Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically "learn" models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? In this work, we investigate existing algorithms for learning probabilistic models for model checking, propose an evolution-based approach for better controlling the degree of generalization and conduct an empirical study in order to answer the questions. One of our findings is that the effectiveness of learning may sometimes be limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

The rise of dentine hypersensitivity and tooth wear in an ageing population

Our understanding of the aetiology of dentine hypersensitivity (DH) has changed dramatically over the past few decades. It is no longer an enigma, but other problems exist. The prevalence of DH in the world and in particular in the UK is increasing, predominately due to increases in tooth wear and the erosive dietary intake in the younger population. DH is increasingly reported in all age groups and is shown to provide clinical indication of an active erosive tooth wear. As the population ages and possibly retain teeth for longer, the likelihood of tooth wear and DH could increase. This paper describes the prevalence, aetiology, diagnosis and management of DH in relation to tooth wear, which work together through a surface phenomenon. The aim is to raise awareness of the conditions and to help inform a prevention strategy in an ageing population, which starts from younger age groups to reduce disease into older age

Bats Use Magnetite to Detect the Earth's Magnetic Field

While the role of magnetic cues for compass orientation has been confirmed in numerous animals, the mechanism of detection is still debated. Two hypotheses have been proposed, one based on a light dependent mechanism, apparently used by birds and another based on a “compass organelle” containing the iron oxide particles magnetite (Fe3O4). Bats have recently been shown to use magnetic cues for compass orientation but the method by which they detect the Earth's magnetic field remains unknown. Here we use the classic “Kalmijn-Blakemore” pulse re-magnetization experiment, whereby the polarity of cellular magnetite is reversed. The results demonstrate that the big brown bat Eptesicus fuscus uses single domain magnetite to detect the Earths magnetic field and the response indicates a polarity based receptor. Polarity detection is a prerequisite for the use of magnetite as a compass and suggests that big brown bats use magnetite to detect the magnetic field as a compass. Our results indicate the possibility that sensory cells in bats contain freely rotating magnetite particles, which appears not to be the case in birds. It is crucial that the ultrastructure of the magnetite containing magnetoreceptors is described for our understanding of magnetoreception in animals

Old Stellar Populations in Nearby Dwarf Galaxies

What can we learn from the somewhat arduous study of old stellar populations in nearby galaxies? Unless the nearby universe is subtly anomalous, it should contain a relatively normal selection of galaxies whose histories are representative of field galaxies in general throughout the Universe. We can therefore take advantage of our ability to resolve local galaxies into individual stars to directly, and accurately, measure star formation histories. The star formation histories are determined from numerical models, based on stellar evolution tracks, of colour-magnitude diagrams. The most accurate information on star formation rates extending back to the earliest epoches can be obtained from the structure of the main sequence. However, the oldest main sequence turnoffs are very faint, and it is often necessary to use the brighter, more evolved, populations to infer the star formation history at older times. A complete star formation history can be compared with the spectroscopic properties of galaxies seen over a large range of lookback times in redshift surveys. There is considerable evidence that the faint blue galaxies seen in large numbers in cosmological surveys are the progenitors of the late-type irregular galaxies seen in copious numbers in the Local Group, and beyond. We consider how the ``Madau-diagram'', the star formation history of the Universe, would look if the Local Group were to be considered representative of the Universe as a whole

Neonatal-onset multisystem inflammatory disease responsive to interleukin-1 beta inhibition

BACKGROUND:Neonatal-onset multisystem inflammatory disease is characterized by fever, urticarial rash, aseptic meningitis, deforming arthropathy, hearing loss, and mental retardation. Many patients have mutations in the cold-induced autoinflammatory syndrome 1 (CIAS1) gene, encoding cryopyrin, a protein that regulates inflammation.METHODS:We selected 18 patients with neonatal-onset multisystem inflammatory disease (12 with identifiable CIAS1 mutations) to receive anakinra, an interleukin-1-receptor antagonist (1 to 2 mg per kilogram of body weight per day subcutaneously). In 11 patients, anakinra was withdrawn at three months until a flare occurred. The primary end points included changes in scores in a daily diary of symptoms, serum levels of amyloid A and C-reactive protein, and the erythrocyte sedimentation rate from baseline to month 3 and from month 3 until a disease flare.RESULTS:All 18 patients had a rapid response to anakinra, with disappearance of rash. Diary scores improved (P<0.001) and serum amyloid A (from a median of 174 mg to 8 mg per liter), C-reactive protein (from a median of 5.29 mg to 0.34 mg per deciliter), and the erythrocyte sedimentation rate decreased at month 3 (all P<0.001), and remained low at month 6. Magnetic resonance imaging showed improvement in cochlear and leptomeningeal lesions as compared with baseline. Withdrawal of anakinra uniformly resulted in relapse within days; retreatment led to rapid improvement. There were no drug-related serious adverse events.CONCLUSIONS:Daily injections of anakinra markedly improved clinical and laboratory manifestations in patients with neonatal-onset multisystem inflammatory disease, with or without CIAS1 mutations

Creation of ultracold molecules from a Fermi gas of atoms

Since the realization of Bose-Einstein condensates (BEC) in atomic gases an experimental challenge has been the production of molecular gases in the quantum regime. A promising approach is to create the molecular gas directly from an ultracold atomic gas; for example, atoms in a BEC have been coupled to electronic ground-state molecules through photoassociation as well as through a magnetic-field Feshbach resonance. The availability of atomic Fermi gases provides the exciting prospect of coupling fermionic atoms to bosonic molecules, and thus altering the quantum statistics of the system. This Fermi-Bose coupling is closely related to the pairing mechanism for a novel fermionic superfluid proposed to occur near a Feshbach resonance. Here we report the creation and quantitative characterization of exotic, ultracold $^{40}$K$_2$ molecules. Starting with a quantum degenerate Fermi gas of atoms at T < 150 nanoKelvin we scan over a Feshbach resonance to adiabatically create over a quarter million trapped molecules, which we can convert back to atoms by reversing the scan. The small binding energy of the molecules is controlled by detuning from the Feshbach resonance and can be varied over a wide range. We directly detect these weakly bound molecules through rf photodissociation spectra that probe the molecular wavefunction and yield binding energies that are consistent with theory

Semi-natural habitats support biological control, pollination and soil conservation in Europe:A review

Semi-natural habitats are integral to most agricultural areas and have the potential to support ecosystem services, especially biological control and pollination by supplying resources for the invertebrates providing these services and for soil conservation by preventing erosion and run-off. Some habitats are supported through agri-environment scheme funding in the European Union, but their value for ecosystem service delivery has been questioned. An improved understanding of previous research approaches and outcomes will contribute to the development of more sustainable farming systems, improve experimental designs and highlight knowledge gaps especially for funders and researchers. Here we compiled a systematic map to allow for the first time a review of the quantity of evidence collected in Europe that semi-natural habitats support biological control, pollination and soil conservation. A literature search selected 2252 publications, and, following review, 270 met the inclusion criteria and were entered into the database. Most publications were of pest control (143 publications) with less on pollination (78 publications) or soil-related aspects (31). For pest control and pollination, most publications reported a positive effect of semi-natural habitats. There were weaknesses in the evidence base though because of bias in study location and the crops, whilst metrics (e.g. yield) valued by end users were seldom measured. Hedgerows, woodland and grassland were the most heavily investigated semi-natural habitats, and the wider landscape composition was often considered. Study designs varied considerably yet only 24% included controls or involved manipulation of semi-natural habitats. Service providers were commonly measured and used as a surrogate for ecosystem service delivery. Key messages for policymakers and funders are that they should encourage research that includes more metrics required by end users, be prepared to fund longer-term studies (61% were of only 1-year duration) and investigate the role of soils within semi-natural habitats in delivering ecosystem services

Role of the mesoamygdaloid dopamine projection in emotional learning

Amygdala dopamine is crucially involved in the acquisition of Pavlovian associations, as measured via conditioned approach to the location of the unconditioned stimulus (US). However, learning begins before skeletomotor output, so this study assessed whether amygdala dopamine is also involved in earlier 'emotional' learning. A variant of the conditioned reinforcement (CR) procedure was validated where training was restricted to curtail the development of selective conditioned approach to the US location, and effects of amygdala dopamine manipulations before training or later CR testing assessed. Experiment 1a presented a light paired (CS+ group) or unpaired (CS- group) with a US. There were 1, 2 or 10 sessions, 4 trials per session. Then, the US was removed, and two novel levers presented. One lever (CR+) presented the light, and lever pressing was recorded. Experiment 1b also included a tone stimulus. Experiment 2 applied intra-amygdala R(+) 7-OH-DPAT (10 nmol/1.0 A mu l/side) before two training sessions (Experiment 2a) or a CR session (Experiment 2b). For Experiments 1a and 1b, the CS+ group preferred the CR+ lever across all sessions. Conditioned alcove approach during 1 or 2 training sessions or associated CR tests was low and nonspecific. In Experiment 2a, R(+) 7-OH-DPAT before training greatly diminished lever pressing during a subsequent CR test, preferentially on the CR+ lever. For Experiment 2b, R(+) 7-OH-DPAT infusions before the CR test also reduced lever pressing. Manipulations of amygdala dopamine impact the earliest stage of learning in which emotional reactions may be most prevalent

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future