-1*swp (bars))). For the machine-learning-based method, we used random forest regression to estimate SWP and received even better results (R2 = 0.6709; RMSE = 3.3742 (-1*swp (bars))). To find the best selection of input variables for the machine-learning-based approach, we tried three different data input datasets, including (1) 9 original spectral bands (e.g., blue, green, red, red edge, near infrared (NIR), and shortwave infrared (SWIR)), (2) 21 vegetation indices, and (3) a combination of original Sentinel-2 spectral bands and vegetation indices. The highest accuracy was achieved when only the original spectral bands were used. We also found the SWIR and red edge band were the most important spectral bands, and the vegetation indices based on red edge and NIR bands were particularly helpful. Finally, we applied the best approach for the linear-regression-based and the machine-learning-based methods to generate cotton water potential maps at a large scale and high temporal frequency. Results suggests that the methods developed here has the potential for continuous monitoring of SWP at large scales and the machine-learning-based method is preferred.

6-Gingerol (6-G) is the main bioactive component in Ginger (Zingiber officinale Roscoe). The aim of this study was to explore the contribution of macrophage polarization in 6-G-associated anti-cancer effects. In a urethane-induced lung carcinogenic model, lung carcinogenesis was positively correlated with macrophage (F4/80+) infiltration in lung interstitial in the control group. Furthermore, higher numbers of arginase+/F4/80+ M2 cells than iNOS+/F4/80+ M1 cells were observed in interstitial macrophages. Moreover, macrophage depletion by liposome-encapsulated clodronate (LEC) could significantly prevent lung carcinogenesis, whereas pexidartinib promoted lung carcinogenesis. After 6-G treatment, lung carcinogenesis was ameliorated with increased M1 macrophages and decreased M2 macrophages in the lung interstitial. ELISA showed that the levels of IFN-γ and IL-12 increased and the levels of IL-10 and TGF-β1 decreased in the alveolar cavity compared to those in the control group. Unexpectedly, the carcinogenesis-preventing efficacy of 6-G was promoted in LEC-treated mice, but completely aborted in pexidartinib-treated mice. In the in vitro experiment, 6-G reset the IL-4-induced arginase+ M2 cells toward iNOS+ M1 cells and exhibited reduced levels of arginase 1 and ROS and elevated levels of L-arginine and NO. LEC and nor-NOHA selectively suppressed M2 macrophages but had a negligible effect on M1 macrophages, whereas pexidartinib decreased both M2 and M1 macrophages. The iNOS+ macrophage-promoting efficacy of 6-G was increased by LEC, but was completely eliminated by pretreatment with pexidartinib or nor-NOHA. M2 macrophage-resetting efficacy of 6-G was confirmed in a Lewis lung cancer allograft model. This study indicated a reprogramming effect of 6-G as an arginase inhibitor on tumor supporting macrophages.

The present study aimed to investigate the mechanisms by which electroacupuncture (EA) ameliorates learning and memory in rats with cerebral ischemic‑reperfusion (I/R) injury. Focal cerebral ischemia was induced in adult male Sprague‑Dawley (SD) rats by transient middle cerebral artery occlusion (MCAO). Following MCAO surgery, the rats received EA at the Shenting (DU24) and Baihui (DU20) acupoints. The results of the present study demonstrated that treatment with EA significantly ameliorated neurological deficits and reduced cerebral infarct volume (P

Electro-acupuncture (EA) is a novel therapy based on combining traditional acupuncture with modern electrotherapy, and it is currently being investigated as a treatment for ischemic stroke. In the present study, we aimed to investigate the mechanisms through which EA regulates the proliferation of neural progenitor cells (NPCs) in the cortical peri‑infarct area after stroke. The neuroprotective effects of EA on ischemic rats were evaluated by determining the neurological deficit scores and cerebral infarct volumes. The proliferation of the NPCs and the activation of the Wnt/β‑catenin signaling pathway in the cortical peri‑infarct area were examined. Our results revealed that EA significantly alleviated neurological deficits, reduced the infarct volume and enhanced NPC proliferation [nestin/glial fibrillary acidic protein (GFAP)‑double positive] in the cortex of rats subjected to middle cerebral artery occlusion (MCAO). Moreover, the Wnt1 and β‑catenin mRNA and protein levels were increased, while glycogen synthase kinase‑3 (GSK3) transcription was suppressed by EA. These results suggest that the upregulatory effects of EA on the Wnt/β‑catenin signaling pathway may promote NPC proliferation in the cortical peri-infarct area after stroke, consequently providing a therapeutic effect against cerebral ischemia.

This paper presents a multi-AUV state-estimator that can determine the 3D position of a tagged fish. In addition to angle measurements, the state-estimator also incorporates distance and depth measurements. These additional sensor measurements allow for greater accuracy in the position es- timates. A newly developed motion model that better accounts for multiple hypotheses of the motion of a tagged fish is used to increase the robustness of the state-estimator. A series of multi-AUV shark tracks were conducted at Santa Catalina Island, California over the span of four days to demonstrate the ability of the state-estimator to determine the 3D position of a tagged leopard shark. Additional experiments in which the AUVs tracked a tagged boat of known location were conducted to quantify the performance of the presented state-estimator. Experimental results demonstrate a three-fold decrease in mean state-estimation error compared to previous works. I. INTRODUCTION Studying the spatial movement of sharks and other fishes is an important tool for monitoring habitat and maintaining fish populations. Typical methods for tracking fish include tagging individuals with acoustic transmitters, and then using hydrophone-receiver systems to detect and measure the signals transmitted. Often, the hydrophone-receivers are placed at fixed locations around an environment of interest to passively track tagged individuals that move through the static array (1). Alternatively, active tracking can be done manually by mounting a directional hydrophone on a boat and continuously following the tagged individual from the surface for periods up to 96h (2). To enable active tracking without the need for human operators, the authors have demonstrated in previous works that a multi-AUV system using only low resolution angle measurements is able to autonomously track and follow tagged leopard sharks (3). A key component of this system is a state-estimator which determines the 2D position of the tagged shark (4). In order to provide more sensor

Featuring pronounced controllability, versatility, and scalability, electrophoretic deposition (EPD) has been proposed as an efficient method for film assembly and electrode/solid electrolyte fabrication in various energy storage/conversion devices including rechargeable batteries, supercapacitors, and fuel cells. High-quality electrodes and solid electrolytes have been prepared through EPD and exhibit advantageous performances in comparison with those realized with traditional methods. Recent advances in the application of EPD materials in electrochemical energy storage and conversion devices are summarized. In particular, the parameters that influence the efficiency of an EPD process from colloidal preparation to deposition are evaluated with the aim to provide insightful guidance for realizing high-performance electrochemical energy conversion materials and devices.