Transformer-based Image Compression with Variable Image Quality Objectives

This paper presents a Transformer-based image compression system that allows for a variable image quality objective according to the user's preference. Optimizing a learned codec for different quality objectives leads to reconstructed images with varying visual characteristics. Our method provides the user with the flexibility to choose a trade-off between two image quality objectives using a single, shared model. Motivated by the success of prompt-tuning techniques, we introduce prompt tokens to condition our Transformer-based autoencoder. These prompt tokens are generated adaptively based on the user's preference and input image through learning a prompt generation network. Extensive experiments on commonly used quality metrics demonstrate the effectiveness of our method in adapting the encoding and/or decoding processes to a variable quality objective. While offering the additional flexibility, our proposed method performs comparably to the single-objective methods in terms of rate-distortion performance

A preliminary study of applying interpreting skills to teaching English reading

Even though the established literature has proven that translation actually plays a significant role in English Language Teaching (ELT) as well as in Second Language Acquisition (SLA), there is lack of empirical evidence showing the correlation between the use of sight translation skills and learners' acquisition of English proficiency. This preliminary study recruited 14 English learners and investigated the potential effect of sight translation on the learners' learning outcomes. By comparing the frequencies of ambiguity and significant features appeared in the learners' reading performance in two different genres of texts, the results suggest that the skills of sight translation can successfully improve English learners' reading comprehension. Implications and potential research directions are further addressed

Transformer-based Variable-rate Image Compression with Region-of-interest Control

This paper proposes a transformer-based learned image compression system. It is capable of achieving variable-rate compression with a single model while supporting the region-of-interest (ROI) functionality. Inspired by prompt tuning, we introduce prompt generation networks to condition the transformer-based autoencoder of compression. Our prompt generation networks generate content-adaptive tokens according to the input image, an ROI mask, and a rate parameter. The separation of the ROI mask and the rate parameter allows an intuitive way to achieve variable-rate and ROI coding simultaneously. Extensive experiments validate the effectiveness of our proposed method and confirm its superiority over the other competing methods.Comment: Accepted to IEEE ICIP 202

TransTIC: Transferring Transformer-based Image Compression from Human Visualization to Machine Perception

This work aims for transferring a Transformer-based image compression codec from human vision to machine perception without fine-tuning the codec. We propose a transferable Transformer-based image compression framework, termed TransTIC. Inspired by visual prompt tuning, we propose an instance-specific prompt generator to inject instance-specific prompts to the encoder and task-specific prompts to the decoder. Extensive experiments show that our proposed method is capable of transferring the codec to various machine tasks and outshining the competing methods significantly. To our best knowledge, this work is the first attempt to utilize prompting on the low-level image compression task

Binding Transition in Quantum Hall Edge States

We study a class of Abelian quantum Hall (QH) states which are topologically unstable (T-unstable). We find that the T-unstable QH states can have a phase transition on the edge which causes a binding between electrons and reduces the number of gapless edge branches. After the binding transition, the single-electron tunneling into the edge gains a finite energy gap, and only certain multi-electron co-tunneling (such as three-electron co-tunneling for $\nu=9/5$ edges) can be gapless. Similar phenomenon also appear for edge state on the boundary between certain QH states. For example edge on the boundary between $\nu=2$ and $\nu=1/5$ states only allow three-electron co-tunneling at low energies after the binding transition.Comment: 4 pages, RevTeX, 1 figur

Peripheral Sympathectomy for Raynaud's Phenomenon: A Salvage Procedure

We retrospectively reviewed the effectiveness of peripheral sympathectomy for severe Raynaud's phenomenon. In this study, a total of 14 digits from six patients with chronic digital ischemic change were included. All patients had pain, ulcer, or gangrenous change in the affected digits and were unresponsive to pharmacologic or other nonsurgical therapies. In all cases, angiography showed multifocal arterial lesions, so microvascular reconstruction was unfeasible. Peripheral sympathectomy was performed as a salvage procedure to prevent digit amputation. The results were analyzed according to reduction of pain, healing of ulcers, and prevention of amputation. In 12 of the 14 digits, the ulcers healed and amputation was avoided. In the other two digits, the ulcers improved and progressive gangrene was limited. As a salvage procedure for Raynaud's phenomenon recalcitrant to conservative treatment, peripheral sympathectomy improves perfusion to ischemic digits and enables amputation to be avoided

Comparison of diffusion-weighted imaging and contrast-enhanced T1-weighted imaging on a single baseline MRI for demonstrating dissemination in time in multiple sclerosis

BACKGROUND: The 2010 Revisions to the McDonald Criteria have established that dissemination in time (DIT) of multiple sclerosis (MS) can be demonstrated by simultaneous presence of asymptomatic gadolinium-enhancing and nonenhancing lesions on a single magnetic resonance imaging (MRI). However, gadolinium-based contrast agents (GBCAs) have contraindications. Diffusion-weighted imaging (DWI) can detect diffusion alterations in active inflammatory lesions. The purpose of this study was to investigate if DWI can be an alternative to contrast-enhanced T1-weighted imaging (CE T1WI) for demonstrating DIT in MS. METHODS: We selected patients with clinically definite MS and evaluated their baseline brain MRI. Asymptomatic lesions were identified as either hyperintense or nonhyperintense on DWI and enhancing or nonenhancing on CE T1WI. Fisher’s exact test was performed to determine whether the hyperintensity on DWI was related to the enhancement on CE T1WI (P < 0.05). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the DWI to predict lesion enhancement were calculated. RESULTS: Twenty-two patients with 384 demyelinating lesions that were hyperintense on T2-weighted imaging and more than 3 mm in size were recruited. The diffusion hyperintensity and lesion enhancement were significantly correlated (P <0.001). The sensitivity, specificity, PPV, NPV and accuracy were 100%, 67.9%, 32.3%, 100% and 72.1%, respectively. CONCLUSIONS: A hyperintense DWI finding does not necessarily overlap with contrast enhancement. There are many false positives, possibly representing other stages of lesion development. Although DWI may not replace CE T1WI imaging to demonstrate DIT due to the low PPV, it may serve as a screening MRI sequence where the use of GBCAs is a concern

Terpenoids from the Octocorals Menella sp. (Plexauridae) and Lobophytum crassum (Alcyonacea)

A new germacrane-type sesquiterpenoid, menelloide E (1), and a new cembrane-type diterpenoid, lobocrassin F (2), were isolated from the octocorals Menella sp. and Lobophytum crassum, respectively. The structures of terpenoids 1 and 2 were determined by spectroscopic and chemical methods and compound 2 was found to display a significant inhibitory effect on the release of elastase by human neutrophils