Controlling the Ultrafast Dynamics of HD+ by the Carrier-Envelope Phases of an Ultrashort Laser Pulse: A Quasi-Classical Dynamics Study

A theoretical study on the coupled electron-nuclear dynamics of HD+ molecular ions under ultrashort, intense laser pulses is performed by employing a well-established quasi-classical model. The influence of the laser carrier-envelope phase on various channel (H + D+, D + H+, and H+ + D+) probabilities is investigated at different laser field intensities. The carrier-envelope phase is found to govern the dissociation (H + D+ and D + H+) and Coulomb explosion (H+ + D+) channel probabilities. The kinetic energy release distributions of the fragments are also found to be sensitive to the carrier-envelope phase of the laser pulse. Our results are in agreement with the previously reported quantum dynamics studies and experiments

Natural Notation for the Domestic Internet of Things

This study explores the use of natural language to give instructions that might be interpreted by Internet of Things (IoT) devices in a domestic `smart home' environment. We start from the proposition that reminders can be considered as a type of end-user programming, in which the executed actions might be performed either by an automated agent or by the author of the reminder. We conducted an experiment in which people wrote sticky notes specifying future actions in their home. In different conditions, these notes were addressed to themselves, to others, or to a computer agent.We analyse the linguistic features and strategies that are used to achieve these tasks, including the use of graphical resources as an informal visual language. The findings provide a basis for design guidance related to end-user development for the Internet of Things.Comment: Proceedings of the 5th International symposium on End-User Development (IS-EUD), Madrid, Spain, May, 201

Inferring aerosol types over the Indo-Gangetic Basin from ground based sunphotometer measurements

A discrimination of aerosol types over the Indo-Gangetic Basin (IGB) region during pre-monsoon period was made using multi-year ground based sun/sky radiometer measured aerosol products associated with the size of aerosols and radiation absorptivity. High dust enriched aerosols (i.e. polluted dust, PD) were found to contribute more over the central IGB station at Kanpur (KNP, 62) as compared to the eastern IGB station at Gandhi College (GC, 31) whereas vice-versa was observed for polluted continental (PC) aerosols, which contain high anthropogenic and less dust aerosols. Contributions of carbonaceous particles having high absorbing (mostly black carbon, MBC) and low absorbing (mostly organic carbon, MOC) aerosols were found to be 11 and 10, respectively at GC, which was ~. 46 and 62 higher than the observed contributions at KNP; however, very less contribution of non-absorbing (NA) aerosols was observed only at GC (2). Variability in aerosol types together with single scattering albedo (SSA) at both the stations were also studied during the forenoon (FN) and afternoon (AN) hour, which suggests their strong association with emission sources. Results were well substantiated with the air mass back-trajectories and the fire products. Spectral information of SSA for each aerosol type discriminates the dominance of natural dust (SSA increases with increasing wavelength) with anthropogenic aerosols (SSA decreases with increasing wavelength) at both the locations. The estimated absorption à ngström exponent (AAE) values suggest relative dominance of absorbing type aerosols over the central part of IGB (due to dominant dust absorption) as compared to the eastern part during pre-monsoon period

A Goal-based Framework for Contextual Requirements Modeling and Analysis

Requirements Engineering (RE) research often ignores, or presumes a uniform nature of the context in which the system operates. This assumption is no longer valid in emerging computing paradigms, such as ambient, pervasive and ubiquitous computing, where it is essential to monitor and adapt to an inherently varying context. Besides influencing the software, context may influence stakeholders' goals and their choices to meet them. In this paper, we propose a goal-oriented RE modeling and reasoning framework for systems operating in varying contexts. We introduce contextual goal models to relate goals and contexts; context analysis to refine contexts and identify ways to verify them; reasoning techniques to derive requirements reflecting the context and users priorities at runtime; and finally, design time reasoning techniques to derive requirements for a system to be developed at minimum cost and valid in all considered contexts. We illustrate and evaluate our approach through a case study about a museum-guide mobile information system

Discovering the right place to check-in using web-based proximate selection

With information technology becoming increasingly embedded in our everyday physical world, there is a growing set of mobile applications that involve a connection with the digital representation of physical places. This association is normally initiated with a check-in procedure, through which a person asserts her presence at a particular place and determines the context for subsequent interactions. The common assumption is that a mobile application will be able to search the surrounding environment and present the user with the intended check-in target; however, in a world of ubiquitous place-based services, this assumption may no longer hold. A person in an urban environment would, at any moment, be surrounded by a large number of places, all of which could be regarded as possible interaction contexts for that person. In this work, we investigate the real-word challenges associated with wide-scale place selection and how the process can be affected by the place environment, by the position of the person in relation to the target place and by positioning errors. To study this reality, we used Google Places as a directory of georeferenced places. We conducted 14,400 nearby place queries structured around different combinations of our three independent variables. The results suggest that the overall performance is poor, except for low-density scenarios, and that this discovery process, albeit relevant, should always be combined with other place discovery approaches. The results also help to understand how this performance is affected by check-in positions and by the properties of the place environment.- (undefined

Type-1 Interferon Responses Underlie Tumor-Selective Replication of Oncolytic Measles Virus

The mechanism of tumor selective replication of oncolytic measles virus (MV) is poorly understood. Using a step-wise model of cellular transformation, in which oncogenic hits were additively expressed in human bone marrow-derived mesenchymal stromal cells, we show that MV-induced oncolysis increased progressively with transformation. Type-1 interferon response to MV infection was significantly reduced and delayed, in accordance with the level of transformation. Consistently, we observed delayed and reduced STAT1 phosphorylation in the fully transformed cells. Pre-treatment with IFNβ restored resistance to MV-mediated oncolysis. Gene expression profiling to identify the genetic correlates of susceptibility to MV oncolysis revealed a dampened basal level of immune-related genes in the fully transformed cells compared to their normal counterparts. Interferon-induced transmembrane protein 1 (IFITM1) was the foremost basally downregulated immune gene. Stable IFITM1 overexpression in MV-susceptible cells resulted in a 50% increase in cell viability and a significant reduction in viral replication at 24 hours post MV infection. Overall, our data indicate that the basal reduction in functions of the type 1 IFN pathway is a major contributor to the oncolytic selectivity of MV. In particular, we have identified IFITM1 as a restriction factor for oncolytic MV, acting at early stages of infection

DeepRank: Adapting Neural Tensor Networks for Ranking the Recommendations

Online real estate property portals are gaining great attraction from masses due to ease in finding properties for rental or sale/purchase. With a few clicks, a real estate portal can display relevant information to a user by ranking the searched items according to user’s specifications. It is highly significant that the ranking results display the most relevant search results to the user. Therefore, an efficient ranking algorithm that takes user’s context is crucial for enhancing user experience in finding real estate properties online. This paper proposes an expressive Neural Tensor Network to rank the properties when searched for based on the similarity between the two property entities. Previous similarity techniques do not take into account the numerous complex features used to define a property. We showed that the performance can be enhanced if the property entities are represented as an average of their constituting features before finding the similarity between them. The proposed method takes into account each feature dynamically and ranks properties according to similarity with an accuracy of 86.6%

Context acquisition in auditory emotional recognition studies

This paper describes an environment to assess auditory emotional recognition based on a mobile application. The primary aim of this work is to provide a valuable instrument that can be used both in research and clinical settings, responding to the strong need of validated measures of emotional processing, especially in Portugal. The secondary aim is to acquire and study the participants' interaction behavior with the technological device (e.g. touch patterns, touch intensity), in search for a relationship with medical conditions, cognitive impairments, auditory emotional recognition capacities or socio-demographic indicators. This will establish the basis for the prediction of such aspects as a function of an individual's interaction with technological devices, potentially providing new diagnostic tools.This work has been supported by FCT-Fundacao para a Ciencia e Tecnologia within the Project Scope UID/ CEC/00319/2013 and Grant PTDC/MHN-PCN/3606/2012. The work of Davide Carneiro is supported by a post-doctoral Grant by FCT (SFRH/BPD/109070/2015). The work of Ana P. Pinheiro is supported by FCT Investigator Grant IF/00334/2012 funded by Fundacao para a Ciencia e a Tecnologia (FCT, Portugal).info:eu-repo/semantics/publishedVersio

Paving the Way for a Real-Time Context-Aware Predictive Architecture

Internet of Things society generates and needs to consume huge amounts of data in a demanding context-aware scenario. Such exponentially growing data sources require the use of novel processing methodologies, technologies and tools to facilitate data processing in order to detect and prevent situations of interest for the users in their particular context. To solve this issue, we propose an architecture which making use of emerging technologies and cloud platforms can process huge amounts of heterogeneous data and promptly alert users of relevant situations for a particular domain according to their context. Last, but not least, we will provide a graphical tool for domain experts to easily model, automatically generate code and deploy the situations to be detected and the actions to be taken in consequence. The proposal will be evaluated through a real case study related to air quality monitoring and lung diseases in collaboration with a doctor specialist on lung diseases of a public hospital