ExMobileViT: Lightweight Classifier Extension for Mobile Vision Transformer

The paper proposes an efficient structure for enhancing the performance of mobile-friendly vision transformer with small computational overhead. The vision transformer (ViT) is very attractive in that it reaches outperforming results in image classification, compared to conventional convolutional neural networks (CNNs). Due to its need of high computational resources, MobileNet-based ViT models such as MobileViT-S have been developed. However, their performance cannot reach the original ViT model. The proposed structure relieves the above weakness by storing the information from early attention stages and reusing it in the final classifier. This paper is motivated by the idea that the data itself from early attention stages can have important meaning for the final classification. In order to reuse the early information in attention stages, the average pooling results of various scaled features from early attention stages are used to expand channels in the fully-connected layer of the final classifier. It is expected that the inductive bias introduced by the averaged features can enhance the final performance. Because the proposed structure only needs the average pooling of features from the attention stages and channel expansions in the final classifier, its computational and storage overheads are very small, keeping the benefits of low-cost MobileNet-based ViT (MobileViT). Compared with the original MobileViTs on the ImageNet dataset, the proposed ExMobileViT has noticeable accuracy enhancements, having only about 5% additional parameters.Comment: Under Revie

Alpha-tocopherol exerts protective function against the mucotoxicity of particulate matter in amphibian and human goblet cells

Exposure to particulate matter (PM) in ambient air is known to increase the risk of cardiovascular disorders and mortality. The cytotoxicity of PM is mainly due to the abnormal increase of reactive oxygen species (ROS), which damage cellular components such as DNA, RNA, and proteins. The correlation between PM exposure and human disorders, including mortality, is based on long-term exposure. In this study we have investigated acute responses of mucus-secreting goblet cells upon exposure to PM derived from a heavy diesel engine. To this end, we employed the mucociliary epithelium of amphibian embryos and human Calu-3 cells to examine PM mucotoxicity. Our data suggest that acute exposure to PM significantly impairs mucus secretion and results in the accumulation of mucus vesicles in the cytoplasm of goblet cells. RNA-seq analysis revealed that acute responses to PM exposure significantly altered gene expression patterns; however, known regulators of mucus production and the secretory pathway were not significantly altered. Interestingly, pretreatment with alpha-tocopherol nearly recovered the hyposecretion of mucus from both amphibian and human goblet cells. We believe this study demonstrates the mucotoxicity of PM and the protective function of alpha-tocopherol on mucotoxicity caused by acute PM exposure from heavy diesel engines

No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization

Key-Value (KV) Caching has become an essential technique for accelerating the inference speed and throughput of generative Large Language Models~(LLMs). However, the memory footprint of the KV cache poses a critical bottleneck in LLM deployment as the cache size grows with batch size and sequence length, often surpassing even the size of the model itself. Although recent methods were proposed to select and evict unimportant KV pairs from the cache to reduce memory consumption, the potential ramifications of eviction on the generative process are yet to be thoroughly examined. In this paper, we examine the detrimental impact of cache eviction and observe that unforeseen risks arise as the information contained in the KV pairs is exhaustively discarded, resulting in safety breaches, hallucinations, and context loss. Surprisingly, we find that preserving even a small amount of information contained in the evicted KV pairs via reduced precision quantization substantially recovers the incurred degradation. On the other hand, we observe that the important KV pairs must be kept at a relatively higher precision to safeguard the generation quality. Motivated by these observations, we propose \textit{Mixed-precision KV cache}~(MiKV), a reliable cache compression method that simultaneously preserves the context details by retaining the evicted KV pairs in low-precision and ensure generation quality by keeping the important KV pairs in high-precision. Experiments on diverse benchmarks and LLM backbones show that our proposed method offers a state-of-the-art trade-off between compression ratio and performance, compared to other baselines

Characteristics and treatments of large cystic brain metastasis: radiosurgery and stereotactic aspiration.

Brain metastasis represents one of the most common causes of intracranial tumors in adults, and the incidence of brain metastasis continues to rise due to the increasing survival of cancer patients. Yet, the development of cystic brain metastasis remains a relatively rare occurrence. In this review, we describe the characteristics of cystic brain metastasis and evaluate the combined use of stereotactic aspiration and radiosurgery in treating large cystic brain metastasis. The results of several studies show that stereotactic radiosurgery produces comparable local tumor control and survival rates as other surgery protocols. When the size of the tumor interferes with radiosurgery, stereotactic aspiration of the metastasis should be considered to reduce the target volume as well as decreasing the chance of radiation induced necrosis and providing symptomatic relief from mass effect. The combined use of stereotactic aspiration and radiosurgery has strong implications in improving patient outcomes

Wave Run-Up Phenomenon on Offshore Platforms: Part 1. Tension Leg Platform

This study reports on an extensive experimental campaign carried out to evaluate non-linear waves applied to offshore structures in extreme marine environments. An offshore tension leg platform (TLP) model was used to observe the waves around a fixed-type offshore structure. The wave amplitude measured in the experiments of this study was indicated as a wave run-up ratio. Both the first-order analysis and the analysis of the entire wave amplitude were described. The experimental results were compared with the calculations from a potential-based code in order to verify the effectiveness of the developed technology