High-efficiency silencing of a β-glucuronidase gene in rice is correlated with repetitive transgene structure but is independent of DNA methylation

Two transgenic callus lines of rice, stably expressing a β-glucuronidase (GUS) gene, were supertransformed with a set of constructs designed to silence the resident GUS gene. An inverted-repeat (i/r) GUS construct, designed to produce mRNA with self-complementarity, was much more effective than simple sense and antisense constructs at inducing silencing. Supertransforming rice calluses with a direct-repeat (d/r) construct, although not as effective as those with the i/r construct, was also substantially more effective in silencing the resident GUS gene than the simple sense and antisense constructs. DNA hybridisation analyses revealed that every callus line supertransformed with either simple sense or antisense constructs, and subsequently showing GUS silencing, had the silence-inducing transgenes integrated into the plant genome in inverted-repeat configurations. The silenced lines containing i/r and d/r constructs did not necessarily have inverted-repeat T-DNA insertions. There was significant methylation of the GUS sequences in most of the silenced lines but not in the unsilenced lines. However, demethylation treatment of silenced lines with 5-azacytidine did not reverse the post-transcriptional gene silencing (PTGS) of GUS. Whereas the levels of RNA specific to the resident GUS gene were uniformly low in the silenced lines, RNA specific to the inducer transgenes accumulated to a substantial level, and the majority of the i/r RNA was unpolyadenylated. Altogether, these results suggest that both sense- and antisense-mediated gene suppression share a similar molecular basis, that unpolyadenylated RNA plays an important role in PTGS, and that methylation is not essential for PTGS.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

When the light goes on

Whether superannuation fund members will achieve adequate retirement incomes is, at least in part, dependent on the superannuation choices they make during their working lives. The two important prerequisites of informed choice are access to good quality information and possession of knowledge and skills to evaluate that information.

Autonomous forced landing system for light general aviation aircraft in unknown environments

This paper presents a system which enhances the capabilities of a light general aviation aircraft to land autonomously in case of an unscheduled event such as engine failure. The proposed system will not only increase the level of autonomy for the general aviation aircraft industry but also increase the level of dependability. Safe autonomous landing in case of an engine failure with a certain level of reliability is the primary focus of our work as both safety and reliability are attributes of dependability. The system is designed for a light general aviation aircraft but can be extended for dependable unmanned aircraft systems. The underlying system components are computationally efficient and provides continuous situation assessment in case of an emergency landing. The proposed system is undergoing an evaluation phase using an experimental platform (Cessna 172R) in real world scenarios.

Visible light photocatalysts for synthesis of fine organic chemicals on supported nanostructures

This thesis is focus on developing new photocatalysts for synthesis of fine organic chemicals on supported nanostructures. These photocatalysts can facilitate reactions by using visible light, moderate temperature and atmospheric pressure which is suitable for a sustainable, green and eco-friendly modern chemical industry. Both Semiconductor Photocatalyst and Noble Metal Photocatalysts are designed to facilitate the homocouplings reaction of imine generation by amines.

Effect of chemical conjugation of L-leucine to chitosan on the dispersibility and drug release of a dry powder inhaler nanoparticle formulation

Purpose: This study investigated the effect of chemical conjugation of the amino acid L-leucine to the polysaccharide chitosan on the dispersibility and drug release pattern of a polymeric nanoparticle (NP)-based controlled release dry powder inhaler (DPI) formulation. Methods: A chemical conjugate of L-leucine with chitosan was synthesized and characterized by Infrared (IR) Spectroscopy, Nuclear Magnetic Resonance (NMR) Spectroscopy, Elemental Analysis and X-ray Photoelectron Spectroscopy (XPS). Nanoparticles of both chitosan and its conjugate were prepared by a water-in-oil emulsification – glutaraldehyde cross-linking method using the antihypertensive agent, diltiazem (Dz) hydrochloride as the model drug. The surface morphology and particle size distribution of the nanoparticles were determined by Scanning Electron Microscopy (SEM) and Dynamic Light Scattering (DLS). The dispersibility of the nanoparticle formulation was analysed by a Twin Stage Impinger (TSI) with a Rotahaler as the DPI device. Deposition of the particles in the different stages was determined by gravimetry and the amount of drug released was analysed by UV spectrophotometry. The release profile of the drug was studied in phosphate buffered saline at 37 ⁰C and analyzed by UV spectrophotometry. Results: The TSI study revealed that the fine particle fractions (FPF), as determined gravimetrically, for empty and drug-loaded conjugate nanoparticles were significantly higher than for the corresponding chitosan nanoparticles (24±1.2% and 21±0.7% vs 19±1.2% and 15±1.5% respectively; n=3, p<0.05). The FPF of drug-loaded chitosan and conjugate nanoparticles, in terms of the amount of drug determined spectrophotometrically, had similar values (21±0.7% vs 16±1.6%). After an initial burst, both chitosan and conjugate nanoparticles showed controlled release that lasted about 8 to 10 days, but conjugate nanoparticles showed twice as much total drug release compared to chitosan nanoparticles (~50% vs ~25%). Conjugate nanoparticles also showed significantly higher dug loading and entrapment efficiency than chitosan nanoparticles (conjugate: 20±1% & 46±1%, chitosan: 16±1% & 38±1%, n=3, p<0.05). Conclusion: Although L-leucine conjugation to chitosan increased dispersibility of formulated nanoparticles, the FPF values are still far from optimum. The particles showed a high level of initial burst release (chitosan, 16% and conjugate, 31%) that also will need further optimization.

Structured feature extraction using association rules

As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

Enhanced n-gram extraction using relevance feature discovery

Guaranteeing the quality of extracted features that describe relevant knowledge to users or topics is a challenge because of the large number of extracted features. Most popular existing term-based feature selection methods suffer from noisy feature extraction, which is irrelevant to the user needs (noisy). One popular method is to extract phrases or n-grams to describe the relevant knowledge. However, extracted n-grams and phrases usually contain a lot of noise. This paper proposes a method for reducing the noise in n-grams. The method first extracts more specific features (terms) to remove noisy features. The method then uses an extended random set to accurately weight n-grams based on their distribution in the documents and their terms distribution in n-grams. The proposed approach not only reduces the number of extracted n-grams but also improves the performance. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms the state-of-art methods underpinned by Okapi BM25, tf*idf and Rocchio.

A web-based approach to data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.

Tuning the surface structure of nitrogen-doped TiO2Nanofibres : an effective method to rnhance photocatalytic activities of visible-light-driven green synthesis and degradation

Nitrogen-doped TiO2 nanofibres of anatase and TiO2(B) phases were synthesised by a reaction between titanate nanofibres of a layered structure and gaseous NH3 at 400–700 °C, following a different mechanism than that for the direct nitrogen doping from TiO2. The surface of the N-doped TiO2 nanofibres can be tuned by facial calcination in air to remove the surface-bonded N species, whereas the core remains N doped. N-Doped TiO2 nanofibres, only after calcination in air, became effective photocatalysts for the decomposition of sulforhodamine B under visible-light irradiation. The surface-oxidised surface layer was proven to be very effective for organic molecule adsorption, and the activation of oxygen molecules, whereas the remaining N-doped interior of the fibres strongly absorbed visible light, resulting in the generation of electrons and holes. The N-doped nanofibres were also used as supports of gold nanoparticle (Au NP) photocatalysts for visible-light-driven hydroamination of phenylacetylene with aniline. Phenylacetylene was activated on the N-doped surface of the nanofibres and aniline on the Au NPs. The Au NPs adsorbed on N-doped TiO2(B) nanofibres exhibited much better conversion (80 % of phenylacetylene) than when adsorbed on undoped fibres (46 %) at 40 °C and 95 % of the product is the desired imine. The surface N species can prevent the adsorption of O2 that is unfavourable for the hydroamination reaction, and thus, improve the photocatalytic activity. Removal of the surface N species resulted in a sharp decrease of the photocatalytic activity. These photocatalysts are feasible for practical applications, because they can be easily dispersed into solution and separated from a liquid by filtration, sedimentation or centrifugation due to their fibril morphology.

Photocatalysis on supported gold and silver nanoparticles under ultraviolet and visible light irradiation

Studies of the optical properties and catalytic capabilities of noble metal nanoparticles (NPs), such as gold (Au) and silver (Ag), have formed the basis for the very recent fast expansion of the field of green photocatalysis: photocatalysis utilizing visible and ultraviolet light, a major part of the solar spectrum. The reason for this growth is the recognition that the localised surface plasmon resonance (LSPR) effect of Au NPs and Ag NPs can couple the light flux to the conduction electrons of metal NPs, and the excited electrons and enhanced electric fields in close proximity to the NPs can contribute to converting the solar energy to chemical energy by photon-driven photocatalytic reactions. Previously the LSPR effect of noble metal NPs was utilized almost exclusively to improve the performance of semiconductor photocatalysts (for example, TiO2 and Ag halides), but recently, a conceptual breakthrough was made: studies on light driven reactions catalysed by NPs of Au or Ag on photocatalytically inactive supports (insulating solids with a very wide band gap) have demonstrated that these materials are a class of efficient photocatalysts working by mechanisms distinct from those of semiconducting photocatalysts. There are several reasons for the significant photocatalytic activity of Au and Ag NPs. (1) The conduction electrons of the particles gain the irradiation energy, resulting in high energy electrons at the NP surface which is desirable for activating molecules on the particles for chemical reactions. (2) In such a photocatalysis system, both light harvesting and the catalysing reaction take place on the nanoparticle, and so charge transfer between the NPs and support is not a prerequisite. (3) The density of the conduction electrons at the NP surface is much higher than that at the surface of any semiconductor, and these electrons can drive the reactions on the catalysts. (4) The metal NPs have much better affinity than semiconductors to many reactants, especially organic molecules. Recent progress in photocatalysis using Au and Ag NPs on insulator supports is reviewed. We focus on the mechanism differences between insulator and semiconductor-supported Au and Ag NPs when applied in photocatalytic processes, and the influence of important factors, light intensity and wavelength, in particular estimations of light irradiation contribution, by calculating the apparent activation energies of photo reactions and thermal reactions.

ZnO nanocones with high-index {101̅1} facets for enhanced energy conversion efficiency of dye-sensitized solar cells

ZnO is a promising photoanode material for dye-sensitized solar cells (DSCs) due to its high bulk electron mobility and because different geometrical structures can easily be tailored. Although various strategies have been taken to improve ZnO-based DSC efficiencies, their performances are still far lower than TiO2 counterparts, mainly because low conductivity Zn2+–dye complexes form on the ZnO surfaces. Here, cone-shaped ZnO nanocrystals with exposed reactive O-terminated {101̅1} facets were synthesized and applied in DSC devices. The devices were compared with DSCs made from more commonly used rod-shaped ZnO nanocrystals where {101̅0} facets are predominantly exposed. When cone-shaped ZnO nanocrystals were used, DSCs sensitized with C218, N719, and D205 dyes universally displayed better power conversion efficiency, with the highest photoconversion efficiency of 4.36% observed with the C218 dye. First-principles calculations indicated that the enhanced DSCs performance with ZnO nanocone photoanodes could be attributed to the strength of binding between the dye molecules and reactive O-terminated {101̅1} ZnO facets and that more effective use of dye molecules occurred due to a significantly less dye aggregation on these ZnO surfaces compared to other ZnO facets.

Light exposure and physical activity in myopic and emmetropic children

Purpose: To objectively assess daily light exposure and physical activity levels in myopic and emmetropic children. Methods: One hundred and two children (41 myopes and 61 emmetropes) aged 10 to 15 years old had simultaneous objective measures of ambient light exposure and physical activity collected over a 2 week period during school term, using a wrist worn actigraphy device (Actiwatch-2). Measures of visible light illuminance and physical activity were captured every 30 seconds, 24 hours a day over this period. Mean hourly light exposure and physical activity for weekdays and weekends were examined. To ensure that seasonal variations didn’t confound comparisons, the light and activity data of the 41 myopes, was compared with 41 age and gender matched emmetropes who wore the Actiwatch over the same two week period. Results: Mean light exposure and physical activity for all 101 children with valid data exhibited significant changes with time of day and day of the week (p<0.0001). On average greater daily light exposure occurred on weekends compared to weekdays (p<0.05), and greater physical activity occurred on weekdays compared to weekends (p<0.01). Myopic children (n = 41, mean daily light exposure 915 ± 519 lux) exhibited significantly lower average light exposure compared to 41 age and gender matched emmetropic children (1272 ± 625 lux, p<0.01). The amount of daily time spent in bright light conditions (>1000 lux) was also significantly greater in emmetropes (127 ± 51 minutes) compared to myopes (91 ± 44 minutes, p<0.001). No significant differences were found between the average daily physical activity levels of myopes and emmetropes (p>0.05). Conclusions: Myopic children exhibit significantly lower daily light exposure, but no significant difference in physical activity compared to emmetropic children. This suggests the important factor involved in documented associations between myopia and outdoor activity is likely exposure to bright outdoor light rather than greater physical activity.

Numerical modelling of load bearing light gauge steel frame wall systems exposed to realistic design fires

Fire safety has become an important part in structural design due to the ever increasing loss of properties and lives during fires. Conventionally the fire rating of load bearing wall systems made of Light gauge Steel Frames (LSF) is determined using fire tests based on the standard time-temperature curve in ISO834 [1]. However, modern commercial and residential buildings make use of thermoplastic materials, which mean considerably high fuel loads. Hence a detailed fire research study into the fire performance of LSF walls was undertaken using realistic design fire curves developed based on Eurocode parametric [2] and Barnett’s BFD [3] curves using both full scale fire tests and numerical studies. It included LSF walls without cavity insulation, and the recently developed externally insulated composite panel system. This paper presents the details of finite element models developed to simulate the full scale fire tests of LSF wall panels under realistic design fires. Finite element models of LSF walls exposed to realistic design fires were developed, and analysed under both transient and steady state fire conditions using the measured stud time-temperature curves. Transient state analyses were performed to simulate fire test conditions while steady state analyses were performed to obtain the load ratio versus time and failure temperature curves of LSF walls. Details of the developed finite element models and the results including the axial deformation and lateral deflection versus time curves, and the stud failure modes and times are presented in this paper. Comparison with fire test results demonstrate the ability of developed finite element models to predict the performance and fire resistance ratings of LSF walls under realistic design fires.

Myosin light chain kinase regulates synaptic plasticity and fear learning in the lateral amygdala

Learning and memory depend on signaling mole- cules that affect synaptic efficacy. The cytoskeleton has been implicated in regulating synaptic transmission but its role in learning and memory is poorly understood. Fear learning depends on plasticity in the lateral nucleus of the amygdala. We therefore examined whether the cytoskeletal-regulatory protein, myosin light chain kinase, might contribute to fear learning in the rat lateral amygdala. Microinjection of ML-7, a specific inhibitor of myosin light chain kinase, into the lateral nucleus of the amygdala before fear conditioning, but not immediately afterward, enhanced both short-term memory and long-term memory, suggesting that myosin light chain kinase is involved specifically in memory acquisition rather than in posttraining consolidation of memory. Myosin light chain kinase inhibitor had no effect on memory retrieval. Furthermore, ML-7 had no effect on behavior when the train- ing stimuli were presented in a non-associative manner. An- atomical studies showed that myosin light chain kinase is present in cells throughout lateral nucleus of the amygdala and is localized to dendritic shafts and spines that are postsynaptic to the projections from the auditory thalamus to lateral nucleus of the amygdala, a pathway specifically impli- cated in fear learning. Inhibition of myosin light chain kinase enhanced long-term potentiation, a physiological model of learning, in the auditory thalamic pathway to the lateral nu- cleus of the amygdala. When ML-7 was applied without as- sociative tetanic stimulation it had no effect on synaptic responses in lateral nucleus of the amygdala. Thus, myosin light chain kinase activity in lateral nucleus of the amygdala appears to normally suppress synaptic plasticity in the cir- cuits underlying fear learning, suggesting that myosin light chain kinase may help prevent the acquisition of irrelevant fears. Impairment of this mechanism could contribute to pathological fear learning.