E2Net: Resource-Efficient Continual Learning with Elastic Expansion Network

Continual Learning methods are designed to learn new tasks without erasing previous knowledge. However, Continual Learning often requires massive computational power and storage capacity for satisfactory performance. In this paper, we propose a resource-efficient continual learning method called the Elastic Expansion Network (E2Net). Leveraging core subnet distillation and precise replay sample selection, E2Net achieves superior average accuracy and diminished forgetting within the same computational and storage constraints, all while minimizing processing time. In E2Net, we propose Representative Network Distillation to identify the representative core subnet by assessing parameter quantity and output similarity with the working network, distilling analogous subnets within the working network to mitigate reliance on rehearsal buffers and facilitating knowledge transfer across previous tasks. To enhance storage resource utilization, we then propose Subnet Constraint Experience Replay to optimize rehearsal efficiency through a sample storage strategy based on the structures of representative networks. Extensive experiments conducted predominantly on cloud environments with diverse datasets and also spanning the edge environment demonstrate that E2Net consistently outperforms state-of-the-art methods. In addition, our method outperforms competitors in terms of both storage and computational requirements

CLIP-KD: An Empirical Study of Distilling CLIP Models

CLIP has become a promising language-supervised visual pre-training framework and achieves excellent performance over a wide range of tasks. This paper aims to distill small CLIP models supervised by a large teacher CLIP model. We propose several distillation strategies, including relation, feature, gradient and contrastive paradigm, to examine the impact on CLIP distillation. We show that the simplest feature mimicry with MSE loss performs best. Moreover, interactive contrastive learning and relation-based distillation are also critical in performance improvement. We apply the unified method to distill several student networks trained on 15 million (image, text) pairs. Distillation improves the student CLIP models consistently over zero-shot ImageNet classification and cross-modal retrieval benchmarks. We hope our empirical study will become an important baseline for future CLIP distillation research. The code is available at \url{https://github.com/winycg/CLIP-KD}

Plasmonic hot electrons for sensing, photodetection, and solar energy applications: A perspective

In plasmonic metals, surface plasmon resonance decays and generates hot electrons and hot holes through non-radiative Landau damping. These hot carriers are highly energetic, which can be modulated by the plasmonic material, size, shape, and surrounding dielectric medium. A plasmonic metal nanostructure, which can absorb incident light in an extended spectral range and transfer the absorbed light energy to adjacent molecules or semiconductors, functions as a “plasmonic photosensitizer.” This article deals with the generation, emission, transfer, and energetics of plasmonic hot carriers. It also describes the mechanisms of hot electron transfer from the plasmonic metal to the surface adsorbates or to the adjacent semiconductors. In addition, this article highlights the applications of plasmonic hot electrons in photodetectors, photocatalysts, photoelectrochemical cells, photovoltaics, biosensors, and chemical sensors. It discusses the applications and the design principles of plasmonic materials and devices

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

HIV-Related Stress Experienced by Newly Diagnosed People Living with HIV in China: A 1-Year Longitudinal Study

This study explored the HIV-related stressors that people living with HIV (PLWH) commonly experience and express as stressful at the time of diagnosis and 1 year later. The factors associated with stress levels and whether social support would moderate the negative effects of stress on psychological health (depressive and anxiety symptoms) were also investigated. Newly diagnosed PLWH were consecutively recruited in this study. Participants rated their stress with the HIV/AIDS Stress Scale at baseline and 1 year later. Social support, depression, and anxiety were also self-reported at both time points. There were significant decreases in stress levels 1 year after diagnosis. Stressors regarding confidentiality, disclosure, emotional distress, fear of infecting others, and excessive attention to physical functions were the most problematic at baseline and 1-year follow-up. A younger age, married status, not living alone, less income, presence of HIV symptoms, and lack of social support were associated with higher levels of stress. No stress-buffering effect of social support on depressive and anxiety symptoms was found in this study. Interventions to reduce stress among PLWH should take into consideration the following priority stressors: confidentiality, discrimination/stigma, serostatus disclosure, distressing emotions, fear of infecting others, and excessive attention to physical functions. More attention should be paid to PLWH with younger age, not living alone, less income, presence of HIV symptoms, and lack of social support

PSCA and Oct-4 Expression in the Benign and Malignant Lesions of Gallbladder: Implication for Carcinogenesis, Progression, and Prognosis of Gallbladder Adenocarcinoma

PSCA and Oct-4 have been thought as markers of cancer stem cells. Although overexpression of PSCA and Oct-4 in cancer has been reported, little is known about the clinical and pathological significance with PSCA and Oct-4 expression in gallbladder adenocarcinoma. In this study, overexpression of PSCA and Oct-4 was detected in gallbladder adenocarcinoma (54.6% and 55.6%). Less expression of PSCA and Oct-4 was detected in the pericancerous tissues (19.6% and 21.7%), gallbladder polyps (13.3% and 13.3%), and gallbladder epithelium with chronic cholecystitis (14.3% and 14.3%). The overexpression of PSCA and Oct-4 was significantly associated with differentiation, tumor mass, lymph node metastasis, invasion of gallbladder adenocarcinoma, and decreased overall survival. Our study suggested that overexpression of PSCA and Oct-4 might be closely related to the carcinogenesis, progression, metastasis, or invasive potential and prognosis of gallbladder carcinoma

Effect of Solution Miscibility on the Morphology of Coaxial Electrospun Cellulose Acetate Nanofibers

Coaxial electrospinning (co-electrospinning) technique has greatly expanded the universality of fabricating core-shell polymer nanofibers. However, the effect of solution miscibility on the morphology of co-electrospun products remains unclear. Herein, different cellulose acetate (CA) solutions with high solution miscibility but distinctly different electrospinnability were used to survey the effect of solution miscibility on the co-electrospinning process. The structural characterizations show that co-electrospun products are composed of nanofibers with and without the core-shell structure. This indicates that partial solution mixing occurred during the co-electrospinning process instead of absolute no-mixing or complete mixing. Importantly, the solution miscibility also shows a significant influence on the product morphology. In particular, the transformation from nanofibers to microparticles was realized with the increase of core-to-shell flow ratio during the co-electrospinning of core electrosprayable CA/dimethylacetamide (DMAc) solution and shell electrospinnable CA/acetone-DMAc (2/1, v/v) solution. Results show that the solution miscibility exerts a significant effect on not only the formation of core-shell structure but also the product morphology. This work provides a new insight for the in-depth understanding of the co-electrospinning process