20,387 research outputs found
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EEG microstates: Functional significance and short-term test-retest reliability
Appendix A: Supplementary data to this article can be found online at https://doi. org/10.1016/j.ynirp.2022.100089.Copyright /© 2022 The Authors. EEG signal power, may have clinical relevance; however, their functional significance and test-retest reliability remain unclear. To investigate the functional significance of the canonical EEG microstate classes and their pairwise transitions, and to establish their within-session test-retest reliability, we recorded 36-channel EEGs in 20 healthy volunteers during three eyes-closed conditions: mind-wandering, verbalization (silently repeating the word âsquareâ every 2 s), and visualization (visualizing a square every 2 s). Each condition lasted 3 min and the sequence of three conditions was repeated four times (two runs of two sequence repetitions). The participants' alertness and their sense of effort during the experiment were rated using visual-analogue scales. The EEG data were 2â20 Hz bandpass-filtered and analysed into the four canonical microstate classes: A, B, C, and D. EEG microstate classes C and D were persistently more dominant than classes A and B in all conditions. Of the first-order microstate parameters, average microstate duration was most reliable. The duration of class D microstate was longer during mind-wandering (106.8 ms) than verbalization (102.2 ms) or visualization (99.8 ms), with a concomitantly higher coverage (36.4% vs. 34.7% and 35.2%), but otherwise there was no clear association of the four microstate classes to particular mental states. The test-retest reliability was higher at the beginning of each run, together with higher average alpha power and subjective ratings of alertness. Only the transitions between classes C and D (from C to D in particular) were significantly higher than what would be expected from the respective microstates' occurrences. The transition probabilities, however, did not distinguish between conditions, and their test-retest reliability was overall lower than that of the first-order parameters such as duration and coverage. Further studies are needed to establish the functional significance of the canonical EEG microstate classes. This might be more fruitfully achieved by looking at their complex syntax beyond pairwise transitions. To ensure greater test-retest reliability of microstate parameters, study designs should allow for shorter experimental runs with regular breaks, particularly when using EEG microstates as clinical biomarkers.BIAL Foundation (grant number: 183/16)
The Professional Identity of Doctors who Provide Abortions: A Sociological Investigation
Abortion is a medicalised problem in England and Wales, where the law places doctors at the centre of legal provision and puts doctors in control of who has an abortion. However, the sex-selection abortion scandal of 2012 presented a very real threat to 'abortion doctors', when the medical profession's values and practices were questioned in the media, society and by Members of Parliament. Doctors found themselves at the centre of a series of claims that stated doctors were acting both illegally and unethically, driven by profit rather than patient needs. Yet, the perspectives of those doctors who provide abortions has been under-researched; this thesis aims to fill that gap by examining the beliefs and values of this group of doctors. Early chapters highlight the ambiguous position of the abortion provider in Britain, where doctors are seen as a collective group of professionals motivated by medical dominance and medical autonomy. They outline how this position is then questioned and contested, with doctors being presented as unethical. By studying abortion at the macro-, meso- and micro-levels, this thesis seeks to better understand the values of the 'abortion doctor', and how these levels shape the work and experiences of abortion providers in England and Wales. This thesis thus addresses the question: 'What do abortion doctors' accounts of their professional work suggest about the contemporary dynamics of the medicalisation of abortion in Britain?'. It investigates the research question using a qualitative methodological approach: face-to-face and telephone interviews were conducted with 47 doctors who provide abortions in England and Wales. The findings from this empirical study show how doctors' values are linked to how they view the 'normalisation of abortion'. At the macro-level doctors, openly resisted the medicalisation of abortion through the position ascribed to them by the legal framework, yet at the meso-level doctors construct an identity where normalising abortion is based on further medicalising services. Finally, at the micro-level, the ambiguous position of the abortion provider is further identified in terms of being both a proud provider and a stigmatised individual. This thesis shows that while the existing medicalisation literature has some utility, it has limited explanatory power when investigating the problem of abortion. The thesis thus provides some innovative insights into the relevance and value of medicalisation through a comprehensive study on doctors' values, beliefs and practices
Upgrading Urban Services Through BPL: Practical Applications for Smart Cities
Current initiatives related to smart cities in LATAM reveal an increasing interest in the improvement of cities and the wellbeing of their citizens. In addition, specific working groups have been created for this purpose. In this sense, the communication technologies set the basis for gathering, transporting, and managing the large amount of data generated in cities to provide a wide range of services. Within the many alternatives available, BPL positions as a promising technology, since smart cities can greatly benefit of its higher data rates and low latency. In addition, since the medium is already deployed and most of the assets and sensors are connected to the same medium, the cost of the communication systems will be reduced in price and simplicity. The work presents four practical applications: smart buildings, urban lighting, energy assets management and broadband access, in which the possibilities and advantages of BPL are further addressed. Finally, some conclusions and key aspects relating BPL to the success of smart cities are identified.Eusko Jaurlaritza IT-1234-19, KK-202
Transportation Planning, Policy, and Electric Micro-Mobilities: A Knowledge Synthesis of Recent Publications
This SSHRC-funded (Grant #972-2020-1009) scoping review synthesizes existing research (2010-2021) related to both private and shared electric micro-mobilities (i.e. e-bikes, e-scooters, e-unicycles, e-skateboards). It considers themes such as: rider demographics, usage, and motivations; mobility justice; benefits of and barriers to EMM use; safety and injuries; modal shift among forms of transportation; rider satisfaction with mode choice; environmental impact; conflict and controversy; EMM pilot programs; and EMM integration, legislation, and policy recommendations. Aside from scholarship, media reports are also included, in order to speak to the environment in which the research takes place
Coverage measurements of NB-IoT technology
Abstract. The narrowband internet of things (NB-IoT) is a cellular radio access technology that provides seamless connectivity to wireless IoT devices with low latency, low power consumption, and long-range coverage. For long-range coverage, NB-IoT offers a coverage enhancement (CE) mechanism that is achieved by repeating the transmission of signals. Good network coverage is essential to reduce the battery usage and power consumption of IoT devices, while poor network coverage increases the number of repetitions in transmission, which causes high power consumption of IoT devices. The primary objective of this work is to determine the network coverage of NB-IoT technology under the University of Ouluâs 5G test network (5GTN) base station. In this thesis work, measurement results on key performance indicators such as reference signal received power (RSRP), reference signal received quality (RSRQ), received signal strength indicator (RSSI), and signal to noise plus interference (SINR) have been reported. The goal of the measurement is to find out the NB-IoT signal strength at different locations, which are served by the 5GTN cells configured with different parameters, e.g., Tx power levels, antenna tilt angles.
The signal strength of NB-IoT technology has been measured at different places under the 5GTN base station in Oulu, Finland. Drive tests have been conducted to measure the signal strength of NB-IoT technology by using the Quectel BG96 module, Qualcomm kDC-5737 dongle and Keysight Nemo Outdoor software. The results have shown the values of RSRP, RSRQ, RSSI, and SINR at different locations within several kilometres of the 5GTN base stations. These values indicate the performance of the network and are used to assess the performance of network services to the end-users.
In this work, the overall performance of the network has been checked to verify if network performance meets good signal levels and good network coverage. Relevant details of the NB-IoT technology, the theory behind the signal coverage and comparisons with the measurement results have also been discussed to check the relevance of the measurement results
Prospective life cycle assessment of hydrogen production by waste photoreforming
Identifying sustainable energy vectors is perhaps one of the most critical issues that needs addressing to achieve a climate-neutral society by 2050. In this context, the hydrogen economy has been proposed as a solution to mitigate our current fossil-based energy system while the concept of the circular economy aims to boost the efficient use of resources. Photoreforming offers a promising opportunity for recycling and transforming widely available biomass-derived wastes (e.g., crude glycerol from biodiesel) into clean hydrogen fuel. This processing technology may be a versatile method that can be performed not only under UV light but also under visible light. However, this approach is currently at the lab-scale and some inherent challenges must be overcome, not least the relatively modest hydrogen production rates for the lamps? substantial energy consumption. This study aims to assess the main environmental impacts, identifying the hotspots and possible trade-off in which this technology could operate feasibly. We introduce an assessment of the windows of opportunity using seven categories of environmental impact with either artificial light or sunlight as the source of photocatalytic conversion. We compared the environmental indicators from this study with those of the benchmark water electrolysis and steam?methane reforming (SMR) technologies, which are currently operating at a commercial scale. The results obtained in this study situate biowaste photoreforming within the portfolio of sustainable H2 production technologies of interest for future development in terms of target H2 production rates and lifetimes of sustainable operation.Financial support from projects RTI2018-099407-B-I00 and RTI2018-099407-B-I00 funded by MCIN/AEI/10.13039/501100011033/FEDER and by âERDF A way of making Europeâ by the âEuropean Unionâ is gratefully acknowledged. We would like also to thank MICIN for providing Marta Rumayor with a Juan de la Cierva postdoctoral contract IJCI-2017-32621
Structure and adsorption properties of gas-ionic liquid interfaces
Supported ionic liquids are a diverse class of materials that have been considered
as a promising approach to design new surface properties within solids for gas
adsorption and separation applications. In these materials, the surface morphology and
composition of a porous solid are modified by depositing ionic liquid. The resulting
materials exhibit a unique combination of structural and gas adsorption properties
arising from both components, the support, and the liquid. Naturally, theoretical and
experimental studies devoted to understanding the underlying principles of exhibited
interfacial properties have been an intense area of research. However, a complete
understanding of the interplay between interfacial gas-liquid and liquid-solid
interactions as well as molecular details of these processes remains elusive.
The proposed problem is challenging and in this thesis, it is approached from
two different perspectives applying computational and experimental techniques. In
particular, molecular dynamics simulations are used to model gas adsorption in films
of ionic liquids on a molecular level. A detailed description of the modeled systems is
possible if the interfacial and bulk properties of ionic liquid films are separated. In this
study, we use a unique method that recognizes the interfacial and bulk structures of
ionic liquids and distinguishes gas adsorption from gas solubility. By combining
classical nitrogen sorption experiments with a mean-field theory, we study how liquid-solid interactions influence the adsorption of ionic liquids on the surface of the porous
support.
The developed approach was applied to a range of ionic liquids that feature
different interaction behavior with gas and porous support. Using molecular
simulations with interfacial analysis, it was discovered that gas adsorption capacity
can be directly related to gas solubility data, allowing the development of a predictive
model for the gas adsorption performance of ionic liquid films. Furthermore, it was
found that this CO2 adsorption on the surface of ionic liquid films is determined by the
specific arrangement of cations and anions on the surface. A particularly important
result is that, for the first time, a quantitative relation between these structural and
adsorption properties of different ionic liquid films has been established. This link
between two types of properties determines design principles for supported ionic
liquids.
However, the proposed predictive model and design principles rely on the
assumption that the ionic liquid is uniformly distributed on the surface of the porous
support. To test how ionic liquids behave under confinement, nitrogen physisorption
experiments were conducted for microâ and mesopore analysis of supported ionic
liquid materials. In conjunction with mean-field density functional theory applied to
the lattice gas and pore models, we revealed different scenarios for the pore-filling
mechanism depending on the strength of the liquid-solid interactions.
In this thesis, a combination of computational and experimental studies provides
a framework for the characterization of complex interfacial gas-liquid and liquid-solid
processes. It is shown that interfacial analysis is a powerful tool for studying
molecular-level interactions between different phases. Finally, nitrogen sorption
experiments were effectively used to obtain information on the structure of supported
ionic liquids
How to Be a God
When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers.
Philosophers have the answers that canât be proven right. Theologians have the answers that canât be proven wrong.
Todayâs designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They canât spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice.
Thatâs todayâs designers. Tomorrowâs will have a whole new set of questions to answer.
The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves?
How should we be gods
Innovation systemsâ response to changes in the institutional impulse: Analysis of the evolution of the European energy innovation system from FP7 to H2020
This study addresses how the institutional impulse developed by the European Union influenced the evolution of the European energy innovation system. Considering the contributing role of innovation systems in the development of new knowledge and technology, it can be stated that the institutional impulse achieved by the European Union through the research framework programmes creates a network of relations between entities and projects. This enables the exchange of information and expertise, which is considered a key element for innovation development. Previous studies have attempted to determine whether institutional impulse is an essential element in understanding the efficiency of innovation systems and their related research policies. However, their investigations have yielded inconclusive results. Using the CORDIS database of the European Commission, this study aims to fill this gap by assessing the European energy innovation system for two periods (2007â2013 and 2014â2020) through two of its research funding programmesâFP7 and H2020âthereby contributing to the literature in the innovation systems field. Social network analysis has been conducted to examine how changes in the institutional impulse, reflected in the new objectives in the research funding programmes, are associated with changes in the structural and topological properties of the innovation systemsâ underlying networks. The first contribution indicates that the innovation system responds to changes in the goals of funding programmes, as the taxonomy, topology, and structural properties of their underlying networks underwent modifications due to the newly proposed objectives. The second contribution shows that network properties (cohesion and centrality metrics) can explain the efficiency and effectiveness of innovation systems, drawing useful conclusions for policymakers and individual entities. This last contribution also has important policymaking implications, as it provides the basis for understanding how innovation policy goals can be achieved by changing the institutional impulse to direct the innovation system towards these objectives
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Reliable Decision-Making with Imprecise Models
The rapid growth in the deployment of autonomous systems across various sectors has generated considerable interest in how these systems can operate reliably in large, stochastic, and unstructured environments. Despite recent advances in artificial intelligence and machine learning, it is challenging to assure that autonomous systems will operate reliably in the open world. One of the causes of unreliable behavior is the impreciseness of the model used for decision-making. Due to the practical challenges in data collection and precise model specification, autonomous systems often operate based on models that do not represent all the details in the environment. Even if the system has access to a comprehensive decision-making model that accounts for all the details in the environment and all possible scenarios the agent may encounter, it may be intractable to solve this complex model optimally. Consequently, this complex, high fidelity model may be simplified to accelerate planning, introducing imprecision. Reasoning with such imprecise models affects the reliability of autonomous systems. A system\u27s actions may sometimes produce unexpected, undesirable consequences, which are often identified after deployment. How can we design autonomous systems that can operate reliably in the presence of uncertainty and model imprecision?
This dissertation presents solutions to address three classes of model imprecision in a Markov decision process, along with an analysis of the conditions under which bounded-performance can be guaranteed. First, an adaptive outcome selection approach is introduced to devise risk-aware reduced models of the environment that efficiently balance the trade-off between model simplicity and fidelity, to accelerate planning in resource-constrained settings. Second, a framework that extends stochastic shortest path framework to problems with imperfect information about the goal state during planning is introduced, along with two solution approaches to solve this problem. Finally, two complementary solution approaches are presented to minimize the negative side effects of agent actions. The techniques presented in this dissertation enable an autonomous system to detect and mitigate undesirable behavior, without redesigning the model entirely
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