Endosulfan: a hidden menace

A clean and healthy environment is paramount to human existence. While pesticide use has successfully sustained agricultural and food production in our lifetime as well as safeguarded human health by controlling insect pests, it has also caused many tragedies including population declines in our wildlife, fatalities in workers exposed to pesticides in its manufacture and use, and the increasing incidence of dreaded human illnesses such as cancer. A delicate balance should be achieved to mitigate the adverse impact of pesticide use to the environment and at the same time ensuring short- and long-term agricultural productivity. Endosulfan has been effectively used as a pesticide, but much evidence on its chronic and sub-lethal effects on humans and wildlife have been gathered in recent years. More research still needs to be done to determine its effects from long-term exposure at very low levels. Endosulfan is highly toxic to fish and other aquatic animals and, thus, not recommended for use in aquatic ecosystems. However, in some countries, it has been incorrectly used as a molluscicide in rice paddies, which could have an adverse impact on the rice-fish farming systems and on other surrounding aquatic ecosystems. It is clear that such practices should be stopped and users must strictly observe the recommended application methods. Agricultural productivity should be achieved with less pesticide by using integrated pest management programs which make use of biological, cultural, and physical control agents and lower doses of safer pesticide on a need only basis. The benefits of biotechnology should also be used to develop more effective and safer products and techniques. This is a valid approach and one that will require a unified and concerted effort among suppliers and users of pesticides in order to ensure that resources are used to our best advantage with minimal risk.

Phase noise analysis of a mechanical autonomous impact oscillator with a MEMS resonator

In this paper, phase noise analysis of a mechanical autonomous impact oscillator with a MEMS resonator is performed. Since the circuit considered belongs to the class of hybrid systems, methods based on the variational model for the evaluation of either phase noise or steady state solutions cannot be directly applied. As a matter of fact, the monodromy matrix is not defined at impact events in these systems. By introducing saltation matrices, this limit is overcome and the aforementioned methods are extended. In particular, the unified theory developed by Demir is used to analyze the phase noise after evaluating the asymptotically stable periodic solution of the system by resorting to the shooting method. Numerical results are presented to show how noise sources affect the phase noise performances. © 2011 IEEE.

A study of Rastrineobola argentea in the Ugandan lakes

Increased stocks of mukene Rastrineobola argentea and the subsequent interest in its fishery on Lake Victoria has been attributed to the poor performance of the endemic fishery as a result of introductions into this lake of foreign fish species Lates niloticus and Oreochromis niloticus. R. argentea now remains the only endemic fish species of economic importance ranking second to the Nile perch in this lake. Despite this importance, biological information on the species and knowledge of its fishery is scanty. Preliminary observations on the species in the Ugandan waters indicate that R. argentea feeds mainly on zooplankton (copepods) during daylight hours. Small quantities of aquatic insect larvae/pupae (chironomids and chaoborids) are also eaten mainly at night. These fishes breed just after the rainy seasons and the young eventually mature at between 43-44 mm standard length. Growth and population parameters show a rate of growth (K) of 0.92 with L of 64.5 mm S.L. Natural mortality (M) is given at 2.371 and total mortality (2) of 3.594. Two mesh size nets 10 and 5 mm are in use in the lake. The smaller mesh size which is more preferred by the artisanal fishermen however tends to capture many immature fishes. There is therefore need for a unified lakewide data collection on the species and its fishery in order to obtain more reliable biological information necessary proper management of this fast developing fishery.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

A model for diffusive and displacive phase transitions: Thermo-chemo-mechanical coupling effects

A diffuse interface phase field model is proposed for the unified analysis of diffusive and displacive phase transitions under nonisothermal conditions. Two order parameters are used for the description of the phenomena: one is related to the solute mass fraction and the other to the strain. The model governing equations come from the balance of linear momentum, the solute mass balance (which will lead to the Cahn-Hilliard equation) and the balance of internal energy. Thermodynamic restrictions allow to define constitutive relations for the thermodynamic forces and for the mechanical and chemical dissipations. Numerical tests carried out at different values of the initial temperature show that the model is able to describe the main features of both the displacive and the diffusive phase transitions, as well as their effect on the temperature. © 2010, Advanced Engineering Solutions.

Robust estimation of local genetic ancestry in admixed populations using a nonparametric Bayesian approach.

We present a new haplotype-based approach for inferring local genetic ancestry of individuals in an admixed population. Most existing approaches for local ancestry estimation ignore the latent genetic relatedness between ancestral populations and treat them as independent. In this article, we exploit such information by building an inheritance model that describes both the ancestral populations and the admixed population jointly in a unified framework. Based on an assumption that the common hypothetical founder haplotypes give rise to both the ancestral and the admixed population haplotypes, we employ an infinite hidden Markov model to characterize each ancestral population and further extend it to generate the admixed population. Through an effective utilization of the population structural information under a principled nonparametric Bayesian framework, the resulting model is significantly less sensitive to the choice and the amount of training data for ancestral populations than state-of-the-art algorithms. We also improve the robustness under deviation from common modeling assumptions by incorporating population-specific scale parameters that allow variable recombination rates in different populations. Our method is applicable to an admixed population from an arbitrary number of ancestral populations and also performs competitively in terms of spurious ancestry proportions under a general multiway admixture assumption. We validate the proposed method by simulation under various admixing scenarios and present empirical analysis results from a worldwide-distributed dataset from the Human Genome Diversity Project.

A computer algorithm for determining the tensile strength of float glass

The extrinsic tensile strength of glass can be determined explicitly if the characteristics of the critical surface flaw are known, or stochastically if the critical flaw characteristics are unknown. This paper makes contributions to both these approaches. Firstly it presents a unified model for determining the strength of glass explicitly, by accounting for both the inert strength limit and the sub-critical crack growth threshold. Secondly, it describes and illustrates the use of a numerical algorithm, based on the stochastic approach, that computes the characteristic tensile strength of float glass by piecewise summation of the surface stresses. The experimental validation and sensitivity analysis reported in this paper show that the proposed computer algorithm provides an accurate and efficient means of determining the characteristic strength of float glass. The algorithm is particularly useful for annealed and thermally treated float glass used in the construction industry. © 2012 Elsevier Ltd.

Monte Carlo-Based Bayesian group object tracking and causal reasoning

We present algorithms for tracking and reasoning of local traits in the subsystem level based on the observed emergent behavior of multiple coordinated groups in potentially cluttered environments. Our proposed Bayesian inference schemes, which are primarily based on (Markov chain) Monte Carlo sequential methods, include: 1) an evolving network-based multiple object tracking algorithm that is capable of categorizing objects into groups, 2) a multiple cluster tracking algorithm for dealing with prohibitively large number of objects, and 3) a causality inference framework for identifying dominant agents based exclusively on their observed trajectories.We use these as building blocks for developing a unified tracking and behavioral reasoning paradigm. Both synthetic and realistic examples are provided for demonstrating the derived concepts. © 2013 Springer-Verlag Berlin Heidelberg.

Templates and anchors for antenna-based wall following in cockroaches and robots

The interplay between robotics and neuromechanics facilitates discoveries in both fields: nature provides roboticists with design ideas, while robotics research elucidates critical features that confer performance advantages to biological systems. Here, we explore a system particularly well suited to exploit the synergies between biology and robotics: high-speed antenna-based wall following of the American cockroach (Periplaneta americana). Our approach integrates mathematical and hardware modeling with behavioral and neurophysiological experiments. Specifically, we corroborate a prediction from a previously reported wall-following template - the simplest model that captures a behavior - that a cockroach antenna-based controller requires the rate of approach to a wall in addition to distance, e.g., in the form of a proportional-derivative (PD) controller. Neurophysiological experiments reveal that important features of the wall-following controller emerge at the earliest stages of sensory processing, namely in the antennal nerve. Furthermore, we embed the template in a robotic platform outfitted with a bio-inspired antenna. Using this system, we successfully test specific PD gains (up to a scale) fitted to the cockroach behavioral data in a "real-world" setting, lending further credence to the surprisingly simple notion that a cockroach might implement a PD controller for wall following. Finally, we embed the template in a simulated lateral-leg-spring (LLS) model using the center of pressure as the control input. Importantly, the same PD gains fitted to cockroach behavior also stabilize wall following for the LLS model. © 2008 IEEE.

Coordinated motion design on lie groups

The present paper proposes a unified geometric framework for coordinated motion on Lie groups. It first gives a general problem formulation and analyzes ensuing conditions for coordinated motion. Then, it introduces a precise method to design control laws in fully actuated and underactuated settings with simple integrator dynamics. It thereby shows that coordination can be studied in a systematic way once the Lie group geometry of the configuration space is well characterized. Applying the proposed general methodology to particular examples allows to retrieve control laws that have been proposed in the literature on intuitive grounds. A link with Brockett's double bracket flows is also made. The concepts are illustrated on SO(3), SE(2) and SE(3). © 2010 IEEE.

Bayesian Learning of Noisy Markov Decision Processes

We consider the inverse reinforcement learning problem, that is, the problem of learning from, and then predicting or mimicking a controller based on state/action data. We propose a statistical model for such data, derived from the structure of a Markov decision process. Adopting a Bayesian approach to inference, we show how latent variables of the model can be estimated, and how predictions about actions can be made, in a unified framework. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from the posterior distribution. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.

A practical system for modelling body shapes from single view measurements

This paper describes an interactive system for quickly modelling 3D body shapes from a single image. It provides the user with a convenient way to obtain their 3D body shapes so as to try on virtual garments online. For the ease of use, we first introduce a novel interface for users to conveniently extract anthropometric measurements from a single photo, while using readily available scene cues for automatic image rectification. Then, we propose a unified probabilistic framework using Gaussian processes, which predict the body parameters from input measurements while correcting the aspect ratio ambiguity resulting from photo rectification. Extensive experiments and user studies have supported the efficacy of our system. This system is now being exploited commercially online1. © 2011. The copyright of this document resides with its authors.

Spectral dependence of spin photocurrent and current-induced spin polarization in an InGaAs/InAlAs two-dimensional electron gas

The converse effects of spin photocurrent and current induced spin polarization are experimentally demonstrated in a two-dimensional electron gas system with Rashba spin splitting. Their consistency with the strength of the Rashba coupling as measured for the same system from beating of the Shubnikov-de Haas oscillations reveals a unified picture for the spin photocurrent, current-induced spin-polarization, and spin-orbit coupling. In addition, the observed spectral inversion of the spin photocurrent indicates a system with dominating structure inversion asymmetry.

Current self-oscillation induced by a transverse magnetic field in a doped GaAs/AlAs superlattice

We investigate the influence of a transverse magnetic field on the current-voltage characteristics of a doped GaAs/AlAs superlattice at 1.6 K. The current transport regimes-stable electric field domain formation and current selfoscillation-are observed with increasing transverse magnetic field up to 13 T. Magnetic-field-induced redistribution of electron momentum and energy is identified as the mechanism triggering the switching over of one process to another lending to a change in the dependence of the effective electron drift velocity on electric field. Simulation yields excellent agreement with observed results.

群组通信环境中的密钥管理协议

随着群组通信业务的普及，群组通信的相关安全研究也随之兴起。群组密码学的概念首先由 Desmedt 提出。与传统通信中的密码学方案相比，群组密码学具有很多优点，并已经成功地运用到视频点播和分布式系统等一些应用场景中。群签名，环签名，广播加密等密码学体制作为群组密码学的重要分支都得到了学术界的密切关注。本文的研究工作集中在群组密码学的一个重要组成部分：群组密钥管理，即多个（群组）用户在不安全的开放网络环境中通过一定的协议产生一个共享的会话密钥，为后面的通信提供各种安全性保护。 本文的研究工作主要包含两个方面，群组密钥分发协议和可证明安全的认证群组密钥协商协议。在对已有的群组密钥管理方案进行了大量的调查与分析后，我们在此基础上提出了一些有价值的研究成果。本文的主要成果包括： 1. 在第二章中，提出了一种高效的长期 self-healing 群组密钥分发方案。和已有方案相比，新方案的优势包括：（1）我们避免了使用指数运算, 而只是域上多项式的相关运算；（2）群组管理者广播消息次数比 Staddon 等人和Blundo 等人的方案少一次；（3）用户端存储私钥数目比 Staddon 等人的方案少将近一半；（4）新协议的安全性为无条件安全。 2. 在第三章中，构造了一个从一般群组密钥协商协议向基于口令认证的群组密钥协商协议转换的编译器。编译器的构造利用了对称加密体制，NM-CCA2 和 IK-CCA2 安全的公钥加密体制，以及 UF-CMA 安全的数字签名体制，从而使得编译器可以避免在线/离线字典攻击。 3. 在第四章中，提出了一个基于口令认证的群组密钥协商协议，使得网关在认证服务器的协助下和多个用户之间建立一个会话密钥，同时认证服务器不知道此会话密钥的任何信息（网关和认证服务器之间的信道是专用信道）。由于意识到口令的泄露往往是由于用户的不当使用造成的，所以，不同于已有的基于口令认证的门限密钥协商机制，我们的门限方案是在用户端实施。我们的门限方案要求把用户群组和认证服务器预先共享的口令（称之为群组口令）以秘密共享方式分散共享在群组用户之间，并且每个用户所存储口令的子秘密（share）值依然是一个易记忆的口令（称之为用户口令）。只有不少于 k 个用户一起才能恢复出群组口令。 4. 在第五章中，利用了Unified 模型（把用户长期私钥嵌入到密钥协商过程）构造了一个在 Strong Corruption 模型下可证明安全的强健的认证群组密钥协商协议。和已有类似方案相比，新方案所需要的签名数量明显减少，从而，计算复杂度和通信复杂度也随之降低。另外，新协议是在 Strong Corruption 模型下可证明安全，在此模型下的类似协议比较少。 5. 在第六章中，对 Desmedt 等人提出的 BD-II（树型）群组密钥协商协议做出改进。利用在树中各个节点上应用遮罩函数，我们把由于群组关系变化而对密钥更新所产生的影响限制在一个比较小的群组范围中，从而提高了协议在动态情况下运行的效率。新协议通过四个子算法：初始化，成员加入，成员撤销，子群组合并来分别应对群组密钥协商过程中所遇到的各种（动态）情况。