Re-learning How to Teach

This artifact addresses teacher education during the pandemic, when teachers have faced great challenges. Many of the student-teacher concepts that Dr. Kazemi and Dr. Ghousseini have advocated for in a pre-pandemic time—such as ambitious teaching, rehearsals, and playful learning—are important right now. Teaching is more than just delivering content; it involves building relationships with students and their families, which is much more difficult in a pandemic world

COVID-19 vaccine perspective from adolescents\u27 lens in the US

Introduction The COVID-19 pandemic has presented an unprecedented global health issue. The World Health Organization estimates 773 million confirmed cases and 7 million deaths. Vaccination continues to be the most effective way to prevent COVID-19 and has demonstrated safety and efficacy in all age groups. Though a lot of studies have looked at COVID-19 vaccination acceptance and hesitancy in adults, there is scarce research addressing adolescent vaccination readiness. COVID-19 infection in this age group may result in lost school days, school and community transmission, and loss of productivity for parents. Aim This study aims to determine COVID-19 vaccination rates and factors influencing its acceptance and hesitancy in adolescents in a community setting. Methods A voluntary survey was conducted at a local high school in May 2023. Information was collected about the demographics of adolescents and the educational background of parents/guardians. The survey assessed the COVID vaccine rate, reasons for COVID-19 vaccine acceptance or refusal, number of doses of COVID-19 vaccine and boosters received, prior history of COVID-19 infection, source of information on COVID-19 vaccine, flu vaccine acceptance by the students, and whether they would be willing to take a COVID-19 vaccine booster. Results Four hundred participants, ranging in age from 13 to 19, were surveyed. The vaccination rate in boys was comparable to that in girls. 72% received at least one COVID-19 vaccine, and 66% were considered completely vaccinated. Of those completely vaccinated, 80% had undergone further updated COVID-19 booster vaccinations. Adolescents whose parents/guardians were college graduates had a higher vaccination rate than those whose parents/guardians were not. Caucasians and Asians had a higher vaccination rate compared to African Americans and mixed races. The vaccination rate was not statistically different in adolescents with prior COVID-19 infection versus no prior infection. Flu vaccination was associated with higher COVID-19 vaccination rates. Lack of trust was an important reason for vaccine hesitancy, along with questions about efficacy, concerns about side effects, parent/guardian decisions, and religious reasons. Protecting oneself, family/friends, and community were the major reasons to take the vaccine. Parents/guardians, physicians, peers, television, social media, flyers, and schools were the primary sources that adolescents relied on for information about the COVID-19 vaccination. Conclusion Lower education attainment among parents/guardians, African Americans, and mixed races was associated with lower vaccination rates. Lack of trust in the vaccine, questions about efficacy, and fear of side effects were the most frequently cited reasons for vaccine hesitancy. Parent/guardian influence and religious reasons were other significant reasons for vaccine hesitancy. Flu vaccination was associated with higher COVID-19 vaccination rates. Understanding factors influencing COVID-19 vaccination will allow us to address barriers to COVID-19 vaccination and other vaccinations appropriate for this age group. Educating adolescents in schools, involving local and state health departments to increase awareness about the vaccine, and educating parents and guardians along with the teenagers can help increase the acceptance of the vaccine. These interventions will also positively affect the acceptance of the booster and prepare us for any future pandemics

One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning

We present Generalized LoRA (GLoRA), an advanced approach for universal parameter-efficient fine-tuning tasks. Enhancing Low-Rank Adaptation (LoRA), GLoRA employs a generalized prompt module to optimize pre-trained model weights and adjust intermediate activations, providing more flexibility and capability across diverse tasks and datasets. Moreover, GLoRA facilitates efficient parameter adaptation by employing a scalable, modular, layer-wise structure search that learns individual adapter of each layer. Originating from a unified mathematical formulation, GLoRA exhibits strong transfer learning, few-shot learning and domain generalization abilities, as it adapts to new tasks through not only weights but also additional dimensions like activations. Comprehensive experiments demonstrate that GLoRA outperforms all previous methods in natural, specialized, and structured vision benchmarks, achieving superior accuracy with fewer parameters and computations. The proposed method on LLaMA-1 and LLaMA-2 also show considerable enhancements compared to the original LoRA in the language domain. Furthermore, our structural re-parameterization design ensures that GLoRA incurs no extra inference cost, rendering it a practical solution for resource-limited applications. Code and models are available at: https://github.com/Arnav0400/ViT-Slim/tree/master/GLoRA.Comment: Technical report. v2: Add LLaMA-1&2 results. Code and models at https://github.com/Arnav0400/ViT-Slim/tree/master/GLoR

Disordered Phase in Ising and Metastability in Cellular Potts Models Hint at Glassy Dynamics

In this paper, quantum algorithms are to be used to simulate glassy systems in toy models. To look for glassy behavior, the energy landscape and spin configurations of the transverse field Ising model in a longitudinal field are studied. The Variational Quantum Eigensolver (VQE) is used to obtain the ground-state energies and corresponding eigenstates for a $6 \times 6$ Ising lattice using 36 qubits and a 1-dimensional Ising chain of length 25. For the $8 \times 8$ Cellular Potts model, the original Hamiltonian is converted to an Ising formulation for the VQE to reduce to its ground state. The energy change during minimization is carefully analyzed to find whether the effects of interfacial tension among cells could probably induce glassiness in the cell system

On designing light-weight object trackers through network pruning: Use CNNs or transformers?

Object trackers deployed on low-power devices need to be light-weight, however, most of the current state-of-the-art (SOTA) methods rely on using compute-heavy backbones built using CNNs or transformers. Large sizes of such models do not allow their deployment in low-power conditions and designing compressed variants of large tracking models is of great importance. This paper demonstrates how highly compressed light-weight object trackers can be designed using neural architectural pruning of large CNN and transformer based trackers. Further, a comparative study on architectural choices best suited to design light-weight trackers is provided. A comparison between SOTA trackers using CNNs, transformers as well as the combination of the two is presented to study their stability at various compression ratios. Finally results for extreme pruning scenarios going as low as 1% in some cases are shown to study the limits of network pruning in object tracking. This work provides deeper insights into designing highly efficient trackers from existing SOTA methods.Comment: Submitted at IEEE ICASSP 202