ResearchPad - computer-architecture https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Fear and stock price bubbles]]> https://www.researchpad.co/article/elastic_article_13818 I evaluate Alan Greenspan’s claim that stock price bubbles build up in periods of euphoria and tend to burst due to increasing fear. Indeed, there is evidence that e.g. during a crisis, triggered by increasing fear, both qualitative and quantitative measures of risk aversion increase substantially. It is argued that fear is a potential mechanism underlying financial decisions and drives the countercyclical risk aversion. Inspired by this evidence, I construct an euphoria/fear index, which is based on an economic model of time varying risk aversion. Based on US industry returns 1959–2014, my findings suggest that (1) Greenspan is correct in that the price run-up initially occurs in periods of euphoria followed by a crash due to increasing fear; (2) on average already roughly a year before an industry is crashing, euphoria is turning into fear, while the market is still bullish; (3) there is no particular euphoria-fear-pattern for price-runs in industries that do not subsequently crash. I interpret the evidence in favor of Greenspan, who was labeled “Mr. Bubble” by the New York Times, and who was accused to be a serial bubble blower.

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<![CDATA[Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts]]> https://www.researchpad.co/article/N836ce8d9-e17d-43c0-9509-c554011a4818

Open source hardware for scientific equipment needs to provide source files and enough documentation to allow the study, replication and modification of the design. In addition, parametric modeling is encouraged in order to facilitate customization for other experiments. Parametric design using a solid modeling programming language allows customization and provides a source file for the design. OpenSCAD is the most widely used scripting tool for parametric modeling of open source labware. However, OpenSCAD lacks the ability to export to standard parametric formats; thus, the parametric dimensional information of the model is lost. This is an important deficiency because it is key to share the design in the most accessible formats with no information loss. In this work we analyze OpenSCAD and compare it with FreeCAD Python scripts. We have created a parametric open source hardware design to compare these tools. Our findings show that although Python for FreeCAD is more arduous to learn, its advantages counterbalance the initial difficulties. The main benefits are being able to export to standard parametric models; using Python language with its libraries; and the ability to use and integrate the models in its graphical interface. Thus, making it more appropriate to design open source hardware for scientific equipment.

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<![CDATA[A deadline constrained scheduling algorithm for cloud computing system based on the driver of dynamic essential path]]> https://www.researchpad.co/article/5c8c195bd5eed0c484b4d4af

To solve the problem of the deadline-constrained task scheduling in the cloud computing system, this paper proposes a deadline-constrained scheduling algorithm for cloud computing based on the driver of dynamic essential path (Deadline-DDEP). According to the changes of the dynamic essential path of each task node in the scheduling process, the dynamic sub-deadline strategy is proposed. The strategy assigns different sub-deadline values to every task node to meet the constraint relations among task nodes and the user’s defined deadline. The strategy fully considers the dynamic sub-deadline affected by the dynamic essential path of task node in the scheduling process. The paper proposed the quality assessment of optimization cost strategy to solve the problem of selecting server for each task node. Based on the sub-deadline urgency and the relative execution cost in the scheduling process, the strategy selects the server that not only meets the sub-deadline but also obtains much lower execution cost. In this way, the proposed algorithm will make the task graph complete within its deadline, and minimize its total execution cost. Finally, we demonstrate the proposed algorithm via the simulation experiments using Matlab tools. The experimental results show that, the proposed algorithm produces remarkable performance improvement rate on the total execution cost that ranges between 10.3% and 30.8% under meeting the deadline constraint. In view of the experimental results, the proposed algorithm provides better-quality scheduling solution that is suitable for scientific application task execution in the cloud computing environment than IC-PCP, DCCP and CD-PCP.

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<![CDATA[SimKinet: A free educational tool based on an electrical analogy to solve chemical kinetic equations]]> https://www.researchpad.co/article/5c8c1982d5eed0c484b4d822

In this article we introduce the software SimKinet, a free tool specifically designed to solve systems of differential equations without any programming skill. The underlying method is the so-called Network Simulation Method, which designs and solves an electrical network equivalent to the mathematical problem. SimKinet is versatile, fast, presenting a real user-friendly interface, and can be employed for both educational and researching purposes. It is particularly useful in the first courses of different scientific degrees, mainly Chemistry and Physics, especially when facing non-analytic or complex-dynamics problems. Moreover, SimKinet would help students to understand fundamental concepts, being an opportunity to improve instruction in Chemistry, Mathematics, Physics and other Sciences courses, with no need of advanced knowledge in differential equations. The potency of SimKinet is demonstrated via two applications in chemical kinetics: the photochemical destruction of stratospheric ozone and the chaotic dynamics of the peroxidase-oxidase reaction.

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<![CDATA[A low-cost, autonomous mobile platform for limnological investigations, supported by high-resolution mesoscale airborne imagery]]> https://www.researchpad.co/article/5c6f1526d5eed0c48467ae54

Two complementary measurement systems—built upon an autonomous floating craft and a tethered balloon—for lake research and monitoring are presented. The autonomous vehicle was assembled on a catamaran for stability, and is capable of handling a variety of instrumentation for in situ and near-surface measurements. The catamaran hulls, each equipped with a small electric motor, support rigid decks for arranging equipment. An electric generator provides full autonomy for about 8 h. The modular power supply and instrumentation data management systems are housed in two boxes, which enable rapid setup. Due to legal restrictions in Switzerland (where the craft is routinely used), the platform must be observed from an accompanying boat while in operation. Nevertheless, the control system permits fully autonomous operation, with motion controlled by speed settings and waypoints, as well as obstacle detection. On-board instrumentation is connected to a central hub for data storage, with real-time monitoring of measurements from the accompanying boat. Measurements from the floating platform are complemented by mesoscale imaging from an instrument package attached to a He-filled balloon. The aerial package records thermal and RGB imagery, and transmits it in real-time to a ground station. The balloon can be tethered to the autonomous catamaran or to the accompanying boat. Missions can be modified according to imagery and/or catamaran measurements. Illustrative results showing the surface thermal variations of Lake Geneva demonstrate the versatility of the combined floating platform/balloon imagery system setup for limnological investigations.

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<![CDATA[Context-explorer: Analysis of spatially organized protein expression in high-throughput screens]]> https://www.researchpad.co/article/5c366800d5eed0c4841a6d01

A growing body of evidence highlights the importance of the cellular microenvironment as a regulator of phenotypic and functional cellular responses to perturbations. We have previously developed cell patterning techniques to control population context parameters, and here we demonstrate context-explorer (CE), a software tool to improve investigation cell fate acquisitions through community level analyses. We demonstrate the capabilities of CE in the analysis of human and mouse pluripotent stem cells (hPSCs, mPSCs) patterned in colonies of defined geometries in multi-well plates. CE employs a density-based clustering algorithm to identify cell colonies. Using this automatic colony classification methodology, we reach accuracies comparable to manual colony counts in a fraction of the time, both in micropatterned and unpatterned wells. Classifying cells according to their relative position within a colony enables statistical analysis of spatial organization in protein expression within colonies. When applied to colonies of hPSCs, our analysis reveals a radial gradient in the expression of the transcription factors SOX2 and OCT4. We extend these analyses to colonies of different sizes and shapes and demonstrate how the metrics derived by CE can be used to asses the patterning fidelity of micropatterned plates. We have incorporated a number of features to enhance the usability and utility of CE. To appeal to a broad scientific community, all of the software’s functionality is accessible from a graphical user interface, and convenience functions for several common data operations are included. CE is compatible with existing image analysis programs such as CellProfiler and extends the analytical capabilities already provided by these tools. Taken together, CE facilitates investigation of spatially heterogeneous cell populations for fundamental research and drug development validation programs.

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<![CDATA[Engineering vasculature: Architectural effects on microcapillary-like structure self-assembly]]> https://www.researchpad.co/article/5c3e4faed5eed0c484d78005

One of the greatest obstacles to clinical translation of bone tissue engineering is the inability to effectively and efficiently vascularize scaffolds. The goal of this work was to explore systematically whether architecture, at a scale of hundreds of microns, can be used to direct the growth of microcapillary-like structures into the core of scaffolds. Biphasic bioceramic patterned architectures were produced using silicone molds of 3D printed parts. Grooves and ridges were designed to have widths of 330 μm and 660 μm, with periodicities respectively of 1240 μm and 630 μm. Groove depth was varied between 150 μm and 585 μm. Co-cultures of human dermal microvascular endothelial cells (HDMECs) and human osteoblasts (hOBs) were used to grow microcapillary-like structures on substrates. Bioceramic architecture was found to significantly affect microcapillary-like structure location and orientation. Microcapillary-like structures were found to form predominantly in grooves or between convexities. For all patterned samples, the CD31 (endothelial cell marker) signal was at least 2.5 times higher along grooves versus perpendicular to grooves. In addition, the average signal was at least two times higher within grooves than outside grooves for all samples. Grooves with a width of 330 μm and a depth of 300 μm resulted in the formation of individual, highly aligned microcapillary-like structures with lengths around 5 mm. Extensive literature has focused on the role of nano- and micro-topography (on the scale below tens of microns) on cellular response. However, the idea that architecture at a scale much larger than a cell could be used to modulate angiogenesis has not been systematically investigated. This work shows the crucial influence of architecture on microcapillary-like structure self-assembly at the scale of hundreds of microns. Elucidating the precise correspondence between architecture and microcapillary-like structure organization will ultimately allow the engineering of microvasculature by tuning local scaffold design to achieve desirable microvessel properties.

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<![CDATA[Remote access protocols for Desktop-as-a-Service solutions]]> https://www.researchpad.co/article/5c390ba8d5eed0c48491db6c

The use of remote desktop services on virtualized machines is a general trend to reduce the cost of desktop seats. Instead of assigning a physical machine with its operating system and software to each user, it is considerably easier to manage a light client machine that connects to a server where the instance of the user’s desktop machine actually executes. Citrix and VMware have been major suppliers of these systems in private clouds. Desktop-as-a-Service solutions such as Amazon WorkSpaces offer a similar functionality, yet in a public cloud environment. In this paper, we review the main offerings of remote desktop protocols for a cloud deployment. We evaluate the necessary network resources using a traffic model based on self-similar processes. We also evaluate the quality of experience perceived by the user, in terms of image quality and interactivity, providing values of Mean Opinion Score (MOS). The results confirm that the type of application running on the remote servers and the mix of users must be considered to determine the bandwidth requirements. Applications such as web browsing result in unexpectedly high traffic rates and long bursts, more than the case of desktop video playing, because the on-page animations are rendered on the server.

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<![CDATA[Body ownership increases the interference between observed and executed movements]]> https://www.researchpad.co/article/5c37b79bd5eed0c48449062f

When we successfully achieve willed actions, the feeling that our moving body parts belong to the self (i.e., body ownership) is barely required. However, how and to what extent the awareness of our own body contributes to the neurocognitive processes subserving actions is still debated. Here we capitalized on immersive virtual reality in order to examine whether and how body ownership influences motor performance (and, secondly, if it modulates the feeling of voluntariness). Healthy participants saw a virtual body either from a first or a third person perspective. In both conditions, they had to draw continuously straight vertical lines while seeing the virtual arm doing the same action (i.e., drawing lines) or deviating from them (i.e., drawing ellipses). Results showed that when there was a mismatch between the intended and the seen movements (i.e., participants had to draw lines but the avatar drew ellipses), motor performance was strongly “attracted” towards the seen (rather than the performed) movement when the avatar’s body part was perceived as own (i.e., first person perspective). In support of previous studies, here we provide direct behavioral evidence that the feeling of body ownership modulates the interference of seen movements to the performed movements.

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<![CDATA[Towards a conceptual model for the use of home healthcare medical devices: The multi-parameter monitor case]]> https://www.researchpad.co/article/5c141e93d5eed0c484d2740f

In the last decade there has been an increase in the use of medical devices in the home environment. These devices are commonly the same as those used in hospitals by healthcare professionals. The use of these these devices by lay users outside of a clinical environment may become unsafe. This study presents a methodology that allows decision makers to identify potential risk situations that may arise when lay users operate healthcare medical devices at home. Through a usability study based on the Grounded Theory methodology, we create a conceptual model in which we identified problems and errors related to the use of a multi-parameter monitor in a home environment by a group of lay users. The conceptual model is reified as a graphical representation, which allows stakeholders to identify (i) the weaknesses of the device, (ii) unsafe operation modes, and (iii) the most suitable device for a specific user.

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<![CDATA[Experiences of treadmill walking with non-immersive virtual reality after stroke or acquired brain injury – A qualitative study]]> https://www.researchpad.co/article/5c1d5b9dd5eed0c4846ec232

Objectives

It is well known that physical activity levels for persons after stroke or acquired brain injuries do not reach existing recommendations. Walking training is highly important since the ability to walk is considered to be a meaningful occupation for most people, and is often reduced after a brain injury. This suggests a need to innovate stroke rehabilitation, so that forms of walking training that are user-friendly and enjoyable can be provided.

Method

An interview study was carried out with persons after stroke (n = 8), or acquired brain injury (n = 2) at a rehabilitation unit at Sahlgrenska University Hospital. We used a semi-structured interview guide to investigate experiences and thoughts about walking on a treadmill with non-immersive virtual reality feedback. The contents were analyzed through an inductive approach, using qualitative content analysis.

Results

The virtual reality experience was perceived as enjoyable, exciting, and challenging. Participants stressed that the visual and auditory feedback increased their motivation to walk on a treadmill. However, for some participants, the virtual reality experience was too challenging, and extreme tiredness or fatigue were reported after the walking session.

Conclusions

Participants’ thoughts and experiences indicated that the Virtual Reality walking system could serve as a complement to more traditional forms of walking training. Early after a brain injury, virtual reality could be a way to train the ability to handle individually adapted multisensory input while walking. Obvious benefits were that participants perceived it as engaging and exciting.

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<![CDATA[Validating quantum-classical programming models with tensor network simulations]]> https://www.researchpad.co/article/5c1813c3d5eed0c484775c05

The exploration of hybrid quantum-classical algorithms and programming models on noisy near-term quantum hardware has begun. As hybrid programs scale towards classical intractability, validation and benchmarking are critical to understanding the utility of the hybrid computational model. In this paper, we demonstrate a newly developed quantum circuit simulator based on tensor network theory that enables intermediate-scale verification and validation of hybrid quantum-classical computing frameworks and programming models. We present our tensor-network quantum virtual machine (TNQVM) simulator which stores a multi-qubit wavefunction in a compressed (factorized) form as a matrix product state, thus enabling single-node simulations of larger qubit registers, as compared to brute-force state-vector simulators. Our simulator is designed to be extensible in both the tensor network form and the classical hardware used to run the simulation (multicore, GPU, distributed). The extensibility of the TNQVM simulator with respect to the simulation hardware type is achieved via a pluggable interface for different numerical backends (e.g., ITensor and ExaTENSOR numerical libraries). We demonstrate the utility of our TNQVM quantum circuit simulator through the verification of randomized quantum circuits and the variational quantum eigensolver algorithm, both expressed within the eXtreme-scale ACCelerator (XACC) programming model.

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<![CDATA[qTorch: The quantum tensor contraction handler]]> https://www.researchpad.co/article/5c181399d5eed0c48477553c

Classical simulation of quantum computation is necessary for studying the numerical behavior of quantum algorithms, as there does not yet exist a large viable quantum computer on which to perform numerical tests. Tensor network (TN) contraction is an algorithmic method that can efficiently simulate some quantum circuits, often greatly reducing the computational cost over methods that simulate the full Hilbert space. In this study we implement a tensor network contraction program for simulating quantum circuits using multi-core compute nodes. We show simulation results for the Max-Cut problem on 3- through 7-regular graphs using the quantum approximate optimization algorithm (QAOA), successfully simulating up to 100 qubits. We test two different methods for generating the ordering of tensor index contractions: one is based on the tree decomposition of the line graph, while the other generates ordering using a straight-forward stochastic scheme. Through studying instances of QAOA circuits, we show the expected result that as the treewidth of the quantum circuit’s line graph decreases, TN contraction becomes significantly more efficient than simulating the whole Hilbert space. The results in this work suggest that tensor contraction methods are superior only when simulating Max-Cut/QAOA with graphs of regularities approximately five and below. Insight into this point of equal computational cost helps one determine which simulation method will be more efficient for a given quantum circuit. The stochastic contraction method outperforms the line graph based method only when the time to calculate a reasonable tree decomposition is prohibitively expensive. Finally, we release our software package, qTorch (Quantum TensOR Contraction Handler), intended for general quantum circuit simulation. For a nontrivial subset of these quantum circuits, 50 to 100 qubits can easily be simulated on a single compute node.

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<![CDATA[Modulation of tactile perception by Virtual Reality distraction: The role of individual and VR-related factors]]> https://www.researchpad.co/article/5c0ed772d5eed0c484f14165

Background

Virtual reality (VR) has shown to be an effective distraction method in health care. However, questions remain regarding individual and VR-related factors that may modulate the effect of VR.

Purpose

To explore the effect of VR distraction on tactile perception thresholds in healthy volunteers, in relation to personal characteristics and interactivity of VR applications.

Methods

A randomized three way cross-over study was conducted to investigate the effects of active and passive VR applications in 50 healthy participants. Main outcome measures were monofilament detection thresholds (MDT) and electrical detection thresholds (EDT). Personal characteristics (e.g. age, gender, susceptibility for immersion) and immersion in the VR conditions were analyzed for their effect on VR induced threshold differences.

Results

The use of VR caused a significant increase in both MDT and EDT compared to the control condition (MDT: F (2, 76) = 20.174, p < 0.001; EDT F (2, 76) = 6.907, p = 0.002). Furthermore, a significant difference in favour of active VR compared to passive VR was found in MDT (p = 0.012), but not in EDT. No significant gender effect was found. There was a significant positive correlation between age and active VR distraction (r = 0.333, p = 0.018). Immersion in the VR world was positively correlated with the effect of VR, whereas visualization and daydreaming were negatively correlated with VR effects.

Conclusion

VR increased tactile perception thresholds, with active VR having the largest effect. Results indicate that the efficacy of VR may increase with increasing age. Gender did not affect VR susceptibility.

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<![CDATA[A deep learning model for the detection of both advanced and early glaucoma using fundus photography]]> https://www.researchpad.co/article/5c06f04ed5eed0c484c6d678

Purpose

To build a deep learning model to diagnose glaucoma using fundus photography.

Design

Cross sectional case study Subjects, Participants and Controls: A total of 1,542 photos (786 normal controls, 467 advanced glaucoma and 289 early glaucoma patients) were obtained by fundus photography.

Method

The whole dataset of 1,542 images were split into 754 training, 324 validation and 464 test datasets. These datasets were used to construct simple logistic classification and convolutional neural network using Tensorflow. The same datasets were used to fine tune pre-trained GoogleNet Inception v3 model.

Results

The simple logistic classification model showed a training accuracy of 82.9%, validation accuracy of 79.9% and test accuracy of 77.2%. Convolutional neural network achieved accuracy and area under the receiver operating characteristic curve (AUROC) of 92.2% and 0.98 on the training data, 88.6% and 0.95 on the validation data, and 87.9% and 0.94 on the test data. Transfer-learned GoogleNet Inception v3 model achieved accuracy and AUROC of 99.7% and 0.99 on training data, 87.7% and 0.95 on validation data, and 84.5% and 0.93 on test data.

Conclusion

Both advanced and early glaucoma could be correctly detected via machine learning, using only fundus photographs. Our new model that is trained using convolutional neural network is more efficient for the diagnosis of early glaucoma than previously published models.

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<![CDATA[Walking along the road with anonymous users in similar attributes]]> https://www.researchpad.co/article/5b6dda11463d7e7491b405ea

Recently, the ubiquitousness of smartphones and tablet computers have changed the style of people’s daily life. With this tendency, location based service (LBS) has become one of the prosperous types of service along with the wireless and positioning technology development. However, as the LBS server needs precise location information about the user to provide service result, the procedure of LBS may reveal location privacy, especially when a user is utilizing continuous query along the road. In continuous query, attributes of the user are released inadvertently with per-query, and the information can be collected by an adversary as background knowledge to correlate the location trajectory and infer the personal privacy. Although, a user can employ a central server (CS) to provide privacy preservation for his location, the trustfulness of CS still is without testified and it is usually considered as an un-trusted entity. Thus, in this paper, the trustfulness of CS is verified by a game tree, and then with the result we propose a hash based attribute anonymous scheme (short for HBAA) to obfuscate the attributes released in each query along the road. With the help of HBAA, the CS has no opportunity to get any information about the user who sends his query for generalization service. Furthermore, as the set of attributes is transmitted into a fixed length of hash value, the processing time that spent in attribute generalization is stripped down and the performance of executive efficiency is improved. At last, security analysis and simulation experiment are proposed, and then results of security proving as well as simulation experiments further reflect the superiority of our proposed scheme.

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<![CDATA[A Parallel Distributed-Memory Particle Method Enables Acquisition-Rate Segmentation of Large Fluorescence Microscopy Images]]> https://www.researchpad.co/article/5989da1bab0ee8fa60b7cfb0

Modern fluorescence microscopy modalities, such as light-sheet microscopy, are capable of acquiring large three-dimensional images at high data rate. This creates a bottleneck in computational processing and analysis of the acquired images, as the rate of acquisition outpaces the speed of processing. Moreover, images can be so large that they do not fit the main memory of a single computer. We address both issues by developing a distributed parallel algorithm for segmentation of large fluorescence microscopy images. The method is based on the versatile Discrete Region Competition algorithm, which has previously proven useful in microscopy image segmentation. The present distributed implementation decomposes the input image into smaller sub-images that are distributed across multiple computers. Using network communication, the computers orchestrate the collectively solving of the global segmentation problem. This not only enables segmentation of large images (we test images of up to 1010 pixels), but also accelerates segmentation to match the time scale of image acquisition. Such acquisition-rate image segmentation is a prerequisite for the smart microscopes of the future and enables online data compression and interactive experiments.

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<![CDATA[VennPainter: A Tool for the Comparison and Identification of Candidate Genes Based on Venn Diagrams]]> https://www.researchpad.co/article/5989d9dbab0ee8fa60b679a8

VennPainter is a program for depicting unique and shared sets of genes lists and generating Venn diagrams, by using the Qt C++ framework. The software produces Classic Venn, Edwards’ Venn and Nested Venn diagrams and allows for eight sets in a graph mode and 31 sets in data processing mode only. In comparison, previous programs produce Classic Venn and Edwards’ Venn diagrams and allow for a maximum of six sets. The software incorporates user-friendly features and works in Windows, Linux and Mac OS. Its graphical interface does not require a user to have programing skills. Users can modify diagram content for up to eight datasets because of the Scalable Vector Graphics output. VennPainter can provide output results in vertical, horizontal and matrix formats, which facilitates sharing datasets as required for further identification of candidate genes. Users can obtain gene lists from shared sets by clicking the numbers on the diagram. Thus, VennPainter is an easy-to-use, highly efficient, cross-platform and powerful program that provides a more comprehensive tool for identifying candidate genes and visualizing the relationships among genes or gene families in comparative analysis.

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<![CDATA[A high-speed brain-computer interface (BCI) using dry EEG electrodes]]> https://www.researchpad.co/article/5989db4fab0ee8fa60bdbaa5

Recently, brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs) have been shown to achieve remarkable communication speeds. As they use electroencephalography (EEG) as non-invasive method for recording neural signals, the application of gel-based EEG is time-consuming and cumbersome. In order to achieve a more user-friendly system, this work explores the usability of dry EEG electrodes with a VEP-based BCI. While the results show a high variability between subjects, they also show that communication speeds of more than 100 bit/min are possible using dry EEG electrodes. To reduce performance variability and deal with the lower signal-to-noise ratio of the dry EEG electrodes, an averaging method and a dynamic stopping method were introduced to the BCI system. Those changes were shown to improve performance significantly, leading to an average classification accuracy of 76% with an average communication speed of 46 bit/min, which is equivalent to a writing speed of 8.8 error-free letters per minute. Although the BCI system works substantially better with gel-based EEG, dry EEG electrodes are more user-friendly and still allow high-speed BCI communication.

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<![CDATA[Virtual Morality: Transitioning from Moral Judgment to Moral Action?]]> https://www.researchpad.co/article/5989dac1ab0ee8fa60bb0c7e

The nature of moral action versus moral judgment has been extensively debated in numerous disciplines. We introduce Virtual Reality (VR) moral paradigms examining the action individuals take in a high emotionally arousing, direct action-focused, moral scenario. In two studies involving qualitatively different populations, we found a greater endorsement of utilitarian responses–killing one in order to save many others–when action was required in moral virtual dilemmas compared to their judgment counterparts. Heart rate in virtual moral dilemmas was significantly increased when compared to both judgment counterparts and control virtual tasks. Our research suggests that moral action may be viewed as an independent construct to moral judgment, with VR methods delivering new prospects for investigating and assessing moral behaviour.

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