Emerging Digital Practices Supporting Student-Centered Learning Environments in Higher Education: A Review of Literature and Lessons Learned from the Covid-19 Pandemic.

The aim of this paper is two-fold: firstly, to provide an overview of emerging digital practices that support collaborative learning, competency development, and digital literacy for student-centered learning environments in higher education during the rapid digital transition caused by pandemic-related lockdowns across the world, and secondly, to analyze and discuss how systematic reviews of generalized themes and trends can be combined with contextualized experiences and the lessons learned from the Covid-19 crisis to inform the digital transformation of higher education, with a particular focus on bridging the gap between campus-based teaching and online learning and on the identification of the digital competencies that teachers and students must acquire during the continuing shift into a 'new normal' for post-pandemic educational practices. This study was motivated by questions and findings emerging from an early reactive case study conducted by three of this paper's co-authors (Lyngdorf et al., 2021a).

Three-dimensional integral imaging in photon-starved environments with high-sensitivity image sensors.

Imaging in poorly illuminated environments using three-dimensional (3D) imaging with passive imaging sensors that operate in the visible spectrum is a formidable task due to the low number of photons detected. 3D integral imaging, which integrates multiple two-dimensional perspectives, is expected to perform well in the presence of noise, as well as statistical fluctuation in the detected number of photons. In this paper, we present an investigation of 3D integral imaging in low-light-level conditions, where as low as a few photons and as high as several tens of photons are detected on average per pixel.

Optical sensing and detection in turbid water using multidimensional integral imaging.

We present an approach for optical sensing and detection in turbid water using multidimensional spatial-temporal domain integral imaging and dedicated signal processing algorithms. An optical signal is encoded using pseudorandom sequences, and an image sensor array is used to capture elemental image video sequences of light propagating through turbid water. Using the captured information, multidimensional image reconstruction followed by multi-dimensional correlation to detect the source signal is performed.

Spatial-temporal human gesture recognition under degraded conditions using three-dimensional integral imaging.

We present spatial-temporal human gesture recognition in degraded conditions including low light levels and occlusions using passive sensing three-dimensional (3D) integral imaging (InIm) system and 3D correlation filters. The 4D (lateral, longitudinal, and temporal) reconstructed data is processed using a variety of algorithms including linear and non-linear distortion-invariant filters; and compared with previously reported space-time interest points (STIP) feature detector, 3D histogram of oriented gradients (3D HOG) feature descriptor, with a standard bag-of-features support vector machine (SVM) framework, etc. The gesture recognition results with different classification algorithms are compared using a variety of performance metrics such as receiver operating characteristic (ROC) curves, area under the curve (AUC), SNR, the probability of classification errors, and confusion matrix.

Sickle cell disease diagnosis based on spatio-temporal cell dynamics analysis using 3D printed shearing digital holographic microscopy.

We present a spatio-temporal analysis of cell membrane fluctuations to distinguish healthy patients from patients with sickle cell disease. A video hologram containing either healthy red blood cells (h-RBCs) or sickle cell disease red blood cells (SCD-RBCs) was recorded using a low-cost, compact, 3D printed shearing interferometer. Reconstructions were created for each hologram frame (time steps), forming a spatio-temporal data cube.

Automatic cell identification and visualization using digital holographic microscopy with head mounted augmented reality devices.

We propose a compact imaging system that integrates an augmented reality head mounted device with digital holographic microscopy for automated cell identification and visualization. A shearing interferometer is used to produce holograms of biological cells, which are recorded using customized smart glasses containing an external camera. After image acquisition, segmentation is performed to isolate regions of interest containing biological cells in the field-of-view, followed by digital reconstruction of the cells, which is used to generate a three-dimensional (3D) pseudocolor optical path length profile.

Automatic multicell identification using a compact lensless single and double random phase encoding system.

We investigate the use of compact, lensless, single random phase encoding (SRPE) and double random phase encoding (DRPE) systems for automatic cell identification when multiple cells, either of the same or mixed classes, are in the field of view. A microscope glass slide containing the sample is inputted into the single or double random phase encoding system, which is then illuminated by a coherent or partially coherent light source generating a unique opto-biological signature (OBS) that is captured by an image sensor. Statistical features such as mean, standard deviation, skewness, kurtosis, entropy, and Pearson's correlation coefficient are extracted from the OBSs and used for cell identification with the random forest classifier.

Three-dimensional object visualization and detection in low light illumination using integral imaging.

Conventional two-dimensional (2D) imaging systems that operate in the visible spectrum may perform poorly in environments under low light illumination. In this work, we present the potential of passive three-dimensional (3D) integral imaging (II) to perform 3D imaging of a scene under low light conditions in the visible spectrum and without the need for a photon counting or cooled CCD camera. Using dedicated algorithms, we demonstrate that the reconstructed 3D integral image is naturally optimum in a maximum likelihood sense in low light levels and in the presence of detector noise enabling object visualization in the scene.

Anchoring on Self and Others During Social Inferences.

When making inferences about similar others, people anchor and adjust away from themselves (Tamir & Mitchell, 2013). However, research on relational self theory (Andersen & Chen, 2002) suggests the possibility of using knowledge about others as an anchor when they are more similar to a target. We investigated whether social inferences are made on the basis of significant other knowledge through an anchoring and adjustment process, and whether anchoring on a significant other is more effortful than anchoring on the self.

Compact and field-portable 3D printed shearing digital holographic microscope for automated cell identification.

We propose a low-cost, compact, and field-portable 3D printed holographic microscope for automated cell identification based on a common path shearing interferometer setup. Once a hologram is captured from the portable setup, a 3D reconstructed height profile of the cell is created. We extract several morphological cell features from the reconstructed 3D height profiles, including mean physical cell thickness, coefficient of variation, optical volume (OV) of the cell, projected area of the cell (PA), ratio of PA to OV, cell thickness kurtosis, cell thickness skewness, and the dry mass of the cell for identification using the random forest (RF) classifier.

Three-dimensional integral imaging and object detection using long-wave infrared imaging.

We propose a passive three-dimensional (3D) imaging technique based on integral imaging using a long-wave infrared (LWIR) camera. 3D imaging can improve visualization and detection of objects in adverse environments, such as low light levels and the presence of partial occlusions, along with depth estimation by reconstructing the scene at the plane of the object. This is achieved by capturing multiple two-dimensional images, known as elemental images (EI), of a scene with each image having a unique perspective of the 3D objects.

Three-dimensional profilometric reconstruction using flexible sensing integral imaging and occlusion removal.

We present a method for three-dimensional (3D) profilometric reconstruction using flexible sensing integral imaging with object recognition and automatic occlusion removal. Two-dimensional images, known as elemental images (EIs), of a scene containing an object behind occlusion are captured by flexible sensing integral imaging using a moving camera randomly placed on a non-planar surface with unknown camera position and orientation. After 3D image acquisition, the unknown camera poses are estimated using the EIs and 3D reconstruction is performed based on flexible sensing integral imaging.

Double-random-phase encryption with photon counting for image authentication using only the amplitude of the encrypted image.

We present a photon-counting double-random-phase encryption technique that only requires the photon-limited amplitude of the encrypted image for decryption. The double-random-phase encryption is used to encrypt an image, generating a complex image. Photon counting is applied to the amplitude of the encrypted image, generating a sparse noise-like image; however, the phase information is not retained.

The influence of the number of relevant causes on the processing of covariation information in causal reasoning.

Research on causal reasoning has focused on the influence of covariation between candidate causes and effects on causal judgments. We suggest that the type of covariation information to which people attend is affected by the task being performed. For this, we manipulated the test questions for the evaluation of contingency information and observed its influence on both contingency learning and subsequent causal selections.

Cell identification using single beam lensless imaging with pseudo-random phase encoding.

In this Letter, we propose a novel compact optical system for automated cell identification. Our system employs pseudo-random encoding of the light modulated by the cells under inspection to capture the unique opto-biological signature of the micro-organisms by an image sensor and without using a microscope objective lens to magnify the object beam. The proposed instrument can be fabricated using a compact light source, a thin diffuser, and an image sensor connected to computational hardware; thus, it can be compact and cost effective.

Integrated circuit authentication using photon-limited x-ray microscopy.

A counterfeit integrated circuit (IC) may contain subtle changes to its circuit configuration. These changes may be observed when imaged using an x-ray; however, the energy from the x-ray can potentially damage the IC. We have investigated a technique to authenticate ICs under photon-limited x-ray imaging.

Security authentication with a three-dimensional optical phase code using random forest classifier.

An object with a unique three-dimensional (3D) optical phase mask attached is analyzed for security and authentication. These 3D optical phase masks are more difficult to duplicate or to have a mathematical formulation compared with 2D masks and thus have improved security capabilities. A quick response code was modulated using a random 3D optical phase mask generating a 3D optical phase code (OPC).

Stereotype Fit Effects for Golf Putting Nonexperts.

Research has connected stereotype threat and regulatory fit by showing improved performance for individuals with negative stereotypes when they focused on minimizing potential losses. In the current study, non-Black participants, who were non-experts at golf putting, were told that a golf-putting task was diagnostic of natural athletic ability (i.e.

Augmented reality three-dimensional object visualization and recognition with axially distributed sensing.

An augmented reality (AR) smartglass display combines real-world scenes with digital information enabling the rapid growth of AR-based applications. We present an augmented reality-based approach for three-dimensional (3D) optical visualization and object recognition using axially distributed sensing (ADS). For object recognition, the 3D scene is reconstructed, and feature extraction is performed by calculating the histogram of oriented gradients (HOG) of a sliding window.

Licensing Novel Role-Governed Categories: An ERP Analysis.

Markman and Stilwell (2001) argued that many natural categories name roles in relational systems, and so they are role-governed categories. This view predicts instantiating a novel relational structure licenses the creation of novel role-governed categories. This paper supports this claim and helps to specify the mechanisms underlying this licensing.

Physiological and behavioral signatures of reflective exploratory choice.

Physiological arousal, a marker of emotional response, has been demonstrated to accompany human decision making under uncertainty. Anticipatory emotions have been portrayed as basic and rapid evaluations of chosen actions. Instead, could these arousal signals stem from a "cognitive" assessment of value that utilizes the full environment structure, as opposed to merely signaling a coarse, reflexive assessment of the possible consequences of choices? Combining an exploration-exploitation task, computational modeling, and skin conductance measurements, we find that physiological arousal manifests a reflective assessment of the benefit of the chosen action, mirroring observed behavior.

Full-phase photon-counting double-random-phase encryption.

We investigate a full-phase-based photon-counting double-random-phase encryption (PC-DRPE) method. A PC technique is applied during the encryption process, creating sparse images. The statistical distribution of the PC decrypted data for full-phase encoding and amplitude-phase encoding are derived, and their statistical parameters are used for authentication.

Priming interdependence affects processing of context information in causal inference--but not how you might think.

Cultural mindset is related to performance on a variety of cognitive tasks. In particular, studies of both chronic and situationally-primed mindsets show that individuals with a relatively interdependent mindset (i.e.

There Are Many Ways to See the Forest for the Trees: A Tour Guide for Abstraction.

Abstraction is a useful process for broadening mental horizons, integrating new experiences, and communicating information to others. Much attention has been directed at identifying the causes and consequences of abstraction across the subdisciplines of psychology. Despite this attention, an integrative review of the methods that are used for studying abstraction is missing from the literature.