An Efficient Two-Tier Causal Protocol for Mobile Distributed Systems

Causal ordering is a useful tool for mobile distributed systems (MDS) to reduce the non-determinism induced by three main aspects: host mobility, asynchronous execution, and unpredictable communication delays. Several causal protocols for MDS exist. Most of them, in order to reduce the overhead and the computational cost over wireless channels and mobile hosts (MH), ensure causal ordering at and according to the causal view of the Base Stations. Nevertheless, these protocols introduce certain disadvantage, such as unnecessary inhibition at the delivery of messages. In this paper, we present an efficient causal protocol for groupware that satisfies the MDS''s constraints, avoiding unnecessary inhibitions and ensuring the causal delivery based on the view of the MHs. One interesting aspect of our protocol is that it dynamically adapts the causal information attached to each message based on the number of messages with immediate dependency relation, and this is not directly proportional to the number of MHs.     

Mobile location estimation using density-based clustering technique for NLoS environments

Mobile location technologies have drawn much attention to cope with the mass demands of wireless communication services. Although clustering spatial data is viewed as an effective way to access the objects located in a physical space, little has been done in estimating mobile location. In wireless communication, one of the main problems with accurate location is nonline of sight (NLoS) propagation. To solve the problem, we present a new location algorithm with clustering technique by utilizing the geometrical feature of cell layout, time of arrival range measurements, and three base stations. The mobile location is estimated by solving the optimal solution of the objective function based on the high density cluster. Furthermore, our proposed algorithm only needs three range measurements and does not distinguish between NLoS and LoS environments. Simulations study was conducted to evaluate the performance of the algorithm for different NLoS error distributions and various upper bound of NLoS error. The results of our experiments demonstrate that the proposed algorithm is significantly more effective in location accuracy than range scaling algorithm, linear lines of position algorithm, and Taylor series algorithm, and also satisfies the location accuracy demand of E-911.

A reduction in hippocampal GABAA receptor α5 subunits disrupts the memory for location of objects in mice

The memory for location of objects, which binds information about objects to discrete positions or spatial contexts of occurrence, is a form of episodic memory particularly sensitive to hippocampal damage. Its early decline is symptomatic for elderly dementia. Substances that selectively reduce α5‐GABA_A receptor function are currently developed as potential cognition enhancers for Alzheimer's syndrome and other dementia, consistent with genetic studies implicating these receptors that are highly expressed in hippocampus in learning performance. Here we explored the consequences of reduced GABA_Aα5‐subunit contents, as occurring in α5(H105R) knock‐in mice, on the memory for location of objects. This required the behavioral characterization of α5(H105R) and wild‐type animals in various tasks examining learning and memory retrieval strategies for objects, locations, contexts and their combinations. In mutants, decreased amounts of α5‐subunits and retained long‐term potentiation in hippocampus were confirmed. They exhibited hyperactivity with conserved circadian rhythm in familiar actimeters, and normal exploration and emotional reactivity in novel places, allocentric spatial guidance, and motor pattern learning acquisition, inhibition and flexibility in T‐ and eight‐arm mazes. Processing of object, position and context memories and object‐guided response learning were spared. Genotype difference in object‐in‐place memory retrieval and in encoding and response learning strategies for object–location combinations manifested as a bias favoring object‐based recognition and guidance strategies over spatial processing of objects in the mutants. These findings identify in α5(H105R) mice a behavioral–cognitive phenotype affecting basal locomotion and the memory for location of objects indicative of hippocampal dysfunction resulting from moderately decreased α5‐subunit contents.     

Testing Global Positioning System Performance for Wildlife Monitoring Using Mobile Collars and Known Reference Points

Abstract: To determine the spatial resolution of Global Positioning System (GPS) receiver data, rigorous testing is essential. We tested performance of the Lotek 3300 GPS collar for medium-sized mammals (Lotek Engineering, Inc., Newmarket, ON, Canada). To mimic real wildlife monitoring situations, we performed both static (stationary receiver) and mobile tests, placing the receiver collar on a dog. We compared fix locations of the mobile receiver with the actual trajectory described by a portable Trimble high-precision GPS. We determined performance in relation to habitat type and leaf cover. Location error was habitat-dependent, with the best results in open habitat and much poorer ones in forest, particularly coniferous-dominated forest. For both static and mobile tests, location accuracy was higher when the number of satellites contacted was high and when the residual positional dilution of precision (PDOP) value was low. However, location error was highly variable, even for a given PDOP value and a given number of satellites contacted. Finally, mobile collars performed less well than their static counterparts, presumably because of frequent changes of GPS position and orientation.     

Research on Location Characteristics and Algorithms based on Frequency Domain for a 2D Underwater Active Electrolocation Positioning System

Weakly electric fish has an ability to generate a low-frequency electric field actively to locate the surrounding object in complete darkness by sensing the change of the electric field.This ability is called active electrolocation.In this paper,we designed a two-dimensional (2D) experimental platform of underwater active electrolocation system by simulating weakly electric fish.On the platform,location characteristics based on frequency domain were investigated.Results indicated that surface shape of 3D location characteristic curves for the 2D underwater active electrolocation positioning system was convex upwards or concave down which was influenced by the material of probed objects and the frequency of the electric field excitation signal.Experiments also confirmed that the amplitude of the electric field excitation signal and the size of the probed object will only influence the amplitude corresponding to 3D location characteristic curves.Based on above location characteristics,we present three location algorithms including Cross Location Algorithm (CLA),Stochastic Location Algorithm (SLA) and Particle Swarm Optimization (PSO) location algorithm in frequency domain and achieved the task of the underwater positioning system.Our work may have reference value for underwater detection study.     

Field test of an automated radio‐telemetry system: tracking local space use of aerial insectivores

Documenting local space use of birds that move rapidly, but are too small to carry GPS tags, such as swallows and swifts, can be challenging. For these species, tracking methods such as manual radio‐telemetry and visual observation are either inadequate or labor‐ and time‐intensive. Another option is use of an automated telemetry system, but equipment for such systems can be costly when many receivers are used. Our objective, therefore, was to determine if an automated radio‐telemetry system, consisting of just two receivers, could provide an alternative to manual tracking for gathering data on local space use of six individuals of three species of aerial insectivores, including one Cliff Swallow (Petrochelidon pyrrhonota), one Eastern Phoebe (Sayornis phoebe), and four Barn Swallows (Hirundo rustica). We established automated radio‐telemetry systems at three sites near the city of Peterborough in eastern Ontario, Canada, from May to August 2015. We evaluated the location error of our two‐receiver system using data from moving and stationary test transmitters at known locations, and used telemetry data from the aerial insectivores as a test of the system's ability to track rapidly moving birds under field conditions. Median location error was ~250 m for automated telemetry test locations after filtering. More than 90% of estimated locations had large location errors and were removed from analysis, including all locations > 1 km from receiver stations. Our automated telemetry receivers recorded 17,634 detections of the six radio‐tagged birds. However, filtering removed an average of 89% of bird location estimates, leaving only the Cliff Swallow with enough locations for analysis of space use. Our results demonstrate that a minimal automated radio‐telemetry system can be used to assess local space use by small, highly mobile birds, but the resolution of the data collected using only two receiver stations was coarse and had a limited range. To improve both location accuracy and increase the percentage of usable location estimates collected, we suggest that, in future studies, investigators use receivers that simultaneously record signals detected by all antennas, and use of a minimum of three receiver stations with more antennas at each station.     

High-Accuracy Brain-Machine Interfaces Using Feedback Information

Sensory feedback is very important for movement control. However, feedback information has not been directly used to update movement prediction model in the previous BMI studies, although the closed-loop BMI system provides the visual feedback to users. Here, we propose a BMI framework combining image processing as the feedback information with a novel prediction method. The feedback-prediction algorithm (FPA) generates feedback information from the positions of objects and modifies movement prediction according to the information. The FPA predicts a target among objects based on the movement direction predicted from the neural activity. After the target selection, the FPA modifies the predicted direction toward the target and modulates the magnitude of the predicted vector to easily reach the target. The FPA repeats the modification in every prediction time points. To evaluate the improvements of prediction accuracy provided by the feedback, we compared the prediction performances with feedback (FPA) and without feedback. We demonstrated that accuracy of movement prediction can be considerably improved by the FPA combining feedback information. The accuracy of the movement prediction was significantly improved for all subjects (P<0.001) and 32.1% of the mean error was reduced. The BMI performance will be improved by combining feedback information and it will promote the development of a practical BMI system.     

A Common Data Set and Framework for Representing Spatial Location Information in the Internet

Many organizations are currently working on how to express and provide location information to services and applications in the Internet. Each of them basically specifies their own way. This raises a problem – the various location information formats, services and applications will not be interoperable in the Internet. Interoperability can be achieved if there is a common way of expressing location information. This paper therefore proposes a common data set and an extensible framework of expressing location information in the Internet. The design aims at bridging various existing/proposed location data representation formats, as well as meeting the requirements of existing/proposed location-aware services.     

A novel representation for apoptosis protein subcellular localization prediction using support vector machine

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.     

Representing where along with what information in a model of a cortical patch

Behaving in the real world requires flexibly combining and maintaining information about both continuous and discrete variables. In the visual domain, several lines of evidence show that neurons in some cortical networks can simultaneously represent information about the position and identity of objects, and maintain this combined representation when the object is no longer present. The underlying network mechanism for this combined representation is, however, unknown. In this paper, we approach this issue through a theoretical analysis of recurrent networks. We present a model of a cortical network that can retrieve information about the identity of objects from incomplete transient cues, while simultaneously representing their spatial position. Our results show that two factors are important in making this possible: A) a metric organisation of the recurrent connections, and B) a spatially localised change in the linear gain of neurons. Metric connectivity enables a localised retrieval of information about object identity, while gain modulation ensures localisation in the correct position. Importantly, we find that the amount of information that the network can retrieve and retain about identity is strongly affected by the amount of information it maintains about position. This balance can be controlled by global signals that change the neuronal gain. These results show that anatomical and physiological properties, which have long been known to characterise cortical networks, naturally endow them with the ability to maintain a conjunctive representation of the identity and location of objects.     

Dispersed information diffusion with level and schema-based coordination in mobile peer to peer networks

Several open ended issues for high resource availability in mobile peer to peer networks have been examined in the recent past. Different approaches were conducted for supporting information distribution and availability, through guided or unguided packet diffusion. The majority of the recently proposed approaches try to benefit from the spatial characteristics of the dynamically varying topologies. In this work a directed information diffusion scheme is examined using a level and schema-based coordination, applied in mobile peer to peer networks. The prioritization degree of any requested advert is modeled and enables directed prioritized diffusions to end mobile users that are traversing a certain geographic region (location based advertisements). The proposed method is robust in disseminating redundant messages to users while maintaining connectivity through Gradual Energy Tree-based (GET) configuration. Simulation is performed for the examination and performance evaluation of the proposed scheme, taking into account the modeled prioritization as well as the diffusion accuracy by using the Hierarchical and Non-hierarchical GET configuration.

Cascaded deep network systems with linked ensemble components for underwater fish detection in the wild

We propose a fish detection system based on deep network architectures to robustly detect and count fish objects under a variety of benthic background and illumination conditions. The algorithm consists of an ensemble of Region-based Convolutional Neural Networks that are linked in a cascade structure by Long Short-Term Memory networks. The proposed network is efficiently trained as all components are jointly trained by backpropagation. We train and test our system for a dataset of 18 videos taken in the wild. In our dataset, there are around 20 to 100 fish objects per frame with many fish objects having small pixel areas (less than 900 square pixels). From a series of experiments and ablation tests, the proposed system preserves detection accuracy despite multi-scale distortions, cropping and varying background environments. We present analysis that shows how object localization accuracy is increased by an automatic correction mechanism in the deep network's cascaded ensemble structure. The correction mechanism rectifies any errors in the predictions as information progresses through the network cascade. Our findings in this experiment regarding ensemble system architectures can be generalized to other object detection applications.     

Territorial dynamics and stable home range formation for central place foragers

Uncovering the mechanisms behind territory formation is a fundamental problem in behavioural ecology. The broad nature of the underlying conspecific avoidance processes are well documented across a wide range of taxa. Scent marking in particular is common to a large range of terrestrial mammals and is known to be fundamental for communication. However, despite its importance, exact quantification of the time-scales over which scent cues and messages persist remains elusive. Recent work by the present authors has begun to shed light on this problem by modelling animals as random walkers with scent-mediated interaction processes. Territories emerge as dynamic objects that continually change shape and slowly move without settling to a fixed location. As a consequence, the utilisation distribution of such an animal results in a slowly increasing home range, as shown for urban foxes (Vulpes vulpes). For certain other species, however, home ranges reach a stable state. The present work shows that stable home ranges arise when, in addition to scent-mediated conspecific avoidance, each animal moves as a central place forager. That is, the animal's movement has a random aspect but is also biased towards a fixed location, such as a den or nest site. Dynamic territories emerge but the probability distribution of the territory border locations reaches a steady state, causing stable home ranges to emerge from the territorial dynamics. Approximate analytic expressions for the animal's probability density function are derived. A programme is given for using these expressions to quantify both the strength of the animal's movement bias towards the central place and the time-scale over which scent messages persist. Comparisons are made with previous theoretical work modelling central place foragers with conspecific avoidance. Some insights into the mechanisms behind allometric scaling laws of animal space use are also given.     

Does the Type of Event Influence How User Interactions Evolve on Twitter?

The number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes it possible to go a step further analyzing the dynamics of the interaction patterns. In this article, we present an analysis of the evolution of user interactions that take place in television, socio-political, conference, and keynote events on Twitter. Interactions have been modeled as networks that are annotated with the time markers. We study changes in the structural properties at both the network level and the node level. As a result of this analysis, we have detected patterns of network evolution and common structural features as well as differences among the events.     

Path-based systems to guide scientists in the maze of biological data sources

Fueled by novel technologies capable of producing massive amounts of data for a single experiment, scientists are faced with an explosion of information which must be rapidly analyzed and combined with other data to form hypotheses and create knowledge. Today, numerous biological questions can be answered without entering a wet lab. Scientific protocols designed to answer these questions can be run entirely on a computer. Biological resources are often complementary, focused on different objects and reflecting various experts' points of view. Exploiting the richness and diversity of these resources is crucial for scientists. However, with the increase of resources, scientists have to face the problem of selecting sources and tools when interpreting their data. In this paper, we analyze the way in which biologists express and implement scientific protocols, and we identify the requirements for a system which can guide scientists in constructing protocols to answer new biological questions. We present two such systems, BioNavigation and BioGuide dedicated to help scientists select resources by following suitable paths within the growing network of interconnected biological resources.     

Motivating Men Who Have Sex with Men to Get Tested for HIV through the Internet and Mobile Phones: A Qualitative Study

Background

Men who have sex with men (MSM) have the highest HIV prevalence in Peru, yet they are underserved by traditional preventive programs. In Peru, the Internet and mobile phones have emerged as an effective and convenient tool to reach this population.

Methods and Findings

From October 2010 to February 2011, we conducted eight focus groups with gay identified MSM (closeted and out-of-the-closet) and with self-identified heterosexual MSM in order to identify key features and preferences to be used to tailor culturally-appropriate messages that could be delivered through Internet and mobile phones to motivate MSM to get tested for HIV. Participants reported that in order to motivate HIV testing among MSM, interventions need to be based on motivational messages that encourage participants to overcome the fear of getting tested. Messages should increase the HIV risk perception (of participants who do not consider themselves at risk) by eliciting risky situations experienced by MSM. Messages should emphasize confidentiality, respect and the professionalism of the personnel conducting the counseling and testing. A thorough explanation of the process of HIV testing and the steps to follow after receiving the results should be provided. Messages should also contain information about the venue where the test will be conducted in terms of client characteristics, location, hours of operation and personnel. Finally, stigmatizing and stereotyping messages or images about “being gay” should not be included, as they act as deterrents for getting tested.

Conclusions

Interventions aimed at motivating HIV testing among MSM should include motivational messages that reduce the fear of getting tested and increase the risk perception of participants. They should also market the venue where the testing will be conducted, the professionals who will perform the tests, and the type of tests available. Stigmatizing messages or images should be avoided.     

Residue-level prediction of DNA-binding sites and its application on DNA-binding protein predictions

Protein-DNA interactions are crucial to many cellular activities such as expression-control and DNA-repair. These interactions between amino acids and nucleotides are highly specific and any aberrance at the binding site can render the interaction completely incompetent. In this study, we have three aims focusing on DNA-binding residues on the protein surface: to develop an automated approach for fast and reliable recognition of DNA-binding sites; to improve the prediction by distance-dependent refinement; use these predictions to identify DNA-binding proteins. We use a support vector machines (SVM)-based approach to harness the features of the DNA-binding residues to distinguish them from non-binding residues. Features used for distinction include the residue's identity, charge, solvent accessibility, average potential, the secondary structure it is embedded in, neighboring residues, and location in a cationic patch. These features collected from 50 proteins are used to train SVM. Testing is then performed on another set of 37 proteins, much larger than any testing set used in previous studies. The testing set has no more than 20% sequence identity not only among its pairs, but also with the proteins in the training set, thus removing any undesired redundancy due to homology. This set also has proteins with an unseen DNA-binding structural class not present in the training set. With the above features, an accuracy of 66% with balanced sensitivity and specificity is achieved without relying on homology or evolutionary information. We then develop a post-processing scheme to improve the prediction using the relative location of the predicted residues. Balanced success is then achieved with average sensitivity, specificity and accuracy pegged at 71.3%, 69.3% and 70.5%, respectively. Average net prediction is also around 70%. Finally, we show that the number of predicted DNA-binding residues can be used to differentiate DNA-binding proteins from non-DNA-binding proteins with an accuracy of 78%. Results presented here demonstrate that machine-learning can be applied to automated identification of DNA-binding residues and that the success rate can be ameliorated as more features are added. Such functional site prediction protocols can be useful in guiding consequent works such as site-directed mutagenesis and macromolecular docking.     

Information generated by the moving pinnae of Rhinolophus rouxi: tuning of the morphology at different harmonics

Bats typically emit multi harmonic calls. Their head morphology shapes the emission and hearing sound fields as a function of frequency. Therefore, the sound fields are markedly different for the various harmonics. As the sound field provides bats with all necessary cues to locate objects in space, different harmonics might provide them with variable amounts of information about the location of objects. Also, the ability to locate objects in different parts of the frontal hemisphere might vary across harmonics. This paper evaluates this hypothesis in R. rouxi, using an information theoretic framework. We estimate the reflector position information transfer in the echolocation system of R. rouxi as a function of frequency. This analysis shows that localization performance reaches a global minimum and a global maximum at the two most energetic frequency components of R. rouxi call indicating tuning of morphology and harmonic structure. Using the fundamental the bat is able to locate objects in a large portion of the frontal hemisphere. In contrast, using the 1st overtone, it can only locate objects, albeit with a slightly higher accuracy, in a small portion of the frontal hemisphere by reducing sensitivity to echoes from outside this region of interest. Hence, different harmonic components provide the bat either with a wide view or a focused view of its environment. We propose these findings can be interpreted in the context of the foraging behaviour of R. rouxi, i.e., hunting in cluttered environments. Indeed, the focused view provided by the 1st overtone suggests that at this frequency its morphology is tuned for clutter rejection and accurate localization in a small region of interest while the finding that overall localization performance is best at the fundamental indicates that the morphology is simultaneously tuned to optimize overall localization performance at this frequency.     

Simulative performance analysis of gossip failure detection for scalable distributed systems

Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which failures can be detected in large distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. The hierarchical protocol leverages the underlying network topology to achieve faster failure detection. In addition to studying the effectiveness and efficiency of these two agreement protocols, we propose a third protocol that extends the hierarchical approach by piggybacking gossip information on application-generated messages. The protocols are simulated and evaluated with a fault-injection model for scalable distributed systems comprised of clusters of workstations connected by high-performance networks, such as the CPlant system at Sandia National Laboratories. The model supports permanent and transient node and link failures, with rates specified at simulation time, for processors functioning in a fail-silent fashion. Through high-fidelity, CAD-based modeling and simulation, we demonstrate the strengths and weaknesses of each approach in terms of agreement time, number of gossips, and overall scalability. This revised version was published online in July 2006 with corrections to the Cover Date.