A Time Mode Pulse Interleaver in a Silicon-on-Insulator Platform for Optical Analog-to-Digital Converters.

We propose and demonstrate a novel on-chip optical sampling pulse interleaver based on time mode interleaving. The designed pulse interleaver was fabricated on a 220 nm silicon-on-insulator (SOI) platform, utilizing only one S-shaped delay waveguide. Interleaving is achieved by the relative time delay between different optical modes in the waveguide, eliminating the need for any active tuning. The total length of the delay waveguide is 5620.5 µm, which is reduced by a factor of 46.3% compared with previously reported time-wavelength interleaver schemes. The experimental results indicate that the device can convert an optical pulse into a 40 GHz pulse sequence composed of four pulses with a root mean square (RMS) timing error of 0.9 ps, making it well suited for generating high-frequency sampling pulses for optical analog-to-digital converters.

No Simple Solutions to Complex Problems: Cognitive Science Principles Can Guide but Not Prescribe Educational Decisions.

Cognitive science of learning points to solutions for making use of existing study and instruction time more effectively and efficiently. However, solutions are not and cannot be one-size-fits-all. This paper outlines the danger of overreliance on specific strategies as one-size-fits-all recommendations and highlights instead the cognitive learning processes that facilitate meaningful and long-lasting learning. Three of the most commonly recommended strategies from cognitive science provide a starting point; understanding the underlying processes allows us to tailor these recommendations to implement at the right time, in the right way, for the right content, and for the right students. Recommendations regard teacher training, the funding and incentivizing of educational interventions, guidelines for the development of educational technologies, and policies that focus on using existing instructional time more wisely.

Cracking the code: using educational gaming for high-level thinking in physiology education.

The multidisciplinary nature of physiology requires students to acquire, retain, apply, and evaluate knowledge from different scientific disciplines. Optimal learning techniques, such as active learning, interleaving topics and conditions, and recall, can greatly enhance the speed and effectiveness with which students achieve this type of higher-order thinking. However, developing and implementing optimal learning techniques in the classroom can be both time-intensive and challenging for the instructor. In addition, students may be resistant or slow to accept novel learning processes. One way to potentially introduce these learning techniques in a fun and engaging way is through educational gaming, or using a game or game elements intentionally to support learning. In this article we present an easy-to-implement adaptation of the Codenames board game for the physiology classroom. The activity requires minimal preparation while addressing high-level learning outcomes. Postintervention surveys of students were collected in three different health-related academic programs, both graduate and undergraduate, at two different institutions. Results suggest that participating in the activity both actively engaged the students and pushed them toward high-level, integrative thinking regardless of class level.NEW & NOTEWORTHY An easy-to-implement word game (Codenames) was used to engage students in higher-level Bloom's thinking about physiology. The gameplay required students to recall, apply, evaluate, and debate as they developed and guessed clues as part of the game. Students found the activity fun, engaging, and challenging. The activity is relatively easy to implement both online and in person, requiring at minimum a simple list of vocabulary terms.

Enhancing application and long-term retention of clinical knowledge using an extracurricular non-credit course.

BACKGROUND AND PURPOSE: Curricular overload in doctor of pharmacy (PharmD) programs is necessitating innovative approaches to support student learning. The purpose of this study was to describe the design, delivery, and assessment of a non-credit extracurricular course that reinforced foundational concepts through the application of learning in case-based activities. EDUCATIONAL ACTIVITY AND SETTING: A 14-week extracurricular course, designed using principles of spaced repetition and interleaving in the context of case-based exercises, was offered to third-year PharmD students. Content focused on Top 300 and over-the-counter medications, brown bag sessions/drug utilization review, and medication therapy management. Short-term course effectiveness was assessed through post-course focus groups. Longitudinal effectiveness was assessed nine months post-course using an online survey. Qualitative data were analyzed using a content analysis process with overarching themes identified. Clinical interventions identified in the post-course survey were analyzed descriptively. FINDINGS: Twenty-four students completed the course and all assessments. Focus group themes were: (1) making connections to prior learning; (2) moving beyond memorizing facts; and (3) benefit from a low-stakes course. Students identified 162 course-linked clinical interventions during advanced pharmacy practice experiences (APPEs) in 16 different settings. SUMMARY: Student learning can be enhanced through integration of evidence-based teaching strategies both within and across the curriculum. This can be accomplished not only through introduction of an extracurricular course but through modification of existing courses. Providing additional opportunities for reinforcing core clinical knowledge and applying clinical decision-making in a low-stakes environment was well-received by students and helped them make clinical interventions during APPEs.

The Effectiveness of Spaced Learning, Interleaving, and Retrieval Practice in Radiology Education: A Systematic Review.

PURPOSE: Radiology is a highly complex field that requires mastery over an ever-expanding body of knowledge. Spaced learning, interleaving, and retrieval practice are evidence-based learning strategies that enhance long-term retention of information. The aim of this systematic review is to assess the effectiveness of these interventions in the setting of radiology education. METHODS: The authors searched MEDLINE, Embase, PsycInfo, ERIC, and forward and backward citations for studies published between database inception and February 19, 2023. Eligibility criteria for included studies were randomized and quasi-randomized controlled trials that investigated the impact of spaced, interleaved, or retrieval practice on knowledge retention of medical trainees after education related to medical imaging as assessed by postinterventional examination scores. RESULTS: Of 1,316 records reviewed, 8 studies met eligibility criteria. Two studies investigated spaced learning, two studies interleaving, and six studies retrieval practice, including two trials that evaluated interventions incorporating both spaced learning and retrieval practice. Five of eight studies reported statistically significant differences between interventional and control groups on either immediate or delayed postinterventional examinations. CONCLUSIONS: Despite extensive evidence in support of spaced, interleaved, and retrieval practice within the broader literature, few studies have examined the effectiveness of these strategies in radiology education. Additional trials are required to evaluate the usefulness of incorporating these techniques into educational programs related to medical imaging.

Engineered Interleaved Random Glass Fiber Composites Using Additive Manufacturing: Effect of Mat Properties, Resin Chemistry, and Resin-Rich Layer Thickness.

Standard lay-up fabrication of fiber-reinforced composites (FRCs) suffer from poor out-of-plane properties and delamination resistance. While advanced manufacturing techniques (e.g., interleaving, braiding, and z-pinning) increase delamination resistance in FRCs, they typically result in significant fabrication complexity and limitations, increased manufacturing costs, and/or overall stiffness reduction. In this work, we demonstrate the use of facile digital light processing (DLP) technique to additively manufacture (AM) random glass FRCs with engineered interleaves. This work demonstrates how vat photo-polymerization techniques can be used to build composites layer-by-layer with controlled interleaf material, thickness, and placement. Note that this engineering control is almost impossible to achieve with traditional manufacturing techniques. A range of specimens were printed to measure the effect of interleaf thickness and material on tensile/flexural properties as well as fracture toughness. One important observation was the ≈60% increase in interlaminar fracture toughness achieved by using a tough resin material in the interleaf. The comparison between AM and traditionally manufactured specimens via vacuum-assisted resin transfer molding (VARTM) highlighted the limitation of AM techniques in achieving high mat consolidation. In other words, the volume fraction of AM parts is limited by the wet fiber mat process, and engineering solutions are discussed. Overall, this technique offers engineering control of FRC design and fabrication that is not available with traditional methods.

The Underappreciated Benefits of Interleaving for Category Learning.

The present study examined the effects of study schedule (interleaving vs. blocking) and feature descriptions on category learning and metacognitive predictions of learning. Across three experiments, participants studied exemplars from different rock categories and later had to classify novel exemplars. Rule-based and information-based categorization was also manipulated by selecting rock sub-categories for which the optimal strategy was the one that aligned with the extraction of a simple rule, or the one that required integration of information that may be difficult to describe verbally. We observed consistent benefits of interleaving over blocking on rock classification, which generalized to both rule-based (Experiment 1) and information-integration learning (Experiments 1-3). However, providing feature descriptions enhanced classification accuracy only when the stated features were diagnostic of category membership, indicating that their benefits were limited to rule-based learning (Experiment 1) and did not generalize to information-integration learning (Experiments 1-3). Furthermore, our examination of participants' metacognitive predictions demonstrated that participants were not aware of the benefits of interleaving on category learning. Additionally, providing feature descriptions led to higher predictions of categorization even when no significant benefits on actual performance were exhibited.

Cognitive perspectives on maintaining physicians' medical expertise: IV. Best practices and open questions in using testing to enhance learning and retention.

Although tests and assessments-such as those used to maintain a physician's Board certification-are often viewed merely as tools for decision-making about one's performance level, strong evidence now indicates that the experience of being tested is a powerful learning experience in its own right: The act of retrieving targeted information from memory strengthens the ability to use it again in the future, known as the testing effect. We review meta-analytic evidence for the learning benefits of testing, including in the domain of medicine, and discuss theoretical accounts of its mechanism(s). We also review key moderators-including the timing, frequency, order, and format of testing and the content of feedback-and what they indicate about how to most effectively use testing for learning. We also identify open questions for the optimal use of testing, such as the timing of feedback and the sequencing of complex knowledge domains. Lastly, we consider how to facilitate adoption of this powerful study strategy by physicians and other learners.

Construction of Optimal Frequency Hopping Sequence Set with Low-Hit-Zone.

In quasi-synchronous frequency-hopping multiple access (QS-FHMA) systems, low-hit-zone (LHZ) frequency-hopping sequence (FHS) sets have been well-applied to reduce mutual interference (MI). In this paper, we propose three constructions of LHZ FHS sets with new parameters via interleaving techniques. The obtained sequences can be verified that they are optimal with respect to the Peng-Fan-Lee bound.

Interleaving Effects in Blindfolded Perceptual Learning Across Various Sensory Modalities.

Research on sequence effects on learning visual categories has shown that interleaving (i.e., studying the categories in a mixed manner) facilitates category induction as compared to blocking (i.e., studying the categories one by one), but learners are unaware of the interleaving effect and prefer blocking. However, little attention has been paid to sequence effects in perceptual learning across further sensory modalities. The present (preregistered) research addresses this shortcoming by using auditory (birdcalls), olfactory (tealeaves), gustatory (ingredient mixtures), and tactile (stones) stimuli across four analog experiments. The number of participants per experiment was determined based on a medium effect size of interleaving. Participants studied six categories (with six exemplars, respectively) either interleaved or blocked. No single experiment showed a significant effect of interleaving. We ran a comprehensive meta-analysis based on the data from all experiments, which revealed a significant small effect of interleaving, demonstrating its applicability to perceptual learning across all sensory modalities. Learners in the interleaved condition underestimated their classification performance. Overall, learners did not rate interleaving as less effective than blocking, which is at odds with previous studies that consistently demonstrated a metacognitive preference of blocking. Our findings suggest that learners rely less on conventional beliefs about the effectivity of study sequence when dealing with unfamiliar (blindfolded) perceptual learning tasks.

High-Density 1R/1W Dual-Port Spin-Transfer Torque MRAM.

Spin-transfer torque magnetic random-access memory (STT-MRAM) has several desirable features, such as non-volatility, high integration density, and near-zero leakage power. However, it is challenging to adopt STT-MRAM in a wide range of memory applications owing to the long write latency and a tradeoff between read stability and write ability. To mitigate these issues, an STT-MRAM bit cell can be designed with two transistors to support multiple ports, as well as the independent optimization of read stability and write ability. The multi-port STT-MRAM, however, is achieved at the expense of a higher area requirement due to an additional transistor per cell. In this work, we propose an area-efficient design of 1R/1W dual-port STT-MRAM that shares a bitline between two adjacent bit cells. We identify that the bitline sharing may cause simultaneous access conflicts, which can be effectively alleviated by using the bit-interleaving architecture with a long interleaving distance and the sufficient number of word lines per memory bank. We report various metrics of the proposed design based on the bit cell design using a 45 nm process. Compared to a standard single-port STT-MRAM, the proposed design shows a 15% lower read power and a 19% higher read-disturb margin. Compared with prior work on the 1R/1W dual-port STT-MRAM, the proposed design improves the area by 25%.

Misconceptions in IONM Part III: Stimulation Repetition Rate Effects on Intraoperative Somatosensory Evoked Potential Amplitude and Latency.

The rate at which stimulation is applied to peripheral nerves is critical to generating high-quality intraoperative somatosensory evoked potentials (SSEPs) in a timely manner. Guidelines based on a limited study and anecdotal evidence present differing, incorrect, or incomplete stimulation rate recommendations. We examined the effect stimulating the ulnar and tibial nerves at 1.05, 2.79, 5.69, and 8.44 Hz had on cortical, subcortical, and peripheral response amplitude and latency in 10 subjects with neuromuscular blockade (NMB) and 10 without NMB in the operating room under general anesthesia. As the stimulation repetition rate increased, the amplitude of upper and lower extremity cortical responses decreased equally in both groups. The ulnar nerve N20 cortical response amplitude decreased 27.9% at 2.79 Hz, 48.8% at 5.69 Hz, and 53.8% at 8.44 Hz. The tibial nerve P37 cortical response amplitude decreased 30.3% at 2.79 Hz, 53.8% at 5.69 Hz, and 56.8% at 8.44 Hz. Neither upper or lower extremity peripheral or subcortical amplitudes nor upper and lower extremity subcortical or peripheral latencies were affected by increasing repetition rate in either group. Low SSEP stimulation repetition rates ensure the highest quality cortical responses.

Familiar Strategies Feel Fluent: The Role of Study Strategy Familiarity in the Misinterpreted-Effort Model of Self-Regulated Learning.

Why do learners not choose ideal study strategies when learning? Past research suggests that learners frequently misinterpret the effort affiliated with efficient strategies as being indicative of poor learning. Expanding on past findings, we explored the integration of study habits into this model. We conducted two experiments where learners experienced two contrasting strategies-blocked and interleaved schedules-to learn to discriminate between images of bird families. After experiencing each strategy, learners rated each according to its perceived effort, learning, and familiarity. Next, learners were asked to choose which strategy they would use in the future. Mediation analyses revealed, for both experiments, that the more mentally effortful interleaving felt, the less learners felt they learned, and the less likely learners were to use it in future learning. Further, in this study, strategy familiarity predicted strategy choice, also mediated by learners' perceived learning. Additionally, Study 2 verified that, in contrast to learners' judgments, the less familiar interleaving schedule resulted in better learning. Consequently, learners are making ineffective learning judgments based on their perceptions of effort and familiarity and, therefore, do not make use of optimal study strategies in self-regulated learning decisions.

An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints.

In image classification with Deep Convolutional Neural Networks (DCNNs), the number of parameters in pointwise convolutions rapidly grows due to the multiplication of the number of filters by the number of input channels that come from the previous layer. Existing studies demonstrated that a subnetwork can replace pointwise convolutional layers with significantly fewer parameters and fewer floating-point computations, while maintaining the learning capacity. In this paper, we propose an improved scheme for reducing the complexity of pointwise convolutions in DCNNs for image classification based on interleaved grouped filters without divisibility constraints. The proposed scheme utilizes grouped pointwise convolutions, in which each group processes a fraction of the input channels. It requires a number of channels per group as a hyperparameter Ch. The subnetwork of the proposed scheme contains two consecutive convolutional layers K and L, connected by an interleaving layer in the middle, and summed at the end. The number of groups of filters and filters per group for layers K and L is determined by exact divisions of the original number of input channels and filters by Ch. If the divisions were not exact, the original layer could not be substituted. In this paper, we refine the previous algorithm so that input channels are replicated and groups can have different numbers of filters to cope with non exact divisibility situations. Thus, the proposed scheme further reduces the number of floating-point computations (11%) and trainable parameters (10%) achieved by the previous method. We tested our optimization on an EfficientNet-B0 as a baseline architecture and made classification tests on the CIFAR-10, Colorectal Cancer Histology, and Malaria datasets. For each dataset, our optimization achieves a saving of 76%, 89%, and 91% of the number of trainable parameters of EfficientNet-B0, while keeping its test classification accuracy.

Applying Interleaving Strategy of Learning Materials and Perceptual Modality to Address Secondary Students' Need to Restore Cognitive Capacity.

Online courses are prevalent around the world, especially during the COVID-19 pandemic. Long hours of highly demanding online learning can lead to mental fatigue and cognitive depletion. According to Attention Restoration Theory, 'being away' or a mental shift could be an important strategy to allow a person to recover from the cognitive overload. The present study aimed to test the interleaving strategy as a mental shift method to help sustain students' online learning attention and to improve learning outcomes. A total of 81 seventh-grade Chinese students were randomly assigned to four learning conditions: blocked (by subject matter) micro-lectures with auditory textual information (B-A condition), blocked (by subject matter) micro-lectures with visual textual information (B-V condition), interleaved (by subject matter) micro-lectures with auditory textual information (I-A condition), and interleaved micro-lectures by both perceptual modality and subject matter (I-all condition). We collected self-reported data on subjective cognitive load (SCL) and attention level, EEG data during the 40 min of online learning, and test results to assess learning outcomes. The results showed that the I-all condition showed the best overall outcomes (best performance, low SCL, and high attention). This study suggests that interleaving by both subject matter and perceptual modality should be preferred in scheduling and planning online classes.

A Computational Model of Context-Dependent Encodings During Category Learning.

Although current exemplar models of category learning are flexible and can capture how different features are emphasized for different categories, they still lack the flexibility to adapt to local changes in category learning, such as the effect of different sequences of study. In this paper, we introduce a new model of category learning, the Sequential Attention Theory Model (SAT-M), in which the encoding of each presented item is influenced not only by its category assignment (global context) as in other exemplar models, but also by how its properties relate to the properties of temporally neighboring items (local context). By fitting SAT-M to data from experiments comparing category learning with different sequences of trials (interleaved vs. blocked), we demonstrate that SAT-M captures the effect of local context and predicts when interleaved or blocked training will result in better testing performance across three different studies. Comparatively, ALCOVE, SUSTAIN, and a version of SAT-M without locally adaptive encoding provided poor fits to the results. Moreover, we evaluated the direct prediction of the model that different sequences of training change what learners encode and determined that the best-fit encoding parameter values match learners' looking times during training.

Interleaving Retrieval Practice Promotes Science Learning.

Can interleaved retrieval practice enhance learning in classrooms? Across a 4-week period, ninth- through 12th-grade students (N = 155) took a weekly quiz in their science courses that tested half of the concepts taught that week. Questions on each quiz were either blocked by concept or interleaved with different concepts. A month after the final quiz, students were tested on the concepts covered in the 4-week period. Replicating the retrieval-practice effect, results showed that participants performed better on concepts that had been on blocked quizzes (M = 54%, SD = 28%) than on concepts that had not been quizzed (M = 47%, SD = 20%; d = 0.30). Interleaved quizzes led to even greater benefits: Participants performed better on concepts that had been on interleaved quizzes (M = 63%, SD = 26%) than on concepts that had been on blocked quizzes (d = 0.35). These results demonstrate a cost-effective strategy to promote classroom learning.

Misconceptions in IONM Part I: Interleaved Intraoperative Somatosensory Evoked Potential Stimulation.

A misconception in the field of intraoperative neurophysiological monitoring (IONM) is that continuous, multi-nerve (four-limb), interleaved somatosensory evoked potential (SSEP) stimulation, while advantageous, is not universally utilized due to variety of misunderstandings regarding this approach to SSEP stimulation. This article addresses the rationale for this misconception. We find that continuous, multi-nerve, interleaved SSEP stimulation is superior to all other stimulation paradigms in most operative scenarios, allowing the fastest acquisition of SSEPs at low stimulation repetition rates, which generate the highest amplitude cortical responses.

Transfer of category learning to impoverished contexts.

Learning often happens in ideal conditions, but then must be applied in less-than-ideal conditions - such as when a learner studies clearly illustrated examples of rocks in a book but then must identify them in a muddy field. Here we examine whether the benefits of interleaving (vs. blocking) study schedules, as well as the use of feature descriptions, supports the transfer of category learning in new, impoverished contexts. Specifically, keeping the study conditions constant, we evaluated learners' ability to classify new exemplars in the same neutral context versus in impoverished contexts in which certain stimulus features are occluded. Over two experiments, we demonstrate that performance in new, impoverished contexts during test is greater for participants who received an interleaved (vs. blocked) study schedule, both for novel and for studied exemplars. Additionally, we show that this benefit extends to both a short (3-min) or long (48-h) test delay. The presence of feature descriptions during learning had no impact on transfer. Together, these results extend the growing literature investigating how changes in context during category learning or test impacts performance and provide support for the use of interleaving to promote the far transfer of category knowledge to impoverished contexts.

Mitigating the Effect of COVID Lockdown Period on Channel and Bandwidth Utilization in Mobile Communication Network in North Western Rajasthan (India).

The COVID-19 lockdown has led all the citizens (mobile subscribers) of India to stay at home and rather work from home. The people have started consuming more channel utilization (in mobile communication) through a continuous long duration conversations and more internet data through more streaming content as well as logging on to work from home. It was also reflected in how data demand from residential areas rose as compared to commercial areas. Consequently the bandwidth and channel saturation has evolved out to be a severe problem thereby affecting the work performance of all online offices and multi-national companies. This research paper proposes the simulation based experimental study of DITMC technique for mitigating this effect with a special concern in North Western Rajasthan part of India. The simulation results show that significant enhancement of 60.52% in channel utilization and bandwidth optimization is possible with negligible overhead of 0.23%. This technique also enables the telecom operators to ponder research in this field that will promisingly lead to manage augmented number of mobile subscribers (independent of any lockdown period) in limited bandwidth thereby using the spectrum efficiently.