Sphingolipid distribution changes with age in the human lens

The formation of an internal barrier to the diffusion of small molecules in the lens during middle age is hypothesized to be a key event in the development of age-related nuclear (ARN) cataract. Changes in membrane lipids with age may be responsible. In this study, we investigated the effect of age on the distribution of sphingomyelins, the most abundant lens phospholipids. Human lens sections were initially analyzed by MALDI mass spectrometry imaging. A distinct annular distribution of the dihydrosphingomyelin, DHSM (d18:0/16:0), in the barrier region was observed in 64- and 70-year-old lenses but not in a 23-year-old lens. An increase in the dihydroceramide, DHCer (d18:0/16:0), in the lens nucleus was also observed in the older lenses. These findings were supported by ESI mass spectrometry analysis of lipid extracts from lenses dissected into outer, barrier, and nuclear regions. A subsequent analysis of 18 lenses ages 20-72 years revealed that sphingomyelin levels increased with age in the barrier region until reaching a plateau at approximately 40 years of age. Such changes in lipid composition will have a significant impact on the physical properties of the fiber cell membranes and may be associated with the formation of a barrier.-Deeley, J. M., J. A. Hankin, M. G. Friedrich, R. C. Murphy, R. J. W. Truscott, T. W. Mitchell, and S. J. Blanksby. Sphingolipid distribution changes with age in the human lens. J. Lipid Res. 2010. 51: 2753-2760.

Smart resource control in distribution network to improve the integration level of PV

This project was an innovative approach in developing smart coordination of available energy resources to improve the integration level of PV in distribution network. Voltage and loading issues are considered as the main concerns for future electricity grid which need to be avoided using such resources. A distributed control structure was proposed for the resources in distribution network to avoid noted power quality issues.

Semantic spaces : measuring the distance between different subspaces

Semantic Space models, which provide a numerical representation of words’ meaning extracted from corpus of documents, have been formalized in terms of Hermitian operators over real valued Hilbert spaces by Bruza et al. [1]. The collapse of a word into a particular meaning has been investigated applying the notion of quantum collapse of superpositional states [2]. While the semantic association between words in a Semantic Space can be computed by means of the Minkowski distance [3] or the cosine of the angle between the vector representation of each pair of words, a new procedure is needed in order to establish relations between two or more Semantic Spaces. We address the question: how can the distance between different Semantic Spaces be computed? By representing each Semantic Space as a subspace of a more general Hilbert space, the relationship between Semantic Spaces can be computed by means of the subspace distance. Such distance needs to take into account the difference in the dimensions between subspaces. The availability of a distance for comparing different Semantic Subspaces would enable to achieve a deeper understanding about the geometry of Semantic Spaces which would possibly translate into better effectiveness in Information Retrieval tasks.

The impacts of variable speed limit on speed variation and headway distribution

This thesis investigates the impacts of variable speed limit on motorway speed variation and headway distribution. Initiative techniques of traffic flow categorisation study contribute in analysing the effects of variable speed limit on various traffic states. The project focuses on the speed harmonisation impacts within and across lanes as well as the uniformity of headway spread in the application of variable speed limit.

Recycling concrete: An undiscovered source of ultrafine particles

While concrete recycling is practiced worldwide, there are many unanswered questions in relation to ultrafine particle (UFP; Dp<100nm) emissions and exposure around recycling sites. In particular: (i) Does recycling produce UFPs and in what quantities? (ii) How do they disperse around the source? (iii) What impact does recycling have on ambient particle number concentrations (PNCs) and exposure? (iv) How effective are commonly used dust respirators to limit exposure? We measured size-resolved particles in the 5-560 nm range at five distances from a simulated concrete recycling source and found that: (i) the size distributions were multimodal, with up to ~93% of total PNC in the UFP size range; and (ii) dilution was a key particle transformation mechanism. UFPs showed a much slower decay rate, requiring ~62% more distance to reach 10% of their initial concentration compared with their larger counterparts. Compared with typical urban exposure during car journeys, exposure decay profiles showed up to ~5 times higher respiratory deposition within 10 m of the source. Dust respirators were found to remove half of total PNC; however the removal factor for UFPs was only ~57% of that observed in the 100-560 nm size range. These findings highlight a need for developing an understanding of the nature of the particles as well as for better control measures to limit UFP exposure.

Opportunities and challenges : combining distance and on-campus students in concurrent courses

Through its Electronic Delivery of Gator Engineering (EDGE) program, University of Florida (UF) offers online master’s degrees from participating departments within the UF College of Engineering. Each master’s degree requires 10 courses (3 credit hours each). One interesting and unique aspect of the EDGE pro-gram is that distance learners are registered concurrently in the same courses with traditional on-campus students. This paper examines the specific challenges involved in integrating distance students into on-campus courses, including communication, interaction, access to resources, and equal grading practices.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Ion impact distribution over plasma exposed nanocone arrays

The effect of an ordered array of nanocones on a conducting substrate immersed in the plasma on the transport of the plasma ions is investigated. The real conical shape of the cones is rigorously incorporated into the model. The movement of 10^5 CH3+ ions in the plasma sheath modified by the nanocone array is simulated. The ions are driven by the electric fields produced by the sheath and the nanostructures. The surface charge density and the total charge on the nanotips with different aspect ratios are computed. The ion transport simulation provides important characteristics of the displacement and velocity of the ions. The relative ion distribution along the lateral surfaces of the carbon nanotips is computed as well. It is shown that a rigorous account of the realistic nanostructure shape leads to very different distribution of the ion fluxes on the nanostructured surfaces compared to the previously reported works. The ion flux distribution is a critical factor in the nucleation process on the substrate and determines the nanostructure growth patterns.

Thin single-walled carbon nanotubes with narrow chirality distribution : constructive interplay of plasma and Gibbs–Thomson effects

Multiscale, multiphase numerical modeling is used to explain the mechanisms of effective control of chirality distributions of single-walled carbon nanotubes in direct plasma growth and suggest effective approaches to further improvement. The model includes an unprecedented combination of the plasma sheath, ion/radical transport, species creation/loss, plasma–surface interaction, heat transfer, surface/bulk diffusion, graphene layer nucleation, and bending/lift-off modules. It is shown that the constructive interplay between the plasma and the Gibbs–Thomson effect can lead to the effective nucleation and lift-off of small graphene layers on small metal catalyst nanoparticles. As a result, much thinner nanotubes with narrower chirality distributions can nucleate at much lower process temperatures and pressures compared to thermal CVD. This approach is validated by a host of experimental results, substantially reduces the amounts of energy and atomic matter required for the nanotube growth, and can be extended to other nanoscale structures and materials systems, thereby nearing the ultimate goal of energy- and matter-efficient nanotechnology.

Plasma-controlled adatom delivery and (re)distribution: Enabling uninterrupted, low-temperature growth of ultralong vertically aligned single walled carbon nanotubes

Large-scale (∼109 atoms) numerical simulations reveal that plasma-controlled dynamic delivery and redistribution of carbon atoms between the substrate and nanotube surfaces enable the growth of ultralong single walled carbon nanotubes (SWCNTs) and explain the common experimental observation of slower growth at advanced stages. It is shown that the plasma-based processes feature up to two orders of magnitude higher growth rates than equivalent neutral-gas systems and are better suited for the SWCNT synthesis at low nanodevice friendly temperatures. © 2008 American Institute of Physics.

Spatially averaged model of complex-plasma discharge with self-consistent electron energy distribution

A global, or averaged, model for complex low-pressure argon discharge plasmas containing dust grains is presented. The model consists of particle and power balance equations taking into account power loss on the dust grains and the discharge wall. The electron energy distribution is determined by a Boltzmann equation. The effects of the dust and the external conditions, such as the input power and neutral gas pressure, on the electron energy distribution, the electron temperature, the electron and ion number densities, and the dust charge are investigated. It is found that the dust subsystem can strongly affect the stationary state of the discharge by dynamically modifying the electron energy distribution, the electron temperature, the creation and loss of the plasma particles, as well as the power deposition. In particular, the power loss to the dust grains can take up a significant portion of the input power, often even exceeding the loss to the wall.

Angular distribution of carbon ion flux in a nanotube array during the plasma process by the Monte Carlo technique

Angular distribution of microscopic ion fluxes around nanotubes arranged into a dense ordered pattern on the surface of the substrate is studied by means of multiscale numerical simulation. The Monte Carlo technique was used to show that the ion current density is distributed nonuniformly around the carbon nanotubes arranged into a dense rectangular array. The nonuniformity factor of the ion current flux reaches 7 in dense (5× 1018 m-3) plasmas for a nanotube radius of 25 nm, and tends to 1 at plasma densities below 1× 1017 m-3. The results obtained suggest that the local density of carbon adatoms on the nanotube side surface, at areas facing the adjacent nanotubes of the pattern, can be high enough to lead to the additional wall formation and thus cause the single- to multiwall structural transition, and other as yet unexplained nanoscience phenomena.

Simulation of ion flux distribution in conductive and nonconductive nanotip patterns

The distribution of flux of carbon-bearing cations over nanopatterned surfaces with conductive nanotips and nonconductive nanoislands is simulated using the Monte-Carlo technique. It is shown that the ion current is focused to nanotip surfaces when the negative substrate bias is low and only slightly perturbed at higher substrate biases. In the low-bias case, the mean horizontal ion displacement caused by the nanotip electric field exceeds 10 nm. However, at higher substrate biases, this value reduces down to 2 nm. In the nonconductive nanopattern case, the ion current distribution is highly nonuniform, with distinctive zones of depleted current density around the nanoislands. The simulation results suggest the efficient means to control ion fluxes in plasma-aided nanofabrication of ordered nanopatterns, such as nanotip microemitter structures and quantum dot or nanoparticle arrays. © World Scientific Publishing Company.

Effect of pupil dilation and constriction on the distribution of bit errors within the iris

Texture information in the iris image is not uniform in discriminatory information content for biometric identity verification. The bits in an iris code obtained from the image differ in their consistency from one sample to another for the same identity. In this work, errors in bit strings are systematically analysed in order to investigate the effect of light-induced and drug-induced pupil dilation and constriction on the consistency of iris texture information. The statistics of bit errors are computed for client and impostor distributions as functions of radius and angle. Under normal conditions, a V-shaped radial trend of decreasing bit errors towards the central region of the iris is obtained for client matching, and it is observed that the distribution of errors as a function of angle is uniform. When iris images are affected by pupil dilation or constriction the radial distribution of bit errors is altered. A decreasing trend from the pupil outwards is observed for constriction, whereas a more uniform trend is observed for dilation. The main increase in bit errors occurs closer to the pupil in both cases.

Electron energy distribution function in low-pressure complex plasmas

The effect of density and size of dust grains on the electron energy distribution function (EEDF) in low-temperature complex plasmas is studied. It is found that the EEDF depends strongly on the dust density and size. The behavior of the electron temperature can differ significantly from that of a pristine plasma. For low-pressure argon glow discharge, the Druyvesteyn-like EEDF often found in pristine plasmas can become nearly Maxwellian if the dust density and/or sizes are large. One can thus control the plasma parameters by the dust grains.