The problem of automatically classifying sensed imagery such as synthetic aperture radar (SAR) into a canonical set of target classes is widely known as automatic target recognition (ATR). A typical ...ATR algorithm comprises the extraction of a meaningful set of features from target imagery followed by a decision engine that performs class assignment. While ATR algorithms have significantly increased in sophistication over the past two decades, two outstanding challenges have been identified in the rich body of ATR literature: 1) the desire to mine complementary merits of distinct feature sets (also known as feature fusion), and 2) the ability of the classifier to excel even as training SAR images are limited. We propose to apply recent advances in probabilistic graphical models to address these challenges. In particular we develop a two-stage target recognition framework that combines the merits of distinct SAR image feature representations with discriminatively learned graphical models. The first stage projects the SAR image chip to informative feature spaces that yield multiple complementary SAR image representations. The second stage models each individual representation using graphs and combines these initially disjoint and simple graphs into a thicker probabilistic graphical model by leveraging a recent advance in discriminative graph learning. Experimental results on the benchmark moving and stationary target acquisition and recognition (MSTAR) data set confirm the benefits of our framework over existing ATR algorithms in terms of improvement in recognition rates. The proposed graphical classifiers are particularly robust when feature dimensionality is high and number of training images is small, a commonly observed constraint in SAR imagery-based target recognition.
Endoplasmic reticulum (ER) stress, a change in the ER homeostasis, leads to initiation of the unfolded protein response (UPR). The primary functions of the UPR are to restore the ER's physiological ...activity and coordinate the apoptotic and adaptive responses. Pathophysiological conditions that augment ER stress include hypoxia, misfolded and/or mutated protein accumulation, and high glucose. Prolonged ER stress is a critical factor in the pathogenesis of metabolic syndrome including type 2 diabetes mellitus, cardiovascular diseases, atherosclerosis, obesity, and fatty liver disease. UPR is a complex homeostatic pathway between newly synthesized proteins and their maturation, although the regulatory mechanisms contributing to the UPR and the possible therapeutic strategies are yet to be clarified. Therefore, a comprehensive understanding of the underlying molecular mechanisms is necessary to develop therapeutic interventions targeting ER stress response. In this review, we discuss the role of ER stress and UPR signaling in the pathogenesis of metabolic syndrome, highlighting the main functions of UPR components. We have emphasized the use of novel small molecular chemical chaperones, considered as modulators of ER stress. The initial studies with these chemical chaperones are promising, but detailed studies are required to define their efficacy and adverse effects during therapeutic use in humans.
For solving linear inverse problems, particularly of the type that appears in tomographic imaging and compressive sensing, this paper develops two new approaches. The first approach is an iterative ...algorithm that minimizes a regularized least squares objective function where the regularization is based on a compound Gaussian prior distribution. The compound Gaussian prior subsumes many of the commonly used priors in image reconstruction, including those of sparsity-based approaches. The developed iterative algorithm gives rise to the paper's second new approach, which is a deep neural network that corresponds to an "unrolling" or "unfolding" of the iterative algorithm. Unrolled deep neural networks have interpretable layers and outperform standard deep learning methods. This paper includes a detailed computational theory that provides insight into the construction and performance of both algorithms. The conclusion is that both algorithms outperform other state-of-the-art approaches to tomographic image formation and compressive sensing, especially in the difficult regime of low training.
Several clinical trials have recently targeted specific pathways implicated in the pathogenesis of idiopathic pulmonary fibrosis (IPF). However, IPF remains plagued by a median survival of 3 yrs and ...emphasises the need for further research with new insights and perspectives. The prevailing pathogenic hypotheses assume that either an inflammatory process or an independent epithelial/fibroblastic disorder may propagate the disease process. Based on knowledge developed with considerable scientific evidence, we provide our perspectives with an alternative point of view that IPF be considered as a neoproliferative disorder of the lung. Genetic alterations, response to growth and inhibitory signals, resistance to apoptosis, myofibroblast origin and behaviour, altered cellular communications, and intracellular signalling pathways are all fundamental pathogenic hallmarks of both IPF and cancer. The concept of IPF as a lethal malignant disorder of the lung might extend beyond the pathogenic link between these two diseases and disclose new pathogenic mechanisms leading to novel therapeutic options, adopted from cancer biology. Moreover, this vision might dawn the awareness of the public, political and scientific community of this devastating disease from an angle different from the current perception and provoke new ideas and studies to get a better understanding to control the otherwise relentless progressive disease.
Dillenia indica L. is an edible plant from the Dilleniaceae family present in the forest of India and other Asian countries. Different parts of this plant are being used in the traditional system of ...medicines for various diseases like diabetes, indigestion, asthma, jaundice, and rheumatic pain by various rural communities. This plant is very common among Khamptis traditional healers, the rural community of the Dhemaji district of Assam, ethnic communities of Dibru-Saikhowa Biosphere Reserve of Northeast, India for various medicinal uses. It is observed as a ‘vat’ suppressant and ‘pitta’ boosting medicine in Ayurveda.
The aim of this research was to evaluate the effect of hydroethanolic extract of Dillenia indica leaf (DI-HET) against non-alcoholic fatty liver disease (NAFLD) as it is reported effective against jaundice in traditional medicine. We are also planning to see the various molecular mechanisms responsible for its effect if it is efficacious.
An in vitro model for NAFLD was employed in this study. For this HepG2 cells were incubated with 100 μM of oleic acid (OA) for 24 h. For evaluation of the effect of DI-HET, the extracts (5 or 10 μg/mL) were pretreated to the OA group. Fenofibrate was the positive control. Various parameters relevant to lipogenesis and β-oxidation of fatty acids like intracellular lipid accumulation, reactive oxygen species (ROS), mitochondrial stress, and key proteins were studied.
DI-HET significantly reduced the intracellular lipid accumulation in OA treated cells. And also substantially decreased the expression of lipogenic proteins and increased β-oxidation in the OA group. OA induced ROS generation was found to reduce with DI-HET treatment. Western blot analysis showed that the expression of LXR-α, SREBP-1C, SREBP-2, HMGCR, FAS, CD-36, and ACOX-1 were downregulated while that of SIRT-1, p-LKB-, p-AMPK, p-ACC, CPT-1, and PPAR-α upregulated in DI-HET treatment. LCMS/MS analysis showed the presence of polyphenols like naringenin, catechin, epicatechin, shikimic acid, syringic acid, vanillic acid, and kaempferol.
These results suggest that DI-HET is effective against NAFLD by activation of the SIRT-1/p-LKB-1/AMPK signaling pathway via polyphenols present in the extract.
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•D. indica was effective against the NAFLD in HepG2.•It exerts its effect via the SIRT-1/p-LKB-1/AMPK signaling pathway.•LCMS/MS analysis revealed the presence of therapeutically important polyphenols.•This can be developed as a nutraceutical for liver diseases.
In the present work, Zinc oxide nanoparticles (ZnO Nps) have been successfully prepared through a simple, effective and low cost solution combustion method using Zn (NO3)2·6H2O as an oxidizer, ...chakkota (Common name=Pomelo) fruit juice as novel fuel. X-ray diffraction pattern indicates the hexagonal wurtzite structure with average crystallite size of ~22nm. ZnO Nps were characterized with the aid of different spectroscopic techniques such as Raman spectroscopy, Fourier Transform Infrared spectroscopy, Photoluminescence and UV–Visible spectroscopy. FTIR shows characteristic ZnO vibrational mode at 393cm−1. SEM images show that the particles are agglomerated. TEM image shows the size of the particles are about 10–20nm. Further, in order to establish practical applicability of the synthesized ZnO Nps, photocatalytic degradation of methylene blue (MB) dye as a model system was studied in presence of UV (665nm) light. In addition to this, the antibacterial activity was screen against 3 bacterial strains and electrochemical sensor performance towards the quantification of dopamine at nano molar concentrations was also explored.
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•Synthesis of ZnO Nps via combustion method using Pamelo fruite juice as a fuel•XRD and Raman spectroscopy confirms the hexagonal wurtzite structure.•TEM images exhibts particle size around 20nm.•ZnO Nps shws good photocatalytic degradation for degradation of methylene blue.•ZnO Nps shows good antibacterial activity and sensor for dopamine at nanomolar
Sonar imaging has seen vast improvements over the last few decades due in part to advances in synthetic aperture sonar. Sophisticated classification techniques can now be used in sonar automatic ...target recognition (ATR) to locate mines and other threatening objects. Among the most promising of these methods is sparse reconstruction-based classification (SRC), which has shown an impressive resiliency to noise, blur, and occlusion. We present a coherent strategy for expanding upon SRC for sonar ATR that retains SRC's robustness while also being able to handle targets with diverse geometric arrangements, bothersome Rayleigh noise, and unavoidable background clutter. Our method, pose-corrected sparsity (PCS), incorporates a novel interpretation of a spike and slab probability distribution toward use as a Bayesian prior for class-specific discrimination in combination with a dictionary learning scheme for localized patch extractions. Additionally, PCS offers the potential for anomaly detection in order to avoid false identifications of tested objects from outside the training set with no additional training required. Compelling results are shown using a database provided by the U.S. Naval Surface Warfare Center.
To document laryngeal framework rupture following voluntary cough-holding as an airway complication of donning a personal protective equipment suit that was too small in size.
Clinical record and ...literature review, with proposition of plausible aerodynamics of the airway injury.
Whilst carrying out his duty in the coronavirus disease ward, a resident attempted to stifle a paroxysm of cough when wearing a personal protective equipment suit that was too small with his neck flexed and restricted. There was a sudden release of pressure, intense pain and swelling in the neck with crepitus. Imaging revealed a non-displaced fracture in the lower end of the partially ossified right thyroid lamina, a cricothyroid membrane tear and subcutaneous emphysema. The symptoms resolved gradually on conservative management.
This report underlines the importance of donning appropriately sized personal protective equipment and encouraging its proper use amongst coronavirus disease 2019 caregivers. Non-traumatic laryngeal injury, itself a rare event, has never been reported as a posture-related complication of wearing personal protective equipment.
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