The Applicability of Augmented Reality Technologies for Evaluating Learning Activities

a new trend in the development of immersive technologies has become augmented reality (AR), which is in demand due to its property to implement visual objects to enrich the learning content. The paper is devoted to the study of the applicability of AR technologies for evaluating learning activi-ties since there is a problem of inconsistency of teaching approaches with tools that lead to biased results. This led to the development of the “AR Quiz” application that contains interaction types such as touch-based, voice, input field, gaze and gesture that stimulate activities. In combination with 10 other forms of assessment materials, its application field has expanded and the tasks for students have diversified. The present study provides the calculation of validity and reliability coefficients of the assessment materials contained in the “AR Quiz” application that reflects the suitability of indicators for the purpose, accuracy and stability of measurements. The paper reveals positive attitudes of expert teachers and students towards the use of AR when evaluating learning activities. Along with integration map of compliance of AR interaction types with assessment materials, the paper provides recommendations for teachers on evaluating learning activities based on AR.

Eternally non-Markovian dynamics of a qubit interacting with a single-photon wavepacket

An evolution of a two-level system (qubit) interacting with a single-photon wave packet is analyzed. It is shown that a hierarchy of master equations gives rise to phase covariant qubit evolution. The temporal correlations in the input field induce nontrivial memory effects for the evolution of a qubit. It is shown that in the resonant case whenever time-local generator is regular (does not display singularities) the qubit evolution never displays information backflow. However, in general the generator might be highly singular leading to intricate non-Markovian effects. A detailed analysis of the exponential profile is provided which allows to illustrate all characteristic feature of the qubit evolution.

Virtual mapping and analytical data integration: a teaching module using Precambrian crystalline basement in Colorado's Front Range (USA)

The COVID-19 pandemic hindered the ability to conduct field geology courses in a hands-on and boots-on traditional manner. In response, we designed a multi-part virtual field module that encompasses many of the basic requirements of an advanced field exercise, including designing a mapping strategy, collecting and processing field observations, synthesizing data from field-based and laboratory analyses, and communicating the results to a broad audience. For the mapping exercise, which is set in deformed Proterozoic crystalline basement exposed in the Front Range of Colorado (USA), student groups make daily navigational decisions and choose stations based on topographic maps, Google Earth satellite imagery, and iterative geological reasoning. For each station, students receive outcrop descriptions, measurements, and photographs from which they input field data and create geologic maps using StraboSpot. Building on the mapping exercise, student groups then choose from six supplements, including advanced field structure, microstructure, metamorphic petrology, and several geochronological datasets. Because scientific projects rarely end when the mapping is complete, the students are challenged to see how samples and analytical data may commonly be collected and integrated with field observations to produce a more holistic understanding of the geological history of the field area. While a virtual course cannot replace the actual field experience, modules like the one shared here can successfully address, or even improve on, some of the key learning objectives that are common to field-based capstone experiences while also fostering a more accessible and inclusive learning environment for all students.

Synthetic plasmonic lattice formation through invariant frequency comb excitation in graphene structures

Nonlinear surface-plasmon polaritons (NSPPs) in nanophotonic waveguides excite with dissimilar temporal properties due to input field modifications and material characteristics, but they possess similar nonlinear spectral evolution. In this work, we uncover the origin of this similarity and establish that the spectral dynamics is an inherent property of the system that depends on the synthetic dimension and is beyond waveguide geometrical dimensionality. To this aim, we design an ultralow loss nonlinear plasmonic waveguide, to establish the invariance of the surface plasmonic frequency combs (FCs) and phase singularities for plasmonic peregrine waves and Akhmediev breather. By finely tuning the nonlinear coefficient of the interaction interface, we uncover the conservation conditions through this plasmonic system and use the mean-value evolution of the quantum NSPP field commensurate with the Schrödinger equation to evaluate spectral dynamics of the plasmonic FCs (PFCs). Through providing suppressed interface losses and modified nonlinearity as dual requirements for conservative conditions, we propose exciting PFCs as equally spaced invariant quantities of this plasmonic scheme and prove that the spectral dynamics of the NSPPs within the interaction interface yields the formation of plasmonic analog of the synthetic photonic lattice, which we termed synthetic plasmonic lattice (SPL).

Four-level double V-type atomic system solved by virtue of supersymmetric unitary transformation

We consider a four-level double V-type atom with two closely-separated top levels and two closely-separated lower levels interacting with a single mode field via multi-photon processes and in the presence of Kerr medium. We show that this atomic system possesses supersymmetric structure and construct its supersymmetric generators. We diagonalize the Hamiltonian of this system using supersymmetric unitary transformation and obtain the corresponding eigenstates and eigenvalues. The atom–field wave functions are obtained when the atom and the field mode are initially in two different cases. The evolution of both the quasi-probability distribution Q-function and the Mandel Q-parameter of the field are studied when the input field is in a coherent state. The influence of the Kerr medium and the detuning parameters on the behavior of these quantum effects is analyzed. The results show that they play a prominent role on the Poissonian statistics of the field. Also, the Kerr medium changes the behavior of the quasi-probability distribution Q-function. We end with discussion and conclusions.

Relative Tomato Spotted Wilt Incidence and Field Performance among Peanut Cultivars as Influenced by Different Input Production Practices in Georgia.

During 2017-19, 30 replicated yield trials were conducted to determine relative tomato spotted wilt (TSW) incidence and general field performance among 19 runner and virginia market type peanut (Arachis hypogaea L.) cultivars. Four different input production practices were compared across three Georgia locations (Tifton, Plains, and Midville). Two early-planted (April) field tests were conducted at Tifton and Plains each year. One early-planted trial involved maximum-input practices of recommended pesticides with irrigation, and the other early-planted field trial did not receive any fungicides, insecticides, or irrigation. Early-planted maximum-input production practices with irrigation resulted in the highest percentage of mid-season TSW and late-season total disease incidences while also producing the highest pod yields and dollar values. Two other optimum-planted (May) maximum-input field tests were conducted at Tifton, Plains, and Midville, GA as part of the official statewide variety trials (OVT). These OVT utilized maximum-input production practices of pesticides both with and without irrigation. In the OVT, midseason TSW incidence showed no difference between irrigated and non-irrigated; however, the end-of-season total disease percentages which were predominantly TSW did show significantly higher disease percentage, produced the highest pod yields and dollar values within the irrigated field tests compared to the non-irrigated tests. In the overall four tests comparison, disease results showed significantly lower TSW incidence in the early-planted tests without fungicides and insecticides input production practices and no-irrigation; whereas, both optimum planted OVT(s) had the lowest total disease incidence. Overall average field performance for pod yields and dollar values were significantly highest in the optimum-planted tests with maximum-inputs including irrigation. Significant differences were also found among the 19 peanut cultivars. ‘Georgia-06G’, ‘Georgia-12Y’, and ‘Georgia-18RU’ had the lowest relative TSW incidence compared to the other runner-type cultivars. ‘Georgia-19HP’ had the lowest TSW incidence and total disease incidence among the virginia-type cultivars. Among the runner cultivars, Georgia-12Y had the lowest total disease incidence at the end of the season. The highest pod yields were found with Georgia-06G and ‘Georgia-16HO’; whereas, Georgia-18RU and Georgia-06G had the highest dollar values among the runner-type peanut cultivars. Georgia-19HP had the highest pod yield and dollar value among the virginia-type cultivars.

Way of application of convolutional neural networks for personality recognition and user emotions by keyboard handwriting

An important direction of increasing the security and expanding the functionality of modern information systems is the introduction of face recognition tools and user emotions by their keyboard handwriting. The expediency of improving the indicated recognition means by introducing modern neural network solutions into them is shown. A way has been developed for using a convolutional neural network for recognizing a user's face and emotions from keyboard handwriting, the features of which are the procedure for adapting the structural parameters of a convolutional neural network of the VGG type to the expected conditions of use and a procedure for determining the input field, which provides the representation of the parameters of colored channels. After adapting the structural parameters, the VGG network was implemented using the MATLAB R2018b application package, which made it possible to carry out computer experiments aimed at verifying the proposed method. As a result of the conducted computer experiments, it was determined that the use of the proposed method of applying a convolutional neural network makes it possible to achieve a user face recognition accuracy of about 82% with 50 learning epochs. The need for further research in the direction of the formation of a training sample is shown, which will ensure high-quality training of the neural network model.

The effect of geothermal heat flux on the deglacial evolution of the Greenland ice sheet

<p>Geothermal heat flux (GHF) is known to be an important control on the basal thermal state of an ice sheet which, in turn, is a key factor in governing how the ice sheet will evolve in response to a given climate forcing. In recent years, several studies have estimated GHF beneath the Greenland ice sheet using different approaches (e.g. Rezvanbehbahani et al., Geophysical Research Letters, 2017; Martos et al., Geophysical Research Letters, 2018; Greve, Polar Data Journal, 2019). Comparing these different estimates indicates poor agreement and thus large uncertainty in our knowledge of this important boundary condition for modelling the ice sheet. The primary aim of this study is to quantify the influence of this uncertainty on modelling the past evolution of the ice sheet with a focus on the most recent deglaciation. We build on past work that considered three GHF models (Rogozhina et al., 2011) by considering over 100 different realizations of this input field. We use the uncertainty estimates from Martos et al. (Geophysical Research Letters, 2018) to generate GHF realisations via a statistical sampling procedure. A sensitivity analysis using these realisations and the Parallel Ice Sheet Model (PISM, Bueler and Brown, Journal of Geophysical Research, 2009) indicates that uncertainty in GHF has a dramatic impact on both the volume and spatial distribution of ice since the last glacial maximum, indicating that more precise constraints on this boundary condition are required to improve our understanding of past ice sheet evolution and, consequently, reduce uncertainty in future projections.</p>

An Integral Field Unit Based on Parabolic Mirror

Recently many modern instruments and systems have been developed to study the Sun. For that, spectral instruments with high spectral resolution are most often used. It is relevant to achieve high spatial resolution along with spectral one for many scientific tasks. In practice, the achievement of both high spectral and spatial resolution can be done by the use of integral field spectroscopy. Current paper is devoted to searching for a system solution for an integral field unit (IFU), which will be implemented to the optical system of solar telescopecoronagraph. The diameter of the main mirror is D = 3 m. Telescope’s working spectral range is ∆λ = 390 − 1600 nm. The integral field unit is based on reflective elements. It divides the input field of a rectangular shape with a size of 0.7500 ×1200(0.145 mm×2.327 mm) into 8 parts with a size of 0.09400×9600(0.018 mm×18.617 mm) each. The possibility of creating an IFU optical system using a parabolic mirror for all (eight) channels is shown. The quality of the optical system was evaluated, as well as the effect of vignetting on the slicing mirrors.