Characterization and structure–property relationship of melt-mixed high density polyethylene/multi-walled carbon nanotube composites under extensional deformation

Melt-mixed high density polyethylene (HDPE)/multi-walled carbon nanotube (MWCNT) nanocomposites with 1–10 wt% MWCNTs were prepared by twin screw extrusion and compression moulded into sheet form. The compression moulded nanocomposites exhibit a 112% increase in modulus at a MWCNT loading of 4 wt%, and a low electrical percolation threshold of 1.9 wt%. Subsequently, uniaxial, sequential (seq-) biaxial and simultaneous (sim-) biaxial stretching of the virgin HDPE and nanocomposite sheets was conducted at different strain rates and stretching temperatures to investigate the processability of HDPE with the addition of nanotubes and the influence of deformation on the structure and final properties of nanocomposites. The results show that the processability of HDPE is improved under all the uniaxial and biaxial deformation conditions due to a strengthened strain hardening behaviour with the addition of MWCNTs. Extensional deformation is observed to disentangle nanotube agglomerates and the disentanglement degree is shown to depend on the stretching mode, strain rate and stretching temperatures applied. The disentanglement effectiveness is: uniaxial stretching < sim-biaxial stretching < seq-biaxial stretching, under the same deformation parameters. In sim-biaxial stretching, reducing the strain rate and stretching temperature can lead to more nanotube agglomerate breakup. Enhanced nanotube agglomerate disentanglement exhibits a positive effect on the mechanical properties and a negative effect on the electrical properties of the deformed nanocomposites. The ultimate stress of the composite containing 4 wt% MWCNTs increased by ∼492% after seq-biaxial stretching, while the resistivity increased by ∼1012 Ω cm.

Effect of cooling rate on the properties of high density polyethylene/multi-walled carbon nanotube composites

High density polyethylene (HDPE)/multi-walled carbon nanotube (MWCNT) nanocomposites were prepared by melt mixing using twin-screw extrusion. The extruded pellets were compression moulded at 200°C for 5min followed by cooling at different cooling rates (20°C/min and 300°C/min respectively) to produce sheets for characterization. Scanning electron microscopy (SEM) shows that the MWCNTs are uniformly dispersed in the HDPE. At 4 wt% addition of MWCNTs composite modulus increased by over 110% compared with the unfilled HDPE (regardless of the cooling rate). The yield strength of both unfilled and filled HDPE decreased after rapid cooling by about 10% due to a lower crystallinity and imperfect crystallites. The electrical percolation threshold of composites, irrespective of the cooling rate, is between a MWCNT concentration of 1∼2 wt%. Interestingly, the electrical resistivity of the rapidly cooled composite with 2 wt% MWCNTs is lower than that of the slowly cooled composites with the same MWCNT loading. This may be due to the lower crystallinity and smaller crystallites facilitating the formation of conductive pathways. This result may have significant implications for both process control and the tailoring of electrical conductivity in the manufacture of conductive HDPE/MWCNT nanocomposites.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

Cross-layer Framework for Fine-grained Channel Access in Next Generation High-density WiFi Networks

Densely deployed WiFi networks will play a crucial role in providing the capacity for next generation mobile internet. However, due to increasing interference, overlapped channels in WiFi networks and throughput efficiency degradation, densely deployed WiFi networks is not a guarantee to obtain higher throughput. An emergent challenge is how to efficiently utilize scarce spectrum resources, by matching physical layer resources to traffic demand. In this aspect, access control allocation strategies play a pivotal role but remain too coarse-grained. As a solution, this research proposes a flexible framework for fine-grained channel width adaptation and multi-channel access in WiFi networks. This approach, named SFCA (Sub-carrier Fine-grained Channel Access), adopts DOFDM (Discontinuous Orthogonal Frequency Division Multiplexing) at the PHY layer. It allocates the frequency resource with a sub-carrier granularity, which facilitates the channel width adaptation for multi-channel access and thus brings more flexibility and higher frequency efficiency. The MAC layer uses a frequency-time domain backoff scheme, which combines the popular time-domain BEB scheme with a frequency-domain backoff to decrease access collision, resulting in higher access probability for the contending nodes. SFCA is compared with FICA (an established access scheme) showing significant outperformance. Finally we present results for next generation 802.11ac WiFi networks.

High-density lipoprotein, beta cells, and diabetes .

High-density lipoproteins (HDLs) exert a series of potentially beneficial effects on many cell types including anti-atherogenic actions on the endothelium and macrophage foam cells. HDLs may also exert anti-diabetogenic functions on the beta cells of the endocrine pancreas, notably by potently inhibiting stress-induced cell death and enhancing glucose-stimulated insulin secretion. HDLs have also been found to stimulate insulin-dependent and insulin-independent glucose uptake into skeletal muscle, adipose tissue, and liver. These experimental findings and the inverse association of HDL-cholesterol levels with the risk of diabetes development have generated the notion that appropriate HDL levels and functionality must be maintained in humans to diminish the risks of developing diabetes. In this article, we review our knowledge on the beneficial effects of HDLs in pancreatic beta cells and how these effects are mediated. We discuss the capacity of HDLs to modulate endoplasmic reticulum stress and how this affects beta-cell survival. We also point out the gaps in our understanding on the signalling properties of HDLs in beta cells. Hopefully, this review will foster the interest of scientists in working on beta cells and diabetes to better define the cellular pathways activated by HDLs in beta cells. Such knowledge will be of importance to design therapeutic tools to preserve the proper functioning of the insulin-secreting cells in our body.

Studies on the Rheology and the Mechanical Properties of Thermoplastic Elastomer from Latex Product Waste and High Density Polyethylene

Latex waste products contain rubber hydrocarbon of very high quality, which is only lightly cross linked. Selected wastes such as thread waste and glove waste were modified into processable materials by a novel economic process and thermoplastic elastomers were prepared by blending these modified waste materials with high density polyethylene in various proportions. The mechanical properties as well as the rheological behaviour of these blends were evaluated and compared with those of the natural rubber-high density polyethylene blends.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

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.

A New Gridding Technique for High Density Microarray Images Using Intensity Projection Profile of Best Sub Image

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

Rice husk ash – A valuable reinforcement for high density polyethylene

This paper presents the results of a study on the use of rice husk ash (RHA) for property modification of high density polyethylene (HDPE). Rice husk is a waste product of the rice processing industry. It is used widely as a fuel which results in large quantities of RHA. Here, the characterization of RHA has been done with the help of X-ray diffraction (XRD), Inductively Coupled Plasma Atomic Emission Spectroscopy (ICPAES), light scattering based particle size analysis, Fourier transform infrared spectroscopy (FTIR) and Scanning Electron Microscope (SEM). Most reports suggest that RHA when blended directly with polymers without polar groups does not improve the properties of the polymer substantially. In this study RHA is blended with HDPE in the presence of a compatibilizer. The compatibilized HDPE-RHA blend has a tensile strength about 18% higher than that of virgin HDPE. The elongation-at-break is also higher for the compatibilized blend. TGA studies reveal that uncompatibilized as well as compatibilized HDPERHA composites have excellent thermal stability. The results prove that RHA is a valuable reinforcing material for HDPE and the environmental pollution arising from RHA can be eliminated in a profitable way by this technique.

Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.

High Density Single Crystalline GaN Nanodot Arrays Fabricated Using Template-Assisted Selective Growth

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.

Evaluation of the use of high-density SNP genotyping to implement UPOV Model 2 for DUS testing in barley

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.

Optimising the analysis of transcript data using high density oligonucleotide arrays and genomic DNA-based probe selection

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.

Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species

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.

APOA5 genotype influences the association between 25-hydroxyvitamin D and high density lipoprotein cholesterol

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.