I feel it in my fingers! Sense of agency with mid-air haptics

Recent technological advances incorporate mid- air haptic feedback, enriching sensory experience during touchless virtual interactions. We investigated how this impacts the user’s sense of agency. Sense of agency refers to the feeling of controlling external events through one’s actions and has attracted growing interest from human-computer interaction researchers. This is mainly due to the fact that the user’s experience of control over a system is of primary importance. Here we measured sense of agency during a virtual button- pressing task, where the button press caused a tone outcome to occur after intervals of different durations. We explored the effect of manipulating a) mid-air haptic feedback and b) the latency of the virtual hand’s movement with respect to the actual hand movement. Sense of agency was quantified with implicit and explicit measures. Results showed that haptic feedback increased implicit sense of agency for the longest action-outcome interval length. Results also showed that latency led to a decrease in explicit sense of agency, but that this reduction was attenuated in the presence of haptic feedback. We discuss the implications of these findings, focusing on the idea that haptic feedback can be used to protect, or even increase, users’ experiences of agency in virtual interactions

Using virtual objects with hand-tracking: the effects of visual congruence and mid-air haptics on sense of agency

Virtual reality expands the possibilities of human action. With hand-tracking technology, we can directly interact with these environments without the need for a mediating controller. Much previous research has looked at the user-avatar relationship. Here we explore the avatar-object relationship by manipulating the visual congruence and haptic feedback of the virtual object of interaction. We examine the effect of these variables on the sense of agency (SoA), which refers to the feeling of control over our actions and their effects. This psychological variable is highly relevant to user experience and is attracting increased interest in the field. Our results showed that implicit SoA was not significantly affected by visual congruence and haptics. However, both of these manipulations significantly affected explicit SoA, which was strengthened by the presence of mid-air haptics and was weakened by the presence of visual incongruence. We propose an explanation of these findings that draws on the cue integration theory of SoA. We also discuss the implications of these findings for HCI research and design

Exploring the Motivations for Migration Among Engineering Students

Students often graduate from a major other than that in which they first enrolled. A large proportion of this migration happens within engineering with students moving from one discipline of engineering to another. This movement between disciplines sometimes happens several times. While there has been extensive examination of why students leave engineering,very little research has looked into why students leave one engineering discipline for another.Longitudinal data collected from several engineering colleges has shown that there are definite trends within the movement of engineering students.This study examines the reasons for some of these trends using a unique approach which combines both environmental and personality factors. The study uses measures based on Social Cognitive Career Theory, which has previously been extensively utilized to explore vocational choice in engineering, in conjunction with measures of social influence, and personality to explain disciplinary choices. In addition this study considers the climate students are exposed to in the various engineering disciplines. The intent is to create a model to connect the motivational, personality, and the climate variables in order to construct a clearer picture of how internal and external factors come together to influence students’ vocational choices; specific ally their decision to remain in engineering and to migrate from one engineering discipline to another.This study uses a survey administered electronically to engineering students beyond their sophomore year (to capture those who have had an opportunity to experience and evaluate their major choice and possibly make changes) at a large engineering program. Data collection is ongoing and will be completed within the next two months. The survey questions students about their goals, their outcome expectations, their self-efficacy beliefs, and the barriers and supports they have encountered, their differential orientation to persons or things (believed to be highly predictive of engineering attitudes), their locus of control, their agentic and communal disposition, their orientation to engineering as a social system, basic measures of personality, and their perceptions of the engineering climate in their disciplines.The survey is expected to yield personality profiles of students in various disciplines, student perceptions of the climate in various disciplines, motivation for migration among disciplines, as well as which personality and environmental factors are most strongly predictive of persistence in engineering. Structural equation modeling will be used to explore the relationships among the variables and develop a theory which would explain how these internal and external factors result in students’ choices

Primary Malignant Fibrous Histiocytoma: A Rare Case

Malignant fibrous histiocytoma (MFH) of the small intestine is an extremely rare condition. It occurs most commonly in the extremities and the trunk. We report a case of a 67-year-old woman who admitted with fever, myalgia, and altered status. After thorough investigation, a tumor of the jejunum was found. The patient underwent complete surgical removal of the tumor. A diagnosis of MFN (undifferentiated high-grade pleomorphic sarcoma) was made. The patient received adjuvant chemotherapy with Gemcitabine. Two years after the operation, the patient died due to recurrence of the disease. MFH of the small intestine is an extremely rare neoplasm with an aggressive biological behaviour. In this paper, pathogenesis, natural history, and treatment are reviewed

Machine Learning for the identification of phase-transitions in interacting agent-based systems

Deriving closed-form, analytical expressions for reduced-order models, and judiciously choosing the closures leading to them, has long been the strategy of choice for studying phase- and noise-induced transitions for agent-based models (ABMs). In this paper, we propose a data-driven framework that pinpoints phase transitions for an ABM in its mean-field limit, using a smaller number of variables than traditional closed-form models. To this end, we use the manifold learning algorithm Diffusion Maps to identify a parsimonious set of data-driven latent variables, and show that they are in one-to-one correspondence with the expected theoretical order parameter of the ABM. We then utilize a deep learning framework to obtain a conformal reparametrization of the data-driven coordinates that facilitates, in our example, the identification of a single parameter-dependent ODE in these coordinates. We identify this ODE through a residual neural network inspired by a numerical integration scheme (forward Euler). We then use the identified ODE -- enabled through an odd symmetry transformation -- to construct the bifurcation diagram exhibiting the phase transition.Comment: 14 pages, 9 Figure

Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning

We identify effective stochastic differential equations (SDE) for coarse observables of fine-grained particle- or agent-based simulations; these SDE then provide coarse surrogate models of the fine scale dynamics. We approximate the drift and diffusivity functions in these effective SDE through neural networks, which can be thought of as effective stochastic ResNets. The loss function is inspired by, and embodies, the structure of established stochastic numerical integrators (here, Euler-Maruyama and Milstein); our approximations can thus benefit from error analysis of these underlying numerical schemes. They also lend themselves naturally to "physics-informed" gray-box identification when approximate coarse models, such as mean field equations, are available. Our approach does not require long trajectories, works on scattered snapshot data, and is designed to naturally handle different time steps per snapshot. We consider both the case where the coarse collective observables are known in advance, as well as the case where they must be found in a data-driven manner.Comment: 19 pages, includes supplemental materia

Updated Field Synopsis and Systematic Meta-Analyses of Genetic Association Studies in Cutaneous Melanoma: The MelGene Database

We updated a field synopsis of genetic associations of cutaneous melanoma (CM) by systematically retrieving and combining data from all studies in the field published as of August 31, 2013. Data were available from 197 studies, which included 83,343 CM cases and 187,809 controls and reported on 1,126 polymorphisms in 289 different genes. Random-effects meta-analyses of 81 eligible polymorphisms evaluated in >4 data sets confirmed 20 single-nucleotide polymorphisms across 10 loci (TYR, AFG3L1P, CDK10, MYH7B, SLC45A2, MTAP, ATM, CLPTM1L, FTO, and CASP8) that have previously been published with genome-wide significant evidence for association (P<5 × 10−8) with CM risk, with certain variants possibly functioning as proxies of already tagged genes. Four other loci (MITF, CCND1, MX2, and PLA2G6) were also significantly associated with 5 × 10−8<P<1 × 10−3. In supplementary meta-analyses derived from genome-wide association studies, one additional locus located 11 kb upstream of ARNT (chromosome 1q21) showed genome-wide statistical significance with CM. Our approach serves as a useful model in analyzing and integrating the reported germline alterations involved in CM