Ge/Si quantum dot formation from non-uniform cluster fluxes

The controlled growth of ultra-small Ge/Si quantum dot (QD) nuclei (≈1 nm) suitable for the synthesis of uniform nanopatterns with high surface coverage, is simulated using atom-only and size non-uniform cluster fluxes. It is found that seed nuclei of more uniform sizes are formed when clusters of non-uniform size are deposited. This counter-intuitive result is explained via adatom-nanocluster interactions on Si(100) surfaces. Our results are supported by experimental data on the geometric characteristics of QD patterns synthesized by nanocluster deposition. This is followed by a description of the role of plasmas as non-uniform cluster sources and the impact on surface dynamics. The technique challenges conventional growth modes and is promising for deterministic synthesis of nanodot arrays.

A non-malleable group key exchange protocol robust against active insiders

In this paper we make progress towards solving an open problem posed by Katz and Yung at CRYPTO 2003. We propose the first protocol for key exchange among n ≥2k+1 parties which simultaneously achieves all of the following properties: 1. Key Privacy (including forward security) against active attacks by group outsiders, 2. Non-malleability — meaning in particular that no subset of up to k corrupted group insiders can ‘fix’ the agreed key to a desired value, and 3. Robustness against denial of service attacks by up to k corrupted group insiders. Our insider security properties above are achieved assuming the availability of a reliable broadcast channel.

Burden of non-communicable diseases (NCDs) in Nepal and the availability and affordability of NCD medicines

Background: Traditionally communicable diseases were the main causes of burden in developing countries like Nepal. In recent years non-communicable diseases (NCDs), mainly cardiovascular diseases (CVDs), cancer, chronic respiratory diseases and diabetes mellitus, impose a larger disease burden compared to communicable diseases. Most elements of health and medicine policies in Nepal are still focused on communicable diseases. There is limited evidence about NCDs and NCD medicines in Nepal. Aim: To explore the gap between the burden of NCDs and the availability and affordability of NCD medicines in Nepal. Methods: Biomedical databases like Medline, Scopus, Web of Science and other online sources (including Global Burden of Diseases data) were searched for data on the burden of NCDs in term of Disability Adjusted Life Years (DALYs). The Essential Medicines List (EML) of Nepal was compared with World Health Organisation (EML) for inclusion of NCD medicines. Results: In Nepal, NCDs caused nearly 45% of the total 10.5 million DALYs in 2010. CVDs (15.2%), were the leading cause of NCDs burden followed by chronic respiratory diseases (14.7%), cancer (7.3%) and diabetes mellitus (3.2%). One hospital based national survey found that 37% of hospitalised patients had NCDs. Among them, 38% had heart disease followed by COPD (33%) , and diabetes (10%). Most (23 out of 28) non-cancer NCD medicines recommended in WHO-EML were present in Nepal's EML, theoretically indicating good availability. However, it is difficult to say whether they are accessible and affordable due to the lack of adequate data on access and pricing. Conclusion: This study gives some insight into the burden of NCDs. Although NCD medicines are available in Nepal, further research is required to determine whether they are accessible and affordable to the general population.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

A Tobit model for analyzing speed limit compliance in work zones

Poor compliance with speed limits is a serious safety concern in work zones. Most studies of work zone speeds have focused on descriptive analyses and statistical testing without systematically capturing the effects of vehicle and traffic characteristics. Consequently, little is known about how the characteristics of surrounding traffic and platoons influence speeds. This paper develops a Tobit regression technique for innovatively modeling the probability and the magnitude of non-compliance with speed limits at various locations in work zones. Speed data is transformed into two groups—continuous for non-compliant and left-censored for compliant drivers—to model in a Tobit model framework. The modeling technique is illustrated using speed data from three long-term highway work zones in Queensland, Australia. Consistent and plausible model estimates across the three work zones support the appropriateness and validity of the technique. The results show that the probability and magnitude of speeding was higher for leaders of platoons with larger front gaps, during late afternoon and early morning, when traffic volumes were higher, and when higher proportions of surrounding vehicles were non-compliant. Light vehicles and their followers were also more likely to speed than others. Speeding was more common and greater in magnitude upstream than in the activity area, with higher compliance rates close to the end of the activity area and close to stop/slow traffic controllers. The modeling technique and results have great potential to assist in deployment of appropriate countermeasures by better identifying the traffic characteristics associated with speeding and the locations of lower compliance.

A non-profit design-led innovation journey

Non-profit organisations in the aged care sector are currently under pressure from more than just a sheer increase of customers. A need to respond to changing legislative requirements, increased expectations from customers and increasing likelihood of shortage in appropriate experienced staff are also contributing to instability within the sector. This paper will present a longitudinal action research study of a non-profit organisation revisiting its core purpose of providing relevant services and attempting to build a customer-centric method for addressing the current and upcoming change drivers in an Australian aged care context. The study found Design- Led Innovation to be an effective methodology for capturing deep customer insights and conceptualising new business models which address the prevalent change drivers. This paper details a design-led approach to innovation, tailored to a non-profit organisation seeking to better understand its stakeholders and redefine its value offering.

Assembly and annotation of a non-model gastropod (Nerita melanotragus) transcriptome: a comparison of De novo assemblers

Background The sequencing, de novo assembly and annotation of transcriptome datasets generated with next generation sequencing (NGS) has enabled biologists to answer genomic questions in non-model species with unprecedented ease. Reliable and accurate de novo assembly and annotation of transcriptomes, however, is a critically important step for transcriptome assemblies generated from short read sequences. Typical benchmarks for assembly and annotation reliability have been performed with model species. To address the reliability and accuracy of de novo transcriptome assembly in non-model species, we generated an RNAseq dataset for an intertidal gastropod mollusc species, Nerita melanotragus, and compared the assembly produced by four different de novo transcriptome assemblers; Velvet, Oases, Geneious and Trinity, for a number of quality metrics and redundancy. Results Transcriptome sequencing on the Ion Torrent PGM™ produced 1,883,624 raw reads with a mean length of 133 base pairs (bp). Both the Trinity and Oases de novo assemblers produced the best assemblies based on all quality metrics including fewer contigs, increased N50 and average contig length and contigs of greater length. Overall the BLAST and annotation success of our assemblies was not high with only 15-19% of contigs assigned a putative function. Conclusions We believe that any improvement in annotation success of gastropod species will require more gastropod genome sequences, but in particular an increase in mollusc protein sequences in public databases. Overall, this paper demonstrates that reliable and accurate de novo transcriptome assemblies can be generated from short read sequencers with the right assembly algorithms. Keywords: Nerita melanotragus; De novo assembly; Transcriptome; Heat shock protein; Ion torrent

Organic non-fullerene acceptors for organic photovoltaics

Heterojunction organic photovoltaics have been the subject of intensive academic interest over the past two decades, and significant commercial efforts have been directed towards this area with the vision of developing the next generation of low-cost solar cells. Materials development has played a vital role in the dramatic improvement of organic solar cell performance in recent years, and this is driven primarily by the advancement of p-type semiconductors as donor materials. With the highest performing solar cells today dominated by acceptors based on members of the fullerene family, much less attention has been devoted to other classes of n-type acceptors. In this review, we will provide an overview of the progress in the synthesis, characterization and implementation of the various classes of non-fullerenebased n-type organic acceptors for photovoltaic applications.

Biodiesel production from non-edible beauty leaf (Calophyllum Inophyllum) oil : process optimization using response surface methodology (RSM)

In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

World emissions and economic growth: Application of non-parametric methods

The Environmental Kuznets Curve (EKC) hypothesises an inverse U-shaped relationship between a measure of environmental pollution and per capita income levels. In this study, we apply non-parametric estimation of local polynomial regression (local quadratic fitting) to allow more flexibility in local estimation. This study uses a larger and globally representative sample of many local and global pollutants and natural resources including Biological Oxygen Demand (BOD) emission, CO2 emission, CO2 damage, energy use, energy depletion, mineral depletion, improved water source, PM10, particulate emission damage, forest area and net forest depletion. Copyright © 2009 Inderscience Enterprises Ltd.

The technical efficiency of the Japanese banks : non-radial directional performance measurement with undesirable output

The paper analyses technical efficiency of the Japanese banks from 2000 to 2007. The estimation technique is based on the Russell directional distance function that takes into consideration not only desirable outputs but also an undesirable output that is represented by non-performing loans (NPLs). The results indicate that NPLs remain a significant burden as for banks' performance. We show that banks' inputs have to be utilised more efficiently, particularly labour and premises. We also argue that a further restructuring process is needed in the segment of Regional Banks. We conclude that the Japanese banking system is still far away from being fully consolidated and restructured.

Non-separability and substitutability among water pollutants : evidence from India

The design and implementation of environmental policy often involve more than one pollutant, and must consider pollution as a byproduct of the production of marketable output. In this paper, we test the implicit assumption in the empirical literature that (1) production of marketable output, pollution and abatement are separable, and (2) different pollutants can be abated separately. Using unique plant-level data in India, we reject the null hypotheses of separability between marketable output and pollutants, and between different pollutants. Firms must incur abatement costs for reducing pollution levels. In addition, complement and substitute relationships between water pollutants are demonstrated with statistical significance.

Non-invasive techniques for imaging in-vivo human corneal sub basal nerve mapping and migration rate in diabetic neuropathy

Purpose Corneal confocal microscopy (CCM) is a rapid non-invasive ophthalmic technique, which has been shown to diagnose and stratify the severity of diabetic neuropathy. Current morphometric techniques assess individual static images of the subbasal nerve plexus; this work explores the potential for non-invasive assessment of the wide-field morphology and dynamic changes of this plexus in vivo. Methods In this pilot study, laser scanning CCM was used to acquire maps (using a dynamic fixation target and semi-automated tiling software) of the central corneal sub-basal nerve plexus in 4 diabetic patients with and 6 without neuropathy and in 2 control subjects. Nerve migration was measured in an additional 7 diabetic patients with neuropathy, 4 without neuropathy and in 2 control subjects by repeating a modified version of the mapping procedure within 2-8 weeks, thus facilitating re-identification of distinctive nerve landmarks in the 2 montages. The rate of nerve movement was determined from these data and normalised to a weekly rate (µm/week), using customised software. Results Wide-field corneal nerve fibre length correlated significantly with the Neuropathy Disability Score (r = -0.58, p < 0.05), vibration perception (r = -0.66, p < 0.05) and peroneal conduction velocity (r = 0.67, p < 0.05). Central corneal nerve fibre length did not correlate with any of these measures of neuropathy (p > 0.05 for all). The rate of corneal nerve migration was 14.3 ± 1.1 µm/week in diabetic patients with neuropathy, 19.7 ± 13.3µm/week in diabetic patients without neuropathy, and 24.4 ± 9.8µm/week in control subjects; however, these differences were not significantly different (p = 0.543). Conclusions Our data demonstrate that it is possible to capture wide-field images of the corneal nerve plexus, and to quantify the rate of corneal nerve migration by repeating this procedure over a number of weeks. Further studies on larger sample sizes are required to determine the utility of this approach for the diagnosis and monitoring of diabetic neuropathy.

PTRF/cavin-1 neutralizes non-caveolar caveolin-1 microdomains in prostate cancer

Caveolin-1 has a complex role in prostate cancer and has been suggested to be a potential biomarker and therapeutic target. As mature caveolin-1 resides in caveolae, invaginated lipid raft domains at the plasma membrane, caveolae have been suggested as a tumor-promoting signaling platform in prostate cancer. However, caveola formation requires both caveolin-1 and cavin-1 (also known as PTRF; polymerase I and transcript release factor). Here, we examined the expression of cavin-1 in prostate epithelia and stroma using tissue microarray including normal, non-malignant and malignant prostate tissues. We found that caveolin-1 was induced without the presence of cavin-1 in advanced prostate carcinoma, an expression pattern mirrored in the PC-3 cell line. In contrast, normal prostate epithelia expressed neither caveolin-1 nor cavin-1, while prostate stroma highly expressed both caveolin-1 and cavin-1. Utilizing PC-3 cells as a suitable model for caveolin-1-positive advanced prostate cancer, we found that cavin-1 expression in PC-3 cells inhibits anchorage-independent growth, and reduces in vivo tumor growth and metastasis in an orthotopic prostate cancer xenograft mouse model. The expression of α-smooth muscle actin in stroma along with interleukin-6 (IL-6) in cancer cells was also decreased in tumors of mice bearing PC-3-cavin-1 tumor cells. To determine whether cavin-1 acts by neutralizing caveolin-1, we expressed cavin-1 in caveolin-1-negative prostate cancer LNCaP and 22Rv1 cells. Caveolin-1 but not cavin-1 expression increased anchorage-independent growth in LNCaP and 22Rv1 cells. Cavin-1 co-expression reversed caveolin-1 effects in caveolin-1-positive LNCaP cells. Taken together, these results suggest that caveolin-1 in advanced prostate cancer is present outside of caveolae, because of the lack of cavin-1 expression. Cavin-1 expression attenuates the effects of non-caveolar caveolin-1 microdomains partly via reduced IL-6 microenvironmental function. With circulating caveolin-1 as a potential biomarker for advanced prostate cancer, identification of the molecular pathways affected by cavin-1 could provide novel therapeutic targets.