Modeling and Analysis of Quantum Well Structures in GaNInGaN Light Emitting Diodes

In recent years, there has been great research interest in the development of efficient Group III-Nitride Light Emitting Diodes (LEDs) due to the range of wavelengths covered by this material family. Quantum wells play a significant role in the performance of these optoelectronic devices as they enable tuning in emission wavelength and color of light through variation in composition and width of the well.;The time and cost associated with iterative development and optimization of such new semiconductor devices through physical materials growth and device fabrication can be prohibitive to full exploration of potential design spaces. Technology Computer Aided Design (TCAD) simulation tools have emerged allowing engineers to explore design alternatives at an early stage. However simulations, especially for new materials and devices exhibiting quantum effects, must reliably model material and device physics and produce results that correspond to those that would have been achieved experimentally. In this thesis, tiberCAD, Crosslight APSYS and Synopsys tools have been evaluated and used to design and analyze components of, as well as complete Multiple Quantum Well LEDs. The effect of variations of mole fraction, well width, and bias on Energy Levels and Electroluminescence (EL) has been examined. Simulation results have been compared with theory and measurements from grown and fabricated GaN/InGaN Multiple Quantum Well LEDs

The Effects of Fiber Orientation and Volume Fraction of Fiber on Mechanical Properties of Additively Manufactured Composite Material

Additive manufacturing (AM) also known as 3D printing has tremendous advancements in recent days with a vast number of applications in industrial, automotive, architecture, consumer projects, fashion, toys, food, art, etc. Composite materials are widely used in structures with weight as a critical factor especially in aerospace industry. Recently, additive manufacturing technology, a rapidly growing innovative technology, has gained lot of importance in making composite materials. The properties of composite materials depend upon the properties of constituent’s matrix and fiber. There is lot of research on effect of fiber orientation on mechanical properties of composite materials made using conventional manufacturing methods. It will be interesting and relevant to study the relationship between the fiber orientation and fiber volume with mechanical properties of additively manufactured composite materials. This thesis work presents experimental investigation of mechanical behavior like tensile strength and fatigue life with variation in fiber orientation and fiber volume fraction of 3D printed composite materials. The aim is to study the best combination of volume fraction of fiber and fiber orientation that has better fatigue strength for additive manufactured composite materials. Using this study, we can decide the type of orientation and volume percent for desired properties. This study also finds the range of fatigue limits of 3d printed composite materials

Machine learning is used to classify and mine tweets on multiple levels

Research on sentiment analysis can be found under the discipline of Natural Language Processing (NLP). It is helpful in determining the feelings and meanings that lie beneath the surface of a piece of literature. When attempting to extract sentiments from Twitter data, you face a particularly unique combination of obstacles as a result of the platform's unstructured format, its relatively small size, and the presence of slang, misspellings, and acronyms. The vast majority of researchers analysed the results of multiple sentiment analysis machine learning algorithms and compared their findings. However, merging these methodologies is a topic that has received insufficient attention in the relevant academic literature. According to the findings of this research, mixing many different machine learning algorithms together produces superior outcomes compared to doing it individually. Due to the unprocessed nature of the tweets, this study employs a wide range of preprocessing techniques in order to generate data that can then be used in machine learning classification models. An inquiry into the potential benefits of combining the machine learning algorithms known as KNN and SVM is the primary focus of this work. When making an analytical observation, the classification accuracy and F-measures for each emotion class, as well as the average of those values, are used as inputs. The results of the evaluation show that the proposed hybrid approach is more accurate and has a better F-measure than individual classifiers

The Complex Role of STAT3 in Viral Infections

Signal transducer and activators of transcription-3 (STAT3) regulates diverse biological functions including cell growth, differentiation, and apoptosis. In addition, STAT3 plays a key role in regulating host immune and inflammatory responses and in the pathogenesis of many cancers. Several studies reported differential regulation of STAT3 in a range of viral infections. Interestingly, STAT3 appears to direct seemingly contradictory responses and both pro- and antiviral roles of STAT3 have been described. This review summarized the currently known functions of STAT3 in the regulation of viral replication and pathogenesis of viral infections. Some of the key unanswered questions and the gap in our current understanding of the role of STAT3 in viral pathogenesis are discussed

Studies on the cellular and molecular mechanisms of innate host susceptibility and resistance to influenza A viruses in chicken and ducks

Avian influenza viruses are considered to be key contributors to the emergence of human influenza pandemics. While aquatic birds and ducks are the major reservoir for influenza viruses, they are typically resistant to the effects of viral infection, in contrast to the frequently severe disease observed in chickens. In order to understand whether differences in receptors might contribute to this observation, anatomical distribution of influenza virus receptors (sialic acid SAα2,3-Gal and SA α2,6-Gal) in key organs of both species was studied using lectin histochemistry with linkage specific lectins, and receptor binding assays with swine H1N1 (classical A/sw/Iowa/15/30) and avian H2N3 (A/mallard duck/England/7277/06) influenza viruses. Widespread presence of both SAα 2,6-Gal and SAα2,3-Gal receptors were found in all major organs examined in both chickens and ducks. Interestingly, the predominant receptor type in chicken tracheal epithelium (TE) was SAα2,6-Gal whereas SAα2,3-Gal receptors were most abundant in duck TE. Paradoxically, infection of primary cell cultures (duck and chicken lung cells and embryo fibroblasts) with the swine H1N1, the low pathogenicity avian H2N3, and a highly pathogenic H5N1 (A/turkey/England/50-92/91) virus resulted in more extensive and rapid cell death in duck cells than in chicken cells. Infected duck cells displayed morphological features of apoptosis, increased DNA fragmentation and activation of caspase-3/7. Infected duck cells produced comparable levels of viral RNA but less infectious virus than infected chicken cells. Notably, such rapid cell death was not observed in duck cells infected with a contemporary Eurasian lineage H5N1 virus (A/turkey/Turkey/1/05) which has been shown to be fatal to ducks. Gene expression profiling of infected chicken and duck cells, 24hrs post-infection, with a chicken Affymetrix microarray platform revealed differential transcription of many genes between the two avian species. In particular, the array results suggested a possible role of BCoR, HSPA-9, STAT-3, AVEN, BCLAF1, IL-18, IFN-α, and TNF-α genes in mediating the contrasting species phenotypic response to influenza infections. In summary, rapid cell death in duck cells, mediated at least in part by apoptosis, results in reduced infective virus production and may well be an important protective host response of resistant ducks. By contrast, longer surviving infected chicken cells produce much higher infective virus load along with high levels of pro-inflammatory cytokines which could account for the susceptibility of chickens to influenza infections

Streptococcus pneumoniae endopeptidase O (PepO): a multifunctional plasminogen and fibronectin binding protein, facilitating evasion of innate immunity and invasion of host cells.

Streptococcus pneumoniae infections remain a major cause of morbidity and mortality worldwide. Therefore a detailed understanding and characterization of the mechanism of host cell colonization and dissemination is critical in order to gain control over this versatile pathogen. Here we identified a novel 72 kDa pneumococcal protein endopeptidase O (PepO), as a plasminogen and fibronectin binding protein. Using a collection of clinical isolates, representing different serotypes, we found PepO to be ubiquitously present both at the gene and at the protein level. In addition, PepO protein was secreted in a growth-phase dependent manner to the culture supernatants of the pneumococcal isolates. Recombinant PepO bound human plasminogen and fibronectin in a dose-dependent manner and plasminogen did not compete with fibronectin for binding PepO. PepO bound plasminogen via lysine residues and the interaction was influenced by ionic strength. Moreover, upon activation of PepO bound plasminogen by urokinase-type plasminogen activator, generated plasmin cleaved complement protein C3b thus assisting in complement control. Furthermore, direct binding assays demonstrated the interaction of PepO with epithelial and endothelial cells that in turn blocked pneumococcal adherence. Moreover, a pepO-mutant strain showed impaired adherence to and invasion of host cells compared to their isogenic wild-type strains. Taken together, the results demonstrated that PepO is ubiquitously expressed plasminogen and fibronectin binding protein, which plays role in pneumococcal invasion of host cells and aids in immune evasion

High basal expression of interferon-stimulated genes in human bronchial epithelial (BEAS-2B) cells contributes to influenza A virus resistance

Respiratory epithelial cells play a key role in influenza A virus (IAV) pathogenesis and host innate response. Transformed human respiratory cell lines are widely used in the study of IAV−host interactions due to their relative convenience, and inherent difficulties in working with primary cells. Transformed cells, however, may have altered susceptibility to virus infection. Proper characterization of different respiratory cell types in their responses to IAV infection is therefore needed to ensure that the cell line chosen will provide results that are of relevance in vivo. We compared replication kinetics of human H1N1 (A/USSR/77) IAVs in normal primary human bronchial epithelial (NHBE) and two commonly used respiratory epithelial cell lines namely BEAS-2B and A549 cells. We found that IAV replication was distinctly poor in BEAS-2B cells in comparison with NHBE, A549 and Madin-Darby canine kidney (MDCK) cells. IAV resistance in BEAS-2B cells was accompanied by an activated antiviral state with high basal expression of interferon (IFN) regulatory factor-7 (IRF-7), stimulator of IFN genes (STING) and IFN stimulated genes (ISGs). Treatment of BEAS-2B cells with a pan-Janus-activated-kinase (JAK) inhibitor decreased IRF-7 and ISG expression and resulted in increased IAV replication. Therefore, the use of highly resistant BEAS-2B cells in IAV infection may not reflect the cytopathogenicity of IAV in human epithelial cells in vivo

Detection of Anaplasma Phagocytophilum in Horses With Suspected Tick-Borne Disease in Northeastern United States by Metagenomic Sequencing

Metagenomic sequencing of clinical diagnostic specimens has a potential for unbiased detection of infectious agents, diagnosis of polymicrobial infections and discovery of emerging pathogens. Herein, next generation sequencing (NGS)-based metagenomic approach was used to investigate the cause of illness in a subset of horses recruited for a tick-borne disease surveillance study during 2017–2019. Blood samples collected from 10 horses with suspected tick-borne infection and five apparently healthy horses were subjected to metagenomic analysis. Total genomic DNA extracted from the blood samples were enriched for microbial DNA and subjected to shotgun next generation sequencing using Nextera DNA Flex library preparation kit and V2 chemistry sequencing kit on the Illumina MiSeq sequencing platform. Overall, 0.4–0.6 million reads per sample were analyzed using Kraken metagenomic sequence classification program. The taxonomic classification of the reads indicated that bacterial genomes were overrepresented (0.5 to 1%) among the total microbial reads. Most of the bacterial reads (~91%) belonged to phyla Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Cyanobacteria and Tenericutes in both groups. Importantly, 10–42.5% of Alphaproteobacterial reads in 5 of 10 animals with suspected tick-borne infection were identified as Anaplasma phagocytophilum. Of the 5 animals positive for A. phagocytophilum sequence reads, four animals tested A. phagocytophilum positive by PCR. Two animals with suspected tick-borne infection and A. phagocytophilum positive by PCR were found negative for any tick-borne microbial reads by metagenomic analysis. The present study demonstrates the usefulness of the NGS-based metagenomic analysis approach for the detection of blood-borne microbes

Differences in influenza virus receptors in chickens and ducks: Implications for interspecies transmission

Avian influenza viruses are considered to be key contributors to the emergence of human influenza pandemics. A major determinant of infection is the presence of virus receptors on susceptible cells to which the viral haemagglutinin is able to bind. Avian viruses preferentially bind to sialic acid α2,3-galactose (SAα2,3-Gal) linked receptors, whereas human strains bind to sialic acid α2,6-galactose (SAα2,6-Gal) linked receptors. While ducks are the major reservoir for influenza viruses, they are typically resistant to the effects of viral infection, in contrast to the frequently severe disease observed in chickens. In order to understand whether differences in receptors might contribute to this observation, we studied the distribution of influenza receptors in organs of ducks and chickens using lectin histochemistry with linkage specific lectins and receptor binding assays with swine and avian influenza viruses. Although the intestinal epithelial cells of both species expressed only SAα2,3-Gal receptors, we found widespread presence of both SAα2,6-Gal and SAα2,3-Gal receptors in many organs of both chickens and ducks. Co-expression of both receptors may allow infection of cells with both avian and human viruses and so present a route to genetic reassortment. There was a marked difference in the primary receptor type in the trachea of chickens and ducks. In chicken trachea, SAα2,6-Gal was the dominant receptor type whereas in ducks SAα2,3-Gal receptors were most abundant. This suggests that chickens could be more important as an intermediate host for the generation of influenza viruses with increased ability to bind to SAα2,6-Gal receptors and thus greater potential for infection of humans. Chicken tracheal and intestinal epithelial cells also expressed a broader range of SAα2,3-Gal receptors (both β(1-4)GlcNAc and β(1-3)GalNAc subtypes) in contrast to ducks, which suggests that they may be able to support infection with a broader range of avian influenza viruses

Comparative distribution of human and avian type sialic acid influenza receptors in the pig

<p>Abstract</p> <p>Background</p> <p>A major determinant of influenza infection is the presence of virus receptors on susceptible host cells to which the viral haemagglutinin is able to bind. Avian viruses preferentially bind to sialic acid α2,3-galactose (SAα2,3-Gal) linked receptors, whereas human strains bind to sialic acid α2,6-galactose (SAα2,6-Gal) linked receptors. To date, there has been no detailed account published on the distribution of SA receptors in the pig, a model host that is susceptible to avian and human influenza subtypes, thus with potential for virus reassortment. We examined the relative expression and spatial distribution of SAα2,3-GalG(1-3)GalNAc and SAα2,6-Gal receptors in the major organs from normal post-weaned pigs by binding with lectins <it>Maackia amurensis agglutinins </it>(MAA II) and <it>Sambucus nigra agglutinin </it>(SNA) respectively.</p> <p>Results</p> <p>Both SAα2,3-Gal and SAα2,6-Gal receptors were extensively detected in the major porcine organs examined (trachea, lung, liver, kidney, spleen, heart, skeletal muscle, cerebrum, small intestine and colon). Furthermore, distribution of both SA receptors in the pig respiratory tract closely resembled the published data of the human tract. Similar expression patterns of SA receptors between pig and human in other major organs were found, with exception of the intestinal tract. Unlike the limited reports on the scarcity of influenza receptors in human intestines, we found increasing presence of SAα2,3-Gal and SAα2,6-Gal receptors from duodenum to colon in the pig.</p> <p>Conclusions</p> <p>The extensive presence of SAα2,3-Gal and SAα2,6-Gal receptors in the major organs examined suggests that each major organ may be permissive to influenza virus entry or infection. The high similarity of SA expression patterns between pig and human, in particular in the respiratory tract, suggests that pigs are not more likely to be potential hosts for virus reassortment than humans. Our finding of relative abundance of SA receptors in the pig intestines highlights a need for clarification on the presence of SA receptors in the human intestinal tract.</p