Design of sensor electronics for electrical capacitance tomography

The design of the sensor electronics for a tomographic imaging system based on electrical capacitance sensors is described. The performance of the sensor electronics is crucial to the performance of the imaging system. The problems associated with such a measurement process are discussed and solutions to these are described. Test results show that the present design has a resolution of 0.3 femtofarad. (For a 12-electrode system imaging an oil/gas flow, this represents a 2% gas void fraction change at the centre of the pipe) with a low noise level of 0.08 fF (RMS value), a large dynamic range of 76 dB and a data acquisition speed of 6600 measurements per second. This enables sensors with up to 12 electrodes to be used in a system with a maximum imaging rate of 100 frames per second, and thus provides an improved image resolution over the earlier 8-electrode system and an adequate electrode area to give sufficient measurement sensitivit

Electrical capacitance tomography for flow imaging: System model for development of image reconstruction algorithms and design of primary sensors

A software tool that facilitates the development of image reconstruction algorithms, and the design of optimal capacitance sensors for a capacitance-based 12-electrode tomographic flow imaging system are described. The core of this software tool is the finite element (FE) model of the sensor, which is implemented in OCCAM-2 language and run on the Inmos T800 transputers. Using the system model, the in-depth study of the capacitance sensing fields and the generation of flow model data are made possible, which assists, in a systematic approach, the design of an improved image-reconstruction algorithm. This algorithm is implemented on a network of transputers to achieve a real-time performance. It is found that the selection of the geometric parameters of a 12-electrode sensor has significant effects on the sensitivity distributions of the capacitance fields and on the linearity of the capacitance data. As a consequence, the fidelity of the reconstructed images are affected. Optimal sensor designs can, therefore, be provided, by accommodating these effect

Three Extensions of Tong and Richardson’s Algorithm for Finding the Optimal Path in Schedule-Based Railway Networks

published_or_final_versio

Observation of 'ghost' islands and surfactant effect of surface gallium atoms during GaN growth by molecular beam epitaxy

GaN (0001) films grown by molecular beam epitaxy (MBE) were studied using scanning tunneling microscopy (STM). 'Ghost' islands were observed on surfaces grown under excess Ga conditions. These ghost islands were associated to a metastable, intermediate nucleation state of the surface.published_or_final_versio

Anisotropic step-flow growth and island growth of GaN(0001) by molecular beam epitaxy

GaN(0001) thin films are grown using radio frequency plasma assisted molecular beam epitaxy. By changing the growth temperature, anisotropic growth rate behavior is observed in both the step-flow growth mode and the 2D island growth mode. Tunneling scanning microscopy reveals, in the step-flow growth mode, strong influences from the growth anisotropy on the shape of the terrace edges, resulting in striking differences between hexagonal and cubic films. In the 2D nucleation growth mode, triangularly shaped islands are formed. The significance of growth anisotropy to growing high quality GaN films is discussed.published_or_final_versio

Aptamer biosensing based on metal enhanced fluorescence platform: A promising diagnostic tool

Diagnosis of disease at an early, curable, and reversible stage allows more conservative treatment and better patient outcomes. Fluorescence biosensing is a widely used method to detect biomarkers, which are early indicators of disease. Importantly, biosensing requires a high level of sensitivity. Traditionally, these sensors use antibodies or enzymes as biorecognition molecules; however, these can lack the specificity required in a clinical setting, limiting their overall applicability. Aptamers are short, single stranded nucleotides that are receiving increasing attention over traditional recognition molecules. These exhibit many advantages, such as high specificity, making them promising for ultrasensitive biosensors. Metal enhanced fluorescence (MEF) utilizes plasmonic materials, which can increase the sensitivity of label-based fluorescent biosensors. The fluorescence enhancement achieved by placing metallic nanostructures in close proximity to fluorophores allows for detection of ultra-low biomarker concentrations. Plasmonic biosensors have been successfully implemented as diagnostic tools for a number of diseases, such as cancer, yet reproducible systems exhibiting high specificity and the ability to multiplex remain challenging. Similarly, while aptasensors have been extensively reported, few systems currently incorporate MEF, which could drastically improve biosensor sensitivity. Here, we review the latest advancements in the field of aptamer biosensing based on MEF that have been explored for the detection of a wide variety of biological molecules. While this emerging biosensing technology is still in its infant stage, we highlight the potential challenges and its clinical potential in early diagnosis of diseases

Synergistic Antibacterial Effects of Metallic Nanoparticle Combinations

© The Author(s) 2019.Metallic nanoparticles have unique antimicrobial properties that make them suitable for use within medical and pharmaceutical devices to prevent the spread of infection in healthcare. The use of nanoparticles in healthcare is on the increase with silver being used in many devices. However, not all metallic nanoparticles can target and kill all disease-causing bacteria. To overcome this, a combination of several different metallic nanoparticles were used in this study to compare effects of multiple metallic nanoparticles when in combination than when used singly, as single elemental nanoparticles (SENPs), against two common hospital acquired pathogens (Staphylococcus aureus and Pseudomonas. aeruginosa). Flow cytometry LIVE/DEAD assay was used to determine rates of cell death within a bacterial population when exposed to the nanoparticles. Results were analysed using linear models to compare effectiveness of three different metallic nanoparticles, tungsten carbide (WC), silver (Ag) and copper (Cu), in combination and separately. Results show that when the nanoparticles are placed in combination (NPCs), antimicrobial effects significantly increase than when compared with SENPs (P < 0.01). This study demonstrates that certain metallic nanoparticles can be used in combination to improve the antimicrobial efficiency in destroying morphologically distinct pathogens within the healthcare and pharmaceutical industry.Peer reviewe

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Scientists Want More Children

Scholars partly attribute the low number of women in academic science to the impact of the science career on family life. Yet, the picture of how men and women in science – at different points in the career trajectory – compare in their perceptions of this impact is incomplete. In particular, we know little about the perceptions and experiences of junior and senior scientists at top universities, institutions that have a disproportionate influence on science, science policy, and the next generation of scientists. Here we show that having fewer children than wished as a result of the science career affects the life satisfaction of science faculty and indirectly affects career satisfaction, and that young scientists (graduate students and postdoctoral fellows) who have had fewer children than wished are more likely to plan to exit science entirely. We also show that the impact of science on family life is not just a woman's problem; the effect on life satisfaction of having fewer children than desired is more pronounced for male than female faculty, with life satisfaction strongly related to career satisfaction. And, in contrast to other research, gender differences among graduate students and postdoctoral fellows disappear. Family factors impede talented young scientists of both sexes from persisting to research positions in academic science. In an era when the global competitiveness of US science is at risk, it is concerning that a significant proportion of men and women trained in the select few spots available at top US research universities are considering leaving science and that such desires to leave are related to the impact of the science career on family life. Results from our study may inform university family leave policies for science departments as well as mentoring programs in the sciences

Transit Timing and Duration Variations for the Discovery and Characterization of Exoplanets

Transiting exoplanets in multi-planet systems have non-Keplerian orbits which can cause the times and durations of transits to vary. The theory and observations of transit timing variations (TTV) and transit duration variations (TDV) are reviewed. Since the last review, the Kepler spacecraft has detected several hundred perturbed planets. In a few cases, these data have been used to discover additional planets, similar to the historical discovery of Neptune in our own Solar System. However, the more impactful aspect of TTV and TDV studies has been characterization of planetary systems in which multiple planets transit. After addressing the equations of motion and parameter scalings, the main dynamical mechanisms for TTV and TDV are described, with citations to the observational literature for real examples. We describe parameter constraints, particularly the origin of the mass/eccentricity degeneracy and how it is overcome by the high-frequency component of the signal. On the observational side, derivation of timing precision and introduction to the timing diagram are given. Science results are reviewed, with an emphasis on mass measurements of transiting sub-Neptunes and super-Earths, from which bulk compositions may be inferred.Comment: Revised version. Invited review submitted to 'Handbook of Exoplanets,' Exoplanet Discovery Methods section, Springer Reference Works, Juan Antonio Belmonte and Hans Deeg, Eds. TeX and figures may be found at https://github.com/ericagol/TTV_revie