945 resultados para High-density polyethylene
Resumo:
Biodegradation is the chemical degradation of materials brought about by the action of naturally occurring microorganisms. Biodegradation is a relatively rapid process under suitable conditions of moisture, temperature and oxygen availability. The logic behind blending biopolymers such as starch with inert polymers like polyethylene is that if the biopolymer component is present in sufficient amount, and if it is removed by microorganisms in the waste disposal environment, then the base inert plastic should slowly degrade and disappear. The present work focuses on the preparation of biodegradable and photodegradable blends based on low density polyethylene incorporating small quantities of ionomers as compatibilizers. The thesis consists of eight chapters. The first chapter presents an introduction to the present research work and literature survey. The details of the materials used and the experimental procedures undertaken for the study are described in the second chapter. Preparation and characterization of low density polyethylene (LDPE)-biopolymer (starch/dextrin) blends are described in the third chapter. The result of investigations on the effect of polyethylene-co-methacrylic acid ionomers on the compatibility of LDPE and starch are reported in chapter 4. Chapter 5 has been divided into two parts. The first part deals with the effect of metal oxides on the photodegradation of LDPE. The second part describes the function of metal stearates on the photodegradation of LDPE. The results of the investigations on the role of various metal oxides as pro-oxidants on the degradation of ionomer compatibilized LDPE-starch blends are reported in chapter 6. Chapter 7 deals with the results of investigations on the role of various metal stearates as pro-oxidants on the degradation of ionomer compatibilized LDPE-starch blends. The conclusion of the investigations is presented in the last chapter of the thesis.
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In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.
Resumo:
Low-density polyethylene was mixed with dextrin having different particle sizes (100, 200 and 300 mesh). Various compositions were prepared and their mechanical properties were evaluated and thermal studies have been carried out. Biodegradability of these samples has been checked using liquid culture medium containing Vibrios (an amylase producing bacteria), which were isolated from marine benthic environment. Soil burial test was done and reprocessability of these samples was evaluated. The results indicate that the newly prepared blends are reprocessable without sacrificing much of their mechanical properties. The biodegradability tests on these blends indicate that these are partially biodegradable
Resumo:
As the technologies for the fabrication of high quality microarray advances rapidly, quantification of microarray data becomes a major task. Gridding is the first step in the analysis of microarray images for locating the subarrays and individual spots within each subarray. For accurate gridding of high-density microarray images, in the presence of contamination and background noise, precise calculation of parameters is essential. This paper presents an accurate fully automatic gridding method for locating suarrays and individual spots using the intensity projection profile of the most suitable subimage. The method is capable of processing the image without any user intervention and does not demand any input parameters as many other commercial and academic packages. According to results obtained, the accuracy of our algorithm is between 95-100% for microarray images with coefficient of variation less than two. Experimental results show that the method is capable of gridding microarray images with irregular spots, varying surface intensity distribution and with more than 50% contamination
Resumo:
Increasing amounts of plastic waste in the environment have become a problem of gigantic proportions. The case of linear low-density polyethylene (LLDPE) is especially significant as it is widely used for packaging and other applications. This synthetic polymer is normally not biodegradable until it is degraded into low molecular mass fragments that can be assimilated by microorganisms. Blends of nonbiodegradable polymers and biodegradable commercial polymers such as poly (vinyl alcohol) (PVA) can facilitate a reduction in the volume of plastic waste when they undergo partial degradation. Further, the remaining fragments stand a greater chance of undergoing biodegradation in a much shorter span of time. In this investigation, LLDPE was blended with different proportions of PVA (5–30%) in a torque rheometer. Mechanical, thermal, and biodegradation studies were carried out on the blends. The biodegradability of LLDPE/PVA blends has been studied in two environments: (1) in a culture medium containing Vibrio sp. and (2) soil environment, both over a period of 15 weeks. Blends exposed to culture medium degraded more than that exposed to soil environment. Changes in various properties of LLDPE/PVA blends before and after degradation were monitored using Fourier transform infrared spectroscopy, a differential scanning calorimeter (DSC) for crystallinity, and scanning electron microscope (SEM) for surface morphology among other things. Percentage crystallinity decreased as the PVA content increased and biodegradation resulted in an increase of crystallinity in LLDPE/PVA blends. The results prove that partial biodegradation of the blends has occurred holding promise for an eventual biodegradable product
Resumo:
High density, uniform GaN nanodot arrays with controllable size have been synthesized by using template-assisted selective growth. The GaN nanodots with average diameter 40nm, 80nm and 120nm were selectively grown by metalorganic chemical vapor deposition (MOCVD) on a nano-patterned SiO2/GaN template. The nanoporous SiO2 on GaN surface was created by inductively coupled plasma etching (ICP) using anodic aluminum oxide (AAO) template as a mask. This selective regrowth results in highly crystalline GaN nanodots confirmed by high resolution transmission electron microscopy. The narrow size distribution and uniform spatial position of the nanoscale dots offer potential advantages over self-assembled dots grown by the Stranski–Krastanow mode.
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Nanocomposites of high-density polyethylene (HDPE) and carbon nanotubes (CNT) of different geometries (single wall, double wall, and multiwall; SWNT, DWNT, and MWNT) were prepared by in situ polymerization of ethylene on CNT whose surface had been previously treated with a metallocene catalytic system. In this work, we have studied the effects of applying the successive self-nucleation and annealing thermal fractionation technique (SSA) to the nanocomposites and have also determined the influence of composition and type of CNT on the isothermal crystallization behavior of the HDPE. SSA results indicate that all types of CNT induce the formation of a population of thicker lamellar crystals that melt at higher temperatures as compared to the crystals formed in neat HDPE prepared under the same catalytic and polymerization conditions and subjected to the same SSA treatment. Furthermore, the peculiar morphology induced by the CNT on the HDPE matrix allows the resolution of thermal fractionation to be much better. The isothermal crystallization results indicated that the strong nucleation effect caused by CNT reduced the supercooling needed for crystallization. The interaction between the HDPE chains and the surface of the CNT is probably very strong as judged by the results obtained, even though it is only physical in nature. When the total crystallinity achieved during isothermal crystallization is considered as a function of CNT content, it was found that a competition between nucleation and topological confinement could account for the results. At low CNT content the crystallinity increases (because of the nucleating effect of CNT on HDPE), however, at higher CNT content there is a dramatic reduction in crystallinity reflecting the increased confinement experienced by the HDPE chains at the interfaces which are extremely large in these nanocomposites. Another consequence of these strong interactions is the remarkable decrease in Avrami index as CNT content increases. When the Avrami index reduces to I or lower, nucleation dominates the overall kinetics as a consequence of confinement effects. Wide-angle X-ray experiments were performed at a high-energy synchrotron source and demonstrated that no change in the orthorhombic unit cell of HDPE occurred during crystallization with or without CNT.
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Developments in high-throughput genotyping provide an opportunity to explore the application of marker technology in distinctness, uniformity and stability (DUS) testing of new varieties. We have used a large set of molecular markers to assess the feasibility of a UPOV Model 2 approach: “Calibration of threshold levels for molecular characteristics against the minimum distance in traditional characteristics”. We have examined 431 winter and spring barley varieties, with data from UK DUS trials comprising 28 characteristics, together with genotype data from 3072 SNP markers. Inter varietal distances were calculated and we found higher correlations between molecular and morphological distances than have been previously reported. When varieties were grouped by kinship, phenotypic and genotypic distances of these groups correlated well. We estimated the minimum marker numbers required and showed there was a ceiling after which the correlations do not improve. To investigate the possibility of breaking through this ceiling, we attempted genomic prediction of phenotypes from genotypes and higher correlations were achieved. We tested distinctness decisions made using either morphological or genotypic distances and found poor correspondence between each method.
Resumo:
Background: Affymetrix GeneChip arrays are widely used for transcriptomic studies in a diverse range of species. Each gene is represented on a GeneChip array by a probe- set, consisting of up to 16 probe-pairs. Signal intensities across probe- pairs within a probe-set vary in part due to different physical hybridisation characteristics of individual probes with their target labelled transcripts. We have previously developed a technique to study the transcriptomes of heterologous species based on hybridising genomic DNA (gDNA) to a GeneChip array designed for a different species, and subsequently using only those probes with good homology. Results: Here we have investigated the effects of hybridising homologous species gDNA to study the transcriptomes of species for which the arrays have been designed. Genomic DNA from Arabidopsis thaliana and rice (Oryza sativa) were hybridised to the Affymetrix Arabidopsis ATH1 and Rice Genome GeneChip arrays respectively. Probe selection based on gDNA hybridisation intensity increased the number of genes identified as significantly differentially expressed in two published studies of Arabidopsis development, and optimised the analysis of technical replicates obtained from pooled samples of RNA from rice. Conclusion: This mixed physical and bioinformatics approach can be used to optimise estimates of gene expression when using GeneChip arrays.
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High-density oligonucleotide (oligo) arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L.) Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM) probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P) stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ webcite and may be used to facilitate transcriptomic analyses of a wide range of plant and animal species in the absence of custom arrays.
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OBJECTIVE: Circulating levels of 25-hydroxyvitamin D (25OHD) are positively associated with high density lipoprotein (HDL) cholesterol. We sought to replicate a previously reported interaction between APOA5 genotype and vitamin D, and to examine whether HDL-associated genetic loci modify the association between serum 25OHD and HDL cholesterol. METHODS: We examined whether 42 single nucleotide polymorphisms (SNPs) modify the association between serum 25OHD and HDL cholesterol in the 1958 British Birth cohort (aged 45 years, n = 4978). RESULTS: We identified a borderline interaction between the SNP rs12272004 (near the APOA5) and serum 25OHD on HDL cholesterol (P(interaction) = 0.05). The interaction was particularly prominent among the samples collected during winter (P(interaction) = 0.001). None of the other loci showed an interaction with serum 25OHD concentrations on HDL cholesterol. CONCLUSIONS: Our study in 4978 British Whites provides further support that APOA5 genotype modifies the association between vitamin D metabolites and HDL cholesterol.
Resumo:
The concentration of high density lipoprotein-cholesterol (HDL-C) has been found consistently to be a powerful negative predictor of premature coronary heart disease (CHD) in human prospective population studies. There is also circumstantial evidence from human intervention studies and direct evidence from animal intervention studies that HDLs protect against the development of atherosclerosis. HDLs have several documented functions, although the precise mechanism by which they prevent atherosclerosis remains uncertain. Nor is it known whether the cardioprotective properties of HDL are specific to one or more of the many HDL subpopulations that comprise the HDL fraction in human plasma. Several lifestyle and pharmacological interventions have the capacity to raise the level of HDL-C, although it is not known whether all are equally protective. Indeed, despite the large body of information identifying HDLs as potential therapeutic targets for the prevention of atherosclerosis, there remain many unanswered questions that must be addressed as a matter of urgency before embarking wholesale on HDL-C-raising therapies as strategies to prevent CHD. This review summarises what is known and highlights what we still need to know.
Resumo:
The role of low-density lipoprotein in the development of coronary heart disease (CHD) is well recognised. There is also growing evidence that high-density lipoprotein cholesterol (HDL-C) is a powerful inverse predictor for premature CHD and that maintaining a high HDL-C level may guard against atherosclerosis. Patients with low HDL-C levels often also have central obesity, insulin resistance and other features of the metabolic syndrome. This syndrome is both increasingly common and strongly implicated in the growing worldwide epidemic of type 2 diabetes. HDL-C may be increased by lifestyle changes, e.g. weight loss, physical activity and smoking cessation. Pharmacological agents such as fibrates, niacin and statins have also been shown significantly to elevate HDL-C. Although current guidelines are beginning to recognise the protective role of HDL-C level in preventing coronary events, HDL-C should be adopted soon as a target for intervention in its own right.
Resumo:
The components of many signaling pathways have been identified and there is now a need to conduct quantitative data-rich temporal experiments for systems biology and modeling approaches to better understand pathway dynamics and regulation. Here we present a modified Western blotting method that allows the rapid and reproducible quantification and analysis of hundreds of data points per day on proteins and their phosphorylation state at individual sites. The approach is of particular use where samples show a high degree of sample-to-sample variability such as primary cells from multiple donors. We present a case study on the analysis of >800 phosphorylation data points from three phosphorylation sites in three signaling proteins over multiple time points from platelets isolated from ten donors, demonstrating the technique's potential to determine kinetic and regulatory information from limited cell numbers and to investigate signaling variation within a population. We envisage the approach being of use in the analysis of many cellular processes such as signaling pathway dynamics to identify regulatory feedback loops and the investigation of potential drug/inhibitor responses, using primary cells and tissues, to generate information about how a cell's physiological state changes over time.