Diurnal Periodicity of Spore Discharge in Ganoderma boninense Pat. from Oil palm in Malaysia

Spore sampling with a Hirst spore trap in an oil palm area infected with G. boninense 'showed that the concentration of G. boninense spores was low in the day especially from noon to 16.00 hr and was very high at night from 22.00 - 06.00 hr; the peak being around midnight. Sampling with a modified hygrothermograph and a Hirst spore trap of spores discharged from individual sporophores of G. boninense produced from infected oil palm trunks in the Botany Garden of University of Malaya also showed a similar pattern of nocturnal maximum and daytime minimum. SUbjecting sporophores to a constant temperature of between 26 - 28°C and relative humidity of85 - 90% in the laboratory did not result in any apparent changes in the diurnal periodicity of spore discharge

Outcomes of HIV treatment from the private sector in low-income and middle-income countries: a systematic review protocol

Introduction: Private sector provision of HIV treatment is increasing in low-income and middle-income countries (LMIC). However, there is limited documentation of its outcomes. This protocol reports a proposed systematic review that will synthesise clinical outcomes of private sector HIV treatment in LMIC. Methods and analysis: This review will be conducted in accordance with the preferred reporting items for systematic review and meta-analyses protocols. Primary outcomes will include: (1) proportion of eligible patients initiating antiretroviral therapy (ART); (2) proportion of those on ART with 90% ART adherence (based on any measure reported); (3) proportion screened for non-communicable diseases (specifically cervical cancer, diabetes, hypertension and mental ill health); (iv) proportion screened for tuberculosis. A search of five electronic bibliographical databases (Embase, Medline, PsychINFO, Web of Science and CINAHL) and reference lists of included articles will be conducted to identify relevant articles reporting HIV clinical outcomes. Searches will be limited to LMIC. No age, publication date, study-design or language limits will be applied. Authors of relevant studies will be contacted for clarification. Two reviewers will independently screen citations and abstracts, identify full text articles for inclusion, extract data and appraise the quality and bias of included studies. Outcome data will be pooled to generate aggregative proportions of primary and secondary outcomes. Descriptive statistics and a narrative synthesis will be presented. Heterogeneity and sensitivity assessments will be conducted to aid interpretation of results. Ethics and dissemination: The results of this review will be disseminated through a peer-reviewed scientific manuscript and at international scientific conferences. Results will inform quality improvement strategies, replication of identified good practices, potential policy changes, and future research

Streaming, Distributed Variational Inference for Bayesian Nonparametrics

This paper presents a methodology for creating streaming, distributed inference algorithms for Bayesian nonparametric (BNP) models. In the proposed framework, processing nodes receive a sequence of data minibatches, compute a variational posterior for each, and make asynchronous streaming updates to a central model. In contrast to previous algorithms, the proposed framework is truly streaming, distributed, asynchronous, learning-rate-free, and truncation-free. The key challenge in developing the framework, arising from the fact that BNP models do not impose an inherent ordering on their components, is finding the correspondence between minibatch and central BNP posterior components before performing each update. To address this, the paper develops a combinatorial optimization problem over component correspondences, and provides an efficient solution technique. The paper concludes with an application of the methodology to the DP mixture model, with experimental results demonstrating its practical scalability and performance.Comment: This paper was presented at NIPS 2015. Please use the following BibTeX citation: @inproceedings{Campbell15_NIPS, Author = {Trevor Campbell and Julian Straub and John W. {Fisher III} and Jonathan P. How}, Title = {Streaming, Distributed Variational Inference for Bayesian Nonparametrics}, Booktitle = {Advances in Neural Information Processing Systems (NIPS)}, Year = {2015}

S-matrix approach to quantum gases in the unitary limit II: the three-dimensional case

A new analytic treatment of three-dimensional homogeneous Bose and Fermi gases in the unitary limit of negative infinite scattering length is presented, based on the S-matrix approach to statistical mechanics we recently developed. The unitary limit occurs at a fixed point of the renormalization group with dynamical exponent z=2 where the S-matrix equals -1. For fermions we find T_c /T_F is approximately 0.1. For bosons we present evidence that the gas does not collapse, but rather has a critical point that is a strongly interacting form of Bose-Einstein condensation. This bosonic critical point occurs at n lambda^3 approximately 1.3 where n is the density and lambda the thermal wavelength, which is lower than the ideal gas value of 2.61.Comment: 26 pages, 16 figure

Synchronized Position Hold, Engage, Reorient, Experimental Satellites

Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) are bowling-ball sized spherical satellites. They will be used inside the space station to test a set of well-defined instructions for spacecraft performing autonomous rendezvous and docking maneuvers. Three free-flying spheres will fly within the cabin of the station, performing flight formations. Each satellite is self-contained with power, propulsion, computers and navigation equipment. The results are important for satellite servicing, vehicle assembly and formation flying spacecraft configurations. SPHERES is a testbed for formation flying by satellites, the theories and calculations that coordinate the motion of multiple bodies maneuvering in microgravity. To achieve this inside the ISS cabin, bowling-ball-sized spheres perform various maneuvers (or protocols), with one to three spheres operating simultaneously . The Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) experiment will test relative attitude control and station-keeping between satellites, re-targeting and image plane filling maneuvers, collision avoidance and fuel balancing algorithms, and an array of geometry estimators used in various missions. SPHERES consists of three self-contained satellites, which are 18 sided polyhedrons that are 0.2 meter in diameter and weigh 3.5 kilograms. Each satellite contains an internal propulsion system, power, avionics, software, communications, and metrology subsystems. The propulsion system uses CO2, which is expelled through the thrusters. SPHERES satellites are powered by AA batteries. The metrology subsystem provides real-time position and attitude information. To simulate ground station-keeping, a laptop will be used to transmit navigational data and formation flying algorithms. Once these data are uploaded, the satellites will perform autonomously and hold the formation until a new command is given

Dynamic polarization vision in mantis shrimps

Gaze stabilization is an almost ubiquitous animal behaviour, one that is required to see the world clearly and without blur. Stomatopods, however, only fix their eyes on scenes or objects of interest occasionally. Almost uniquely among animals they explore their visual environment with a series pitch, yaw and torsional (roll) rotations of their eyes, where each eye may also move largely independently of the other. In this work, we demonstrate that the torsional rotations are used to actively enhance their ability to see the polarization of light. Both Gonodactylus smithii and Odontodactylus scyllarus rotate their eyes to align particular photoreceptors relative to the angle of polarization of a linearly polarized visual stimulus, thereby maximizing the polarization contrast between an object of interest and its background. This is the first documented example of any animal displaying dynamic polarization vision, in which the polarization information is actively maximized through rotational eye movements

Reinforcement learning with misspecified model classes

Real-world robots commonly have to act in complex, poorly understood environments where the true world dynamics are unknown. To compensate for the unknown world dynamics, we often provide a class of models to a learner so it may select a model, typically using a minimum prediction error metric over a set of training data. Often in real-world domains the model class is unable to capture the true dynamics, due to either limited domain knowledge or a desire to use a small model. In these cases we call the model class misspecified, and an unfortunate consequence of misspecification is that even with unlimited data and computation there is no guarantee the model with minimum prediction error leads to the best performing policy. In this work, our approach improves upon the standard maximum likelihood model selection metric by explicitly selecting the model which achieves the highest expected reward, rather than the most likely model. We present an algorithm for which the highest performing model from the model class is guaranteed to be found given unlimited data and computation. Empirically, we demonstrate that our algorithm is often superior to the maximum likelihood learner in a batch learning setting for two common RL benchmark problems and a third real-world system, the hydrodynamic cart-pole, a domain whose complex dynamics cannot be known exactly.United States. Office of Naval Research. Multidisciplinary University Research Initiative (N00014-11-1-0688

Non-intrusive Head Movement Analysis of Videotaped Seizures of Epileptic Origin

Abstract — In this work we propose a non-intrusive video analytic system for patient’s body parts movement analysis in Epilepsy Monitoring Unit. The system utilizes skin color modeling, head/face pose template matching and face detection to analyze and quantify the head movements. Epileptic patients’ heads are analyzed holistically to infer seizure and normal random movements. The patient does not require to wear any special clothing, markers or sensors, hence it is totally nonintrusive. The user initializes the person-specific skin color and selects few face/head poses in the initial few frames. The system then tracks the head/face and extracts spatio-temporal features. Support vector machines are then used on these features to classify seizure-like movements from normal random movements. Experiments are performed on numerous long hour video sequences captured in an Epilepsy Monitoring Unit at a local hospital. The results demonstrate the feasibility of the proposed system in pediatric epilepsy monitoring and seizure detection. I