Consideration of multiple template switches is critical to the determination of the recombination rate on the HIV genome

Retroviral recombination drives viral diversity and facilitates the emergence of immune escape and drug resistant mutants that contribute to disease progression. Current estimates of retroviral recombination rates are based on indirect measurements that do not take into account the effects of multiple recombination events. In the presence of multiple template switches, any even number of template switches result in no observed recombination and any odd number is detected as a single recombination event. We demonstrate that ignoring multiple recombination events consistently underestimates the true recombination rate, especially over large genetic distances and high rates of recombination. Here, we present a novel approach to measure rates of recombination across different gene segments regardless of the effects of genetic distance and the overall rate of recombination. We apply these tools to a novel HIV-1 marker system, which mimics the recombination process between closely related genomes, analogous to those found within the quasispecies of an infected individual. We directly measure the recombination rate in gag, correcting for the effects of multiple template switches and background recombination. Furthermore, our analysis indicates that recombination rates are likely to vary across the viral genome. This system is applicable to other studies to accurately measure the recombination rate that is critical for the diversification of retroviruses.

eLearning content authentication using bipartite matching

Content authenticity and correctness is one of the important challenges in eLearning as there can be many solutions for one specific problem in the cyber space. Therefore, we feel the necessity of mapping problem to solutions using graph partition and weighted bipartite matching. This paper presents a novel architecture and methodology for a personal eLearning system called PELS that is developed by us. We also present an efficient algorithm to partition question-answer (QA) space and explore best possible solution to a particular problem. Our approach can be efficiently applied to social eLearning space where there is one-to-many and many-to-many relationship with a level of bonding. The main advantage of our approach is that we use QA ranking by adjusted edge weights provided by subject matter experts (SME) or expert database. Finally, we use statistical methods called confidence interval and hypothesis test on the data to check the reliability and dependability of the quality of results.

Object matching using boundary descriptors

The problem of object recognition is of immense practical importance and potential, and the last decade has witnessed a number of breakthroughs in the state of the art. Most of the past object recognition work focuses on textured objects and local appearance descriptors extracted around salient points in an image. These methods fail in the matching of smooth, untextured objects for which salient point detection does not produce robust results. The recently proposed bag of boundaries (BoB) method is the first to directly address this problem. Since the texture of smooth objects is largely uninformative, BoB focuses on describing and matching objects based on their post-segmentation boundaries. Herein we address three major weaknesses of this work. The first of these is the uniform treatment of all boundary segments. Instead, we describe a method for detecting the locations and scales of salient boundary segments. Secondly, while the BoB method uses an image based elementary descriptor (HoGs + occupancy matrix), we propose a more compact descriptor based on the local profile of boundary normals’ directions. Lastly, we conduct a far more systematic evaluation, both of the bag of boundaries method and the method proposed here. Using a large public database, we demonstrate that our method exhibits greater robustness while at the same time achieving a major computational saving – object representation is extracted from an image in only 6% of the time needed to extract a bag of boundaries, and the storage requirement is similarly reduced to less than 8%.

Scalable Solid-Template Reduction for Designed Reduced Graphene Oxide Architectures

Herein, we report a solid-state reduction process (in contrast to solution-based approach) by using an environmentally friendly reductant, such as vitamin C (denoted VC), to be directly employed to solid-state graphene oxide (GO) templates to give the highly active rGO architecture with a sheet resistance of as low as 10 Ω sq–1. In addition, predesigned rGO patterns/tracks with tunable resistivity can be directly “written” on a preprepared solid GO film via the inkjet-printing technique using VC/H2O as the printing-ink. This advanced reduction process allows foreign active materials to be preincorporated into the GO matrix to form quality active composite architectures.

Fabrication of meso-porous sintered metal thin films by selective etching of silica based sacrificial template

 Meso-porous metal materials have enhanced surface energies offering unique surface properties with potential applications in chemical catalysis, molecular sensing and selective separation. In this paper, commercial 20 nm diameter metal nano-particles, including silver and copper were blended with 7 nm silica nano-particles by shear mixing. The resulted powders were cold-sintered to form dense, hybrid thin films. The sacrificial silica template was then removed by selective etching in 12 wt% hydrofluoric acid solutions for 15 min to reveal a purely metallic meso-porous thin film material. The impact of the initial silica nano-particle diameter (7–20 nm) as well as the sintering pressure (5–20 ton·m−2) and etching conditions on the morphology and properties of the final nano-porous thin films were investigated by porometry, pyknometery, gas and liquid permeation and electron microscopy. Furthermore, the morphology of the pores and particle aggregation during shear mixing were assessed through cross-sectioning by focus ion beam milling. It is demonstrated that meso-pores ranging between 50 and 320 nm in average diameter and porosities up to 47% can be successfully formed for the range of materials tested.

Template-free synthesis of functional 3D BN architecture for removal of dyes from water.

Three-dimensional (3D) architectures are of interest in applications in electronics, catalysis devices, sensors and adsorption materials. However, it is still a challenge to fabricate 3D BN architectures by a simple method. Here, we report the direct synthesis of 3D BN architectures by a simple thermal treatment process. A 3D BN architecture consists of an interconnected flexible network of nanosheets. The typical nitrogen adsorption/desorption results demonstrate that the specific surface area for the as-prepared samples is up to 1156 m(2) g(-1), and the total pore volume is about 1.17 cm(3) g(-1). The 3D BN architecture displays very high adsorption rates and large capacities for organic dyes in water without any other additives due to its low densities, high resistance to oxidation, good chemical inertness and high surface area. Importantly, 88% of the starting adsorption capacity is maintained after 15 cycles. These results indicate that the 3D BN architecture is potential environmental materials for water purification and treatment.

3D motion matching algorithm using signature feature descriptor

This paper introduces a basic frame for rehabilitation motion practice system which detects 3D motion trajectory with the Microsoft Kinect (MSK) sensor system and proposes a cost-effective 3D motion matching algorithm. The rehabilitation motion practice system displays a reference 3D motion in the database system that the player (patient) tries to follow. The player’s motion is traced by the MSK sensor system and then compared with the reference motion to evaluate how well the player follows the reference motion. In this system, 3D motion matching algorithm is a key feature for accurate evaluation for player’s performance. Even though similarity measurement of 3D trajectories is one of the most important tasks in 3D motion analysis, existing methods are still limited. Recent researches focus on the full length 3D trajectory data set. However, it is not true that every point on the trajectory plays the same role and has the same meaning. In this situation, we developed a new cost-effective method that only uses the less number of features called ‘signature’ which is a flexible descriptor computed from the region of ‘elbow points’. Therefore, our proposed method runs faster than other methods which use the full length trajectory information. The similarity of trajectories is measured based on the signature using an alignment method such as dynamic time warping (DTW), continuous dynamic time warping (CDTW) or longest common sub-sequence (LCSS) method. In the experimental studies, we applied the MSK sensor system to detect, trace and match the 3D motion of human body. This application was assumed as a system for guiding a rehabilitation practice which can evaluate how well the motion practice was performed based on comparison of the patient’s practice motion traced by the MSK system with the pre-defined reference motion in a database. In order to evaluate the accuracy of our 3D motion matching algorithm, we compared our method with two other methods using Australian sign word dataset. As a result, our matching algorithm outperforms in matching 3D motion, and it can be exploited for a base framework for various 3D motion-based applications at low cost with high accuracy.

String matching query verification on the cloud-hosted databases

Database query verification schemes attempt to provide authenticity, completeness, and freshness guarantees for queries executed on untrusted cloud servers. A number of such schemes currently exist in the literature, allowing query verification for queries that are based on matching whole values (such as numbers, dates, etc.) or for queries based on keyword matching. However, there is a notable gap in the research with regard to query verification schemes for pattern-matching queries. Our contribution here is to provide such a verification scheme that provides correctness guarantees for pattern-matching queries executed on the cloud. We describe a trivial scheme, ȃŸż and show how it does not provide completeness guarantees, and then proceed to describe our scheme based on efficient primitives such as cryptographic hashing and Merkle hash trees along with suffix arrays. We also provide experimental results based on a working prototype to show the practicality of our scheme.Ÿż

Estimating the in-vivo HIV template switching and recombination rate

BACKGROUND: HIV recombination has been estimated in vitro using a variety of approaches, and shows a high rate of template switching per reverse transcription event. In-vivo studies of recombination generally measure the accumulation of recombinant strains over time, and thus do not directly estimate a comparable template switching rate. METHOD: To examine whether the estimated in-vitro template switching rate is representative of the rate that occurs during HIV infection in vivo, we adopted a novel approach, analysing single genome sequences from early founder viruses to study the in-vivo template switching rate in the env region of HIV. RESULTS: We estimated the in-vivo per cycle template switching rate to be between 0.5 and 1.5/1000 nt, or approximately 5-14 recombination events over the length of the HIV genome. CONCLUSION: The in-vivo estimated template switching rate is close to the in-vitro estimated rate found in primary T lymphocytes but not macrophages, which is consistent with the majority of HIV infection occurring in T lymphocytes.

Clinical trial adaptation by matching evidence in complementary patient sub-groups of auxiliary blinding questionnaire responses

Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. Such adjustment may take on various forms, including the change in the dose of administered medicines, the frequency of administering an intervention, the number of trial participants, or the duration of the trial, to name just some possibilities. The main goal is to make the process of introducing new medical interventions to patients more efficient, either by reducing the cost or the time associated with evaluating their safety and efficacy. The principal challenge, which is an outstanding research problem, is to be found in the question of how adaptation should be performed so as to minimize the chance of distorting the outcome of the trial. In this paper we propose a novel method for achieving this. Unlike most of the previously published work, our approach focuses on trial adaptation by sample size adjustment i.e. by reducing the number of trial participants in a statistically informed manner. We adopt a stratification framework recently proposed for the analysis of trial outcomes in the presence of imperfect blinding and based on the administration of a generic auxiliary questionnaire that allows the participants to express their belief concerning the assigned intervention (treatment or control). We show that this data, together with the primary measured variables, can be used to make the probabilistically optimal choice of the particular sub-group a participant should be removed from if trial size reduction is desired. Extensive experiments on a series of simulated trials are used to illustrate the effectiveness of our method.

Robot coordination for energy-balanced matching and sequence dispatch of robots to events

Given a set of events and a set of robots, the dispatch problem is to allocate one robot for each event to visit it. In a single round, each robot may be allowed to visit only one event (matching dispatch), or several events in a sequence (sequence dispatch). In a distributed setting, each event is discovered by a sensor and reported to a robot. Here, we present novel algorithms aimed at overcoming the shortcomings of several existing solutions. We propose pairwise distance based matching algorithm (PDM) to eliminate long edges by pairwise exchanges between matching pairs. Our sequence dispatch algorithm (SQD) iteratively finds the closest event-robot pair, includes the event in dispatch schedule of the selected robot and updates its position accordingly. When event-robot distances are multiplied by robot resistance (inverse of the remaining energy), the corresponding energy-balanced variants are obtained. We also present generalizations which handle multiple visits and timing constraints. Our localized algorithm MAD is based on information mesh infrastructure and local auctions within the robot network for obtaining the optimal dispatch schedule for each robot. The simulations conducted confirm the advantages of our algorithms over other existing solutions in terms of average robot-event distance and lifetime.

The design of charitable fund-raising schemes: matching grants or seed money

For a fixed large donation a matching scheme that simply uses a one-for-one match ratio can actually raise less money than a seed money scheme. But when the match ratio is chosen to reflect the characteristics of the small donor base so as to exhaust the large donor's willingness to give, matching schemes always raise more money and are preferred by both charities and large donors. However, when the large donor chooses the size of her donation, a conflict can arise. The large donor can prefer a smaller leadership gift and more reliance on small donor matching while the charity can prefer seed money.