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Generative Artificial Intelligence (GAI), such as OpenAI’s ChatGPT, has rapidly emerged as a transformative tool in higher education, offering opportunities to enhance teaching and learning. This paper describes the design and implementation of ChatGPT-integrated curriculum activities, featuring coding learning in psychology and conceptual discussions in physics, and presents the findings of a year-long experimental study in both types of classrooms. Our findings suggest that students generally found ChatGPT easy to use and beneficial to their learning, reporting improved confidence, motivation, and engagement. However, its ability to address individual needs or replace instructors was viewed less favorably. Comparative analyses showed that coding activities in psychology led to higher levels of activity satisfaction and perceived usefulness of ChatGPT compared to the more abstract discussion activities in physics. While graduate students were more enthusiastic about using ChatGPT for skill acquisition than undergraduates, demographic factors such as gender, race, and first-generation college status showed no significant influence on such perceptions. Meanwhile, instructors’ reflections emphasize the importance of thoughtful integration, technical support, and pedagogical balance to maximize GAI’s potential while mitigating its limitations. Recommendations for integrating GAI into teaching practices and future research directions are discussed, contributing to the evolving discourse on GAI’s role in transforming modern classrooms. 

Analyzing the kinetics of biological processes plays a significant role in understanding fundamental cellular functions. Many physics-based technologies used to study such processes are limited by the shot noise inherent to the coherent states of light. These technologies can greatly benefit from leveraging quantum probes to improve the sensitivity of measurements in cellular biology. The surface plasmon resonance technique has been used effectively to achieve label-free, real-time measurements of protein binding kinetics, which constitutes an important biological phenomenon occurring near the cell membrane. Here, we demonstrate the integration of this technique with the two-mode bright squeezed state having fewer fluctuations as compared to the coherent state to improve the sensitivity of measurement in studying a protein-gold adsorption process. We show 4 dB of squeezing as we record the signal-to-noise ratio as the function of time, and it is maintained throughout the kinetic process. The improved signal-to-noise ratio leads to a $60\%$improvement in the sensitivity of measuring the observable rate constant $k_s$. The quantum advantage as shown in terms of squeezing is achieved despite the total absorption of $74\%$from the source until the final detection after the sensor. Overall, we provide the most practical setup for improving the sensitivity of the time-dependent measurements involved in various biological processes at the molecular level. 

The biomechanical properties of cells and tissues play an important role in our fundamental understanding of the structures and functions of biological systems at both the cellular and subcellular levels. Recently, Brillouin microscopy, which offers a label-free spectroscopic means of assessing viscoelastic properties in vivo, has emerged as a powerful way to interrogate those properties on a microscopic level in living tissues. However, susceptibility to photodamage and photobleaching, particularly when high-intensity laser beams are used to induce Brillouin scattering, poses a significant challenge. This article introduces a transformative approach designed to mitigate photodamage in biological and biomedical studies, enabling nondestructive, label-free assessments of mechanical properties in live biological samples. By leveraging quantum-light-enhanced stimulated Brillouin scattering (SBS) imaging contrast, the signal-to-noise ratio is significantly elevated, thereby increasing sample viability and extending interrogation times without compromising the integrity of living samples. The tangible impact of this methodology is evidenced by a notable three-fold increase in sample viability observed after subjecting the samples to three hours of continuous squeezed-light illumination, surpassing the traditional coherent light-based approaches. The quantum-enhanced SBS imaging holds promise across diverse fields, such as cancer biology and neuroscience where preserving sample vitality is of paramount significance. By mitigating concerns regarding photodamage and photobleaching associated with high-intensity lasers, this technological breakthrough expands our horizons for exploring the mechanical properties of live biological systems, paving the way for an era of research and clinical applications. 

Strong quantum correlated sources are essential but delicate resources for quantum information science and engineering protocols. Decoherence and loss are the two main disruptive processes that lead to the loss of nonclassical behavior in quantum correlations. In quantum systems, scattering can contribute to both decoherence and loss. In this work, we present an experimental scheme capable of significantly mitigating the adverse impact of scattering in quantum systems. Our quantum system is composed of a two-mode squeezed light generated with the four-wave-mixing process in hot rubidium vapor and a scatterer is introduced to one of the two modes. An integrating sphere is then placed after the scatterer to recollect the scattered photons. We use mutual information between the two modes as the measure of quantum correlations and demonstrate a 47.5% mutual information recovery from scattering, despite an enormous photon loss of greater than 85%. Our scheme is the very first step toward recovering quantum correlations from disruptive random processes and thus has the potential to bridge the gap between proof-of-principle demonstrations and practical real-world implementations of quantum protocols. Published by the American Physical Society2024 

Federated learning (FL) aims to collaboratively train a global model using local data from a network of clients. To warrant collaborative training, each federated client may expect the resulting global model to satisfy some individual requirement, such as achieving a certain loss threshold on their local data. However, in real FL scenarios, the global model may not satisfy the requirements of all clients in the network due to the data heterogeneity across clients. In this work, we explore the problem of global model appeal in FL, which we define as the total number of clients that find that the global model satisfies their individual requirements. We discover that global models trained using traditional FL approaches can result in a significant number of clients unsatisfied with the model based on their local requirements. As a consequence, we show that global model appeal can directly impact how clients participate in training and how the model performs on new clients at inference time. Our work proposes MaxFL, which maximizes the number of clients that find the global model appealing. MaxFL achieves a 22-40% and 18-50% improvement in the test accuracy of training clients and (unseen) test clients respectively, compared to a wide range of FL approaches that tackle data heterogeneity, aim to incentivize clients, and learn personalized/fair models. 

This paper investigates and compares people’s subjective impression of an office with a biophilic design and blue lighting. Existing studies have examined their influence on perception separately, but how they compare is unclear. Additionally, only a few studies have used an office setting as a case study. To address this research gap, this study collected people’s ratings and rankings of four simulated interior scenes of a private office using an online survey. The scenes include blue lighting, a biophilic design with daylight and view, a biophilic design with indoor plants, and a non-biophilic baseline with conventional white lighting. A total of 284 complete responses were collected and analyzed using a mixed-effect model. It was found that the two biophilic designs improved people’s perception of the office compared to the base case. The biophilic design with access to daylight and view outperformed the space with indoor plants in all the examined perceptual categories, specifically how the office space was perceived by participants as brighter, more comfortable, and spacious. On the contrary, the space with blue lighting decreased people’s ratings in most perceptual attributes in comparison to the baseline. The negative influence was notably significant in how lively, comfortable, bright, and appealing the space was perceived as being by participants. Subjects’ preference rankings of the four simulated office spaces showed a similar pattern. 

A series of twelve two-coordinate coinage metal, Cu, Ag and Au, complexes with carbene-metal-amide structures were prepared. The complexes all display thermal assisted delayed fluorescence (TADF) emission at room temperature from interligand charge transfer (ICT) excited state with short lifetimes (less than 2 μs) and photoluminescent quantum yields that reach near unity. Owing to the involvement of the substituents in the emissive transitions and different metal ion volume, the natural transition orbital (NTO) overlap of the emissive state can be adjusted in a wide range from 0.21 to 0.41. Investigations on the relationship between the NTO overlap of the emissive state and key TADF photophysical properties demonstrated that both singlet–triplet energy gap and radiative decay rate of S 1 state increase along with the NTO overlap exponentially. Consequently, the overall TADF radiative decay rate leads to a maximum when plotted against the NTO overlap, giving the ideal zone from 0.25 to 0.30 for high TADF radiative decay rate in this class of two-coordinate coinage metal complex luminophores.