Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

Prediction of thermal expansion properties of carbon nanotubes using molecular dynamics simulations

The axial coefficients of thermal expansion (CTE) of various carbon nanotubes (CNTs), i.e., single-wall carbon nanotubes (SWCNTs), and some multi-wall carbon nanotubes (MWCNTs), were predicted using molecular dynamics (MDs) simulations. The effects of two parameters, i.e., temperature and the CNT diameter, on CTE were investigated extensively. For all SWCNTs and MWCNTs, the obtained results clearly revealed that within a wide low temperature range, their axial CTEs are negative. As the diameter of CNTs decreases, this temperature range for negative axial CTEs becomes narrow, and positive axial CTEs appear in high temperature range. It was found that the axial CTEs vary nonlinearly with the temperature, however, they decrease linearly as the CNT diameter increases. Moreover, within a wide temperature range, a set of empirical formulations was proposed for evaluating the axial CTEs of armchair and zigzag SWCNTs using the above two parameters. Finally, it was found that the absolute value of the negative axial CTE of any MWCNT is much smaller than those of its constituent SWCNTs, and the average value of the CTEs of its constituent SWCNTs. The present fundamental study is very important for understanding the thermal behaviors of CNTs in such as nanocomposite temperature sensors, or nanoelectronics devices using CNTs.

An improved method for undertaking limiting dilution assays for in vitro cloning of Plasmodium falciparum parasites

Background Obtaining single parasite clones is required for many techniques in malaria research. Cloning by limiting dilution using microscopy-based assessment for parasite growth is an arduous and labor-intensive process. An alternative method for the detection of parasite growth in limiting dilution assays is using a commercial ELISA histidine-rich protein II (HRP2) detection kit. Methods Detection of parasite growth was undertaken using HRP2 ELISA and compared to thick film microscopy. An HRP2 protein standard was used to determine the detection threshold of the HRP2 ELISA assay, and a HRP2 release model was used to extrapolate the amount of parasite growth required for a positive result. Results The HRP2 ELISA was more sensitive than microscopy for detecting parasite growth. The minimum level of HRP2 protein detection of the ELISA was 0.11ng/ml. Modeling of HRP2 release determined that 2,116 parasites are required to complete a full erythrocytic cycle to produce sufficient HRP2 to be detected by the ELISA. Under standard culture conditions this number of parasites is likely to be reached between 8 to 14 days of culture. Conclusions This method provides an accurate and simple way for the detection of parasite growth in limiting dilution assays, reducing time and resources required in traditional methods. Furthermore the method uses spent culture media instead of the parasite-infected red blood cells, enabling culture to continue.

Synthesis of diketopyrrolopyrrole based copolymers via the direct arylation method for p-channel and ambipolar OFETs

In this paper, we have synthesized two novel diketopyrrolopyrrole (DPP) based donor-acceptor (D-A) copolymers poly{3,6-dithiophene-2-yl-2,5-di(2-octyl)- pyrrolo[3,4-c]pyrrole-1,4-dione-alt-1,5-bis(dodecyloxy)naphthalene} (PDPPT-NAP) and poly{3,6-dithiophene-2-yl-2,5-di(2-butyldecyl)-pyrrolo[3,4-c]pyrrole-1,4- dione-alt-2-dodecyl-2H-benzo[d][1,2,3]triazole} (PDPPT-BTRZ) via direct arylation organometallic coupling. Both copolymers contain a common electron withdrawing DPP building block which is combined with electron donating alkoxy naphthalene and electron withdrawing alkyl-triazole comonomers. The number average molecular weight (Mn) determined by gel permeation chromatography (GPC) for polymer PDPPT-NAP is around 23 400 g mol-1 whereas for polymer PDPPT-BTRZ it is 18 600 g mol-1. The solid state absorption spectra of these copolymers show a wide range of absorption from 400 nm to 1000 nm with optical band gaps calculated from absorption cut off values in the range of 1.45-1.30 eV. The HOMO values determined for PDPPT-NAP and PDPPT-BTRZ copolymers from photoelectron spectroscopy in air (PESA) data are 5.15 eV and 5.25 eV respectively. These polymers exhibit promising p-channel and ambipolar behaviour when used as an active layer in organic thin-film transistor (OTFT) devices. The highest hole mobility measured for polymer PDPPT-NAP is around 0.0046 cm2 V-1 s-1 whereas the best ambipolar performance was calculated for PDPPT-BTRZ with a hole and electron mobility of 0.01 cm2 V-1 s-1 and 0.006 cm2 V-1 s-1.

A new method of interfacing battery/supercapacitor energy storage systems for distributed energy sources

Battery-supercapacitor hybrid energy storage systems can achieve better power and energy performances compared to their individual use. These hybrid systems require separate dc-dc converters, or at least one dc-dc converter for the supercapacitor bank, to connect them to the dc-link of the grid connecting inverter. However, the use of such dc-dc converters introduces additional cost and power losses. Therefore, the possibility of direct connection of energy storage systems, to the dc-link of a diode clamped 3-level inverter is investigated in this paper. Even though the proposed topology does not use dc-dc converters, a vector selection method is proposed to produce a similar control flexibility that is found in the separate dc-dc converter topology. The major issue with the proposed system is the imminent imbalance of the neutral point potential. A PWM technique with modified carriers is used to solve this problem. Simulations are carried out using MATLAB/SIMULINK to verify the efficacy of the proposed system.

A novel dc-link voltage regulation method for single source hybrid multilevel inverters

This paper presents a novel dc-link voltage regulation technique for a hybrid inverter system formed by cascading two 3-level inverters. The two inverters are named as “bulk inverter” and “conditioning inverter”. For the hybrid system to act as a nine level inverter, conditioning inverter dc link voltage should be maintained at one third of the bulk inverter dc link voltage. Since the conditioning inverter is energized by two series connected capacitors, dc-link voltage regulation should be carried out by controlling the capacitor charging/discharging times. A detailed analysis of conditioning inverter capacitor charging/discharging process and a simplified general rule, derived from the analysis, are presented in this paper. Time domain simulations were carried out to demonstrate efficacy of the proposed method on regulating the conditioning inverter dc-link voltage under various operating conditions.

A review selection method using product feature taxonomy

As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.

A case study of the Iranian national railway and its absolute capacity expansion using analytical models

Identifying railway capacity is an important task that can identify "in principal" whether the network can handle an intended traffic flow, and whether there is any free capacity left for additional train services. Capacity determination techniques can also be used to identify how best to improve an existing network, and at least cost. In this article an optimization approach has been applied to a case study of the Iran national railway, in order to identify its current capacity and to optimally expand it given a variety of technical conditions. This railway is very important in Iran and will be upgraded extensively in the coming years. Hence the conclusions in this article may help in that endeavor. A sensitivity analysis is recommended to evaluate a wider range of possible scenarios. Hence more useful lower and upper bounds can be provided for the performance of the system

Stature estimation of a contemporary Australian sub-population: An evaluation of the Trotter and Gleser method using computed tomography of the femur

Utilising computed tomography scans to allow a virtual analysis of three-dimensional reconstructions of the femur, this project confirms that the traditional 1952 Trotter and Gleser stature estimation equations are inapplicable for a contemporary Queensland population. Therefore, this study introduces modern stature estimation equations for femoral length and fragmentary femoral remains using Bayesian statistics for application in forensic anthropological casework. In addition, it was found that caution needs to be applied when comparing estimated stature to reported stature on the missing persons database due to inaccuracy in Queensland drivers' licences.

Governing virtual worlds : to what extent is it possible to empower players and preserve their rights in virtual worlds, and what is the best method of doing so?

In this paper the author considers the possibilities for establishing democratic governance in virtual worlds. He looks at the freedoms currently available to players in “Second Life”, contrasting these to those established in Raph Koster’s “A Declaration of the Rights of Avatars”, and assess whether some restrictions are more necessary in game spaces than social spaces. The author looks at the early implementations of self-governance in online spaces, and consider what lessons can be taken from these, investigating what a contemporary democratic space looks like, in the form of “A Tale in the Desert”, and finally considers how else we may think of giving players more rights in these developing social spaces.

A novel method of Fiber Bragg Grating (FBG) strain modulation and its application in FBG accelerometers

This thesis has systemically investigated the possibility of improving one type of optical fiber sensors by using a novel mechanism. Many parameters of the sensor have been improved, and one outcome of this innovation is that civil structures, such as bridges and high-rise buildings, may be operated more safely and used longer.

Real or imagined? A study exploring the existence of common method variance effects in road safety research

Common method variance (CMV) has received little attention within the field of road safety research despite a heavy reliance on self-report data. Two surveys were completed by 214 motorists over a two-month period, allowing associations between social desirability and key road safety variables and relationships between scales across the two survey waves to be examined. Social desirability was found to have a strong negative correlation with the Driver Behaviour Questionnaire (DBQ) sub-scales as well as age, but not with crashes and offences. Drivers who scored higher on the social desirability scale were also less likely to report aberrant driving behaviours as measured by the DBQ. Controlling for social desirability did not substantially alter the predictive relationship between the DBQ and the crash and offences variables. The strength of the correlations within and between the two waves were also compared with the results strongly suggesting that effects associated with CMV were present. Identification of CMV would be enhanced by the replication of this study with a larger sample size and comparing self-report data with official sources.

Q-RARA : a rapid and rigorous method for researching small, primary health care organisations

Understanding the organisational processes driving quality primary care is crucial to the maintaining and improving practice. Qualitative methods are increasingly popular in health services research, but this area is dominated by interview studies. Multiple qualitative methods are rarely used in a systematically integrated fashion. We developed a method to study small primary health care organizations using rapid appraisal and qualitative mixed methods: Q-RARA – Qualitative Rapid Appraisal, Rigorous Analysis

A rating aggregation method for generating product reputations

Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.