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Solid Core Photonic Crystal Fiber for Dispersion tailoring in Optical Tele Communication systems
Get PDFThe studies have been carried out on the viability in realizing fully infiltrated solid core photonic crystal fiber based dispersion compensating fiber with suitable high index infiltrate and tapered solid core large mode area fiber for optical communication networks in telecommunication band. The commercial fiber LMA-20 can be made to stretch negative dispersion by suitable fluid infiltration in all air holes of fiber cladding hexagonal structure and can be used as an alternative of existing dispersion compensators (PCFs with low pitch values)
Epigenetic Modulations Induction Using DSCR1 Ectopic Expression in Breast Cancer Cells
Get PDFToday, prognosis, diagnosis and treatment of cancers are progressing with non-invasive methods, including investigation and modification of the DNA methylation profile in cancer cells. One of the effective factors in regulating gene expression in mammals is DNA methylation. Methylation alterations of genes by external factors can change the expression of genes and inhibit the cancer. In the present study, we investigated the effect of Down syndrome critical region 1 gene (DSCR1) ectopic expression on the methylation status of the BCL-XL, ITGA6, TCF3, RASSF1A, DOK7, VIM and CXCR4 genes in breast cancer cell lines. The effect of DSCR1 ectopic expression on cell viability in MCF7, MDA-MB-468, MDA-MB-231 and MCF10A cell lines was evaluated using MTT assay after the cells treated by lentivirus vectors harboring DSCR1 for 72 hours. Methylation status of BCL-XL, ITGA6, TCF3, RASSF1A, DOK7, VIM and CXCR4 genes in breast cancer cell lines was assessed by Restriction Enzyme PCR (REP) method. Also, methylation changes of these genes in breast cancer cell lines after treatment by lentivirus vectors harboring DSCR1 for 7 days were analyzed by REP method. To confirm the effect of DSCR1 on methylation of genes, Real-time PCR was performed. The MTT assay results indicated that DSCR1 ectopic expression reduced cell viability in all three human breast cancer cell lines. Our results showed that DSCR1 ectopic expression after 6 days reversed the hypomethylation status of the BCL-XL, ITGA6, TCF3, VIM and CXCR4 genes and hypermethylation of RASSF1A and DOK7 genes. The expression levels of BCL-XL, ITGA6, TCF3, VIM and CXCR4 mRNA significantly reduced (PRASSF1A and DOK7 mRNA significantly increased (PDSCR1 ectopic expression on the methylation status of breast cancer cells and identify a novel agent for epigenetic therapy
Systems Neuroprotective Mechanisms in Ischemic Stroke
Get PDFIschemic stroke, although causing brain infarction and neurological deficits, can activate innate neuroprotective mechanisms, including regional mechanisms within the ischemic brain and distant mechanisms from non-ischemic organs such as the liver, spleen, and pancreas, supporting neuronal survival, confining brain infarction, and alleviating neurological deficits. Both regional and distant mechanisms are defined as systems neuroprotective mechanisms. The regional neuroprotective mechanisms involve release and activation of neuroprotective factors such as adenosine and bradykinin, inflammatory responses, expression of growth factors such as nerve growth factors and neurotrophins, and activation and differentiation of resident neural stem cells to neurons and glial cells. The distant neuroprotective mechanisms are implemented by expression and release of endocrine neuroprotective factors such as fibroblast growth factor 21, resistin like molecule γ, and trefoil factor 3 from the liver; brain-derived neurotrophic factor and nerve growth factor from the spleen; and neurotrophin 3 and vascular endothelial growth factor C from the pancreas. Furthermore, ischemic stroke induces mobilization of bone marrow hematopoietic stem cells and endothelial progenitor cells into the circulatory system and brain, contributing to neuroprotection. The regional and distant mechanisms may act in coordination and synergy to protect the ischemic brain from injury and death. This paper addresses these mechanisms and associated signaling networks
Fast Force Loading Disrupts Molecular Binding Stability in Human and Mouse Cell Adhesions
Get PDFForce plays critical roles in cell adhesion and mechano-signaling, partially by regulating the dissociation rate, i.e., off-rate, of receptor-ligand bonds. However, the mechanism of such regulation still remains elusive. As a controversial topic of the field, when measuring the “off-rate vs. force” relation of the same molecular system, different dynamic force spectroscopy (DFS) assays (namely, force-clamp and force-ramp assays) often yield contradictive results. Such discrepancies hurdled our further understanding of molecular binding, and casted doubt on the existing theoretical models. In this work, we used a live-cell DFS technique, biomembrane force probe, to measure the single-bond dissociation in three receptor-ligand systems which respectively have important functions in vascular and immune systems: human platelet GPIbα-VWF, mouse T cell receptor-OVA peptide:MHC, and mouse platelet integrin αIIbβ3-fibrinogen. Using force-clamp and force-ramp assays in parallel, we identified that the force loading disrupted the stability of molecular bonds in a rate-dependent manner. This disruptive effect was achieved by the transitioning of bonds between two dissociation states: faster force loading induces more bonds to adopt the fast-dissociating state (and less to adopt the slow-dissociating state). Based on this mechanism, a new biophysical model of bond dissociation was established which took into account the effects of both force magnitude and loading rate. Remarkably, this model reconciled the results from the two assays in all three molecular systems under study. Our discoveries provided a new paradigm for understanding how force regulates receptor-ligand interactions and a guideline for the proper use of DFS technologies. Furthermore, our work highlighted the opportunity of using different DFS assays to answer specific biological questions in the field of cell adhesion and mechano-signalin
2-D Statistical Damage Detection of Concrete Structures Combining Smart Piezoelectric Materials and Scanning Laser Doppler Vibrometry
Get PDFIn the present study a new structural health monitoring (SHM) technique is proposed as well as a new damage index based on 2-D error statistics. The proposed technique combines the electromechanical impedance technique (EMI) which is based on the use of piezoelectric Lead Zirconate Titanate (PZT) patches and Scanning Laser Doppler Vibrometry (SLDV) for damage detection purposes of concrete structures and early age monitoring. Typically the EMI technique utilizes the direct and inverse piezoelectric effect of a PZT patch attached to a host structure via an impedance analyzer that is used for both the actuation and sensing the response of the PZT-Host structure system. In the proposed technique the attached PZTs are actuated via a function generator and the PZT-Host structure response is obtained by a Scanning Laser Doppler Vibrometer. Spectrums of oscillation velocity of the surface of the attached PZTs vertical to the laser beam versus frequency are obtained and are evaluated for SHM purposes. This damage detection approach also includes the use of a damage index denoted as ECAR (Ellipse to Circle Area Ratio) based on 2-D error statistics and is compared to the Root Mean Square Deviation (RMSD) damage index commonly used in SHM applications. Experimental results include ascending uniaxial compressive load of concrete cubic specimens, ascending three point bending of reinforced concrete beam specimens and early age monitoring of concrete. Results illustrate the efficiency of the proposed technique in damage detection as well as early age monitoring as, in the first case, both severity and location of damage can be determined by examining the values of damage indices for each damaged state and in the early age monitoring case damage indices follow the strength gain curve
Multi-Mode Guided Waves Based Reference-Free Damage Diagnostic Imaging in Plates
Get PDFProbability-based diagnostic imaging (PDI) is one of the most well-known damage identification methods using guided waves. It is usually applied to diagnose damage in plates. The previous studies were dependent on the certain damage index (DI) which is always calculated from the guided wave signals. In conventional methods, DI is simply defined by comparing the real-time data with the baseline data as reference. However, the baseline signal is easily affected by varying environmental conditions of structures. In this paper, a reference-free diagnostic imaging method is developed to avoid the influence of environmental factors, such as temperature and load conditions. The DI is defined based on the mode conversion of multi-mode guided waves with real-time signals without baseline signals. To improve the accuracy of diagnosis, two terms are included in the reference-free DI. One is called energy DI, which is defined based on the feature of signal energy. The other is called correlation DI and is defined based on the correlation coefficient. Then the PDI algorithm can be carried out instantaneously according to the reference-free DI. The real-time signals which are used to calculate DI are collected by the piezoelectric lead zirconate titanate (PZT) transducers placed on both sides of a plate. The numerical simulations by the finite element (FE) method on aluminum plates with PZT arrays are performed to validate the effectiveness of the reference-free damage diagnostic imaging. The approach is validated by two different arrays: a circle network and a square network. The results of diagnostic imaging are demonstrated and discussed in this paper. Furthermore, the advantage of reference-free DI is investigated by comparing the accuracy of defined reference-free DI and energy DI
Saccharification of Sugarcane Bagasse Using an Enzymatic Extract Produced by Aspergillus fumigatus
Get PDFThis study investigates the efficiency of a crude enzymatic extract produced by Aspergillus fumigatus SCBM6 by solid state fermentation (SSF) in the hydrolysis of alkali pretreated sugarcane bagasse (PTB). After SSF using in natura sugarcane bagasse (SCB), the enzymatic extract presented 21.33 U.g–1 of β-glucosidase and 544.46 U.g–1of xylanase. The alkaline pretreatment with sodium hydroxide (2% NaOH (w/v) removed 43% of the lignin from PTB and the cellulosic fraction increased to 75%. The hydrolysis was optimized as a function of time, temperature, and concentration of PTB. After hydrolysis, the maximum yield (30.05%) of total released reducing sugars (TRS) was obtained under the following conditions: 24 h, 55 °C, 2% of PTB and 3 U.g–1 of β-glucosidase (CBU). Furthermore, an approximate TRS value (26.4%) was also obtained after saccharification carried out during 6 h, 55 °C, 4% of PTB and 1 CBU. These results indicate that hydrolysis can be performed in a short incubation period and with low enzymatic load for reasonable TRS release
Quantum Blockchain: A Decentralized, Encrypted and Distributed Database Based on Quantum Mechanics
Get PDFQuantum blockchain can be understood as a decentralized, encrypted and distributed database based on quantum computation and quantum information theory. Once the data is recorded in the quantum blockchain, it will not be maliciously tampered with. In recent years, the development of quantum computation and quantum information theory makes more and more researchers focus on the research of quantum blockchain. In this paper, we review the developments in the field of quantum blockchain, and briefly analyze its advantages compared with the classical blockchain. The construction and the framework of the quantum blockchain are introduced. Then we introduce the method of applying quantum technology to a certain part of the general blockchain. In addition, the advantages of quantum blockchain compared with classical blockchain and its development prospects are summarized
Review on Video Object Tracking Based on Deep Learning
Get PDFVideo object tracking is an important research topic of computer vision, which finds a wide range of applications in video surveillance, robotics, human-computer interaction and so on. Although many moving object tracking algorithms have been proposed, there are still many difficulties in the actual tracking process, such as illumination change, occlusion, motion blurring, scale change, self-change and so on. Therefore, the development of object tracking technology is still challenging. The emergence of deep learning theory and method provides a new opportunity for the research of object tracking, and it is also the main theoretical framework for the research of moving object tracking algorithm in this paper. In this paper, the existing deep tracking-based target tracking algorithms are classified and sorted out. Based on the previous knowledge and my own understanding, several solutions are proposed for the existing methods. In addition, the existing deep learning target tracking method is still difficult to meet the requirements of real-time, how to design the network and tracking process to achieve speed and effect improvement, there is still a lot of research space
Analysis of the Efficiency-Energy with Regression and Classification in Household Using K-NN
Get PDFThis paper aims to study energy consumption in a house. Home energy man-agement system (HEMS) has become very important, because energy consumption of a residential sector accounts for a significant amount of total energy consumption. However, a conventional HEMS has some architectural limitations among dimensional variables reusability and interoperability. Furthermore, the cost of implementation in HEMS is very expensive, which leads to the disturbance of the spread of a HEMS. Therefore, this study proposes an Internet of Things (IoT) based HEMS with lightweight photovoltaic (PV) system over dynamic home area networks (DHANs), which enables the construction of a HEMS to be scalable reusable and interoperable. The study suggests a technique for decreasing cost of energy that HEMS is using and various perspectives in system. The method that proposed is K-NN (K-Nearest Neighbor) which helps us to analyze the classification and regression datasets. This paper has the result from the data relevant in October 2018 from some buildings of Nanjing University of Information Science and Technology