417 research outputs found

    Transit Detection in the MEarth Survey of Nearby M Dwarfs: Bridging the Clean-First, Search-Later Divide

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    In the effort to characterize the masses, radii, and atmospheres of potentially habitable exoplanets, there is an urgent need to find examples of such planets transiting nearby M dwarfs. The MEarth Project is an ongoing effort to do so, as a ground-based photometric survey designed to detect exoplanets as small as 2 Earth radii transiting mid-to-late M dwarfs within 33 pc of the Sun. Unfortunately, identifying transits of such planets in photometric monitoring is complicated both by the intrinsic stellar variability that is common among these stars and by the nocturnal cadence, atmospheric variations, and instrumental systematics that often plague Earth-bound observatories. Here we summarize the properties of MEarth data gathered so far, and we present a new framework to detect shallow exoplanet transits in wiggly and irregularly-spaced light curves. In contrast to previous methods that clean trends from light curves before searching for transits, this framework assesses the significance of individual transits simultaneously while modeling variability, systematics, and the photometric quality of individual nights. Our Method for Including Starspots and Systematics in the Marginalized Probability of a Lone Eclipse (MISS MarPLE) uses a computationally efficient semi-Bayesian approach to explore the vast probability space spanned by the many parameters of this model, naturally incorporating the uncertainties in these parameters into its evaluation of candidate events. We show how to combine individual transits processed by MISS MarPLE into periodic transiting planet candidates and compare our results to the popular Box-fitting Least Squares (BLS) method with simulations. By applying MISS MarPLE to observations from the MEarth Project, we demonstrate the utility of this framework for robustly assessing the false alarm probability of transit signals in real data. [slightly abridged]Comment: accepted to the Astronomical Journal, 21 pages, 12 figure

    Classifying network attack scenarios using an ontology

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    This paper presents a methodology using network attack ontology to classify computer-based attacks. Computer network attacks differ in motivation, execution and end result. Because attacks are diverse, no standard classification exists. If an attack could be classified, it could be mitigated accordingly. A taxonomy of computer network attacks forms the basis of the ontology. Most published taxonomies present an attack from either the attacker's or defender's point of view. This taxonomy presents both views. The main taxonomy classes are: Actor, Actor Location, Aggressor, Attack Goal, Attack Mechanism, Attack Scenario, Automation Level, Effects, Motivation, Phase, Scope and Target. The "Actor" class is the entity executing the attack. The "Actor Location" class is the Actor‟s country of origin. The "Aggressor" class is the group instigating an attack. The "Attack Goal" class specifies the attacker‟s goal. The "Attack Mechanism" class defines the attack methodology. The "Automation Level" class indicates the level of human interaction. The "Effects" class describes the consequences of an attack. The "Motivation" class specifies incentives for an attack. The "Scope" class describes the size and utility of the target. The "Target" class is the physical device or entity targeted by an attack. The "Vulnerability" class describes a target vulnerability used by the attacker. The "Phase" class represents an attack model that subdivides an attack into different phases. The ontology was developed using an "Attack Scenario" class, which draws from other classes and can be used to characterize and classify computer network attacks. An "Attack Scenario" consists of phases, has a scope and is attributed to an actor and aggressor which have a goal. The "Attack Scenario" thus represents different classes of attacks. High profile computer network attacks such as Stuxnet and the Estonia attacks can now be been classified through the “Attack Scenario” class

    Kindness as an Intervention for Student Social Interaction Anxiety, Resilience, Affect, and Mood: The KISS of Kindness Study II

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    The purpose of this study was to assess the impact of deliberate acts of kindness (DAKs) plus access to a stress management booklet (intervention), compared to the booklet alone (control) on the stress-related outcomes of resilience, social interaction anxiety, affect, and mood of undergraduate and graduate students. Participants’ study-related experiences were also explored, as were the types of DAKs. This repeated-measures, randomized controlled trial included 112 students (80 undergraduate and 32 graduate) with 56 in each condition. Four previously validated scales were implemented at baseline, immediate post-intervention, and 3-months post-intervention. A linear mixed effects model was utilized with group and time entered as fixed effects. Content analysis of open-ended question responses and DAKs logs was conducted. The KISS of Kindness II had a statistically significant interaction effect on the intervention group participants’ resilience (p = 0.0099), social anxiety (p = 0.0016), and negative affect (p = 0.0033), but had no significant impact on their positive affect or mood. Intervention participants described improvements in mental wellbeing. DAKs were plentiful (1,542 DAKs, 26 types), and show promise for university-based mental health interventions

    Liposomal Encapsulation of Amoxicillin via Microfluidics with Subsequent Investigation of the Significance of PEGylated Therapeutics

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    With an increasing concern of global antimicrobial resistance, the efforts to improve the formulation of a narrowing library of therapeutic antibiotics must be confronted. The liposomal encapsulation of antibiotics using a novel and sustainable microfluidic method has been employed in this study to address this pressing issue, via a targeted, lower-dose medical approach. The study focusses upon microfluidic parameter optimisation, formulation stability, cytotoxicity, and future applications. Particle sizes of circa. 130 nm, with viable short-term (28-day) physical stability were obtained, using two different non-cytotoxic liposomal formulations, both of which displayed suitable antibacterial efficacy. The microfluidic method allowed for high encapsulation efficiencies (≈77 %) and the subsequent in vitro release profile suggested high limits of antibiotic dissociation from the nanovessels, achieving 90% release within 72 h. In addition to the experimental data, the growing use of poly(ethylene) glycol (PEG) within lipid-based formulations is discussed in relation to anti-PEG antibodies, highlighting the key pharmacological differences between PEGylated and non-PEGylated formulations and their respective advantages and drawbacks. It's surmised that in the case of the formulations used in this study, the addition of PEG upon the liposomal membrane would still be a beneficial feature to possess owing to beneficial features such as stability, antibiotic efficacy and the capacity to further modify the liposomal membrane.</p